1 00:00:05,372 --> 00:00:08,141 >> LET'S GET STARTED. 2 00:00:08,208 --> 00:00:10,610 SO, TODAY IT'S A GREAT PLEASURE 3 00:00:10,677 --> 00:00:13,313 TO WELCOME DR. BRIAN SEARLE TO 4 00:00:13,380 --> 00:00:15,281 OUR PROTEOMICS INTEREST GROUP 5 00:00:15,348 --> 00:00:15,582 SEMINAR. 6 00:00:15,648 --> 00:00:17,050 TO ME, BRIAN IS KIND OF A LEGEND 7 00:00:17,117 --> 00:00:18,918 IN HIS OWN WAY. 8 00:00:18,985 --> 00:00:20,887 YOU'LL FIND OUT. 9 00:00:20,954 --> 00:00:23,189 SO, BRIAN IS ASSISTANT 10 00:00:23,256 --> 00:00:26,559 PROFESSOR, OHIO STATE UNIVERSITY 11 00:00:26,626 --> 00:00:29,295 MEDICAL CENTER, DEPARTMENT OF 12 00:00:29,362 --> 00:00:33,900 BIOMEDICAL INFORMATICS, A MEMBER 13 00:00:33,967 --> 00:00:38,938 OF THE INSTITUTE FOR 14 00:00:39,005 --> 00:00:39,906 IMMUNO-ONCOLOGY, RECEIVED 15 00:00:39,973 --> 00:00:41,007 BACHELOR'S DEGREE IN CHEMISTRY 16 00:00:41,074 --> 00:00:43,543 IN 2001, AND GO DIRECTLY TO GRAD 17 00:00:43,610 --> 00:00:44,511 SCHOOL. 18 00:00:44,577 --> 00:00:47,447 IN 2004, HE CO-FOUNDED THE 19 00:00:47,514 --> 00:00:49,315 PROTEOME SOFTWARE COMPANY WITH 20 00:00:49,382 --> 00:00:53,052 MARK TURNER AND DR. ASHLEY 21 00:00:53,119 --> 00:00:56,456 McCOMAK TO PRODUCE AND 22 00:00:56,523 --> 00:00:58,425 DISTRIBUTE CUTTING EDGE 23 00:00:58,491 --> 00:00:59,292 SOFTWARE. 24 00:00:59,359 --> 00:01:02,695 A LOT OF PEOPLE DON'T ASSOCIATE 25 00:01:02,762 --> 00:01:04,764 PROTEOME SOFTWARE WITH BRAND 26 00:01:04,831 --> 00:01:07,300 NAME SCAFFOLD, AND MOST OF US 27 00:01:07,367 --> 00:01:09,803 DOING PROTEOMICS IN EARLY DAYS, 28 00:01:09,869 --> 00:01:12,305 LATE 2000s, EARLY 2010 YEARS, 29 00:01:12,372 --> 00:01:14,407 KNOW THE SOFTWARE SCAFFOLD. 30 00:01:14,474 --> 00:01:17,076 THAT'S BASICALLY THE GO-TO 31 00:01:17,143 --> 00:01:18,478 SOFTWARE FOR PROTEOMICS, 32 00:01:18,545 --> 00:01:20,346 ESPECIALLY FOR CORE FACILITIES. 33 00:01:20,413 --> 00:01:22,615 THAT'S A SUCCESSFUL BUSINESS AND 34 00:01:22,682 --> 00:01:25,819 WE ALL RELY ON ITS PUBLICATIONS 35 00:01:25,885 --> 00:01:27,787 FOR QUITE A WHILE UNTIL PROTEOME 36 00:01:27,854 --> 00:01:30,757 DISCOVERY CAUGHT UP. 37 00:01:30,824 --> 00:01:33,927 BUT THEN IN 2014, HE DECIDED HE 38 00:01:33,993 --> 00:01:35,795 WENT BACK TO GRADUATE SCHOOL, 39 00:01:35,862 --> 00:01:39,966 AND GOT HIS Ph.D. WITH DR. 40 00:01:40,033 --> 00:01:41,401 MIKE McCASS, UNIVERSITY OF 41 00:01:41,468 --> 00:01:44,337 WASHINGTON, WHERE HE DEVELOPED 42 00:01:44,404 --> 00:01:47,640 METHODS TO DETECT PROTEINS USING 43 00:01:47,707 --> 00:01:48,074 MASS SPECTROMETRY. 44 00:01:48,141 --> 00:01:49,809 SO, OF COURSE THAT'S A 45 00:01:49,876 --> 00:01:53,346 SUCCESSFUL Ph.D. PROGRAM AND 46 00:01:53,413 --> 00:02:00,353 THEN NOW HE'S STARTED HIS OWN 47 00:02:00,420 --> 00:02:00,987 LAB IN 2018? 48 00:02:01,054 --> 00:02:03,523 >> (INAUDIBLE). 49 00:02:03,590 --> 00:02:03,890 >> OKAY. 50 00:02:03,957 --> 00:02:04,591 IN 2018. 51 00:02:04,657 --> 00:02:08,528 AND THEN MOVED TO OHIO STATE IN 52 00:02:08,595 --> 00:02:10,196 2019. 53 00:02:10,263 --> 00:02:12,465 AND HIS LAB SPANS INTERSECTION 54 00:02:12,532 --> 00:02:14,434 OF PROTEOMICS, MASS 55 00:02:14,501 --> 00:02:15,468 SPECTROMETRY, BIOINFORMATICS AND 56 00:02:15,535 --> 00:02:20,073 TECHNOLOGY, DEVELOPMENT TO STUDY 57 00:02:20,139 --> 00:02:22,775 HUMAN GENETIC VARIATION WITH 58 00:02:22,842 --> 00:02:23,209 CANCER. 59 00:02:23,276 --> 00:02:26,412 HERE IS BRIAN, WITHOUT FURTHER 60 00:02:26,479 --> 00:02:26,579 ADO. 61 00:02:26,646 --> 00:02:28,681 >> THANKS. 62 00:02:33,820 --> 00:02:37,724 YEAH, I HAD A SMALL LAB AT ISB. 63 00:02:37,790 --> 00:02:40,226 VERY LIMITED LAB, ONE POSTDOC, 64 00:02:40,293 --> 00:02:41,761 WE WERE DOING MOSTLY 65 00:02:41,828 --> 00:02:45,131 COMPUTATIONAL WORK AT THE TIME. 66 00:02:45,198 --> 00:02:48,535 BUT IT LED INTO THIS LAB THAT 67 00:02:48,601 --> 00:02:51,271 I'VE BEEN BUILDING AT OSU. 68 00:02:51,337 --> 00:02:53,673 SO, TODAY I WANT TO TELL YOU 69 00:02:53,740 --> 00:02:57,744 SOMETHING, A STORY ABOUT 70 00:02:57,810 --> 00:02:58,511 SOMETHING THAT'S DIFFERENT THAN 71 00:02:58,578 --> 00:03:02,248 WHAT I USUALLY TALK ABOUT. 72 00:03:02,315 --> 00:03:03,449 MY BACKGROUND IS COMPUTATIONALLY 73 00:03:03,516 --> 00:03:04,250 ORIENTED. 74 00:03:04,317 --> 00:03:06,953 I STARTED IN A BIOINFORMATICS 75 00:03:07,020 --> 00:03:08,154 POSITION, AND I STARTED A 76 00:03:08,221 --> 00:03:08,955 BIOINFORMATICS COMPANY. 77 00:03:09,022 --> 00:03:13,059 I WENT TO GRAD SCHOOL MOSTLY, IN 78 00:03:13,126 --> 00:03:14,594 PART AT LEAST, FOCUSING ON 79 00:03:14,661 --> 00:03:15,595 BIOINFORMATICS. 80 00:03:15,662 --> 00:03:17,864 MANY OF MY TALKS ARE AROUND 81 00:03:17,931 --> 00:03:18,631 BIOINFORMATICS TYPE OF 82 00:03:18,698 --> 00:03:18,898 QUESTIONS. 83 00:03:18,965 --> 00:03:21,868 THIS IS NOT ONE OF THEM. 84 00:03:21,935 --> 00:03:23,403 THIS IS A PROJECT THAT'S A 85 00:03:23,469 --> 00:03:24,270 BIOLOGY PROJECT. 86 00:03:24,337 --> 00:03:27,574 AND WHAT'S EVEN WEIRDER IS IT'S 87 00:03:27,640 --> 00:03:28,575 A BIOMARKER DISCOVERY PROJECT. 88 00:03:28,641 --> 00:03:30,009 WHEN I STARTED MY LAB, THE FIRST 89 00:03:30,076 --> 00:03:33,146 THING I SAID WAS I'M NEVER GOING 90 00:03:33,212 --> 00:03:34,781 TO TAKE A BIOMARKER DISCOVERY 91 00:03:34,847 --> 00:03:35,882 PROJECT ON. 92 00:03:35,949 --> 00:03:37,216 THAT'S THE LAST THING I WANTED 93 00:03:37,283 --> 00:03:38,618 TO DO. 94 00:03:38,685 --> 00:03:39,919 I WANT A MECHANISM, HYPOTHESIS, 95 00:03:39,986 --> 00:03:41,888 I WANT TO KNOW WHAT I'M 96 00:03:41,955 --> 00:03:43,856 STUDYING, TO MAKE SURE THAT I'M 97 00:03:43,923 --> 00:03:46,159 MAKING THE RIGHT CHOICES FOR 98 00:03:46,225 --> 00:03:46,492 THAT. 99 00:03:46,559 --> 00:03:47,794 SO, THE PROJECT THAT I WANT TO 100 00:03:47,860 --> 00:03:57,971 TALK TO YOU TODAY ABOUT IS ABOUT 101 00:03:58,037 --> 00:03:59,706 IDENTIFYING THESE NOVEL 102 00:03:59,772 --> 00:04:00,540 PANCREATITIS BIOMARKERS 103 00:04:00,607 --> 00:04:01,808 SPECIFICALLY IN URINE SAMPLES. 104 00:04:01,874 --> 00:04:05,945 THIS IS INTEREST FROM MY 105 00:04:06,012 --> 00:04:06,946 PERSPECTIVE, A DEVIATION, SO TO 106 00:04:07,013 --> 00:04:09,449 ME THIS IS A NEW TALK. 107 00:04:09,515 --> 00:04:12,852 WE SHOULD HAVE FUN WITH IT. 108 00:04:12,919 --> 00:04:16,889 IF YOU HAVE QUESTIONS ALONG THE 109 00:04:16,956 --> 00:04:19,525 WAY, I'D PREFER THEM AS WE'RE 110 00:04:19,592 --> 00:04:19,726 GOING. 111 00:04:19,792 --> 00:04:23,062 RAISE YOUR HAND, ASK THEM, IT 112 00:04:23,129 --> 00:04:25,098 WILL BE MORE FUN IF IT'S 113 00:04:25,164 --> 00:04:25,598 INTERACTIVE. 114 00:04:25,665 --> 00:04:25,932 COOL? 115 00:04:25,999 --> 00:04:26,566 OKAY. 116 00:04:26,633 --> 00:04:30,169 SO THE FIRST THING I WANT TO DO 117 00:04:30,236 --> 00:04:34,641 IS TALK ABOUT SOME DISCLOSURES. 118 00:04:34,707 --> 00:04:37,443 SO, AS WAS SAID, I'M EMPLOYED AS 119 00:04:37,510 --> 00:04:38,645 ASSISTANT PROFESSOR AT OHIO 120 00:04:38,711 --> 00:04:39,445 STATE UNIVERSITY. 121 00:04:39,512 --> 00:04:42,749 BUT I'M ALSO THE FOUNDER OF THE 122 00:04:42,815 --> 00:04:45,051 COMPANY SCAFFOLD, I'M ALSO ON 123 00:04:45,118 --> 00:04:48,888 THE SCIENTIFIC ADVISORY BOARD 124 00:04:48,955 --> 00:04:49,989 FOR TALUS BIOSCIENCES. 125 00:04:50,056 --> 00:04:52,558 AND MY RESEARCH IS FUNDED 126 00:04:52,625 --> 00:04:57,430 THROUGH NIGMS AND THROUGH THE 127 00:04:57,497 --> 00:04:57,597 NCI. 128 00:04:57,664 --> 00:04:59,065 THE FIRST THING I WANT TO TALK 129 00:04:59,132 --> 00:05:01,134 ABOUT, AS A CHILD OF THE '80s, 130 00:05:01,200 --> 00:05:04,537 LIKE WE WOULD SEE SLOGANS LIKE 131 00:05:04,604 --> 00:05:07,140 THIS FOR DARE. 132 00:05:07,206 --> 00:05:08,541 FRIENDS DON'T LET FRIENDS DO 133 00:05:08,608 --> 00:05:08,741 DRUGS. 134 00:05:08,808 --> 00:05:12,645 I WANT TO CHANGE THIS AROUND A 135 00:05:12,712 --> 00:05:15,348 LITTLE BIT, BECAUSE WHAT I WANT 136 00:05:15,415 --> 00:05:17,417 TO SAY, FRIENDS DON'T LET 137 00:05:17,483 --> 00:05:19,952 FRIENDS USE ANTIBODIES AS 138 00:05:20,019 --> 00:05:20,353 READOUTS. 139 00:05:20,420 --> 00:05:21,254 SPECIFICALLY, LET ME SEE IF I 140 00:05:21,320 --> 00:05:22,355 CAN MOVE THAT. 141 00:05:22,422 --> 00:05:22,555 NO? 142 00:05:22,622 --> 00:05:24,657 WE'LL GIVE UP ON THAT. 143 00:05:24,724 --> 00:05:28,594 AS AN UNVALIDATED READOUT. 144 00:05:28,661 --> 00:05:30,897 AND THIS TALK IS ABOUT REALIZING 145 00:05:30,963 --> 00:05:32,765 ANTIBODIES AT LEAST FOR CERTAIN 146 00:05:32,832 --> 00:05:33,833 TYPES OF EXPERIMENTS, DON'T 147 00:05:33,900 --> 00:05:34,467 NECESSARILY WORK. 148 00:05:34,534 --> 00:05:37,904 AND THAT A LOT OF MY TALKS MORE 149 00:05:37,970 --> 00:05:41,607 RECENTLY HAVE TURNED INTO THIS 150 00:05:41,674 --> 00:05:42,408 DIAL OF TALK, UNFORTUNATELY, 151 00:05:42,475 --> 00:05:45,144 BECAUSE OF THE PREVALENCE 152 00:05:45,211 --> 00:05:47,847 THROUGHOUT THE COMMUNITY. 153 00:05:47,914 --> 00:05:49,315 SO, THE QUESTION I WANT TO TALK 154 00:05:49,382 --> 00:05:54,654 TO YOU ABOUT TODAY IS ON 155 00:05:54,721 --> 00:05:56,556 PANCREATIC DISEASE. 156 00:05:56,622 --> 00:05:59,759 SO, ACUTE PANCREATITIS IS ONE OF 157 00:05:59,826 --> 00:06:02,328 THE BIGGEST, ONE OF THE MOST 158 00:06:02,395 --> 00:06:03,763 IMPORTANT PANCREATIC DISEASES 159 00:06:03,830 --> 00:06:05,932 FROM THE STANDPOINT OF THE 160 00:06:05,998 --> 00:06:08,568 NUMBER OF PEOPLE IT AFFECTS, AND 161 00:06:08,634 --> 00:06:10,002 THAT ACUTE PANCREATITIS IS ONE 162 00:06:10,069 --> 00:06:14,574 OF THE MOST COMMON G.I. 163 00:06:14,640 --> 00:06:17,110 DISORDERS IN GENERAL. 164 00:06:17,176 --> 00:06:20,046 AND PARTICULARLY IN THAT IT HAS 165 00:06:20,113 --> 00:06:22,248 SORT OF VERY UNUSUAL PHYSIOLOGY, 166 00:06:22,315 --> 00:06:22,448 RIGHT? 167 00:06:22,515 --> 00:06:23,549 IT STARTS AT VERY DIFFERENT AGES 168 00:06:23,616 --> 00:06:24,650 FOR DIFFERENT PEOPLE. 169 00:06:24,717 --> 00:06:26,953 IT HAS VERY DIFFERENT 170 00:06:27,019 --> 00:06:30,890 ASSOCIATIONS WITH WHAT'S GOING 171 00:06:30,957 --> 00:06:31,390 ON. 172 00:06:31,457 --> 00:06:32,992 AND DESPITE SORT OF THE -- LIKE 173 00:06:33,059 --> 00:06:34,927 THESE ISSUES WITH TRYING TO MAKE 174 00:06:34,994 --> 00:06:35,695 MEASUREMENTS AND HOW IMPORTANT 175 00:06:35,762 --> 00:06:37,463 IT IS, IT'S REALLY KIND OF 176 00:06:37,530 --> 00:06:38,865 CHALLENGING TO TRY TO MAKE 177 00:06:38,931 --> 00:06:40,933 MEASUREMENTS OF IT. 178 00:06:41,000 --> 00:06:41,734 SPECIFICALLY BECAUSE THERE ARE A 179 00:06:41,801 --> 00:06:45,004 LOT OF CO-MORBIDITIES ASSOCIATED 180 00:06:45,071 --> 00:06:46,973 WITH PANCREATIC DISEASES IN 181 00:06:47,039 --> 00:06:47,640 GENERAL, ACUTE PANCREATITIS AND 182 00:06:47,707 --> 00:06:48,574 CHRONIC PANCREATITIS. 183 00:06:48,641 --> 00:06:54,680 WE'LL GET TO SOME A LITTLE BIT 184 00:06:54,747 --> 00:06:54,881 LATER. 185 00:06:54,947 --> 00:06:55,748 BUT SPECIFICALLY, PANCREATITIS 186 00:06:55,815 --> 00:06:59,352 HAS BEEN STUDIED IN VERY LARGE 187 00:06:59,418 --> 00:07:00,086 COHORTS SURROUNDING ALCOHOLISM 188 00:07:00,153 --> 00:07:03,956 AND SMOKING, WHICH TEND TO BE 189 00:07:04,023 --> 00:07:04,724 THE BIGGEST DRIVERS FOR 190 00:07:04,791 --> 00:07:08,361 PANCREATIC DISEASE IN GENERAL, 191 00:07:08,427 --> 00:07:10,196 SPECIFICALLY WITH CHRONIC 192 00:07:10,263 --> 00:07:11,230 PANCREATITIS. 193 00:07:11,297 --> 00:07:13,232 SO, FOR ACUTE PANCREATITIS, WE 194 00:07:13,299 --> 00:07:15,535 DO HAVE BIOMARKERS FOR THIS 195 00:07:15,601 --> 00:07:15,868 DISEASE. 196 00:07:15,935 --> 00:07:17,770 AND LIPASE IS THE ONE THAT IS 197 00:07:17,837 --> 00:07:19,372 THE MOST COMMONLY USED. 198 00:07:19,438 --> 00:07:21,908 LIPASE IS A BIOMARKER THAT WAS 199 00:07:21,974 --> 00:07:24,410 DISCOVERED IN THE EARLY 1900s. 200 00:07:24,477 --> 00:07:29,482 AND WAS FOUND TO BE INCREASED IN 201 00:07:29,549 --> 00:07:30,783 ACUTE PANCREATITIS, AS A 202 00:07:30,850 --> 00:07:35,555 POTENTIAL MARKER FOR THE 203 00:07:35,621 --> 00:07:36,956 DIAGNOSIS FOR THE DISEASE. 204 00:07:37,023 --> 00:07:39,992 BUT HONESTLY WE MAY HAVE BEEN 205 00:07:40,059 --> 00:07:40,993 TAKING LIPASE FOR GRANTED AS A 206 00:07:41,060 --> 00:07:45,131 FIELD IN THE USE OF THIS TYPE OF 207 00:07:45,198 --> 00:07:46,799 BIOMARKER, JUST BECAUSE OF OTHER 208 00:07:46,866 --> 00:07:50,403 SOURCES OF ELEVATION OF LIPASE. 209 00:07:50,469 --> 00:07:53,606 FOR EXAMPLE, WE SEE THAT IN THE 210 00:07:53,673 --> 00:07:55,141 PANCREAS, FOR EXAMPLE, THERE'S A 211 00:07:55,208 --> 00:08:00,179 HIGHER LEVEL OF LIPASE JUST SORT 212 00:08:00,246 --> 00:08:03,349 OF GENERALLY, NOT JUST IN -- NOT 213 00:08:03,416 --> 00:08:05,985 JUST IN ACUTE PANCREATITIS OR 214 00:08:06,052 --> 00:08:08,554 CHRONIC PANCREATITIS, BUT AS 215 00:08:08,621 --> 00:08:11,123 WELL THERE ARE REASONABLY HIGH 216 00:08:11,190 --> 00:08:13,860 LEVELS OF LIPASE IN OTHER ORGANS 217 00:08:13,926 --> 00:08:15,061 AS WELL, OTHER BIOFLUIDS AS 218 00:08:15,127 --> 00:08:15,828 WELL. 219 00:08:15,895 --> 00:08:17,697 AS A RESULT, IT IS A COMPLICATED 220 00:08:17,763 --> 00:08:18,531 BIOMARKER TO USE. 221 00:08:18,598 --> 00:08:20,533 BECAUSE FIGURING OUT WHAT ARE 222 00:08:20,600 --> 00:08:22,468 THE APPROPRIATE LEVELS FOR THIS 223 00:08:22,535 --> 00:08:24,003 IN A DISEASE POPULATION CAN BE A 224 00:08:24,070 --> 00:08:25,972 LITTLE BIT CHALLENGING BECAUSE 225 00:08:26,038 --> 00:08:26,572 THE DIFFERENCE BETWEEN WHETHER 226 00:08:26,639 --> 00:08:28,507 SOMEONE HAS THE DISEASE AND 227 00:08:28,574 --> 00:08:30,142 WHETHER THEY DON'T IS VERY 228 00:08:30,209 --> 00:08:32,011 SHALLOW MARGIN OF ERROR FOR 229 00:08:32,078 --> 00:08:34,313 MAKING A CALL, AS TO WHETHER 230 00:08:34,380 --> 00:08:40,086 THEY HAVE -- THAT THEY HAVE A 231 00:08:40,152 --> 00:08:40,353 DISORDER. 232 00:08:40,419 --> 00:08:42,188 SO, LIPASE IS A CHALLENGE FOR A 233 00:08:42,255 --> 00:08:43,155 WIDE VARIETY OF REASONS. 234 00:08:43,222 --> 00:08:45,258 AND IT CAN LEAD TO MISSED 235 00:08:45,324 --> 00:08:47,059 DIAGNOSIS IN LOTS OF DIFFERENT 236 00:08:47,126 --> 00:08:47,260 CASES. 237 00:08:47,326 --> 00:08:51,030 THIS DIAGNOSIS IN THESE CASES 238 00:08:51,097 --> 00:08:52,031 HAS PRETTY MAJOR CONSEQUENCES. 239 00:08:52,098 --> 00:08:53,766 IN FACT, GOING ALL THE WAY TO 240 00:08:53,833 --> 00:08:55,034 SORT OF LIKE PANCREAS REMOVAL, 241 00:08:55,101 --> 00:08:56,269 AND THAT SORT OF THING. 242 00:08:56,335 --> 00:09:02,074 SO LOTS OF DISEASES CAN ACTUALLY 243 00:09:02,141 --> 00:09:04,043 CAUSE INCREASED LIPASE, SO 244 00:09:04,110 --> 00:09:07,013 THERE'S A WIDE VARIETY OF 245 00:09:07,079 --> 00:09:08,547 INTERABDOMINAL DISEASES THAT CAN 246 00:09:08,614 --> 00:09:10,182 BE ASSOCIATED WITH INCREASED 247 00:09:10,249 --> 00:09:10,416 LIPASE. 248 00:09:10,483 --> 00:09:12,251 BUT ALSO IT CAN BE ASSOCIATED 249 00:09:12,318 --> 00:09:15,855 WITH TOTALLY DIFFERENT THINGS AS 250 00:09:15,922 --> 00:09:16,756 WELL. 251 00:09:16,822 --> 00:09:18,824 SO, IT CAN HAVE -- BE RESULTING 252 00:09:18,891 --> 00:09:21,894 IN SORT OF REDUCE THE CLEARANCE 253 00:09:21,961 --> 00:09:23,529 OF LIPASE IN GENERAL. 254 00:09:23,596 --> 00:09:25,197 ASSOCIATED WITH A VARIETY OF 255 00:09:25,264 --> 00:09:26,499 THINGS LIKE BRAIN DAMAGE, FOR 256 00:09:26,565 --> 00:09:29,368 EXAMPLE, OR JUST DRUG USAGE, FOR 257 00:09:29,435 --> 00:09:33,506 EXAMPLE. 258 00:09:33,572 --> 00:09:36,542 AND SO, AS A RESULT, THERE'S 259 00:09:36,609 --> 00:09:41,614 BEEN A MAJOR PUSH BY THE 260 00:09:41,681 --> 00:09:43,783 PANCREAS COMMUNITY TO START TO 261 00:09:43,849 --> 00:09:47,486 LOOK FOR DIFFERENT TYPES OF 262 00:09:47,553 --> 00:09:48,387 APPROACHES TO DIAGNOSING THIS 263 00:09:48,454 --> 00:09:49,488 PARTICULAR DISEASE AND TREATING 264 00:09:49,555 --> 00:09:53,526 THIS DISEASE. 265 00:09:53,592 --> 00:09:58,564 SO IN PARTICULAR, THE TOP GOAL 266 00:09:58,631 --> 00:10:01,767 FOR ACUTE PANCREATITIS RESEARCH 267 00:10:01,834 --> 00:10:04,370 PUBLISHED IN THIS MAJOR SURVEY 268 00:10:04,437 --> 00:10:08,541 WAS TRYING TO FIGURE OUT WAYS TO 269 00:10:08,607 --> 00:10:11,377 TREAT PANCREATITIS WITHOUT USING 270 00:10:11,444 --> 00:10:13,679 KIND OF OPIATE-STYLE DRUGS THAT 271 00:10:13,746 --> 00:10:16,882 WE KNOW ARE QUITE PREVALENT. 272 00:10:16,949 --> 00:10:18,284 SO THE PAIN MANAGEMENT IS ONE OF 273 00:10:18,351 --> 00:10:19,952 THE KEY ASPECTS OF IT. 274 00:10:20,019 --> 00:10:20,853 THIS IS DEFINITELY A DIRECTION 275 00:10:20,920 --> 00:10:23,122 THAT MY LAB HAS BEEN FOCUSING IN 276 00:10:23,189 --> 00:10:24,190 MORE RECENTLY. 277 00:10:24,256 --> 00:10:27,727 BUT JUST TRYING TO FIGURE OUT 278 00:10:27,793 --> 00:10:30,229 WHEN SOMEONE PRESENTS WITH 279 00:10:30,296 --> 00:10:31,998 HAVING ABDOMINAL PAIN SAYING DO 280 00:10:32,064 --> 00:10:33,933 THEY ACTUALLY HAVE PANCREATITIS 281 00:10:34,000 --> 00:10:37,570 AS A POTENTIAL AVENUE FOR DOING 282 00:10:37,636 --> 00:10:38,871 DIAGNOSIS, HAVING QUICK AND 283 00:10:38,938 --> 00:10:42,241 EARLY ACCESS TO GOOD BIOMARKERS 284 00:10:42,308 --> 00:10:43,676 ARE GOOD IDENTIFICATION OF THE 285 00:10:43,743 --> 00:10:47,947 DISEASE, CAN BE REALLY CRITICAL 286 00:10:48,014 --> 00:10:50,082 TO HOW WELL THAT THEY CAN 287 00:10:50,149 --> 00:10:52,251 SUCCEED ON TREATMENT, FOR 288 00:10:52,318 --> 00:10:54,186 EXAMPLE. 289 00:10:54,253 --> 00:10:58,124 SO, THIS IS THE DISEASE THAT HAS 290 00:10:58,190 --> 00:11:01,093 A WIDE VARIETY OF EXISTING 291 00:11:01,160 --> 00:11:01,627 POTENTIAL BIOMARKERS THAT 292 00:11:01,694 --> 00:11:02,528 ALREADY EXIST. 293 00:11:02,595 --> 00:11:05,031 SO, WE TALKED ABOUT LIPASE, SORT 294 00:11:05,097 --> 00:11:07,099 OF THE GOLD STANDARD FOR DOING 295 00:11:07,166 --> 00:11:09,068 DIAGNOSIS, AND IT'S BEEN THE 296 00:11:09,135 --> 00:11:11,370 STANDARD OF CARE FOR ALMOST 100 297 00:11:11,437 --> 00:11:14,006 YEARS AT THIS POINT. 298 00:11:14,073 --> 00:11:16,942 SERUM AMYLASE IS A NEWER MARKER 299 00:11:17,009 --> 00:11:20,112 THAT IS ALSO THE OTHER SORT OF 300 00:11:20,179 --> 00:11:21,747 HALLMARK OF THIS DISEASE. 301 00:11:21,814 --> 00:11:25,384 SO, BEING ABLE TO DETECT SERUM 302 00:11:25,451 --> 00:11:28,320 AMYLASE AT CERTAIN LEVELS TENDS 303 00:11:28,387 --> 00:11:30,289 TO BE REALLY BENEFICIAL FOR 304 00:11:30,356 --> 00:11:34,794 MAKING A DETECTION. 305 00:11:34,860 --> 00:11:38,397 THERE'S ANOTHER EXISTING 306 00:11:38,464 --> 00:11:40,066 BIOMARKER, TRYPSINOGEN, 307 00:11:40,132 --> 00:11:40,900 IDENTIFIED AS USED IN EUROPE 308 00:11:40,966 --> 00:11:42,101 PRACTICE BUT NOT APPROVED IN THE 309 00:11:42,168 --> 00:11:43,202 U.S. AT THIS POINT. 310 00:11:43,269 --> 00:11:44,637 THERE ARE A FEW OTHER 311 00:11:44,703 --> 00:11:45,071 BIOMARKERS. 312 00:11:45,137 --> 00:11:46,505 WE'LL COME BACK TO SOME OF THESE 313 00:11:46,572 --> 00:11:48,674 A LITTLE BIT LATER. 314 00:11:48,741 --> 00:11:49,875 BUT KNOW THAT THERE'S BEEN WORK 315 00:11:49,942 --> 00:11:53,913 IN THIS AREA TO TRY TO IDENTIFY 316 00:11:53,979 --> 00:11:55,581 OTHER MARKERS OF THIS DISEASE, 317 00:11:55,648 --> 00:11:57,216 IN GENERAL THESE ARE NOT BEEN AS 318 00:11:57,283 --> 00:12:01,587 PARTICULARFUL, -- SUCCESSFUL, 319 00:12:01,654 --> 00:12:04,323 IDENTIFIED BUT NOT USED. 320 00:12:04,390 --> 00:12:08,527 I THINK THIS IS AN INTERESTING 321 00:12:08,594 --> 00:12:10,096 PROBLEM, BUT I WOULDN'T GET INTO 322 00:12:10,162 --> 00:12:12,531 THIS TYPE OF THINK AS AN 323 00:12:12,598 --> 00:12:14,800 ANALYTICAL CHEMIST IF IT WEREN'T 324 00:12:14,867 --> 00:12:16,335 FOR SORT OF THE TRYING TO SEE 325 00:12:16,402 --> 00:12:17,736 THERE WAS AN OPPORTUNITY AND 326 00:12:17,803 --> 00:12:20,072 TRYING TO MAKE A MEASUREMENT. 327 00:12:20,139 --> 00:12:23,576 AND THE OPPORTUNITY FOR MAKING A 328 00:12:23,642 --> 00:12:25,644 DIFFERENCE HERE ACTUALLY CAME 329 00:12:25,711 --> 00:12:29,381 FROM THIS COLLEAGUE OF MINE, 330 00:12:29,448 --> 00:12:31,450 MAISAM, FROM CINCINNATI 331 00:12:31,517 --> 00:12:31,750 CHILDREN'S. 332 00:12:31,817 --> 00:12:33,085 MAISAM APPROACHED ME A COUPLE 333 00:12:33,152 --> 00:12:35,054 YEARS AGO AND SON THAT SHE WAS 334 00:12:35,121 --> 00:12:38,457 INTERESTED IN TRYING TO STUDY 335 00:12:38,524 --> 00:12:39,758 THIS PARTICULAR DISEASE, AND 336 00:12:39,825 --> 00:12:41,927 TRIED TO MAKE PROGRESS IN IT. 337 00:12:41,994 --> 00:12:43,429 BUT SHE WAS FOCUSING ON 338 00:12:43,496 --> 00:12:46,966 SOMETHING THAT WAS A LITTLE BIT 339 00:12:47,032 --> 00:12:49,068 DIFFERENT, NOT TRYING TO 340 00:12:49,135 --> 00:12:50,703 IDENTIFY PANCREATITIS IN THE 341 00:12:50,769 --> 00:12:51,804 GLOBAL POPULATION BUT 342 00:12:51,871 --> 00:12:53,305 SPECIFICALLY TRYING TO IDENTIFY 343 00:12:53,372 --> 00:12:54,740 IT IN CHILDREN. 344 00:12:54,807 --> 00:12:57,910 SO, IF YOU THINK BACK, WHAT ARE 345 00:12:57,977 --> 00:13:00,112 THE MOST IMPORTANT 346 00:13:00,179 --> 00:13:02,381 CHARACTERISTICS OR WHAT ARE THE 347 00:13:02,448 --> 00:13:03,883 MOST LIKELY DRIVERS OF 348 00:13:03,949 --> 00:13:04,783 PANCREATIC DISEASE? 349 00:13:04,850 --> 00:13:07,553 THEY ARE GOING TO BE THINGS LIKE 350 00:13:07,620 --> 00:13:09,922 SMOKING AND DRINKING, AND DRUG 351 00:13:09,989 --> 00:13:12,458 USE, OBESITY ARE GOING TO BE THE 352 00:13:12,525 --> 00:13:13,559 BIGGEST DRIVERS THAT HAVE BEEN 353 00:13:13,626 --> 00:13:15,928 ASSOCIATED WITH THE DISEASE 354 00:13:15,995 --> 00:13:16,162 ALREADY. 355 00:13:16,228 --> 00:13:17,696 AND SO ONE ADVANTAGE WITH 356 00:13:17,763 --> 00:13:18,697 WORKING IN A CHILDREN'S 357 00:13:18,764 --> 00:13:21,100 POPULATION IS WE HAVE TO WORRY A 358 00:13:21,167 --> 00:13:23,502 LOT LESS ABOUT THE IMPACT OF 359 00:13:23,569 --> 00:13:28,107 DRUG USE, IMPACT OF DRUGS AND 360 00:13:28,174 --> 00:13:29,775 ALCOHOL, ON THEIR LIKELIHOOD OF 361 00:13:29,842 --> 00:13:30,943 GETTING THE DISEASE, AND WE ALSO 362 00:13:31,010 --> 00:13:32,811 HAVE TO WORRY A LITTLE BIT LESS 363 00:13:32,878 --> 00:13:34,146 ABOUT OBESITY BEING AN ISSUE. 364 00:13:34,213 --> 00:13:35,548 WE DON'T HAVE TO WORRY QUITE SO 365 00:13:35,614 --> 00:13:37,349 MUCH ABOUT AGE BEING AN ISSUE, 366 00:13:37,416 --> 00:13:39,385 BECAUSE THE OLDER YOU ARE, THE 367 00:13:39,451 --> 00:13:45,191 MORE LIKELY YOU'RE GOING TO 368 00:13:45,257 --> 00:13:45,424 PRESENT. 369 00:13:45,491 --> 00:13:46,058 SO, THERE'S SOME REAL 370 00:13:46,125 --> 00:13:47,193 INTERESTING ADVANTAGES TO BEING 371 00:13:47,259 --> 00:13:50,229 ABLE TO WORK WITH THIS DISEASE 372 00:13:50,296 --> 00:13:52,965 IN CHILDREN, IN THAT WE CAN HONE 373 00:13:53,032 --> 00:13:53,933 IN SPECIFICALLY ON MAYBE 374 00:13:53,999 --> 00:13:54,833 POTENTIAL MARKERS THAT ARE 375 00:13:54,900 --> 00:13:56,802 UNIQUE TO THE DISEASE AND NOT 376 00:13:56,869 --> 00:14:00,105 UNIQUE TO THE PHENOTYPE ITSELF. 377 00:14:00,172 --> 00:14:03,275 OR THE OTHER ASSOCIATED 378 00:14:03,342 --> 00:14:03,709 MALADIES. 379 00:14:03,776 --> 00:14:06,245 SO, THE OTHER ASPECT OF THIS WAS 380 00:14:06,312 --> 00:14:08,314 THAT WE WANTED TO CONTROL THIS 381 00:14:08,380 --> 00:14:11,483 EXPERIMENT FOR A VARIETY OF 382 00:14:11,550 --> 00:14:12,251 DIFFERENT TYPES OF DISEASE 383 00:14:12,318 --> 00:14:14,220 STATES AS WELL. 384 00:14:14,286 --> 00:14:16,855 SO, RATHER THAN JUST GET ACUTE 385 00:14:16,922 --> 00:14:18,290 PANCREATITIS INDIVIDUALS AND 386 00:14:18,357 --> 00:14:19,725 MATCH THEM WITH CONTROLS, WE 387 00:14:19,792 --> 00:14:21,894 ACTUALLY WANTED TO MATCH THEM 388 00:14:21,961 --> 00:14:23,162 WITH TWO ADDITIONAL DIFFERENT 389 00:14:23,229 --> 00:14:24,330 TYPES OF CONTROLS. 390 00:14:24,396 --> 00:14:26,832 SO, ONE OF THEM, WE WANTED TO 391 00:14:26,899 --> 00:14:28,367 CONTROL AROUND FOR PANCREATIC 392 00:14:28,434 --> 00:14:29,802 DISEASE IN GENERAL, RIGHT? 393 00:14:29,868 --> 00:14:33,172 SO WE WANTED TO HAVE A CHRONIC 394 00:14:33,239 --> 00:14:34,273 PANCREATITIS COHORT AS WELL 395 00:14:34,340 --> 00:14:37,243 AS -- OR PART OF OUR COHORT, AS 396 00:14:37,309 --> 00:14:38,544 WELL AS THE ACUTE PANCREATITIS 397 00:14:38,611 --> 00:14:40,179 SECTION OF OUR COHORT. 398 00:14:40,246 --> 00:14:41,380 SO, WE COULD CONTRAST THE TWO OF 399 00:14:41,447 --> 00:14:43,148 THEM AND FIND OUT WHAT WAS 400 00:14:43,215 --> 00:14:45,417 UNIQUE TO EACH ONE OF THOSE. 401 00:14:45,484 --> 00:14:47,052 WE ALSO, YOU KNOW, THESE 402 00:14:47,119 --> 00:14:48,387 INDIVIDUALS, THEY ARE IN PAIN, 403 00:14:48,454 --> 00:14:49,154 RIGHT? 404 00:14:49,221 --> 00:14:52,191 SO WE ALSO WANTED A PAIN CONTROL 405 00:14:52,258 --> 00:14:54,260 AS WELL BECAUSE WE KNOW THERE 406 00:14:54,326 --> 00:14:56,262 ARE OTHER MARKERS FOR PAIN THAT 407 00:14:56,328 --> 00:14:57,896 CIRCULATE IN BLOOD AND IN URINE, 408 00:14:57,963 --> 00:14:59,465 AND WE WANTED TO MAKE SURE THAT 409 00:14:59,531 --> 00:15:00,766 WE WEREN'T LOOKING AT SOMETHING 410 00:15:00,833 --> 00:15:01,834 THAT WAS JUST ASSOCIATED WITH 411 00:15:01,900 --> 00:15:02,067 PAIN. 412 00:15:02,134 --> 00:15:06,872 SO WE ALSO HAD A SECTION OF OUR 413 00:15:06,939 --> 00:15:09,408 COHORT THAT WAS BROUGHT INTO THE 414 00:15:09,475 --> 00:15:10,509 HOSPITAL FOR EXTREMITY FRACTURE, 415 00:15:10,576 --> 00:15:13,779 SO BROKEN ARM OR BROKEN LEG, AND 416 00:15:13,846 --> 00:15:16,715 SO FOR THAT WE HAD A COHORT THAT 417 00:15:16,782 --> 00:15:19,685 WAS NOT EXCEPTIONALLY LARGE, 418 00:15:19,752 --> 00:15:19,885 RIGHT? 419 00:15:19,952 --> 00:15:24,490 OUR COHORT HERE IS AROUND 120, 420 00:15:24,556 --> 00:15:24,957 130 INDIVIDUALS HERE. 421 00:15:25,024 --> 00:15:25,958 130 INDIVIDUALS. 422 00:15:26,025 --> 00:15:29,728 OF WHICH WE HAD 28 THAT WERE 423 00:15:29,795 --> 00:15:31,397 ACUTE PANCREATITIS, AND 50 424 00:15:31,463 --> 00:15:32,798 CHRONIC PANCREATITIS, THE REST 425 00:15:32,865 --> 00:15:34,566 REMAINED FOR THE OTHER CONTROLS. 426 00:15:34,633 --> 00:15:38,604 BUT WE WERE DOING SORT OF MORE 427 00:15:38,671 --> 00:15:39,405 CLASSICAL BIOMARKER DISCOVERY 428 00:15:39,471 --> 00:15:40,572 FOR THESE. 429 00:15:40,639 --> 00:15:42,374 WE ALSO WANTED TO FOCUS ON 430 00:15:42,441 --> 00:15:45,244 CONTROLLING FOR A BUNCH OF OTHER 431 00:15:45,311 --> 00:15:47,046 TYPES OF VARIABLES, SO AS I 432 00:15:47,112 --> 00:15:50,215 SAID, OBESITY IS ASSOCIATE D 433 00:15:50,282 --> 00:15:51,984 WITH THE DISEASE, WE WANTED TO 434 00:15:52,051 --> 00:15:53,485 CONTROL FOR BMI, MAKE SURE THEIR 435 00:15:53,552 --> 00:15:56,555 AGE WAS ABOUT THE SAME AGE 436 00:15:56,622 --> 00:15:57,122 RANGE, IF POSSIBLE. 437 00:15:57,189 --> 00:15:59,158 THEIR HEIGHT AND WEIGHT WERE 438 00:15:59,224 --> 00:16:01,160 ABOUT THE SAME HEIGHT AND WEIGHT 439 00:16:01,226 --> 00:16:01,460 AS POSSIBLE. 440 00:16:01,527 --> 00:16:04,430 WE WERE ABLE TO REALLY WELL 441 00:16:04,496 --> 00:16:05,864 CONTROL I THINK FOR BMI, HEIGHT 442 00:16:05,931 --> 00:16:06,432 AND WEIGHT. 443 00:16:06,498 --> 00:16:08,500 BUT ONE OF THE THINGS THAT WAS 444 00:16:08,567 --> 00:16:10,302 SORT OF IMMEDIATELY SURPRISING 445 00:16:10,369 --> 00:16:12,104 TO US WAS ACTUALLY THE SORT OF 446 00:16:12,171 --> 00:16:16,041 STRUCTURE OF THE COHORT ITSELF. 447 00:16:16,108 --> 00:16:17,142 SO, TYPICALLY WHENEVER I'M GIVEN 448 00:16:17,209 --> 00:16:18,544 AN EXPERIMENT WHERE THERE'S A 449 00:16:18,610 --> 00:16:20,212 POTENTIAL COHORT FOR ME TO 450 00:16:20,279 --> 00:16:23,248 STUDY, BEFORE I'M EVEN GOING TO 451 00:16:23,315 --> 00:16:26,118 ACTUALLY TRY TO DIG INTO WHETHER 452 00:16:26,185 --> 00:16:27,753 THIS IS -- WHETHER I'M GOING TO 453 00:16:27,820 --> 00:16:28,587 MAKE MEASUREMENTS OR NOT TO 454 00:16:28,654 --> 00:16:30,155 BEGIN WITH, I WANT TO HAVE SOME 455 00:16:30,222 --> 00:16:31,357 UNDERSTANDING OF THE COHORT 456 00:16:31,423 --> 00:16:31,590 ITSELF. 457 00:16:31,657 --> 00:16:33,959 SO THE FIRST THING I DID WAS TRY 458 00:16:34,026 --> 00:16:38,230 TO SEE WERE THERE DRIVERS OR 459 00:16:38,297 --> 00:16:39,264 SEPARATIONS INSIDE THE COHORT 460 00:16:39,331 --> 00:16:40,099 CONFOUNDING FACTORS THAT MIGHT 461 00:16:40,165 --> 00:16:41,100 BE A PROBLEM. 462 00:16:41,166 --> 00:16:42,935 ONE OF THE ONES THAT WAS 463 00:16:43,001 --> 00:16:43,736 SURPRISING TO US, UP FRONT, WAS 464 00:16:43,802 --> 00:16:46,672 EVEN WHEN WE TRIED TO CONTROL 465 00:16:46,739 --> 00:16:49,742 FOR AGE AND FOR SEX, WHAT WE 466 00:16:49,808 --> 00:16:51,110 FOUND WERE THAT THERE WAS A 467 00:16:51,176 --> 00:16:54,113 LITTLE BIT OF A DEVIATION IN AGE 468 00:16:54,179 --> 00:16:57,015 AND SEX AS A COMBINED VARIABLE. 469 00:16:57,082 --> 00:16:58,550 THIS WAS SOMETHING THAT WAS SORT 470 00:16:58,617 --> 00:17:03,355 OF SURPRISING TO US, BUT IT 471 00:17:03,422 --> 00:17:05,457 SEEMED LIKE ACUTE PANCREATITIS 472 00:17:05,524 --> 00:17:07,292 AND CHRONIC PANCREATITIS FEMALES 473 00:17:07,359 --> 00:17:09,361 TENDED TO PRESENT SLIGHTLY LATER 474 00:17:09,428 --> 00:17:12,097 THAN OUR MALE COHORTS, SO WE 475 00:17:12,164 --> 00:17:12,865 WERE MATCHING SPECIFICALLY BASED 476 00:17:12,931 --> 00:17:14,733 ON SORT OF THE EXPECTED AVERAGE 477 00:17:14,800 --> 00:17:15,033 RANGE. 478 00:17:15,100 --> 00:17:16,835 AND WE FOUND THAT THERE WAS 479 00:17:16,902 --> 00:17:19,638 ACTUALLY SOME DEVIATION HERE. 480 00:17:19,705 --> 00:17:21,507 SO THESE FEMALES ENDED UP BEING 481 00:17:21,573 --> 00:17:22,508 A LITTLE BIT OLDER AS WELL. 482 00:17:22,574 --> 00:17:25,711 SO THIS WAS SOMETHING WE HAD TO 483 00:17:25,778 --> 00:17:28,113 CAREFULLY CONTROL FOR. 484 00:17:28,180 --> 00:17:29,848 BUT I RECOMMEND WHENEVER YOU'RE 485 00:17:29,915 --> 00:17:31,950 STARTING AN EXPERIMENT OF THESE 486 00:17:32,017 --> 00:17:33,118 TYPES OF NATURES, FIGURE OUT 487 00:17:33,185 --> 00:17:34,987 KIND OF ARE THERE OTHER 488 00:17:35,053 --> 00:17:36,221 POTENTIAL CONFOUNDING FACTORS 489 00:17:36,288 --> 00:17:37,990 BEFORE YOU EVEN BEGIN THE 490 00:17:38,056 --> 00:17:40,058 EXPERIMENT, BECAUSE NOW THIS IS 491 00:17:40,125 --> 00:17:41,794 SOMETHING WE CAN ACTUALLY START 492 00:17:41,860 --> 00:17:43,762 CONTROLLING THE EXPERIMENT 493 00:17:43,829 --> 00:17:45,497 AROUND. 494 00:17:45,564 --> 00:17:47,599 SO, WHEN WE DESIGNED THE -- SO 495 00:17:47,666 --> 00:17:48,901 WHEN WE DESIGNED THE EXPERIMENT 496 00:17:48,967 --> 00:17:51,537 TO BEGIN WITH, ON THE MASS SPEC, 497 00:17:51,603 --> 00:17:52,971 OUR SAMPLE ORDER ANALYSIS, FOR 498 00:17:53,038 --> 00:17:55,941 EXAMPLE, THE FIRST THING THAT WE 499 00:17:56,008 --> 00:17:58,577 DID WAS WE BLOCKED AROUND THIS 500 00:17:58,644 --> 00:18:00,412 PARTICULAR PROBLEM, ORGANIZED IT 501 00:18:00,479 --> 00:18:02,281 SUCH THAT WE DIDN'T HAVE LIKE 502 00:18:02,347 --> 00:18:06,018 ALL OF THE CHRONIC FEMALES AT A 503 00:18:06,084 --> 00:18:07,219 SPECIFIC SECTION IN OUR POOL. 504 00:18:07,286 --> 00:18:10,622 SO WE WERE ABLE TO KIND OF FOCUS 505 00:18:10,689 --> 00:18:13,659 IN ON SEPARATING THEM OUT BY AGE 506 00:18:13,725 --> 00:18:14,526 AS WELL. 507 00:18:14,593 --> 00:18:18,063 SO, THINKING ABOUT THESE THINGS 508 00:18:18,130 --> 00:18:20,132 AS PARTICULARLY PROBLEMATIC, AND 509 00:18:20,199 --> 00:18:23,335 WORTH TRYING TO INVESTIGATE. 510 00:18:25,103 --> 00:18:27,005 SO, FROM A DIAGNOSIS 511 00:18:27,072 --> 00:18:27,906 PERSPECTIVE, ACUTE PANCREATITIS 512 00:18:27,973 --> 00:18:29,208 IS A LITTLE BIT CHALLENGING TO 513 00:18:29,274 --> 00:18:29,641 DIAGNOSE. 514 00:18:29,708 --> 00:18:34,813 WE WANTED TO MAKE SURE WE HAD A 515 00:18:34,880 --> 00:18:38,984 REALLY COHERENT COHORT, AND SO 516 00:18:39,051 --> 00:18:41,086 WE HAD A LONG LIFT WITH ALL OF 517 00:18:41,153 --> 00:18:43,422 THE INDIVIDUALS, ALL OF THE 518 00:18:43,489 --> 00:18:44,389 ACUTE PANCREATITIS INDIVIDUALS 519 00:18:44,456 --> 00:18:46,158 WHO WERE DIAGNOSED WITH IMAGING 520 00:18:46,225 --> 00:18:46,925 DATA AS WELL. 521 00:18:46,992 --> 00:18:53,565 SO WE WERE ABLE TO SAY, OKAY, 522 00:18:53,632 --> 00:18:54,266 WELL, THERE'S THESE INDIVIDUALS 523 00:18:54,333 --> 00:18:56,668 DEFINITELY HAVE IT NOT JUST 524 00:18:56,735 --> 00:18:58,670 BECAUSE OF ELEVATED LEVELS BUT 525 00:18:58,737 --> 00:19:00,372 ALSO BECAUSE THEY HAD MORE FLUID 526 00:19:00,439 --> 00:19:01,607 IN THE PANCREAS. 527 00:19:01,673 --> 00:19:04,076 YOU CAN SEE THAT HERE. 528 00:19:04,142 --> 00:19:05,711 THIS PANCREATIC BODY LOOKS MORE 529 00:19:05,777 --> 00:19:08,013 LIKE THE LIVER BUT OVER HERE 530 00:19:08,080 --> 00:19:09,781 IT'S A BIT DARKER IN THE ACUTE 531 00:19:09,848 --> 00:19:10,616 PANCREATITIS INDIVIDUALS, THAT 532 00:19:10,682 --> 00:19:14,820 MEANS MORE FLUID IN THE PANCREAS 533 00:19:14,887 --> 00:19:16,889 AND IT'S SWOLLEN A LITTLE BIT. 534 00:19:16,955 --> 00:19:18,090 WE USED THIS IMAGING AS 535 00:19:18,156 --> 00:19:20,526 VALIDATION FOR TRYING TO MAKE 536 00:19:20,592 --> 00:19:23,195 MEASUREMENTS. 537 00:19:25,697 --> 00:19:28,800 SO, FOR THIS TYPE OF WORK, WE 538 00:19:28,867 --> 00:19:30,168 WERE INTERESTED IN TRYING TO DO 539 00:19:30,235 --> 00:19:33,071 ANALYSIS OF IT TO TRY TO 540 00:19:33,138 --> 00:19:33,739 IDENTIFY POTENTIAL PROTEINS THAT 541 00:19:33,805 --> 00:19:36,708 WOULD BE INTERESTING FOR MAKING 542 00:19:36,775 --> 00:19:37,276 MEASUREMENT. 543 00:19:37,342 --> 00:19:40,746 AND AS AN ANALYTICAL CHEMIST, I 544 00:19:40,812 --> 00:19:42,414 WANTED TO APPROACH THIS PROBLEM 545 00:19:42,481 --> 00:19:46,552 FROM A SLIGHTLY DIFFERENT 546 00:19:46,618 --> 00:19:49,521 PERSPECTIVE THAN A NORMAL 547 00:19:49,588 --> 00:19:50,289 MEASUREMENT PERSPECTIVE. 548 00:19:50,355 --> 00:19:52,090 AND SO JUST TO KIND OF PUT 549 00:19:52,157 --> 00:19:53,392 EVERYONE ON THE SAME FRAMEWORK, 550 00:19:53,458 --> 00:19:57,162 I WANT TO TALK ABOUT WHAT A 551 00:19:57,229 --> 00:19:58,263 NORMAL PROTEOMIC EXPERIMENT 552 00:19:58,330 --> 00:20:01,300 TYPICALLY IS. 553 00:20:01,366 --> 00:20:05,904 YOU GUYS HAVE ALL DONE 554 00:20:05,971 --> 00:20:06,572 PROTEOMICS EXPERIMENTS BEFORE, 555 00:20:06,638 --> 00:20:07,773 OR MASS SPECTROMETRY EXPERIMENT. 556 00:20:07,839 --> 00:20:09,875 AND SO JUST TO KIND OF REFRESH 557 00:20:09,942 --> 00:20:11,710 YOUR BRAINS, LIKE THE MOST 558 00:20:11,777 --> 00:20:13,312 COMMON APPROACH TO TRYING TO DO 559 00:20:13,378 --> 00:20:16,548 MASS SPECTROMETRY IS TO DO 560 00:20:16,615 --> 00:20:20,485 DATA-DEPENDENT ACQUISITION. 561 00:20:20,552 --> 00:20:23,221 WHEN YOU'RE THINKING ABOUT 562 00:20:23,288 --> 00:20:23,989 ACQUISITION YOU'RE SEPARATING 563 00:20:24,056 --> 00:20:25,390 PEPTIDES ACROSS RETENTION TIME. 564 00:20:25,457 --> 00:20:26,825 EACH IS A DIFFERENT PEPTIDE 565 00:20:26,892 --> 00:20:29,127 ELUDING OVER TIME AND YOU CAN 566 00:20:29,194 --> 00:20:32,931 SEE THE RISE AND FALL OF THAT 567 00:20:32,998 --> 00:20:34,600 PARTICULAR PEPTIDE IN THAT 568 00:20:34,666 --> 00:20:34,900 DATASET. 569 00:20:34,967 --> 00:20:37,002 SO, AS THE INSTRUMENT IS GOING 570 00:20:37,069 --> 00:20:39,004 ALONG, IT'S CHUNKING THROUGH 571 00:20:39,071 --> 00:20:41,273 TIME, COLLECTING THESE PRECURSOR 572 00:20:41,340 --> 00:20:41,473 SCANS. 573 00:20:41,540 --> 00:20:43,241 AND WAITS FOR ONE OF THESE PEAKS 574 00:20:43,308 --> 00:20:45,444 TO RISE ABOVE A CERTAIN 575 00:20:45,510 --> 00:20:45,777 THRESHOLD. 576 00:20:45,844 --> 00:20:47,746 ONCE IT RISES ABOVE THE 577 00:20:47,813 --> 00:20:49,815 THRESHOLD WE COLLECT A 578 00:20:49,881 --> 00:20:51,783 SEQUENCING SPECTRUM FOR THAT 579 00:20:51,850 --> 00:20:53,452 PARTICULAR PEPTIDE, AND WE STICK 580 00:20:53,518 --> 00:20:54,987 IT ON AN EXCLUSION LIST. 581 00:20:55,053 --> 00:20:57,723 WE'VE MEASURED THIS PEPTIDE, 582 00:20:57,789 --> 00:21:00,525 DON'T NEED TO MEASURE IT AGAIN. 583 00:21:00,592 --> 00:21:01,693 SO WE'LL PUT IT ON AN EXCLUSION 584 00:21:01,760 --> 00:21:03,161 LIST FOR A CERTAIN PERIOD OF 585 00:21:03,228 --> 00:21:03,595 TIME. 586 00:21:03,662 --> 00:21:05,063 THEN THE INSTRUMENT WILL GO ON 587 00:21:05,130 --> 00:21:08,967 THE NEXT ONE, PICK THE NEXT MOST 588 00:21:09,034 --> 00:21:11,503 ABUNDANT SCAN, THAT'S THE NEXT 589 00:21:11,570 --> 00:21:17,509 ONE I'M GOING SEQUENCING 590 00:21:17,576 --> 00:21:19,578 SPECTRUM FOR, AND ANOTHER AND 591 00:21:19,645 --> 00:21:21,013 ANOTHER, JUST TICKING THROUGH 592 00:21:21,079 --> 00:21:23,081 TIME, RIGHT? 593 00:21:23,148 --> 00:21:24,282 SO, THIS APPROACH IS EFFECTIVE 594 00:21:24,349 --> 00:21:27,819 AS TRYING TO DIG DEEPLY INTO A 595 00:21:27,886 --> 00:21:29,988 PARTICULAR EXPERIMENT, BECAUSE 596 00:21:30,055 --> 00:21:31,790 IT USES EXCLUSION AS A WAY TO 597 00:21:31,857 --> 00:21:33,692 SAY I DON'T NEED TO SAMPLE THIS 598 00:21:33,759 --> 00:21:35,327 THING OVER AND OVER AGAIN, I 599 00:21:35,394 --> 00:21:41,333 JUST WANT TO MEASURE ONCE AND BE 600 00:21:41,400 --> 00:21:42,134 DONE WIT. 601 00:21:42,200 --> 00:21:43,101 THE INSTRUMENT MAKES A LOT OF 602 00:21:43,168 --> 00:21:44,636 DECISIONS AS PART OF THE 603 00:21:44,703 --> 00:21:45,404 PROCESS. 604 00:21:45,470 --> 00:21:47,272 OKAY, THIS IS MOST ABUNDANT PEAK 605 00:21:47,339 --> 00:21:50,542 AT THIS SPECIFIC TIME AND 606 00:21:50,609 --> 00:21:51,543 CONSEQUENTLY THERE'S SOME 607 00:21:51,610 --> 00:21:53,045 STOCHASTICITY BUILD INTO THE 608 00:21:53,111 --> 00:21:53,278 SYSTEM. 609 00:21:53,345 --> 00:21:57,416 SO, MY LAB HAS BEEN FOCUSING ON 610 00:21:57,482 --> 00:21:58,750 DATA INDEPENDENT ACQUISITION AS 611 00:21:58,817 --> 00:22:01,920 A MODALITY FOR MAKING 612 00:22:01,987 --> 00:22:09,594 MEASUREMENTS, SO WITH 613 00:22:09,661 --> 00:22:10,395 DATA-INDEPENDENT ACQUISITION, WE 614 00:22:10,462 --> 00:22:11,496 SELECT RANGES TO MAKE SEQUENCING 615 00:22:11,563 --> 00:22:12,130 SCANS FOR. 616 00:22:12,197 --> 00:22:20,005 WE'VE GOT A RANGE OF 500 TO 525, 617 00:22:20,072 --> 00:22:21,573 ANOTHER 525 TO 550, TAKING THOSE 618 00:22:21,640 --> 00:22:22,974 RANGES, INSTEAD OF SELECTING 619 00:22:23,041 --> 00:22:25,510 INDIVIDUAL PEPTIDES FOR MAKING 620 00:22:25,577 --> 00:22:26,511 MEASUREMENT, WE'RE 621 00:22:26,578 --> 00:22:27,045 CO-FRAGMENTING THEM. 622 00:22:27,112 --> 00:22:29,781 SO AT EACH TIME POINT WE'RE 623 00:22:29,848 --> 00:22:31,516 MAKING ANOTHER SEQUENCING SCAN 624 00:22:31,583 --> 00:22:33,385 OVER AND OVER AGAIN. 625 00:22:33,452 --> 00:22:35,353 AND SO I COLOR-CODED THESE 626 00:22:35,420 --> 00:22:37,022 PEPTIDE PEAKS ASSOCIATED WITH 627 00:22:37,089 --> 00:22:38,190 THE PRECURSORS THAT THEY COME 628 00:22:38,256 --> 00:22:41,727 FROM, BUT EACH ONE OF THESE IS A 629 00:22:41,793 --> 00:22:43,595 FRAGMENT ION SIMILAR TO FRAGMENT 630 00:22:43,662 --> 00:22:45,530 IONS HERE, JUST ACQUIRED OVER 631 00:22:45,597 --> 00:22:45,864 TIME. 632 00:22:45,931 --> 00:22:47,733 AND BECAUSE WE SEE THE RISE AND 633 00:22:47,799 --> 00:22:49,601 FALL OF THAT PRECURSOR PEAK, WE 634 00:22:49,668 --> 00:22:51,803 SHOULD SIMILARLY SEE A RISE AND 635 00:22:51,870 --> 00:22:54,506 FALL OF THE FRAGMENT ION PEAKS 636 00:22:54,573 --> 00:22:56,508 AS WELL, RIGHT? 637 00:22:56,575 --> 00:22:58,577 AND SO WE ARE CO-FRAGMENTS 638 00:22:58,643 --> 00:22:59,778 MULTIPLE PEPTIDES TOGETHER AT 639 00:22:59,845 --> 00:23:02,514 THE SAME TIME WHICH MAKES FOR 640 00:23:02,581 --> 00:23:04,483 FAIRLY COMPLICATED SPECTRA. 641 00:23:04,549 --> 00:23:07,319 IF YOU INVESTIGATE ANY ONE OF 642 00:23:07,385 --> 00:23:09,087 THESE SPECTRA THEY SEEM TO BE 643 00:23:09,154 --> 00:23:10,522 EXTREMELY MESSY AND DIFFICULT TO 644 00:23:10,589 --> 00:23:13,358 INTERPRET USING SORT OF MORE 645 00:23:13,425 --> 00:23:13,792 STANDARD APPROACHES. 646 00:23:13,859 --> 00:23:15,994 AND IT BECOMES KIND OF AN 647 00:23:16,061 --> 00:23:18,830 INFORMATIC PROBLEM TO TRY TO 648 00:23:18,897 --> 00:23:22,234 TEASE APART SORT OF WHAT PEAKS 649 00:23:22,300 --> 00:23:26,037 ARE ASSOCIATED WITH ONE PEPTIDE 650 00:23:26,104 --> 00:23:27,172 OVER ANOTHER PEPTIDE, RIGHT? 651 00:23:27,239 --> 00:23:28,240 AND SO, FROM THIS PARTICULAR 652 00:23:28,306 --> 00:23:29,674 CASE WE CAN SAY, OKAY, WELL, 653 00:23:29,741 --> 00:23:31,009 THESE BLUE PEAKS ARE ASSOCIATED 654 00:23:31,076 --> 00:23:32,978 WITH THIS PEPTIDE WHILE THE RED 655 00:23:33,044 --> 00:23:34,179 PEAKS ARE ACTUALLY ASSOCIATED 656 00:23:34,246 --> 00:23:36,548 WITH SOMETHING THAT'S COMPLETELY 657 00:23:36,615 --> 00:23:37,249 DIFFERENT. 658 00:23:37,315 --> 00:23:40,185 SOMETHING THAT'S NOISE ORIENTED. 659 00:23:40,252 --> 00:23:42,921 AND SO THE WAY IN WHICH WE TEND 660 00:23:42,988 --> 00:23:44,589 TO TALK ABOUT THIS DATA, LOOK AT 661 00:23:44,656 --> 00:23:47,192 THIS DATA, SORT OF HEAD-ON. 662 00:23:47,259 --> 00:23:49,294 WE LOOK AT THE RISE AND FALL OF 663 00:23:49,361 --> 00:23:50,695 THOSE SPECIFIC PEAKS, AND WE 664 00:23:50,762 --> 00:23:53,365 LOOK AT THEM AS CHROMATOGRAMS, 665 00:23:53,431 --> 00:23:54,766 ACROSS RETENTION TIME RATHER 666 00:23:54,833 --> 00:23:56,168 THAN ACROSS MASS SPACE SO THE 667 00:23:56,234 --> 00:23:59,337 INTERPRETATION OF THIS DATA IS A 668 00:23:59,404 --> 00:24:03,108 LITTLE BIT DIFFERENT THAN -- SO 669 00:24:03,175 --> 00:24:04,943 WHEN I SHOW DATA IT WILL BE A 670 00:24:05,010 --> 00:24:06,044 LITTLE BIT DIFFERENT THAN USUAL. 671 00:24:06,111 --> 00:24:10,015 THE ONE BIG ADVANTAGE TO THIS 672 00:24:10,081 --> 00:24:11,416 TYPE OF APPROACH IS THAT IT 673 00:24:11,483 --> 00:24:13,518 ALLOWS US TO KIND OF MAKE 674 00:24:13,585 --> 00:24:14,586 MEASUREMENTS OF PEPTIDES THAT 675 00:24:14,653 --> 00:24:16,354 ARE CHALLENGING TO MAKE 676 00:24:16,421 --> 00:24:16,721 MEASUREMENTS OF. 677 00:24:16,788 --> 00:24:20,091 SO, FOR EXAMPLE, UP HERE WITH 678 00:24:20,158 --> 00:24:22,027 DATA-DEPENDENT ACQUISITION THESE 679 00:24:22,093 --> 00:24:23,261 TWO PEAKS NEVER ROSE ABOVE 680 00:24:23,328 --> 00:24:24,896 THRESHOLD FOR MAKING A 681 00:24:24,963 --> 00:24:25,430 MEASUREMENT. 682 00:24:25,497 --> 00:24:27,833 AND THEY WOULD NEVER GET 683 00:24:27,899 --> 00:24:28,066 SCANNED. 684 00:24:28,133 --> 00:24:29,267 WHILE IN ANOTHER SAMPLE YOU 685 00:24:29,334 --> 00:24:32,237 MIGHT SEE THEM RISE ABOVE THAT 686 00:24:32,304 --> 00:24:33,104 THRESHOLD, COLLECT MEASUREMENT 687 00:24:33,171 --> 00:24:33,872 FOR THEM. 688 00:24:33,939 --> 00:24:36,541 HERE WE'RE GOING TO FRAGMENT 689 00:24:36,608 --> 00:24:38,243 THOSE SPECIFIC PEAKS, NO MATTER 690 00:24:38,310 --> 00:24:38,710 WHAT. 691 00:24:38,777 --> 00:24:40,412 EVEN IF IT'S VERY LOW INTENSITY, 692 00:24:40,478 --> 00:24:42,280 WE SHOULD STILL SEE SOMETHING OF 693 00:24:42,347 --> 00:24:43,815 A SIGNATURE FOR IT. 694 00:24:43,882 --> 00:24:46,451 AND THIS GIVES US A WAY OR SOME 695 00:24:46,518 --> 00:24:49,287 VISIBILITY TO SEE THAT 696 00:24:49,354 --> 00:24:51,456 SIGNATURE, EVEN IF THAT 697 00:24:51,523 --> 00:24:52,357 SIGNATURE IS DEEP IN THE NOISE. 698 00:24:52,424 --> 00:24:54,860 WE TEND TO THINK OF THIS TYPE OF 699 00:24:54,926 --> 00:24:56,094 MEASUREMENT WHERE WE'RE 700 00:24:56,161 --> 00:24:58,263 COLLECTING THIS GLOBAL DATA HERE 701 00:24:58,330 --> 00:24:59,564 OF FRAGMENTATION ACROSS ALL TIME 702 00:24:59,631 --> 00:25:03,401 AS KIND OF A BEAUTIFUL PICTURE, 703 00:25:03,468 --> 00:25:03,602 RIGHT? 704 00:25:03,668 --> 00:25:07,339 AS A MONA LISA HERE, RIGHT? 705 00:25:07,405 --> 00:25:10,075 IN REALITY, LIKE AS A PICTURE OF 706 00:25:10,141 --> 00:25:12,510 THE ENTIRE PORTRAIT OF THE 707 00:25:12,577 --> 00:25:14,813 LANDSCAPE OF THAT SPECIFIC 708 00:25:14,880 --> 00:25:15,881 IMAGE, MAPPING EVERY PARTICULAR 709 00:25:15,947 --> 00:25:18,516 PIXEL FOR IT, IN REALITY THESE 710 00:25:18,583 --> 00:25:20,585 TEND TO BE REALLY MUDDY, RIGHT? 711 00:25:20,652 --> 00:25:21,987 THE MEASUREMENTS THEMSELVES 712 00:25:22,053 --> 00:25:23,555 TENDING TO REALLY MUDDY BECAUSE 713 00:25:23,622 --> 00:25:25,957 OF ALL OF THE OTHER PEPTIDES 714 00:25:26,024 --> 00:25:27,792 THAT ARE PRESENT AT EXACTLY THE 715 00:25:27,859 --> 00:25:28,059 SAME TIME. 716 00:25:28,126 --> 00:25:29,995 FOR EXAMPLE, HERE WE HAVE TO 717 00:25:30,061 --> 00:25:32,964 TELL THIS BLUE PEAK IS SEPARATE 718 00:25:33,031 --> 00:25:34,032 FROM THIS PURPLE PEAK, SEPARATE 719 00:25:34,099 --> 00:25:36,268 FROM THE PINK PEAK. 720 00:25:36,334 --> 00:25:38,236 SEE ALL OF THESE DIFFERENT 721 00:25:38,303 --> 00:25:39,337 PIXELS ARE BLENDED TOGETHER, WE 722 00:25:39,404 --> 00:25:41,206 END UP WITH A REALLY BLURRY 723 00:25:41,273 --> 00:25:41,706 IMAGE. 724 00:25:41,773 --> 00:25:43,808 IT WOULD BE TRICKY TO TELL WHICH 725 00:25:43,875 --> 00:25:45,010 FRAGMENT IONS ARE ASSOCIATED 726 00:25:45,076 --> 00:25:47,345 WITH THAT PEPTIDE BUT ALSO WHICH 727 00:25:47,412 --> 00:25:48,413 FRAGMENT IONS ARE QUANTITATED 728 00:25:48,480 --> 00:25:49,614 FOR THAT PEPTIDE BECAUSE THEY 729 00:25:49,681 --> 00:25:51,483 MAY BE ASSOCIATED WITH MULTIPLE 730 00:25:51,549 --> 00:25:53,118 PEPTIDES AT THE SAME TIME. 731 00:25:53,184 --> 00:25:59,157 AND SO, ONE OF THE APPROACHES TO 732 00:25:59,224 --> 00:26:01,426 DEAL WITH THAT IS ONE THAT I'M 733 00:26:01,493 --> 00:26:03,194 GOING TO TALK ABOUT THIS NEXT 734 00:26:03,261 --> 00:26:03,561 BIT. 735 00:26:03,628 --> 00:26:05,263 AND I WANT TO TALK ABOUT THIS 736 00:26:05,330 --> 00:26:09,968 FROM THE STANDPOINT OF DOING AN 737 00:26:10,035 --> 00:26:15,707 ANALYSIS USING WHAT WE CALL GAS 738 00:26:15,774 --> 00:26:16,308 PHASE FRACTIONATION, ANALOGOUS 739 00:26:16,374 --> 00:26:17,008 TO THE MEASUREMENT WE MADE 740 00:26:17,075 --> 00:26:17,475 BEFORE. 741 00:26:17,542 --> 00:26:23,248 SO THIS IS A PRECURSOR SCAN FROM 742 00:26:23,315 --> 00:26:24,582 400 TO, SAY, 1,000. 743 00:26:24,649 --> 00:26:26,318 AND THESE ARE THE DIFFERENT 744 00:26:26,384 --> 00:26:28,086 FRAGMENT ION SCANS WE'LL COLLECT 745 00:26:28,153 --> 00:26:29,621 ALONG THE WAY BEFORE WE HIT 746 00:26:29,688 --> 00:26:31,156 ANOTHER CYCLE TO MAKE ANOTHER 747 00:26:31,222 --> 00:26:31,589 MEASUREMENT. 748 00:26:31,656 --> 00:26:31,790 OKAY? 749 00:26:31,856 --> 00:26:34,292 SO THIS WOULD BE KIND OF LIKE 750 00:26:34,359 --> 00:26:36,061 THE STRUCTURE OF OUR DIA 751 00:26:36,127 --> 00:26:36,361 EXPERIMENT. 752 00:26:36,428 --> 00:26:42,634 SO IN THIS PARTICULAR STRUCTURE, 753 00:26:42,701 --> 00:26:45,370 WE'RE USING 24 M/Z WINDOWS, IN 754 00:26:45,437 --> 00:26:49,641 OUR MEASUREMENTS USING SOMETHING 755 00:26:49,708 --> 00:26:52,610 AKIN TO 16 M/Z WIDE WINDOWS, 756 00:26:52,677 --> 00:26:54,679 STAGGERED TO OFF SET BY A 757 00:26:54,746 --> 00:26:54,946 FRACTION. 758 00:26:55,013 --> 00:26:56,114 ANOTHER MODALITY TO TRY TO MAKE 759 00:26:56,181 --> 00:26:57,515 A MEASUREMENT OF THIS WOULD BE 760 00:26:57,582 --> 00:26:59,918 TO TAKE THAT SAME SAMPLE AND 761 00:26:59,985 --> 00:27:01,453 RATHER THAN ANALYZE THE FULL 762 00:27:01,519 --> 00:27:03,521 PROFILE OF WHERE YOU FIND 763 00:27:03,588 --> 00:27:08,526 PEPTIDES, ANALYZE JUST A 764 00:27:08,593 --> 00:27:08,893 SUBSET. 765 00:27:08,960 --> 00:27:16,868 RATHER THAN 400 TO 1,000, 766 00:27:16,935 --> 00:27:20,805 MEASURE FROM 400 TO 500, LET'S 767 00:27:20,872 --> 00:27:24,542 DO IT WITH 4 M/Z WIDE WINDOWS, 768 00:27:24,609 --> 00:27:27,278 IF THEY ARE STAGRD, OFFSET BY 769 00:27:27,345 --> 00:27:30,315 50%, IT'S POSSIBLE USING 770 00:27:30,382 --> 00:27:30,849 MULTIPLEXING SOFTWARE TO 771 00:27:30,915 --> 00:27:32,617 INTERPRET LATE AS IF WE WERE 772 00:27:32,684 --> 00:27:36,554 DOING HALF OF THE WINDOW WIDTH. 773 00:27:36,621 --> 00:27:37,889 SO 2 M/Z WINDOWS. 774 00:27:37,956 --> 00:27:44,529 IF WE CAN GET DOWN TO TWO WE'VE 775 00:27:44,596 --> 00:27:46,865 COLLECTED THE SAME QUALITY DATA 776 00:27:46,931 --> 00:27:52,003 WITH DDA, SAME ISOLATION LEVEL 777 00:27:52,070 --> 00:27:53,171 AS DDA, BUT WE'RE COLLECTING 778 00:27:53,238 --> 00:27:54,939 OVER TIME SO YOU SEE EVERY 779 00:27:55,006 --> 00:27:56,908 POSSIBLE PEAK AT THE APEX AS 780 00:27:56,975 --> 00:27:57,475 WELL. 781 00:27:57,542 --> 00:28:02,814 SO IT'S REALLY AKIN TO PRM DATA. 782 00:28:02,881 --> 00:28:06,217 IT'S PRM DATA BUT WITH A GLOBAL 783 00:28:06,284 --> 00:28:07,318 PRM. 784 00:28:07,385 --> 00:28:08,253 PRM FOR EVERY POSSIBLE PEPTIDE 785 00:28:08,319 --> 00:28:10,355 SCANNED IN THIS SORT OF WAY. 786 00:28:10,422 --> 00:28:12,223 SO THAT OPENS UP SOME REALLY 787 00:28:12,290 --> 00:28:14,526 INTERESTING WAYS OF TRYING TO DO 788 00:28:14,592 --> 00:28:14,859 ANALYSIS. 789 00:28:14,926 --> 00:28:16,194 THIS IS EXPENSIVE, RIGHT? 790 00:28:16,261 --> 00:28:20,665 IF WE WANTED TO DO THIS ACROSS 791 00:28:20,732 --> 00:28:22,901 THE ENTIRE MASS, WE NEED TO RUN 792 00:28:22,967 --> 00:28:24,836 EVERY SIMPLE SIX TIMES. 793 00:28:24,903 --> 00:28:25,770 REALISTICALLY THERE'S NO WAY MY 794 00:28:25,837 --> 00:28:28,339 INSTRUMENT IS GOING TO WORK FOR 795 00:28:28,406 --> 00:28:33,378 SIX TIMES -- WE ENDED UP DOING 796 00:28:33,445 --> 00:28:34,913 150 MEASUREMENTS, NO WAY I CAN 797 00:28:34,979 --> 00:28:36,448 DO SIX TIMES THAT AND HAVE THE 798 00:28:36,514 --> 00:28:40,385 INSTRUMENT CONTINUE TO FUNCTION. 799 00:28:40,452 --> 00:28:40,652 YEAH? 800 00:28:40,718 --> 00:28:46,925 [ 801 00:28:46,991 --> 00:28:48,526 >> (INAUDIBLE). 802 00:28:48,593 --> 00:28:50,895 >> WE DEVELOPED ENCYCLOPEDIA 803 00:28:50,962 --> 00:28:53,264 SOFTWARE, ENCYCLOPEDIA IS A DIA 804 00:28:53,331 --> 00:28:57,068 SEARCH TOOL ANALOGOUS TO 805 00:28:57,135 --> 00:28:58,002 SOMETHING LIKE SPECTRUM, FOR 806 00:28:58,069 --> 00:28:59,437 EXAMPLE, OPEN SOURCED THAT MY 807 00:28:59,504 --> 00:29:00,138 LAB PRODUCES. 808 00:29:00,205 --> 00:29:02,040 THIS TOOL IS DESIGNED AROUND 809 00:29:02,107 --> 00:29:04,109 THIS TYPE OF EXPERIMENT 810 00:29:04,175 --> 00:29:04,509 MODALITY. 811 00:29:04,576 --> 00:29:05,977 NOW, BECAUSE IT'S OPEN SOURCE 812 00:29:06,044 --> 00:29:07,745 AND FREELY AVAILABLE TO 813 00:29:07,812 --> 00:29:10,515 EVERYONE, PEOPLE HAVE STARTED 814 00:29:10,582 --> 00:29:17,689 WRAPPING IT UP INTO OTHER TYPES 815 00:29:17,755 --> 00:29:20,258 OF SOFTAIRE. 816 00:29:20,325 --> 00:29:21,126 SCAFFOLD DIA USES ENCYCLOPEDIA 817 00:29:21,192 --> 00:29:22,393 UNDER THE COVERS. 818 00:29:22,460 --> 00:29:24,896 SKYLINE HAS A MODULE THAT RUNS 819 00:29:24,963 --> 00:29:26,131 ENCYCLOPEDIA IN THIS BACKGROUND 820 00:29:26,197 --> 00:29:29,100 SO THAT IT CAN DO PEAK PICKING 821 00:29:29,167 --> 00:29:34,873 AND ASSIGNMENT OUT OF DIA DATA. 822 00:29:34,939 --> 00:29:36,174 WE LIKE TO MAKE THIS POSSIBLE IN 823 00:29:36,241 --> 00:29:37,575 LOTS OF AVENUES. 824 00:29:37,642 --> 00:29:40,111 SO IT'S A REALLY POWERFUL 825 00:29:40,178 --> 00:29:41,646 TECHNIQUE AND SKYLINE HAS A 826 00:29:41,713 --> 00:29:44,582 REALLY NICE WORKFLOW FOR THIS 827 00:29:44,649 --> 00:29:46,651 SPECIFIC TYPE OF EXPERIMENT 828 00:29:46,718 --> 00:29:47,785 WHERE YOU'VE GOVERNMENT SIX GAS 829 00:29:47,852 --> 00:29:48,353 PHASE FRACTIONS. 830 00:29:48,419 --> 00:29:51,389 AS I SAID, IT'S A REALLY 831 00:29:51,456 --> 00:29:52,891 EXPENSIVE EXPERIMENT TO RUN. 832 00:29:52,957 --> 00:29:55,326 BECAUSE YOU HAVE TO RUN SIX 833 00:29:55,393 --> 00:29:56,161 INJECTIONS FOR EVERY TIME. 834 00:29:56,227 --> 00:29:58,062 BUT THE QUALITY OF THE DATA IS 835 00:29:58,129 --> 00:29:58,930 INCREDIBLE, RIGHT? 836 00:29:58,997 --> 00:30:01,766 SO IF WE GO BACK TO OUR SORT OF 837 00:30:01,833 --> 00:30:04,502 MOCKUP HERE, IF WE LOOK AT THE 838 00:30:04,569 --> 00:30:08,106 GAS PHASE FRACTIONATION WE HAVE 839 00:30:08,173 --> 00:30:13,578 NARROW WINDOWS, BECAUSE THEY ARE 840 00:30:13,645 --> 00:30:16,080 2 MZ WIDE APART AFTER 841 00:30:16,147 --> 00:30:17,749 DEMULTIPLEXING WE CAN GET EACH 842 00:30:17,815 --> 00:30:19,250 PEPTIDE IN ISOLATION AT EACH 843 00:30:19,317 --> 00:30:22,220 TIME POINT. 844 00:30:22,287 --> 00:30:23,621 WE'RE DOING TARGETED EXTRACTION 845 00:30:23,688 --> 00:30:25,089 FOR OUR PEPTIDES OF INTEREST, 846 00:30:25,156 --> 00:30:27,258 ABLE TO IDENTIFY THEM IN 847 00:30:27,325 --> 00:30:29,227 ISOLATION, WE KNOW EXACTLY WHAT 848 00:30:29,294 --> 00:30:30,895 FRAGMENTATION PATTERN THEY HAVE 849 00:30:30,962 --> 00:30:32,096 AND EXACTLY WHAT RETENTION TIME 850 00:30:32,163 --> 00:30:32,964 THEY HAVE. 851 00:30:33,031 --> 00:30:34,799 AND WE DO THIS FOR EVERY 852 00:30:34,866 --> 00:30:36,467 POSSIBLE PEPTIDE SO WE CAN TAKE 853 00:30:36,534 --> 00:30:38,002 WHICH EVER WINDOW WE'RE 854 00:30:38,069 --> 00:30:38,603 INTERESTED IN, MAKE 855 00:30:38,670 --> 00:30:40,271 IDENTIFICATIONS OUT OF IT AND 856 00:30:40,338 --> 00:30:44,976 HAVE A LIST OF IDENTIFICATIONS. 857 00:30:45,043 --> 00:30:45,243 SO, YEAH? 858 00:30:45,310 --> 00:30:55,587 >> (INAUDIBLE) 859 00:30:59,090 --> 00:31:00,124 >> POTENTIALLY YOU COULD. 860 00:31:00,191 --> 00:31:02,193 I WOULD SAY I WOULDN'T DO THE 861 00:31:02,260 --> 00:31:03,428 EXPERIMENT THAT WAY. 862 00:31:03,494 --> 00:31:05,230 IF I WERE USING -- THE QUESTION 863 00:31:05,296 --> 00:31:12,737 FOR THE PEOPLE ON ZOOM IS ABOUT 864 00:31:12,804 --> 00:31:14,038 USING TMT ESSENTIALLY WITH DIA 865 00:31:14,105 --> 00:31:18,109 IS IT A WAY TO GET TMT TO WORK 866 00:31:18,176 --> 00:31:18,977 WITH DIA. 867 00:31:19,043 --> 00:31:19,744 THEORETICALLY YOU COULD IMAGINE 868 00:31:19,811 --> 00:31:25,783 THAT BUT YOU WOULD LOSE 869 00:31:25,850 --> 00:31:29,087 ADVANTAGES OF TNT, LOSE ABILITY 870 00:31:29,153 --> 00:31:32,223 TO COLLECT MS 3, SO MS 3 871 00:31:32,290 --> 00:31:33,658 ISOLATION IS MORE POWERFUL THAN 872 00:31:33,725 --> 00:31:35,193 MS 2. 873 00:31:35,260 --> 00:31:44,035 WE HAVE RATIO COMPRESSION. 874 00:31:44,102 --> 00:31:46,471 WE'RE NOT GETTING TO THE SAME 875 00:31:46,537 --> 00:31:48,539 ISOLATION AS WITH MS 3s. 876 00:31:48,606 --> 00:31:51,276 FOR MOST PEOPLE DOING TMT, DOING 877 00:31:51,342 --> 00:31:53,678 MS 3s IS PROBABLY CRITICAL TO 878 00:31:53,745 --> 00:31:54,345 THEM MAKING GOOD MEASUREMENTS TO 879 00:31:54,412 --> 00:31:54,779 BEGIN WITH. 880 00:31:54,846 --> 00:31:58,049 THERE ARE SOFTWARE THAT YOU CAN 881 00:31:58,116 --> 00:31:58,716 USE TO DISENTANGLE IT BUT THEY 882 00:31:58,783 --> 00:32:01,286 TEND NOT TO WORK AS WELL AS 883 00:32:01,352 --> 00:32:02,520 ACTUALLY COLLECTING MS 3 884 00:32:02,587 --> 00:32:03,187 MEASUREMENTS THEMSELVES. 885 00:32:03,254 --> 00:32:04,555 THAT WOULD BE MY RECOMMENDATION 886 00:32:04,622 --> 00:32:06,691 FOR IT. 887 00:32:06,758 --> 00:32:12,063 I THINK THAT DIA WITH TMT IS 888 00:32:12,130 --> 00:32:14,465 CHALLENGING AT BEST. 889 00:32:14,532 --> 00:32:16,034 AND DANGEROUS AT WORST. 890 00:32:16,100 --> 00:32:17,235 DESPITE THE LITERATURE THAT 891 00:32:17,302 --> 00:32:20,071 EXISTS IN THIS AREA. 892 00:32:20,138 --> 00:32:23,675 BECAUSE ALL PEPTIDES PRODUCE THE 893 00:32:23,741 --> 00:32:27,512 SAME REPORTER ION REGION, SO 894 00:32:27,578 --> 00:32:29,147 EVERY PEPTIDE PRODUCES THAT SAME 895 00:32:29,213 --> 00:32:29,814 REPORTER ION REGION. 896 00:32:29,881 --> 00:32:31,449 THEY ARE ALL GOING TO REPORT IN 897 00:32:31,516 --> 00:32:32,550 THE SAME REGION AND THAT'S WHERE 898 00:32:32,617 --> 00:32:35,720 YOU GET THAT RATIO COMPRESSION 899 00:32:35,787 --> 00:32:36,587 BECAUSE AVERAGING THE SIGNALS 900 00:32:36,654 --> 00:32:38,356 TOGETHER GETS YOU ESSENTIALLY 901 00:32:38,423 --> 00:32:41,693 CLOSER TO THE AVERAGE, CLOSER TO 902 00:32:41,759 --> 00:32:44,696 THE 1 TO 1 TO 1 RATIOS. 903 00:32:44,762 --> 00:32:48,866 CRITICAL PART OF THIS IS THAT 904 00:32:48,933 --> 00:32:51,703 EACH PEPTIDE THAT YOU SEE 905 00:32:51,769 --> 00:32:52,904 ACTUALLY DOESN'T HAVE LIKE ONE 906 00:32:52,970 --> 00:32:55,873 OR TWO PEPTIDES BEHIND IT. 907 00:32:55,940 --> 00:32:58,276 THE PROTEOME GOES DOWN LIKE WE 908 00:32:58,343 --> 00:33:00,111 THINK OF THE PROTEOME AS WHEN WE 909 00:33:00,178 --> 00:33:06,150 MAKE A MEASUREMENT WE MIGHT MAKE 910 00:33:06,217 --> 00:33:07,585 FOUR AS TO MAGNITUDE. 911 00:33:07,652 --> 00:33:09,887 EIGHT IS MAGNITUDE IN CELL 912 00:33:09,954 --> 00:33:11,956 LINES, BLOOD SAMPLES, IT GOES 913 00:33:12,023 --> 00:33:13,591 DOWN FURTHER THAN EIGHT ORDERS 914 00:33:13,658 --> 00:33:16,227 OF MAGNITUDE. 915 00:33:16,294 --> 00:33:18,196 ALL THE GRAPHS, THAT DOESN'T 916 00:33:18,262 --> 00:33:20,398 MAKE IT -- IT MAKES IT INTO THE 917 00:33:20,465 --> 00:33:27,372 MASS MASS SPEC, YOU SEE VERY 918 00:33:27,438 --> 00:33:29,006 LITTLE BLIPS, OTHER NOISE, OTHER 919 00:33:29,073 --> 00:33:30,441 PEPTIDES PRODUCING THAT OTHER 920 00:33:30,508 --> 00:33:30,875 SIGNAL. 921 00:33:30,942 --> 00:33:32,076 IT JUST LOOKS LIKE NOISE BECAUSE 922 00:33:32,143 --> 00:33:33,411 IT'S ALL DOWN AT THE BOTTOM OF 923 00:33:33,478 --> 00:33:35,380 THE GRAPHS. 924 00:33:35,446 --> 00:33:37,014 THEY ARE TINY PEPTIDES THAT 925 00:33:37,081 --> 00:33:37,882 YOU'LL NEVER DETECT BUT THEY 926 00:33:37,949 --> 00:33:39,317 HAVE A PRESENCE AND THEY ALSO 927 00:33:39,384 --> 00:33:43,287 REPORT IN THE SAME REPORTER ION 928 00:33:43,354 --> 00:33:43,788 REGION. 929 00:33:43,855 --> 00:33:43,988 RIGHT? 930 00:33:44,055 --> 00:33:45,323 CONSEQUENTLY, YOU NEED TO BE 931 00:33:45,390 --> 00:33:47,425 ABLE TO DO SOME ADDITIONAL LEVEL 932 00:33:47,492 --> 00:33:49,861 OF ISOLATION. 933 00:33:49,927 --> 00:33:52,530 SO, DIA WITH TMT DOESN'T WORK 934 00:33:52,597 --> 00:33:53,865 VERY WELL. 935 00:33:53,931 --> 00:33:56,100 I WOULD SAY AT WORST CASE 936 00:33:56,167 --> 00:33:58,403 DANGEROUS, BEST CASE 937 00:33:58,469 --> 00:33:59,370 CHALLENGING. 938 00:33:59,437 --> 00:34:00,037 OKAY? 939 00:34:00,104 --> 00:34:02,573 BUT YOU DO GET ISOLATION, RIGHT? 940 00:34:02,640 --> 00:34:03,975 YOU GET QUITE GOOD ISOLATION, 941 00:34:04,041 --> 00:34:07,478 THAT GETS YOU TO THE LEVEL AS IF 942 00:34:07,545 --> 00:34:09,680 YOU WERE DOING PRM MEASUREMENTS 943 00:34:09,747 --> 00:34:10,915 USING GAS PHASE FRACTIONATION, 944 00:34:10,982 --> 00:34:12,417 REALLY EXPENSIVE BUT REALLY 945 00:34:12,483 --> 00:34:12,750 POWERFUL. 946 00:34:12,817 --> 00:34:14,152 NOW WE'RE BASICALLY TAKING THAT 947 00:34:14,218 --> 00:34:16,220 IMAGE AND CUTTING IT UP INTO 948 00:34:16,287 --> 00:34:17,021 DIFFERENT PIECES AND MEASURING 949 00:34:17,088 --> 00:34:18,990 EACH ONE OF THOSE DIFFERENT 950 00:34:19,056 --> 00:34:20,525 PIECES WITH HIGH FIDELITY AND 951 00:34:20,591 --> 00:34:22,059 STITCHING THEM BACK TOGETHER 952 00:34:22,126 --> 00:34:23,361 WITH THESE SIX INJECTIONS BACK 953 00:34:23,428 --> 00:34:24,262 TOGETHER, RIGHT? 954 00:34:24,328 --> 00:34:25,897 SO BASICALLY WHAT WE'RE MAKING A 955 00:34:25,963 --> 00:34:28,566 MEASUREMENT OF IS THIS ZOOMED-IN 956 00:34:28,633 --> 00:34:32,236 VIEW OF THE PICTURE INSTEAD. 957 00:34:32,303 --> 00:34:32,470 OKAY? 958 00:34:32,537 --> 00:34:33,671 SO, OBVIOUSLY IT'S WAY TOO 959 00:34:33,738 --> 00:34:36,274 EXPENSIVE TO DO ON EVERY SINGLE 960 00:34:36,340 --> 00:34:36,841 EXPERIMENT. 961 00:34:36,908 --> 00:34:39,577 BUT WE CAN LEVERAGE THIS IDEA TO 962 00:34:39,644 --> 00:34:40,311 BUILD LIBRARIES. 963 00:34:40,378 --> 00:34:42,747 SO WHEN WE'RE TRYING TO THINK 964 00:34:42,814 --> 00:34:43,881 ABOUT BUILDING LIBRARIES, WHAT 965 00:34:43,948 --> 00:34:45,383 WE ACTUALLY DO IS END UP 966 00:34:45,450 --> 00:34:47,351 COLLECTING A BUNCH OF THESE 967 00:34:47,418 --> 00:34:51,289 DIFFERENT MEASUREMENTS SO 968 00:34:51,355 --> 00:34:55,026 DIFFERENT SAMPLES, WE'LL RUN 969 00:34:55,092 --> 00:34:57,762 PROTEIN QUANT ON EACH ONE, DIA 970 00:34:57,829 --> 00:34:59,730 MEASUREMENTS, WIDE WINDOW DIA 971 00:34:59,797 --> 00:35:00,398 FOR EACH. 972 00:35:00,465 --> 00:35:02,800 OF THOSE WE'LL TAKE A POOL OF 973 00:35:02,867 --> 00:35:06,204 SAMPLES AND ANALYZE THIS USING 974 00:35:06,270 --> 00:35:09,707 SIX GAS PHASE FRACTIONATION 975 00:35:09,774 --> 00:35:11,075 EXPERIMENT. 976 00:35:11,142 --> 00:35:14,378 FROM THIS PRM QUALITY DATA WE 977 00:35:14,445 --> 00:35:15,379 DETERMINE EXACT LOCATION IN TIME 978 00:35:15,446 --> 00:35:21,185 AND MASS FOR WHAT WE SHOULD BE 979 00:35:21,252 --> 00:35:23,521 LOOKING AT, WE KNOW WHICH 980 00:35:23,588 --> 00:35:25,823 FRAGMENT IONS ARE MOST ON OUR 981 00:35:25,890 --> 00:35:30,061 INTENSE I, WHERE THEY ELUTE. 982 00:35:30,127 --> 00:35:31,696 MORE POWERFUL THAN CHEMICAL 983 00:35:31,762 --> 00:35:32,997 FRACTIONATION, TYPICALLY PEOPLE 984 00:35:33,064 --> 00:35:35,967 WOULD DO HIGH PH REVERSE 985 00:35:36,033 --> 00:35:38,503 FRACTIONATION FOLLOWED BY DDA TO 986 00:35:38,569 --> 00:35:39,904 BUILD LIBRARIES. 987 00:35:39,971 --> 00:35:42,039 YOU'LL DO 10, 30, 50, 100 988 00:35:42,106 --> 00:35:43,107 FRACTIONS OF THAT, MULTIPLE 989 00:35:43,174 --> 00:35:44,742 TIMES OVER AND OVER AGAIN. 990 00:35:44,809 --> 00:35:47,812 BUT EACH ONE OF THOSE FRACTIONS 991 00:35:47,879 --> 00:35:50,147 ACTUALLY CHANGES THE MATRIX THAT 992 00:35:50,214 --> 00:35:52,750 LIVES BEHIND THAT PARTICULAR 993 00:35:52,817 --> 00:35:53,417 PEPTIDE. 994 00:35:53,484 --> 00:35:54,986 CONSEQUENTLY, THE RETENTION 995 00:35:55,052 --> 00:35:56,687 TIMES SHIFTS NOT BY A LOT BUT BY 996 00:35:56,754 --> 00:36:01,592 A MINUTE OR TWO IN A 90 OR 997 00:36:01,659 --> 00:36:04,128 100-MINUTE GRADIENT. 998 00:36:04,195 --> 00:36:05,763 BY 1 TO 2% YOU'LL GET RETENTION 999 00:36:05,830 --> 00:36:07,198 TIME SHIFTS. 1000 00:36:07,265 --> 00:36:13,037 THE ADVANTAGE, WE'RE USING THE 1001 00:36:13,104 --> 00:36:14,906 INSTRUMENT AS FRACTIONATION 1002 00:36:14,972 --> 00:36:21,679 POOL, THE MAY -- MATRIX IS THE 1003 00:36:21,746 --> 00:36:21,879 SAME. 1004 00:36:21,946 --> 00:36:22,947 ELUTIONS ARE EXACTLY THE SAME AS 1005 00:36:23,014 --> 00:36:25,616 THEY WOULD BE IN THE WIDE WINDOW 1006 00:36:25,683 --> 00:36:27,051 DIA MEASUREMENTS. 1007 00:36:27,118 --> 00:36:29,220 SO, WE ACTUALLY KNOW THEIR 1008 00:36:29,287 --> 00:36:31,756 RETENTION TIME TO ABOUT 20 1009 00:36:31,822 --> 00:36:33,057 SECONDS, IN ACCURACY, ON OUR 1010 00:36:33,124 --> 00:36:33,357 MEASUREMENT. 1011 00:36:33,424 --> 00:36:36,861 SO WHEN WE'RE ACTUALLY MAKING 1012 00:36:36,928 --> 00:36:37,828 OUR MEASUREMENT, WE DETECT 1013 00:36:37,895 --> 00:36:39,163 PEPTIDES OUT OF HERE. 1014 00:36:39,230 --> 00:36:41,032 IN THIS PARTICULAR CASE WE WERE 1015 00:36:41,098 --> 00:36:43,134 ABLE TO DETECT OUT OF THE GAS 1016 00:36:43,200 --> 00:36:44,502 PHASE FRACTIONATION EXPERIMENT 1017 00:36:44,569 --> 00:36:46,003 OVER 2,000 PROTEINS, TYPICALLY 1018 00:36:46,070 --> 00:36:48,706 THIS IS WHAT PEOPLE THINK OF AS 1019 00:36:48,773 --> 00:36:51,976 ENTIRE COHORT, ENTIRE SIZE OF 1020 00:36:52,043 --> 00:36:54,145 THE URINE PROTEOME, RIGHT? 1021 00:36:54,211 --> 00:36:55,012 WITH SIX INJECTIONS HERE, 1022 00:36:55,079 --> 00:36:59,417 ESSENTIALLY FREE TO US BECAUSE 1023 00:36:59,483 --> 00:37:00,284 THE MASS SPECTROMETER IS DOING 1024 00:37:00,351 --> 00:37:00,952 THE WORK. 1025 00:37:01,018 --> 00:37:04,221 IT'S EASY TO MAKE THESE 1026 00:37:04,288 --> 00:37:04,989 MEASUREMENTS. 1027 00:37:05,056 --> 00:37:06,090 NOW WE KNOW COORDINATES FOR 1028 00:37:06,157 --> 00:37:08,826 THESE PEPTIDES. 1029 00:37:08,893 --> 00:37:12,763 WE HAVE TO LOOK THEM UP IN 1030 00:37:12,830 --> 00:37:14,165 SINGLE INJECTION EXPERIMENTS WE 1031 00:37:14,231 --> 00:37:16,801 KNOW WHEN IT IS ON OUR COLUMN 1032 00:37:16,867 --> 00:37:19,437 WHEN ELUTE, WHICH ARE THE 1033 00:37:19,503 --> 00:37:20,171 QUANTITATIVE IONS. 1034 00:37:20,237 --> 00:37:26,010 FROM THAT EXPERIMENT WE'RE ABLE 1035 00:37:26,077 --> 00:37:28,179 TO IDENTIFY 1700 PROTEINS 1036 00:37:28,245 --> 00:37:29,947 QUANTIFIED IN WIDE WINDOW DIA 1037 00:37:30,014 --> 00:37:30,915 MEASUREMENTS BECAUSE ALL WE'RE 1038 00:37:30,982 --> 00:37:33,684 DOING IS LOOKING THEM UP AND 1039 00:37:33,751 --> 00:37:34,518 APPLYING FALSE DISCOVERY 1040 00:37:34,585 --> 00:37:35,486 CORRECTION TO THE SIGNAL THAT WE 1041 00:37:35,553 --> 00:37:36,854 LOOK UP TO SEE WHETHER IT'S 1042 00:37:36,921 --> 00:37:38,723 BACKGROUND OR NOT. 1043 00:37:38,789 --> 00:37:40,491 WE KNOW EXACTLY WHERE TO LOOK 1044 00:37:40,558 --> 00:37:43,961 FOR THESE PARTICULAR PEPTIDES 1045 00:37:44,028 --> 00:37:44,261 THOUGH. 1046 00:37:46,263 --> 00:37:48,366 IN THIS PARTICULAR CASE, SO WHAT 1047 00:37:48,432 --> 00:37:49,667 CHEMICAL MODIFICATIONS WE SEARCH 1048 00:37:49,734 --> 00:37:51,335 FOR, IN THIS CASE WE ACTUALLY 1049 00:37:51,402 --> 00:37:53,638 DIDN'T SEARCH FOR ANY CHEMICAL 1050 00:37:53,704 --> 00:37:53,971 MODIFICATIONS. 1051 00:37:54,038 --> 00:37:55,606 HERE WHAT WE WERE DOING IN THIS 1052 00:37:55,673 --> 00:38:00,311 SEARCH WAS ACTUALLY JUST USING A 1053 00:38:00,378 --> 00:38:04,148 PREDICTED LIBRARY TO DO OUR 1054 00:38:04,215 --> 00:38:04,682 ANALYSIS, PREDICTED EVERY 1055 00:38:04,749 --> 00:38:07,752 POSSIBLE PEPTIDE IN THE HUMAN 1056 00:38:07,818 --> 00:38:09,053 PROTEOME, LOOKED FOR EVERY 1057 00:38:09,120 --> 00:38:10,154 PEPTIDE AND TRIED TO MAKE A 1058 00:38:10,221 --> 00:38:11,489 DETECTION THAT WAY. 1059 00:38:11,555 --> 00:38:13,758 WE DO THIS USING PEPTIDE-CENTRIC 1060 00:38:13,824 --> 00:38:14,425 SEARCH APPROACH. 1061 00:38:14,492 --> 00:38:17,161 AGAIN, THIS IS PART OF THE 1062 00:38:17,228 --> 00:38:21,332 ENCYCLOPEDIA WAY OF ANALYZING 1063 00:38:21,399 --> 00:38:23,100 DIA DATA. 1064 00:38:23,167 --> 00:38:32,543 YEAH? 1065 00:38:36,180 --> 00:38:46,457 >> (INAUDIBLE) 1066 00:38:47,091 --> 00:38:50,761 >> THAT'S AN INTERESTING IDEA. 1067 00:38:50,828 --> 00:38:52,630 SO I THINK THE WAY I'M GOING TO 1068 00:38:52,697 --> 00:38:54,365 ANSWER THAT IS WITH THE 1069 00:38:54,432 --> 00:38:55,566 DIFFERENT QUESTION THAN I 1070 00:38:55,633 --> 00:38:57,201 TYPICALLY GET ASKED ABOUT, WHY 1071 00:38:57,268 --> 00:38:57,435 DO THIS. 1072 00:38:57,501 --> 00:38:59,503 THE QUESTION IS, WHY DO WE POOL 1073 00:38:59,570 --> 00:39:02,239 IN THE FIRST PLACE, RIGHT? 1074 00:39:02,306 --> 00:39:04,208 WHAT DOES POOLING ACTUALLY GIVE 1075 00:39:04,275 --> 00:39:06,977 US AND SO DO WE END UP LOSING 1076 00:39:07,044 --> 00:39:08,813 PEPTIDES THAT WE WOULD OTHERWISE 1077 00:39:08,879 --> 00:39:11,115 NOT BE ABLE TO SEE IF WE HAD 1078 00:39:11,182 --> 00:39:12,550 ANALYZED THAT ONE SAMPLE 1079 00:39:12,616 --> 00:39:12,883 INDIVIDUALLY. 1080 00:39:12,950 --> 00:39:14,618 IS THAT CLOSE ENOUGH TO THE 1081 00:39:14,685 --> 00:39:15,853 QUESTION? 1082 00:39:15,920 --> 00:39:18,355 BECAUSE THAT WOULD BE LIKE WHY 1083 00:39:18,422 --> 00:39:20,558 NOT JUST ANALYZE THE AP COHORT 1084 00:39:20,624 --> 00:39:26,163 ON ITS OWN AND TREAT THAT ON ITS 1085 00:39:26,230 --> 00:39:26,597 OWN. 1086 00:39:26,664 --> 00:39:28,566 THE WAY ARATIONALIZE BY POOLING 1087 00:39:28,632 --> 00:39:30,868 HERE, WE HAVE DILUTED ALL OF AP 1088 00:39:30,935 --> 00:39:33,204 SAMPLES BY 1/4, ESSENTIALLY, SO 1089 00:39:33,270 --> 00:39:34,772 ANYBODY BIOMARKER THAT'S IN THE 1090 00:39:34,839 --> 00:39:37,441 AP SAMPLES NEEDS TO BE 1091 00:39:37,508 --> 00:39:38,776 DETECTABLE EVEN THOUGH IT'S BEEN 1092 00:39:38,843 --> 00:39:40,711 DILUTED BY A FOURTH IN ITS 1093 00:39:40,778 --> 00:39:41,245 SIGNAL. 1094 00:39:41,312 --> 00:39:44,014 BUT WHAT I WOULD SAY IS IF YOU 1095 00:39:44,081 --> 00:39:45,149 CAN'T IDENTIFY PEPTIDES HERE, 1096 00:39:45,216 --> 00:39:47,718 EVEN WITH 1/4 OF THE SIGNAL, 1097 00:39:47,785 --> 00:39:49,587 WHEN YOU'RE DOING PRM QUALITY 1098 00:39:49,653 --> 00:39:50,254 MEASUREMENTS YOU'RE NEVER GOING 1099 00:39:50,321 --> 00:39:53,290 TO SEE THEM IN WIDE WINDOW DIA 1100 00:39:53,357 --> 00:39:54,825 MEASUREMENTS. 1101 00:39:54,892 --> 00:39:56,961 AND IF YOU WERE ABLE TO SEE -- 1102 00:39:57,027 --> 00:39:59,330 DETECT A PEPTIDE ONLY IN HERE 1103 00:39:59,396 --> 00:40:01,198 AND NOT IN HERE, I DON'T THINK I 1104 00:40:01,265 --> 00:40:02,500 WOULD TRUST THAT DETECTION. 1105 00:40:02,566 --> 00:40:04,535 I THINK IT'S MUCH MORE LIKELY TO 1106 00:40:04,602 --> 00:40:05,369 BE A FALSE POSITIVE THAN 1107 00:40:05,436 --> 00:40:06,237 ANYTHING ELSE. 1108 00:40:06,303 --> 00:40:10,608 SO THIS IS ONE OF THE REASONS I 1109 00:40:10,674 --> 00:40:12,576 THINK MAKING DETECTIONS DIRECTLY 1110 00:40:12,643 --> 00:40:15,412 FROM DIA CAN LEAD YOU ASTRAY, IF 1111 00:40:15,479 --> 00:40:16,514 YOU MAKE DETECTIONS DIRECTLY 1112 00:40:16,580 --> 00:40:18,783 FROM HERE I WOULD MUCH RATHER 1113 00:40:18,849 --> 00:40:22,653 MAKE DETECTIONS FROM HERE, FROM 1114 00:40:22,720 --> 00:40:28,325 THE GLOBAL -- FROM THIS GLOBAL 1115 00:40:28,392 --> 00:40:30,094 SIX-INJECTION PRM QUALITY DATA 1116 00:40:30,161 --> 00:40:31,495 BECAUSE I'M MORE CONFIDENT IN 1117 00:40:31,562 --> 00:40:32,263 THE DATA UP FRONT AND ISOLATION 1118 00:40:32,329 --> 00:40:33,063 OF THE DATA. 1119 00:40:33,130 --> 00:40:35,432 ANYTHING I CAN SEE ONLY IN THESE 1120 00:40:35,499 --> 00:40:38,836 SAMPLES WOULD MAKE ME NERVOUS, 1121 00:40:38,903 --> 00:40:39,036 RIGHT? 1122 00:40:39,103 --> 00:40:40,271 TO TRY TO SAY SOMETHING ABOUT. 1123 00:40:40,337 --> 00:40:44,008 AT LEAST FROM A GLOBAL 1124 00:40:44,074 --> 00:40:51,415 PERSPECTIVE. 1125 00:40:51,482 --> 00:40:51,882 >> (INAUDIBLE). 1126 00:41:08,699 --> 00:41:15,306 >> AND IT HAS TO DO -- SO 1127 00:41:15,372 --> 00:41:17,608 SPECTRONAUT DOESN'T SUPPORT 1128 00:41:17,675 --> 00:41:18,709 GLASS PHASE FRACTIONATION, THE 1129 00:41:18,776 --> 00:41:23,547 SOFTWARE IS DESIGNED TO SAY I 1130 00:41:23,614 --> 00:41:25,282 NEED TO HAVE THESE DIAGNOSIS 1131 00:41:25,349 --> 00:41:28,652 PEPTIDES IN MY SAMPLE TO DO 1132 00:41:28,719 --> 00:41:30,087 ALIGNMENTS, TO DO MY ASSESSMENT. 1133 00:41:30,154 --> 00:41:32,089 BECAUSE YOU NEED THOSE PEPTIDES, 1134 00:41:32,156 --> 00:41:33,090 THOSE PEPTIDES HAVE DIFFERENT 1135 00:41:33,157 --> 00:41:34,558 MASSES, SO YOU ONLY HAVE A 1136 00:41:34,625 --> 00:41:35,659 HANDFUL OF THOSE PEPTIDES IN 1137 00:41:35,726 --> 00:41:38,195 EACH ONE OF OUR FRACTIONS. 1138 00:41:38,262 --> 00:41:41,365 THAT'S THE PROBLEM WITH IT. 1139 00:41:41,432 --> 00:41:42,700 AND IT REQUIRES ESSENTIALLY 1140 00:41:42,766 --> 00:41:43,367 SOFTWARE IS DESIGNED TO REQUIRE 1141 00:41:43,434 --> 00:41:45,536 YOU TO BUY THEIR PEPTIDES, TO BE 1142 00:41:45,603 --> 00:41:46,503 ABLE TO RUN THE SOFTWARE. 1143 00:41:46,570 --> 00:41:49,907 IT'S BECAUSE THEY MAKE THE MONEY 1144 00:41:49,974 --> 00:41:51,976 OFF THE PEPTIDES, NOT THE 1145 00:41:52,042 --> 00:41:53,644 SOFTWARE, BUT THAT'S A TOTALLY 1146 00:41:53,711 --> 00:41:55,613 DIFFERENT STORY. 1147 00:41:55,679 --> 00:41:57,481 IT'S NOT A FUNDAMENTAL FACT OF 1148 00:41:57,548 --> 00:42:01,185 GAS PHASE FRACTIONATION OR DIA. 1149 00:42:01,252 --> 00:42:03,487 YOU DON'T NEED DIAGNOSIS 1150 00:42:03,554 --> 00:42:06,323 PEPTIDES TO DO DIA, IF YOU CAN 1151 00:42:06,390 --> 00:42:07,625 IDENTIFY THE MOST ABUNDANT 1152 00:42:07,691 --> 00:42:08,626 PEPTIDES, RIGHT? 1153 00:42:08,692 --> 00:42:10,494 JUST WITHOUT HAVING ANY 1154 00:42:10,561 --> 00:42:11,896 RETENTION TIME ASSESSMENT OF 1155 00:42:11,962 --> 00:42:13,631 THEM, YOU CAN USE THOSE 1156 00:42:13,697 --> 00:42:15,165 POTENTIALLY AS ANCHORS, FOR 1157 00:42:15,232 --> 00:42:15,499 EXAMPLE. 1158 00:42:15,566 --> 00:42:17,601 SO THAT'S HOW ENCYCLOPEDIA 1159 00:42:17,668 --> 00:42:17,902 WORKS. 1160 00:42:17,968 --> 00:42:19,803 IT ACTUALLY HAS A TWO-PASS 1161 00:42:19,870 --> 00:42:21,372 PROCESS, IT TRIES TO IDENTIFY 1162 00:42:21,438 --> 00:42:22,339 PEPTIDES NOT KNOWING ANYTHING 1163 00:42:22,406 --> 00:42:23,841 ABOUT RETENTION TIME FIRST AND 1164 00:42:23,908 --> 00:42:26,377 HAS TO MAKE DETECTIONS WITHOUT 1165 00:42:26,443 --> 00:42:27,878 RETENTION AND DISCOVERS THE 1166 00:42:27,945 --> 00:42:29,079 RETENTION TIME COORDINATES FOR 1167 00:42:29,146 --> 00:42:31,282 WHERE ALL THE PEPTIDES SHOULD 1168 00:42:31,348 --> 00:42:32,716 ACTUALLY LIVE, THROUGH THAT 1169 00:42:32,783 --> 00:42:35,119 FIRST PASS ANALYSIS, AND DOES A 1170 00:42:35,185 --> 00:42:36,320 SECOND PASS AFTERWARDS KNOWING 1171 00:42:36,387 --> 00:42:37,821 WHERE THOSE PEPTIDES SHOULD LIVE 1172 00:42:37,888 --> 00:42:40,824 AND MAKING A CALL AS TO WHICH 1173 00:42:40,891 --> 00:42:42,159 PEPTIDES ARE ACTUALLY PRESENT OR 1174 00:42:42,226 --> 00:42:42,359 NOT. 1175 00:42:42,426 --> 00:42:43,661 DOES THAT MAKE SENSE? 1176 00:42:43,727 --> 00:42:46,063 AS A RESULT, IT DOESN'T MATTER 1177 00:42:46,130 --> 00:42:48,365 WHICH PEPTIDES EXIST IN THAT 1178 00:42:48,432 --> 00:42:48,599 SAMPLE. 1179 00:42:48,666 --> 00:42:52,403 IT CAN MAKE ALIGNMENT. 1180 00:42:52,469 --> 00:42:54,071 EVEN IN GAS PHASE FRACTIONS YOU 1181 00:42:54,138 --> 00:42:55,506 CAN IDENTIFY TENS OF THOUSANDS 1182 00:42:55,572 --> 00:42:57,908 OF PEPTIDES IN EACH ONE OF THESE 1183 00:42:57,975 --> 00:42:58,342 FRACTIONS. 1184 00:42:58,409 --> 00:42:59,877 DOES THAT ANSWER YOUR QUESTION? 1185 00:42:59,944 --> 00:43:03,280 IT'S A SOFTWARE LIMITATION, NOT 1186 00:43:03,347 --> 00:43:08,085 A CONCEPTUAL LIMITATION. 1187 00:43:08,419 --> 00:43:18,796 >> [OFF MICROPHONE] 1188 00:43:25,235 --> 00:43:31,108 >> AGAIN, IT WOULD BE 1189 00:43:31,175 --> 00:43:34,712 CONCEPTUALLY POSSIBLE TO, BUT 1190 00:43:34,778 --> 00:43:36,146 BIOGONOSIS WANTS YOU TO BUY 1191 00:43:36,213 --> 00:43:37,581 THEIR PEPTIDES AND HAVE 1192 00:43:37,648 --> 00:43:38,482 LIMITATIONS FOR THAT PARTICULAR 1193 00:43:38,549 --> 00:43:38,782 REASON. 1194 00:43:38,849 --> 00:43:41,618 LET ME TELL WHAT YOU WE FOUND 1195 00:43:41,685 --> 00:43:42,486 FROM A PANCREATITIS PERSPECTIVE 1196 00:43:42,553 --> 00:43:49,493 AND ASK MORE QUESTIONS ABOUT DIA 1197 00:43:49,560 --> 00:43:49,793 AFTERWARDS. 1198 00:43:49,860 --> 00:43:53,330 THERE WERE A BUNCH OF ROBUST 1199 00:43:53,397 --> 00:43:53,630 BIOMARKERS. 1200 00:43:53,697 --> 00:43:57,368 WE HONED IN ON THESE SPECIFIC 1201 00:43:57,434 --> 00:43:58,736 SIX MARKERS, INTERESTED FROM A 1202 00:43:58,802 --> 00:43:59,903 GLOBAL PERSPECTIVE LOOKING AT 1203 00:43:59,970 --> 00:44:05,609 EYE -- ACUTE PANCREATITIS 1204 00:44:05,676 --> 00:44:07,478 VERSUS CONTROLS, THESE SEEMED 1205 00:44:07,544 --> 00:44:08,979 INTERESTING MARKERS INCLUDING 1206 00:44:09,046 --> 00:44:12,049 THE GOLD STANDARD, AMYLASE. 1207 00:44:12,116 --> 00:44:13,951 NOT ONLY SERUM AMYLASE, WE FOUND 1208 00:44:14,018 --> 00:44:19,323 A SPECIFIC ISOFORM OF AMYLASE, 1209 00:44:19,390 --> 00:44:23,060 PARALOG, NOT JUST AMYLASE IN 1210 00:44:23,127 --> 00:44:23,293 GENERAL. 1211 00:44:23,360 --> 00:44:27,798 WE'LL GET BACK TO THAT AGAIN. 1212 00:44:27,865 --> 00:44:31,735 >> [OFF MICROPHONE]. 1213 00:44:31,802 --> 00:44:32,302 >> EXACTLY. 1214 00:44:32,369 --> 00:44:35,739 SO CRP IS MORE OF A SANITY 1215 00:44:35,806 --> 00:44:44,948 CHECK, CRP IS ELEVATED 1216 00:44:45,015 --> 00:44:45,716 INFLAMMATION, ASSOCIATED WITH 1217 00:44:45,783 --> 00:44:47,084 TONS OF DISEASES. 1218 00:44:47,151 --> 00:44:48,452 IT'S A TERRIBLE BIOMARKER FROM 1219 00:44:48,519 --> 00:44:49,653 THE STANDPOINT OF BIOMARKER 1220 00:44:49,720 --> 00:44:50,087 DISCOVERY. 1221 00:44:50,154 --> 00:44:53,490 WE KNEW THAT GOING IN, RIGHT? 1222 00:44:53,557 --> 00:44:56,660 AND SO WE WANTED TO KEEP IT IN 1223 00:44:56,727 --> 00:45:01,165 MIND TO SEE IT OUT, BUT IT'S NOT 1224 00:45:01,231 --> 00:45:02,466 GOING TO BE USEFUL AS A 1225 00:45:02,533 --> 00:45:04,101 BIOMARKER GOING FORWARD. 1226 00:45:04,168 --> 00:45:04,868 YOU'RE ABSOLUTELY RIGHT. 1227 00:45:04,935 --> 00:45:09,440 AT LEAST IN THIS COHORT IT WAS 1228 00:45:09,506 --> 00:45:12,309 DIFFERENT, ALTHOUGH IT WAS NOT 1229 00:45:12,376 --> 00:45:13,744 DIFFERENT ENOUGH. 1230 00:45:13,811 --> 00:45:14,845 SO THESE FIVE MARKERS WERE THE 1231 00:45:14,912 --> 00:45:17,748 ONLY ONES THAT WERE ACTUALLY 1232 00:45:17,815 --> 00:45:23,153 DIFFERENT ACROSS ALL OF THE 1233 00:45:23,220 --> 00:45:25,889 DIFFERENT COHORTS, IN DIRECT AB 1234 00:45:25,956 --> 00:45:27,191 COMPARISONS. 1235 00:45:27,257 --> 00:45:32,463 OF ALL THE PROTEINS WE DETECTED 1236 00:45:32,529 --> 00:45:34,198 RED ONES ARE POTENTIAL MARKERS, 1237 00:45:34,264 --> 00:45:34,865 ALL EXTREME VALUES. 1238 00:45:34,932 --> 00:45:37,401 WE COULD HAVE CONSIDERED ALL RED 1239 00:45:37,468 --> 00:45:39,470 ONES AS POTENTIAL MARKERS. 1240 00:45:39,536 --> 00:45:44,541 THE REASON WE HONED IN ON THESE 1241 00:45:44,608 --> 00:45:47,611 AND CRP IS AN OUTSIDER, AN AB 1242 00:45:47,678 --> 00:45:49,246 VERSUS EACH OF OUR DIFFERENT 1243 00:45:49,313 --> 00:45:51,415 CONTROL COHORTS, THESE WERE THE 1244 00:45:51,482 --> 00:45:53,383 ONLY ONES THAT WERE SIGNIFICANT 1245 00:45:53,450 --> 00:45:55,919 ACROSS ALL OF THOSE DIFFERENT 1246 00:45:55,986 --> 00:45:56,186 CONTROLS. 1247 00:45:56,253 --> 00:46:05,896 SO, KEEPING A TON OF DIFFERENT 1248 00:46:05,963 --> 00:46:08,532 TYPES OF CONTROLS IS USEFUL. 1249 00:46:08,599 --> 00:46:10,134 CP WASN'T PART OF THIS. 1250 00:46:10,200 --> 00:46:12,503 IT WAS UP IN THE EXTREMITY 1251 00:46:12,569 --> 00:46:13,370 FRACTURES AS WELL. 1252 00:46:13,437 --> 00:46:15,772 IT WASN'T AS YOU MIGHT IMAGINE 1253 00:46:15,839 --> 00:46:17,407 NOT A GOOD BIOMARKER. 1254 00:46:17,474 --> 00:46:18,041 OKAY. 1255 00:46:18,108 --> 00:46:19,943 SOME MARKERS ARE BETTER THAN 1256 00:46:20,010 --> 00:46:20,344 OTHERS. 1257 00:46:20,410 --> 00:46:21,879 CP WAS ONE OF THOSE. 1258 00:46:21,945 --> 00:46:24,548 OH, IT WAS UP IN CHRONIC 1259 00:46:24,615 --> 00:46:28,018 PANCREATITIS AS WELL. 1260 00:46:28,085 --> 00:46:31,288 SO, CP IS AN EXAMPLE OF LIKE NOT 1261 00:46:31,355 --> 00:46:33,056 A GREAT BIOMARKER. 1262 00:46:33,123 --> 00:46:35,159 IT IS ELEVATED. 1263 00:46:35,225 --> 00:46:36,894 BUT AMYLASE IS AN EXAMPLE OF 1264 00:46:36,960 --> 00:46:38,629 SORT OF WHAT WE HAVE BEEN KNOWN 1265 00:46:38,695 --> 00:46:41,832 TO SEE IN THIS TYPE OF COHORT 1266 00:46:41,899 --> 00:46:44,101 WHICH IS SLIGHTLY ELEVATED, BUT 1267 00:46:44,168 --> 00:46:45,536 NOT INCREDIBLY ELEVATED. 1268 00:46:45,602 --> 00:46:47,070 WHEREAS OUR MARKER THAT WE FOUND 1269 00:46:47,137 --> 00:46:55,512 HERE AS OUR PRIMARY MARKER OF 1270 00:46:55,579 --> 00:46:58,248 INTEREST, CELA 2A WAS MORE 1271 00:46:58,315 --> 00:47:00,384 ELEVATED, HERE WE HAVE A 60-FOLD 1272 00:47:00,450 --> 00:47:02,452 ELEVATION IN URINE, THIS IS A 1273 00:47:02,519 --> 00:47:06,924 MARKER FOR GENERAL INFLAMMATION. 1274 00:47:06,990 --> 00:47:09,660 THESE ARE SUCCESSFUL TO A 1275 00:47:09,726 --> 00:47:10,093 DEGREE. 1276 00:47:10,160 --> 00:47:12,496 MORE INTERESTING FROM BIOLOGY 1277 00:47:12,563 --> 00:47:13,363 PERSPECTIVE AN BIOMARKER 1278 00:47:13,430 --> 00:47:14,164 DISCOVERY PERSPECTIVE, THIS ONE 1279 00:47:14,231 --> 00:47:16,133 MARKER IS THE ONE WE'RE 1280 00:47:16,200 --> 00:47:18,535 INTERESTED IN FROM A BIOMARKER 1281 00:47:18,602 --> 00:47:19,169 PERSPECTIVE. 1282 00:47:19,236 --> 00:47:21,271 THESE THREE OTHER ONES ARE ALSO 1283 00:47:21,338 --> 00:47:23,440 ASSOCIATED WITH PANCREATIC 1284 00:47:23,507 --> 00:47:24,541 CANCER. 1285 00:47:24,608 --> 00:47:26,410 THE SUPER INTERESTING, RIGHT? 1286 00:47:26,476 --> 00:47:28,178 PROGRESSION IN DISEASE, THERE'S 1287 00:47:28,245 --> 00:47:30,347 A HYPOTHESIZED PROGRESSION IN 1288 00:47:30,414 --> 00:47:33,417 DISEASE FROM ACUTE PANCREATITIS 1289 00:47:33,483 --> 00:47:34,618 TO CHRONIC PANCREATITIS TO 1290 00:47:34,685 --> 00:47:36,053 PANCREATIC CANCER AND SEE AS 1291 00:47:36,119 --> 00:47:39,189 PRIMARY MARKERS OF THE OTHER 1292 00:47:39,256 --> 00:47:40,824 THREE THESE ARE ASSOCIATED WITH 1293 00:47:40,891 --> 00:47:42,926 THAT PROGRESSION RATHER THAN 1294 00:47:42,993 --> 00:47:44,895 MAYBE THE DISEASE ITSELF. 1295 00:47:44,962 --> 00:47:47,564 WHICH IS INTERESTING -- YEAH? 1296 00:47:47,631 --> 00:47:51,368 >> [OFF MICROPHONE] 1297 00:47:51,435 --> 00:47:56,273 >> NO, NO, NO, WE SEE THESE AS 1298 00:47:56,340 --> 00:48:00,244 MARKERS AS INCREASING IN CHRONIC 1299 00:48:00,310 --> 00:48:01,645 PANCREATITIS SIGNATURES. 1300 00:48:01,712 --> 00:48:03,614 SORRY, THERE'S SIGNATURES, WHEN 1301 00:48:03,680 --> 00:48:04,848 THEY ARE INCREASED THEY 1302 00:48:04,915 --> 00:48:07,117 TYPICALLY ARE GOOD MARKERS FOR 1303 00:48:07,184 --> 00:48:07,684 PANCREATIC CANCER. 1304 00:48:07,751 --> 00:48:09,753 OKAY. 1305 00:48:09,820 --> 00:48:15,759 AND THAT FOLLOWS OUR DATA AS 1306 00:48:15,826 --> 00:48:15,959 WELL. 1307 00:48:16,026 --> 00:48:20,163 SO, ELASTASE TRACKS WELL WITH 1308 00:48:20,230 --> 00:48:21,665 AMYLASE, THIS IS ELASTASE HERE, 1309 00:48:21,732 --> 00:48:22,899 AMYLASE HERE. 1310 00:48:22,966 --> 00:48:26,403 ONE THING THAT'S CLEAR, THE 1311 00:48:26,470 --> 00:48:28,238 SEPARATION, RIGHT, BETWEEN THE 1312 00:48:28,305 --> 00:48:30,974 AP COHORT AND NON-AP COHORT IS 1313 00:48:31,041 --> 00:48:35,279 QUITE WIDE WHEN WE'RE LOOKING AT 1314 00:48:35,345 --> 00:48:36,480 ELASTASE AND NARROW WHEN LOOKING 1315 00:48:36,546 --> 00:48:39,116 AT AMYLASE AS A MARKER IN 1316 00:48:39,182 --> 00:48:39,650 PARTICULAR. 1317 00:48:39,716 --> 00:48:42,653 SIMILARLY IF WE'RE THINKING FROM 1318 00:48:42,719 --> 00:48:44,421 A BIOMARKER DIAGNOSTIC 1319 00:48:44,488 --> 00:48:46,156 PERSPECTIVE, AMYLASE IS LESS 1320 00:48:46,223 --> 00:48:48,558 SUCCESSFUL THAN ACTUALLY USING 1321 00:48:48,625 --> 00:48:49,760 AMYLASE IN COMBINATION WITH OUR 1322 00:48:49,826 --> 00:48:50,861 MARKER OF CHOICE. 1323 00:48:50,927 --> 00:48:52,929 WHERE OUR MARKER IS THE ONE THAT 1324 00:48:52,996 --> 00:48:55,666 SORT OF DRIVES THE SEPARATION IN 1325 00:48:55,732 --> 00:48:56,199 PARTICULAR. 1326 00:48:56,266 --> 00:48:57,868 JUST TO KIND OF GO THROUGH SOME 1327 00:48:57,934 --> 00:49:06,043 OF THE THIS QUICKLY, WE TESTED 1328 00:49:06,109 --> 00:49:07,611 ANOTHER 30 INDIVIDUALS AT A 1329 00:49:07,678 --> 00:49:08,945 DIFFERENT TIME, ANOTHER SET OF 1330 00:49:09,012 --> 00:49:11,148 SAMPLES WHERE WE WERE ABLE TO 1331 00:49:11,214 --> 00:49:12,215 REPRODUCE THIS MEASUREMENT AS 1332 00:49:12,282 --> 00:49:15,285 WELL IN SORT OF MORE TARGETED 1333 00:49:15,352 --> 00:49:19,122 INTERPRETATION OF DIA DATA. 1334 00:49:19,189 --> 00:49:25,896 SO, IN AP CP HEALTHY COHORT 1335 00:49:25,962 --> 00:49:28,198 WITHOUT EXTREMITY FRACTURE, A 1336 00:49:28,265 --> 00:49:29,299 SEPARATE BATCH, CELA2A IS ONE OF 1337 00:49:29,366 --> 00:49:31,368 THE HIGH MARKERS FOR THIS 1338 00:49:31,435 --> 00:49:31,702 DISEASE. 1339 00:49:31,768 --> 00:49:33,337 AMYLASE IS NICELY SEPARATED. 1340 00:49:33,403 --> 00:49:35,105 WE SEE MULTIPLE FORMS OF AMYLASE 1341 00:49:35,172 --> 00:49:35,305 TOO. 1342 00:49:35,372 --> 00:49:38,141 AND SOME OF THEM HAVE DIFFERENT 1343 00:49:38,208 --> 00:49:39,776 LEVELS OF MARKER ACTIVITY THAN 1344 00:49:39,843 --> 00:49:41,111 OTHERS, RIGHT? 1345 00:49:41,178 --> 00:49:43,046 WHEN YOU MAKE AN ELISA AND USE 1346 00:49:43,113 --> 00:49:45,382 AN ANTIBODY FOR A READOUT, IT'S 1347 00:49:45,449 --> 00:49:46,917 MEASURING ALL OF THEM, RIGHT? 1348 00:49:46,983 --> 00:49:49,186 IT'S MEASURING THEM BASED ON 1349 00:49:49,252 --> 00:49:52,055 SHAPE, NOT BASED ON SEQUENCE OR 1350 00:49:52,122 --> 00:49:54,558 IDENTITY TO A SPECIFIC ISOFORM. 1351 00:49:54,624 --> 00:49:55,859 WHEN YOU'RE MEASURING THEM THIS 1352 00:49:55,926 --> 00:50:02,866 IS THE MARKER THAT IS PROBABLY 1353 00:50:02,933 --> 00:50:04,434 THE MOST PRECISE, AMY2A, CRP IS 1354 00:50:04,501 --> 00:50:06,036 AGAIN ELEVATED COME WHAT. 1355 00:50:06,103 --> 00:50:10,974 WE ALSO VALIDATED THIS IN A 1356 00:50:11,041 --> 00:50:12,309 DIFFERENT WAY TOO WITH BASELINE 1357 00:50:12,376 --> 00:50:13,910 SO INDIVIDUALS COME IN WITH 1358 00:50:13,977 --> 00:50:16,113 ACUTE PANCREATITIS, WE MAKE A 1359 00:50:16,179 --> 00:50:17,114 MEASUREMENT, THREE MONTHS LATER 1360 00:50:17,180 --> 00:50:18,081 DO A FOLLOW-UP MEASUREMENT, 1361 00:50:18,148 --> 00:50:18,281 RIGHT? 1362 00:50:18,348 --> 00:50:20,050 SO HERE ONE OF THE THINGS WE 1363 00:50:20,117 --> 00:50:22,352 WOULD LIKE TO SEE, HERE ARE SOME 1364 00:50:22,419 --> 00:50:23,453 SIGNALS DROP, WE SEE SOME OF 1365 00:50:23,520 --> 00:50:25,756 THEM DROP BUT NOT ALL OF THEM 1366 00:50:25,822 --> 00:50:26,623 DROP. 1367 00:50:26,690 --> 00:50:27,924 THAT'S INTERESTING TO US AS 1368 00:50:27,991 --> 00:50:28,392 WELL. 1369 00:50:28,458 --> 00:50:32,095 SO ALSO TRUE FOR AMYLOIDS AND 1370 00:50:32,162 --> 00:50:32,262 CRP. 1371 00:50:32,329 --> 00:50:36,566 WE THINK THAT SOME OF THESE 1372 00:50:36,633 --> 00:50:37,768 INDIVIDUALS ACTUALLY ARE, YOU 1373 00:50:37,834 --> 00:50:39,002 KNOW, IN ACUTE PANCREATITIS THEY 1374 00:50:39,069 --> 00:50:40,537 WILL GET AN ATTACK AND THEN 1375 00:50:40,604 --> 00:50:41,805 FREQUENTLY WILL GET A RECURRENT 1376 00:50:41,872 --> 00:50:43,907 ATTACK AGAIN LATER. 1377 00:50:43,974 --> 00:50:46,443 THAT RECURRENT ATTACK WILL BUILD 1378 00:50:46,510 --> 00:50:48,545 INTO CHRONIC PANCREATITIS 1379 00:50:48,612 --> 00:50:50,046 AFTERWARDS THAT. 1380 00:50:50,113 --> 00:50:55,419 THAT PATHWAY ARE KNOWN, WE'RE 1381 00:50:55,485 --> 00:50:57,220 CONCERNED THESE ARE SLATED TO 1382 00:50:57,287 --> 00:50:58,321 GET CHRONIC PANCREATITIS IN THE 1383 00:50:58,388 --> 00:50:58,588 FUTURE. 1384 00:50:58,655 --> 00:50:59,656 THIS IS FOLLOW-UP WORK FOR 1385 00:50:59,723 --> 00:51:00,857 LATER. 1386 00:51:00,924 --> 00:51:01,958 JUST TO GIVE YOU SOME FEELING 1387 00:51:02,025 --> 00:51:09,733 FOR THIS, IF WE LOOK AT OUR 1388 00:51:09,800 --> 00:51:11,468 MARKERS ELASTASE VERSUS AMYLASE, 1389 00:51:11,535 --> 00:51:12,602 THIS IS CHANGED. 1390 00:51:12,669 --> 00:51:16,640 A FOLD CHANGE FROM BASELINE TO 1391 00:51:16,706 --> 00:51:17,407 FOLLOW-UP MEASUREMENT. 1392 00:51:17,474 --> 00:51:18,842 IN GENERAL FOLLOWING ON KIND OF 1393 00:51:18,909 --> 00:51:23,447 A LINE WITH SOME OUTLIERS HERE, 1394 00:51:23,513 --> 00:51:25,415 WHICH STRUCK US AS UNUSUAL, 1395 00:51:25,482 --> 00:51:27,684 SOMETHING HARD TO EXPLAIN HOW 1396 00:51:27,751 --> 00:51:29,986 CAN SOMEONE HAVE THEIR HIGH 1397 00:51:30,053 --> 00:51:30,987 ELASTASE WITHOUT HAVING HIGH 1398 00:51:31,054 --> 00:51:31,888 AMYLASE AS WELL? 1399 00:51:31,955 --> 00:51:33,824 WE'RE NOT TOTALLY SURE ABOUT THE 1400 00:51:33,890 --> 00:51:35,692 DETAILS OF THAT. 1401 00:51:35,759 --> 00:51:39,196 WE DO KNOW THAT ELASTASE FOLLOWS 1402 00:51:39,262 --> 00:51:41,264 QUITE CLEANLY WITH CRP LEVELS SO 1403 00:51:41,331 --> 00:51:46,536 MIGHT BE THESE PEOPLE HAVE SOME 1404 00:51:46,603 --> 00:51:49,673 SORT OF VESTIGIAL OR LATENT 1405 00:51:49,739 --> 00:51:51,341 PANCREATIC DISEASE STILL, BUT 1406 00:51:51,408 --> 00:51:52,542 THEY ARE NOT EXPRESSING IN THE 1407 00:51:52,609 --> 00:51:56,613 SAME SORT OF WAY AS WITH 1408 00:51:56,680 --> 00:51:56,947 AMYLASE. 1409 00:51:57,013 --> 00:51:57,247 OKAY. 1410 00:51:57,314 --> 00:51:59,015 SO, I SHOWED YOU THIS LIST OF 1411 00:51:59,082 --> 00:52:01,651 BIOMARKERS AT THE BEGINNING. 1412 00:52:01,718 --> 00:52:04,154 AND ONE OF THE BIOMARKERS THAT I 1413 00:52:04,221 --> 00:52:07,757 HAD LISTED HERE IS ACTUALLY 1414 00:52:07,824 --> 00:52:08,325 CALLED PANCREATIC ELASTASE 1415 00:52:08,391 --> 00:52:08,558 ALREADY. 1416 00:52:08,625 --> 00:52:12,829 AND SO WHEN I SAW THIS, IN THE 1417 00:52:12,896 --> 00:52:14,464 LITERATURE, OH, MAN, WE JUST 1418 00:52:14,531 --> 00:52:15,665 FOUND SOMETHING THAT SOMEONE 1419 00:52:15,732 --> 00:52:19,503 ELSE FOUND A WHILE AGO. 1420 00:52:19,569 --> 00:52:26,076 AND PANCREATIC ELASTASE IS CELL 1421 00:52:26,142 --> 00:52:27,577 1A, DIFFERENT SEQUENCE, 1422 00:52:27,644 --> 00:52:29,012 DIFFERENT PROTEIN, DIFFERENT 1423 00:52:29,079 --> 00:52:30,013 CHAIN. 1424 00:52:30,080 --> 00:52:31,882 DESPITE ITS NAME, PANCREATIC 1425 00:52:31,948 --> 00:52:33,517 ELASTASE, IT ORIGINATES SO WE 1426 00:52:33,583 --> 00:52:35,785 SEE IT IN STOOL, WE DON'T SEE IT 1427 00:52:35,852 --> 00:52:38,755 IN URINE OR IN BLOOD. 1428 00:52:38,822 --> 00:52:40,390 IT'S ONLY ASSOCIATED WITH STOOL. 1429 00:52:40,457 --> 00:52:43,226 AND SO WHILE IT'S BEEN CALLED 1430 00:52:43,293 --> 00:52:48,965 PANCREATIC ELASTASE, IT'S 1431 00:52:49,032 --> 00:52:50,400 ACTUALLY NOTED IN UNIPROTE 1432 00:52:50,467 --> 00:52:52,102 DOESN'T ORIGINATE FROM THE 1433 00:52:52,168 --> 00:52:53,303 PANCREAS. 1434 00:52:53,370 --> 00:52:54,638 THIS SHOWS WORSE LEVELS OF 1435 00:52:54,704 --> 00:52:57,474 ACTIVITY IN THESE OLDER PAPERS 1436 00:52:57,541 --> 00:52:58,775 SO THIS IS FROM 1998. 1437 00:52:58,842 --> 00:52:59,976 SO, AT THE TIME THEY WERE LIKE, 1438 00:53:00,043 --> 00:53:02,612 OKAY, THIS IS AN INTERESTING 1439 00:53:02,679 --> 00:53:04,548 MARKER, BUT IT DOESN'T WORK AS 1440 00:53:04,614 --> 00:53:06,783 WELL AS AMYLASE, WE'RE GOING TO 1441 00:53:06,850 --> 00:53:07,551 THROW IT OUT. 1442 00:53:07,617 --> 00:53:10,654 AND SO THEY STOPPED WORKING ON 1443 00:53:10,720 --> 00:53:10,921 THIS AREA. 1444 00:53:10,987 --> 00:53:12,689 AND SO ONE OF THE THINGS THAT WE 1445 00:53:12,756 --> 00:53:14,424 THINK IS INTERESTING, SO IN OUR 1446 00:53:14,491 --> 00:53:16,493 DATASETS IN URINE AND IN PLASMA 1447 00:53:16,560 --> 00:53:17,961 WE ACTUALLY DON'T SEE THIS 1448 00:53:18,028 --> 00:53:20,163 PROTEIN AT ALL, RIGHT? 1449 00:53:20,230 --> 00:53:23,433 SHOULD BE NOT FOUND, ONLY FOUND 1450 00:53:23,500 --> 00:53:24,834 IN STOOL. 1451 00:53:24,901 --> 00:53:26,903 BUT IT IS PRESENT IN THESE 1452 00:53:26,970 --> 00:53:28,338 EXISTING DATASETS BECAUSE AGAIN 1453 00:53:28,405 --> 00:53:30,073 THEY ARE USING ANTIBODIES, 1454 00:53:30,140 --> 00:53:33,276 RIGHT, FOR MEASUREMENT, 1455 00:53:33,343 --> 00:53:33,743 ELISAs. 1456 00:53:33,810 --> 00:53:36,112 IF YOU LOOK AT SEQUENCE 1457 00:53:36,179 --> 00:53:39,049 HOMOLOGY, CELL 1A AND 2A, THEY 1458 00:53:39,115 --> 00:53:41,084 ARE SIMILAR ENOUGH AT THE 1459 00:53:41,151 --> 00:53:41,918 SEQUENCE LEVEL, BUT DIFFERENT 1460 00:53:41,985 --> 00:53:44,220 ENOUGH THAT WE CAN DEFINITELY 1461 00:53:44,287 --> 00:53:47,390 TELL THE DIFFERENCE, RIGHT? 1462 00:53:47,457 --> 00:53:49,025 WITH MASS SPEC, DIFFERENT 1463 00:53:49,092 --> 00:53:50,093 PROTEINS, WE'RE NOT GOING TO 1464 00:53:50,160 --> 00:53:50,894 CONFUSE THE TOO. 1465 00:53:50,961 --> 00:53:52,562 BUT ANTIBODIES ARE NOT BINDING 1466 00:53:52,629 --> 00:53:54,297 TO SEQUENCE BUT TO THE SHAPE OF 1467 00:53:54,364 --> 00:53:55,599 THE PROTEIN. 1468 00:53:55,665 --> 00:53:57,334 THESE WHO PROTEINS HAVE 1469 00:53:57,400 --> 00:53:59,102 ESSENTIALLY THE SAME PHYSICAL 1470 00:53:59,169 --> 00:53:59,302 SHAPE. 1471 00:53:59,369 --> 00:54:05,141 AND BECAUSE OF THAT, THE 1472 00:54:05,208 --> 00:54:06,209 ANTIBODIES ARE PROBABLY 1473 00:54:06,276 --> 00:54:06,576 CROSS-REACTIVE. 1474 00:54:06,643 --> 00:54:08,411 WE THINK WHAT THIS PERSON WAS 1475 00:54:08,478 --> 00:54:09,946 FINDING AS URINE BIOMARKER IN A 1476 00:54:10,013 --> 00:54:12,349 PROTEIN SUPPOSED TO ONLY EXIST 1477 00:54:12,415 --> 00:54:14,551 IN STOOL WAS ACTUALLY THE 1478 00:54:14,618 --> 00:54:16,286 PROTEIN THAT WE FOUND. 1479 00:54:16,353 --> 00:54:18,254 IF THEY HAD DONE FOLLOW-UP OR 1480 00:54:18,321 --> 00:54:19,990 BETTER TYPE OF ASSAY, THEY WOULD 1481 00:54:20,056 --> 00:54:21,992 HAVE ACTUALLY FOUND THE RIGHT 1482 00:54:22,058 --> 00:54:24,060 PROTEIN AS THE MARKER, AND WOULD 1483 00:54:24,127 --> 00:54:26,896 HAVE ACTUALLY HAD A MUCH BETTER 1484 00:54:26,963 --> 00:54:28,565 ASSAY 30 YEARS WHEN THIS STUDY 1485 00:54:28,632 --> 00:54:31,167 WAS FIRST DONE. 1486 00:54:31,234 --> 00:54:32,135 AGAIN, THESE ANTIBODIES BECOME 1487 00:54:32,202 --> 00:54:33,703 REALLY PROBLEMATIC WHEN WE USE 1488 00:54:33,770 --> 00:54:35,271 THEM AND REQUIRE THEM AS 1489 00:54:35,338 --> 00:54:37,107 READOUTS FOR A LOT OF THESE 1490 00:54:37,173 --> 00:54:37,974 BIOLOGICAL MEASUREMENTS. 1491 00:54:38,041 --> 00:54:42,345 WE HAVE TO BE ABLE TO BUILD 1492 00:54:42,412 --> 00:54:44,547 ASSAY TOOLS THAT ARE MORE ROBUST 1493 00:54:44,614 --> 00:54:49,119 THAN SINGLE ANTIBODY BINDING, 1494 00:54:49,185 --> 00:54:49,319 RIGHT? 1495 00:54:49,386 --> 00:54:50,787 OKAY. 1496 00:54:50,854 --> 00:54:52,656 SO I WANTED TO TOUCH BRIEFLY ON 1497 00:54:52,722 --> 00:54:57,594 THIS NOTE AGAIN. 1498 00:54:57,661 --> 00:54:58,128 ACUTE PANCREATITIS BECOMES 1499 00:54:58,194 --> 00:55:00,530 RECURRENT PANCREATITIS, BECOMES 1500 00:55:00,597 --> 00:55:08,872 CHRONIC PANCREATITIS, BECOMES 1501 00:55:08,938 --> 00:55:11,074 CHRONIC PANCREATIC SIGNATURE, A 1502 00:55:11,141 --> 00:55:11,708 HYPOTHESIZED IDEA. 1503 00:55:11,775 --> 00:55:15,679 WE ARE DIGGING INTO THIS A 1504 00:55:15,745 --> 00:55:18,615 LITTLE BIT MORE BECAUSE WE HAD A 1505 00:55:18,682 --> 00:55:21,885 CP COHORT WITH AP COHORT, CP 1506 00:55:21,951 --> 00:55:23,186 PROTEINS ARE ALREADY INTERESTING 1507 00:55:23,253 --> 00:55:25,155 FROM THAT PERSPECTIVE. 1508 00:55:25,221 --> 00:55:27,891 TOP SIX CP PROTEINS SPECIFIC TO 1509 00:55:27,957 --> 00:55:29,993 CP ALONE, OF THESE SIX FIVE HAVE 1510 00:55:30,060 --> 00:55:31,194 ALREADY BEEN ASSOCIATED WITH 1511 00:55:31,261 --> 00:55:34,597 PANCREATIC CANCER AS WELL. 1512 00:55:34,664 --> 00:55:38,535 SO, FROM THIS PERSPECTIVE, WE 1513 00:55:38,601 --> 00:55:41,137 SEE THIS COINCIDENCE IS WORTH 1514 00:55:41,204 --> 00:55:46,176 DIGGING INTO MORE SERIOUSLY, AS 1515 00:55:46,242 --> 00:55:48,545 A TRUE PROGRESSION THAT COMES 1516 00:55:48,611 --> 00:55:50,647 OUT OF THE DATASET. 1517 00:55:50,714 --> 00:55:52,515 CHRONIC PANCREATITIS IS EASIER 1518 00:55:52,582 --> 00:55:53,717 TO DIAGNOSE, SO THIS IS TOP 1519 00:55:53,783 --> 00:55:56,252 MARKER OF THIS. 1520 00:55:56,319 --> 00:55:58,088 FROM ITS IDENTIFICATION RATE, 1521 00:55:58,154 --> 00:55:59,089 IT'S ALMOST A PERFECT BIOMARKER 1522 00:55:59,155 --> 00:56:00,290 FOR THIS TYPE OF MEASUREMENT. 1523 00:56:00,356 --> 00:56:02,559 WE'RE FOLLOWING UP ON THIS AS A 1524 00:56:02,625 --> 00:56:03,560 SEPARATE STUDY THAT WE'RE GOING 1525 00:56:03,626 --> 00:56:07,831 TO BE WORKING ON IN THE FUTURE. 1526 00:56:07,897 --> 00:56:12,102 BUT THAT ONE IS STILL LEFT TO BE 1527 00:56:12,168 --> 00:56:12,435 DISCUSSED. 1528 00:56:12,502 --> 00:56:12,769 THAT SECTION. 1529 00:56:12,836 --> 00:56:14,504 BUT JUST IN THE LAST FEW MINUTES 1530 00:56:14,571 --> 00:56:16,806 I WANT TO OUTLINE A COUPLE 1531 00:56:16,873 --> 00:56:17,674 DIFFERENT CONCLUSIONS HERE. 1532 00:56:17,741 --> 00:56:21,311 SO ONE OF THEM IS THAT URINE IS 1533 00:56:21,377 --> 00:56:22,278 A REALLY POWERFUL SOURCE FOR 1534 00:56:22,345 --> 00:56:23,813 THINKING ABOUT BIOMARKERS. 1535 00:56:23,880 --> 00:56:26,216 WE DON'T TYPICALLY THINK ABOUT 1536 00:56:26,282 --> 00:56:28,518 BIOMARKERS IN URINE BECAUSE 1537 00:56:28,585 --> 00:56:30,153 ASSAYS TEND NOT TO WORK WELL FOR 1538 00:56:30,220 --> 00:56:32,355 THEM BECAUSE OF VARIATION IN 1539 00:56:32,422 --> 00:56:34,457 LEVEL IN URINE. 1540 00:56:34,524 --> 00:56:36,860 IF YOU HAVE A THOUSAND-FOLD 1541 00:56:36,926 --> 00:56:38,495 VARIATION IN THE PROTEIN 1542 00:56:38,561 --> 00:56:39,696 ABUNDANCE IN URINE, TRYING TO 1543 00:56:39,763 --> 00:56:41,765 SEE YOUR PROTEIN OF INTEREST IN 1544 00:56:41,831 --> 00:56:42,866 THAT NOISE IS REALLY 1545 00:56:42,932 --> 00:56:43,399 CHALLENGING. 1546 00:56:43,466 --> 00:56:45,502 THE FIRST THING WE DO IN TRYING 1547 00:56:45,568 --> 00:56:49,839 TO DO A PROTEOMIC ASSESSMENT OF 1548 00:56:49,906 --> 00:56:52,041 IT IS TO DO -- TO TRY TO CRASH 1549 00:56:52,108 --> 00:56:54,010 OUT THE PROTEIN TO BEGIN WITH. 1550 00:56:54,077 --> 00:56:55,578 BECAUSE OF THAT WE'RE ALREADY 1551 00:56:55,645 --> 00:56:57,313 NORMALIZING BASICALLY ON THE 1552 00:56:57,380 --> 00:56:58,615 PROTEIN ABUNDANCE AS THE FIRST 1553 00:56:58,681 --> 00:57:00,250 STEP IN OUR PRACTICE FOR THIS. 1554 00:57:00,316 --> 00:57:04,287 SO, WHILE IT DOESN'T WORK REALLY 1555 00:57:04,354 --> 00:57:05,922 WELL FOR TRADITIONAL ASSAYS, 1556 00:57:05,989 --> 00:57:08,258 USING ELISAS OF DIRECT URINE WE 1557 00:57:08,324 --> 00:57:18,735 THINK IT WOULD WORK WELL 1558 00:57:19,636 --> 00:57:23,573 ELISAs OF PROTEIN. 1559 00:57:23,640 --> 00:57:25,308 AP WE'RE FOLLOWING UP ON FIRST, 1560 00:57:25,375 --> 00:57:27,277 CP HAS A STORY WE'RE COMING OUT 1561 00:57:27,343 --> 00:57:30,246 WITH LATER THAT WE'RE WORKING ON 1562 00:57:30,313 --> 00:57:32,315 RIGHT NOW. 1563 00:57:32,382 --> 00:57:37,220 THE LAST THING IS THAT WE DO SEE 1564 00:57:37,287 --> 00:57:39,322 THIS STRONG PROGRESSION FROM AP 1565 00:57:39,389 --> 00:57:46,763 TO CP TO PANCREATIC CANCER, 1566 00:57:46,830 --> 00:57:47,831 DRIVERS FOR CANCER, AND SO THIS 1567 00:57:47,897 --> 00:57:49,699 I THINK IS A DIFFERENT AVENUE 1568 00:57:49,766 --> 00:57:52,235 FOR US TO START INVESTIGATING 1569 00:57:52,302 --> 00:57:53,269 THE EFFECTS OF THESE SPECIFIC 1570 00:57:53,336 --> 00:57:55,505 TYPES OF PROTEINS FROM A 1571 00:57:55,572 --> 00:57:57,373 MECHANISTIC PERSPECTIVE, NOT 1572 00:57:57,440 --> 00:58:00,443 JUST BIOLOGICAL PERSPECTIVE. 1573 00:58:00,510 --> 00:58:00,643 OKAY. 1574 00:58:00,710 --> 00:58:02,212 WITH THAT I WANT TO ACKNOWLEDGE 1575 00:58:02,278 --> 00:58:03,213 MY COLLABORATORS, THIS WORK 1576 00:58:03,279 --> 00:58:05,815 WOULD NOT BE POSSIBLE WITHOUT 1577 00:58:05,882 --> 00:58:08,985 THE COLLABORATION FROM 1578 00:58:09,052 --> 00:58:12,555 CINCINNATI CHILDREN'S. 1579 00:58:12,622 --> 00:58:14,224 SO MAISAM HAS BEEN CRITICAL IN 1580 00:58:14,290 --> 00:58:15,225 TRYING TO DO THIS. 1581 00:58:15,291 --> 00:58:16,926 WE'VE BEEN ACTING AS PARTNERS 1582 00:58:16,993 --> 00:58:18,194 THROUGHOUT THE ENTIRE PROCESS. 1583 00:58:18,261 --> 00:58:23,766 TWO MEMBERS OF MY LAB ARE 1584 00:58:23,833 --> 00:58:27,070 INVOLVED IN THIS WORK. 1585 00:58:27,136 --> 00:58:32,542 MADDIE AND ARIANA, COLLABORATORS 1586 00:58:32,609 --> 00:58:35,044 AT OSU, VENKATA IS THE FIRST 1587 00:58:35,111 --> 00:58:36,112 AUTHOR, DRIVING INTERPRETATION 1588 00:58:36,179 --> 00:58:37,547 OF DATA AFTERWARDS. 1589 00:58:37,614 --> 00:58:39,549 SO, WITH THAT I THINK WE HAD A 1590 00:58:39,616 --> 00:58:40,516 LOT OF QUESTIONS DURING. 1591 00:58:40,583 --> 00:58:43,519 I'M HAPPY TO TAKE OTHER 1592 00:58:43,586 --> 00:58:44,487 QUESTIONS TOO. 1593 00:58:44,554 --> 00:58:47,190 BUT WE CAN CLOSE. 1594 00:59:01,437 --> 00:59:05,441 >> [OFF MICROPHONE]. 1595 00:59:05,508 --> 00:59:06,509 >> YEAH, I DON'T ANY. 1596 00:59:06,576 --> 00:59:16,953 >> [OFF MICROPHONE] 1597 00:59:26,162 --> 00:59:31,000 >> SO, WHAT DO WE DO ABOUT BATCH 1598 00:59:31,067 --> 00:59:31,801 EFFECTS? THE FIRST THING IS 1599 00:59:31,868 --> 00:59:33,569 MAKE SURE WE DON'T HAVE BATCH 1600 00:59:33,636 --> 00:59:34,971 EFFECTS TO BEGIN WITH. 1601 00:59:35,038 --> 00:59:36,839 AND SO, THE FIRST THING I SHOWED 1602 00:59:36,906 --> 00:59:38,574 YOU AT THE BEGINNING WAS THOSE 1603 00:59:38,641 --> 00:59:40,243 BOX PLOTS, RIGHT? 1604 00:59:40,310 --> 00:59:43,947 THE BOX PLOTS ARE A SIMPLE 1605 00:59:44,013 --> 00:59:45,481 BIOINFORMATIC APPROACH TO SAY IS 1606 00:59:45,548 --> 00:59:46,916 THERE ANY CONFOUNDING VARIABLE I 1607 00:59:46,983 --> 00:59:49,319 HAVEN'T THOUGHT ABOUT YET, IS 1608 00:59:49,385 --> 00:59:50,954 THERE ANY CORRELATION OF ONE 1609 00:59:51,020 --> 00:59:51,821 VARIABLE WITH ANOTHER VARIABLE 1610 00:59:51,888 --> 00:59:53,356 THAT I HAVEN'T THOUGHT ABOUT 1611 00:59:53,423 --> 00:59:53,790 YET. 1612 00:59:53,856 --> 00:59:56,326 AND I THINK IT'S ALWAYS 1613 00:59:56,392 --> 00:59:58,394 WORTHWHILE BEFORE YOU BEGIN AN 1614 00:59:58,461 --> 00:59:59,629 EXPERIMENT TO TRY TO TEASE APART 1615 00:59:59,696 --> 01:00:01,831 WHAT MIGHT BE A CONFOUNDING 1616 01:00:01,898 --> 01:00:03,132 FACTOR BEFORE YOU BEGIN, AND 1617 01:00:03,199 --> 01:00:05,635 MAKE SURE THAT BECOMES PART OF 1618 01:00:05,702 --> 01:00:08,071 HOW YOU DO BATCHING TO BEGIN 1619 01:00:08,137 --> 01:00:08,538 WITH. 1620 01:00:08,604 --> 01:00:11,107 SO YOU DON'T WANT ALL OF ONE 1621 01:00:11,174 --> 01:00:14,744 TIME OF -- TYPE OF SAMPLE IN ONE 1622 01:00:14,811 --> 01:00:16,546 TYPE OF BATCH. 1623 01:00:16,612 --> 01:00:17,380 IT MAY BE CRYPTIC, NOT OBVIOUS 1624 01:00:17,447 --> 01:00:19,983 THIS IS THE SAMPLE THAT'S A 1625 01:00:20,049 --> 01:00:20,750 PROBLEMATIC SAMPLE. 1626 01:00:20,817 --> 01:00:22,051 IT WASN'T JUST THE CP 1627 01:00:22,118 --> 01:00:23,052 INDIVIDUALS. 1628 01:00:23,119 --> 01:00:24,554 IT WAS SPECIFICALLY THE CP 1629 01:00:24,620 --> 01:00:26,356 INDIVIDUALS THAT WERE FEMALE 1630 01:00:26,422 --> 01:00:28,091 THAT WERE OLDER, RIGHT? 1631 01:00:28,157 --> 01:00:30,193 THOSE WERE A DIFFERENT COHORT 1632 01:00:30,259 --> 01:00:31,594 ALMOST, DIFFERENT GROUP IN OUR 1633 01:00:31,661 --> 01:00:35,999 COHORT THAT WE NEEDED TO MAKE 1634 01:00:36,065 --> 01:00:37,533 SURE THEY WERE SPREAD ACROSS THE 1635 01:00:37,600 --> 01:00:37,967 EXPERIMENT. 1636 01:00:38,034 --> 01:00:40,036 STEP 1, TRY TO AVOID THE 1637 01:00:40,103 --> 01:00:40,737 POTENTIAL PROBLEM. 1638 01:00:40,803 --> 01:00:43,539 STEP 2, THAT WE DO, WE ALWAYS 1639 01:00:43,606 --> 01:00:45,174 TRY TO MONITOR HOW THE 1640 01:00:45,241 --> 01:00:46,476 INSTRUMENT IS PERFORMING OVER 1641 01:00:46,542 --> 01:00:46,709 TIME. 1642 01:00:46,776 --> 01:00:51,147 SO THAT WE CAN MAKE SURE THAT WE 1643 01:00:51,214 --> 01:00:53,850 ARE SUCCESSFULLY MAKING THE SAME 1644 01:00:53,916 --> 01:00:55,718 NOT JUST DETECTIONS BUT THE SAME 1645 01:00:55,785 --> 01:00:56,552 INTENSITY MEASUREMENTS. 1646 01:00:56,619 --> 01:00:57,887 ALL OF THE MEASUREMENTS WE'RE 1647 01:00:57,954 --> 01:00:59,322 MAKING HERE ARE BASED OFF 1648 01:00:59,389 --> 01:01:01,057 INTENSITY NOT BASED ON WHETHER 1649 01:01:01,124 --> 01:01:02,158 WE DETECTED THAT PARTICULAR 1650 01:01:02,225 --> 01:01:06,429 PEPTIDE OR NOT, AS WOULD YOU 1651 01:01:06,496 --> 01:01:12,335 WITH DDA. 1652 01:01:12,402 --> 01:01:15,972 OUR EQUAL CONTROL ISN'T RUNNING 1653 01:01:16,039 --> 01:01:17,707 STANDARD HeLa. 1654 01:01:17,774 --> 01:01:19,142 YOU CAN STILL DETECT THE SAME 1655 01:01:19,208 --> 01:01:20,676 AMOUNT OF PROTEINS FROM A 1656 01:01:20,743 --> 01:01:21,978 HeLa DIGEST. 1657 01:01:22,045 --> 01:01:24,147 WE SEE DEGRADATION IN INTENSITY 1658 01:01:24,213 --> 01:01:25,248 FAR EARLIER, USUALLY THAT 1659 01:01:25,314 --> 01:01:26,382 HAPPENS WITHIN A COUPLE WEEKS. 1660 01:01:26,449 --> 01:01:29,852 YOU START TO SEE DIRTYING OF 1661 01:01:29,919 --> 01:01:31,387 CERTAIN PARTS OF THE INSTRUMENT, 1662 01:01:31,454 --> 01:01:32,522 USUALLY INPUT CAPILLARY IS THE 1663 01:01:32,588 --> 01:01:34,223 FIRST THING THAT GETS DIRTY. 1664 01:01:34,290 --> 01:01:35,458 AND THAT ACTUALLY TYPICALLY 1665 01:01:35,525 --> 01:01:37,093 DOESN'T AFFECT YOUR DETECTION 1666 01:01:37,160 --> 01:01:37,827 RATE. 1667 01:01:37,894 --> 01:01:41,998 IT JUST AFFECTS INTENSITIES OF 1668 01:01:42,065 --> 01:01:43,866 YOUR FRAGMENT IONS. 1669 01:01:43,933 --> 01:01:44,734 THAT'S ONE ADDITIONAL ASPECT. 1670 01:01:44,801 --> 01:01:47,103 WE TRY TO MAKE SURE SAMPLES 1671 01:01:47,170 --> 01:01:49,972 AFTER THEY HAVE BEEN BATCHED 1672 01:01:50,039 --> 01:01:53,276 TOGETHER CAN GET ACKNOWLEDGIZED 1673 01:01:53,342 --> 01:01:54,610 QUANTITATIVELY AS A GROUP. 1674 01:01:54,677 --> 01:01:56,112 I DIDN'T SHOW YOU A SLIDE 1675 01:01:56,179 --> 01:01:57,246 TALKING ABOUT BATCHING BUT WE 1676 01:01:57,313 --> 01:02:00,550 TRY TO MAKE SURE ALL SAMPLES CAN 1677 01:02:00,616 --> 01:02:02,018 BE NORMALIZED TOGETHER. 1678 01:02:02,085 --> 01:02:04,987 IF THEY CAN'T FROM A GLOBAL 1679 01:02:05,054 --> 01:02:06,089 PERSPECTIVE WE WILL EITHER THROW 1680 01:02:06,155 --> 01:02:09,692 OUT A SAMPLE OR MARK IT AS BEING 1681 01:02:09,759 --> 01:02:09,992 PROBLEMATIC. 1682 01:02:10,059 --> 01:02:12,195 SO, THE WAY WE DO THAT IS 1683 01:02:12,261 --> 01:02:13,830 ACTUALLY LOOK AT, AGAIN, BOX 1684 01:02:13,896 --> 01:02:15,731 PLOTS OF THE GLOBAL INTENSITY 1685 01:02:15,798 --> 01:02:17,366 MEASUREMENTS THAT WE'RE MAKING 1686 01:02:17,433 --> 01:02:18,968 FOR ALL OUR PROTEINS. 1687 01:02:19,035 --> 01:02:20,837 IF THEY ARE STAYING CONSISTENT 1688 01:02:20,903 --> 01:02:22,939 WE CAN SAY THESE SAMPLES DON'T 1689 01:02:23,005 --> 01:02:25,374 NEED TO BE SORT OF ADDITIONALLY 1690 01:02:25,441 --> 01:02:27,743 NORMALIZED TOGETHER BEYOND THE 1691 01:02:27,810 --> 01:02:28,544 LEVEL OF NORMALIZATION WE'VE 1692 01:02:28,611 --> 01:02:28,945 ALREADY EMPLOYED. 1693 01:02:29,011 --> 01:02:31,581 BUT THERE ARE WAYS OF CORRECTING 1694 01:02:31,647 --> 01:02:32,815 ONE BATCH VERSUS ANOTHER BATCH, 1695 01:02:32,882 --> 01:02:34,884 IF YOU NEED TO. 1696 01:02:34,951 --> 01:02:35,952 YOU JUST TYPICALLY IF YOU CAN 1697 01:02:36,018 --> 01:02:38,788 GET AWAY WITH NOT DOING IT, 1698 01:02:38,855 --> 01:02:40,223 HAVING FEWER CORRECTIONS IS 1699 01:02:40,289 --> 01:02:41,090 USUALLY SAFER. 1700 01:02:41,157 --> 01:02:44,927 DOES THAT ANSWER YOUR QUESTIONS? 1701 01:02:44,994 --> 01:02:48,464 COOL. 1702 01:02:48,531 --> 01:02:58,908 >> [OFF MICROPHONE] 1703 01:03:32,441 --> 01:03:36,245 COULD YOU DISCUSS WHAT WE CAN DO 1704 01:03:36,312 --> 01:03:39,515 TO CONTROL FALSE DISCOVERY RATE 1705 01:03:39,582 --> 01:03:43,152 WITH DIA, WHAT PUBLICATION 1706 01:03:43,219 --> 01:03:44,453 PROTOCOL SOFTWARE METHODS? 1707 01:03:44,520 --> 01:03:47,290 >> LET'S -- WHAT I WOULD SAY, 1708 01:03:47,356 --> 01:03:49,692 I'LL EXPLAIN THE PROBLEM AND 1709 01:03:49,759 --> 01:03:52,094 THEN WE CAN TALK ABOUT KIND OF 1710 01:03:52,161 --> 01:03:53,196 DIFFERENT APPROACHES OFFLINE. 1711 01:03:53,262 --> 01:03:55,498 THAT MIGHT BE THE BEST SOLUTION. 1712 01:03:55,565 --> 01:03:57,233 BUT THE PROBLEM I THINK IS 1713 01:03:57,300 --> 01:03:59,769 REALLY INTERESTING. 1714 01:03:59,835 --> 01:04:03,139 WE USE TARGET DECOY AS AN 1715 01:04:03,206 --> 01:04:05,107 APPROACH FOR DOING DIA ANALYSIS, 1716 01:04:05,174 --> 01:04:07,743 HOW HE WE DO WITH DDA. 1717 01:04:07,810 --> 01:04:10,146 YOU SEARCH AS MANY TARGETS AS DO 1718 01:04:10,213 --> 01:04:11,247 YOU DECOYS, YOU SAY, I WANT MY 1719 01:04:11,314 --> 01:04:15,518 TARGETS TO SCORE BETTER THAN 1720 01:04:15,585 --> 01:04:15,751 DECOYS. 1721 01:04:15,818 --> 01:04:18,588 A GREAT WAY TO SAY DECOYS 1722 01:04:18,654 --> 01:04:20,356 REPRESENT WRONG MATCHES AND I 1723 01:04:20,423 --> 01:04:21,958 WANT SUFFICIENT NUMBER -- I WANT 1724 01:04:22,024 --> 01:04:25,361 AS FEW DECOYS TO KIND OF BE 1725 01:04:25,428 --> 01:04:27,797 ACCEPTED AS PART OF MY BATCH. 1726 01:04:27,863 --> 01:04:30,299 SO, DECOYS AS I SAID REPRESENT 1727 01:04:30,366 --> 01:04:31,534 WRONG MATCHES, RIGHT? 1728 01:04:31,601 --> 01:04:34,570 VERY MUCH WRONG MATCHES. 1729 01:04:34,637 --> 01:04:35,871 REVERSE SEQUENCES, WON'T 1730 01:04:35,938 --> 01:04:36,872 FRAGMENT AT ALL ALIKE. 1731 01:04:36,939 --> 01:04:39,375 SO THE PROBLEM WITH TARGET DECOY 1732 01:04:39,442 --> 01:04:41,577 IS IT CONTROLS FOR WRONG 1733 01:04:41,644 --> 01:04:42,178 MATCHES. 1734 01:04:42,245 --> 01:04:44,647 NOT FOR KIND OF WRONG MATCHES. 1735 01:04:44,714 --> 01:04:46,515 AND THERE'S A CLASS OF KIND OF 1736 01:04:46,582 --> 01:04:48,251 WRONG MATCHES THAT BECOME A 1737 01:04:48,317 --> 01:04:50,453 PROBLEM WITH DIA. 1738 01:04:50,519 --> 01:04:56,125 SO, WITH DIA, YOU END UP HAVING 1739 01:04:56,192 --> 01:04:57,326 WIDER PRECURSOR ISOLATION 1740 01:04:57,393 --> 01:04:59,862 WINDOWS WHICH ALLOW PEPTIDES TO 1741 01:04:59,929 --> 01:05:01,697 FALL IN THAT WINDOW. 1742 01:05:01,764 --> 01:05:03,699 FOR YOUR DIA WORK WHAT'S THE 1743 01:05:03,766 --> 01:05:10,239 WINDOW YOU TYPICALLY USE? 1744 01:05:10,306 --> 01:05:10,439 SORRY? 1745 01:05:10,506 --> 01:05:11,040 7.5 WINDOWS? 1746 01:05:11,107 --> 01:05:18,981 WHAT'S YOUR CYCLE TIME IN THAT? 1747 01:05:19,048 --> 01:05:20,416 SO YOUR POINTS ACROSS THE PEAK 1748 01:05:20,483 --> 01:05:23,586 ARE NOT VERY GOOD. 1749 01:05:23,653 --> 01:05:27,089 YOU'VE GOT LIKE 60-SECOND LENGTH 1750 01:05:27,156 --> 01:05:27,290 PEAKS? 1751 01:05:27,356 --> 01:05:30,026 YEAH, NO, THE PEAK WIDTH. 1752 01:05:30,092 --> 01:05:30,926 HOW MANY POINTS ACROSS THE PEAK 1753 01:05:30,993 --> 01:05:31,794 DO YOU GET? 1754 01:05:31,861 --> 01:05:34,463 WE COULD TALK ABOUT THAT 1755 01:05:34,530 --> 01:05:34,964 AFTERWARDS. 1756 01:05:35,031 --> 01:05:37,500 7.5, RIGHT? 1757 01:05:37,566 --> 01:05:41,771 WHAT FITS IN 7.5? 1758 01:05:41,837 --> 01:05:46,442 WELL, OXIDATION, A SHIFT OF 1759 01:05:46,509 --> 01:05:48,678 METHYL WOULD FIT IN 7.5. 1760 01:05:48,744 --> 01:05:50,746 HOW MANY SEQUENCE VARIANTS ARE A 1761 01:05:50,813 --> 01:05:52,148 SHIFT OF METHYL? 1762 01:05:52,214 --> 01:05:54,784 MOST OF THEM. 1763 01:05:54,850 --> 01:06:02,091 MOST ARE THEM TO VALENE, THOSE 1764 01:06:02,158 --> 01:06:04,527 FALL IN THE ISOLATION WINDOW AND 1765 01:06:04,593 --> 01:06:05,294 BECOME POTENTIALLY A PROBLEM 1766 01:06:05,361 --> 01:06:09,532 BECAUSE NOW YOU HAVE A DIFFERENT 1767 01:06:09,598 --> 01:06:10,866 SOURCE OF FALSE DETECTIONS, THEY 1768 01:06:10,933 --> 01:06:12,301 ARE FALSE DETECTIONS THAT ARE 1769 01:06:12,368 --> 01:06:14,036 ALMOST THE SAME PEPTIDE BUT NOT 1770 01:06:14,103 --> 01:06:14,937 THE SAME PEPTIDE. 1771 01:06:15,004 --> 01:06:18,207 SO IT'S VERY EASY FOR US TO 1772 01:06:18,274 --> 01:06:19,742 OVERCALL IN OUR DETECTIONS. 1773 01:06:19,809 --> 01:06:22,244 WE SEE THIS ALL THE TIME WITH 1774 01:06:22,311 --> 01:06:23,979 SEQUENCE VARIANTS, EVEN WHEN YOU 1775 01:06:24,046 --> 01:06:25,214 REQUIRE A PRECURSOR SIGNAL YOU 1776 01:06:25,281 --> 01:06:28,150 STILL END UP IN CIRCUMSTANCES 1777 01:06:28,217 --> 01:06:31,320 WHERE YOU CAN MAKE ERRORS 1778 01:06:31,387 --> 01:06:32,321 ASSOCIATED WITH HAVING MOSTLY 1779 01:06:32,388 --> 01:06:34,390 THE RIGHT SEQUENCE BUT NOT 1780 01:06:34,457 --> 01:06:35,725 EXACTLY THE RIGHT SEQUENCE 1781 01:06:35,791 --> 01:06:38,461 BECAUSE OF THE WIDER PRECURSOR 1782 01:06:38,527 --> 01:06:38,861 ISOLATION WINDOW. 1783 01:06:38,928 --> 01:06:41,630 NOW, ONE WAY TO SORT OF DEAL 1784 01:06:41,697 --> 01:06:45,034 WITH THAT IS BY USING THE GAS 1785 01:06:45,101 --> 01:06:47,870 PHASE FRACTIONATION APPROACH, 1786 01:06:47,937 --> 01:06:50,039 TWO M-Z WIDE WINDOWS, NOW YOU 1787 01:06:50,106 --> 01:06:58,581 CAN SAY, WELL, I COULD MISS 1788 01:06:58,647 --> 01:06:59,415 ISOLUCING, MISSING DEAMIDATION, 1789 01:06:59,482 --> 01:07:00,683 WHATEVER THE MASS SHIFT IS HAS 1790 01:07:00,750 --> 01:07:02,752 TO BE REALLY SMALL. 1791 01:07:02,818 --> 01:07:05,054 WE WANT TO GET AT LEAST WITHIN 1792 01:07:05,121 --> 01:07:07,556 FOUR M/Z WIDE WINDOWS BEFORE WE 1793 01:07:07,623 --> 01:07:09,859 START ESCAPING THESE TYPES OF 1794 01:07:09,925 --> 01:07:10,259 PROBLEMS. 1795 01:07:10,326 --> 01:07:11,827 THIS IS A SOURCE OF FALSE 1796 01:07:11,894 --> 01:07:13,129 DISCOVERIES THAT LOOKS DIFFERENT 1797 01:07:13,195 --> 01:07:15,197 THAN WRONG PEPTIDES. 1798 01:07:15,264 --> 01:07:16,432 THESE ARE RIGHT PEPTIDES BUT 1799 01:07:16,499 --> 01:07:19,268 THEY ARE NOT EXACTLY THE RIGHT 1800 01:07:19,335 --> 01:07:19,502 PEPTIDE. 1801 01:07:19,568 --> 01:07:20,970 LET ME GIVE AN IDEA FOR HOW BAD 1802 01:07:21,036 --> 01:07:23,305 OF A PROBLEM THIS IS. 1803 01:07:23,372 --> 01:07:32,047 SO IN 12 M/Z WIDE WINDOWS SIZES 1804 01:07:32,114 --> 01:07:34,049 EVERY PEPTIDES THAT 20% CHANCE 1805 01:07:34,116 --> 01:07:35,351 OF SEQUENCE SIMILAR PEPTIDE IN 1806 01:07:35,418 --> 01:07:36,452 THE SAME WINDOW. 1807 01:07:36,519 --> 01:07:40,523 0% -- 20%. 1808 01:07:40,589 --> 01:07:42,792 THEY ALL HAVE THE SAME CHEMICAL 1809 01:07:42,858 --> 01:07:44,894 STRUCTURE ESSENTIALLY, BECAUSE 1810 01:07:44,960 --> 01:07:46,729 THEY ALL ARE ROUGHLY THE SAME 1811 01:07:46,796 --> 01:07:48,164 AMINO ACID, THEY ALL ELUTE AT 1812 01:07:48,230 --> 01:07:50,366 THE SAME TIME PERIOD AS WELL. 1813 01:07:50,433 --> 01:07:52,535 SO BECAUSE OF THOSE CONFOUNDING 1814 01:07:52,601 --> 01:07:54,870 FACTORS WE END UP WITH HAVING 1815 01:07:54,937 --> 01:07:56,472 CHALLENGES MAKING CALLS AS TO 1816 01:07:56,539 --> 01:07:59,241 WHICH ONE IS ACTUALLY PRESENT 1817 01:07:59,308 --> 01:08:00,242 AND MOST SOFTWARES WILL CALL 1818 01:08:00,309 --> 01:08:01,143 BOTH AS BEING PRESENT. 1819 01:08:01,210 --> 01:08:04,547 THAT'S WHERE WE GET SOURCE OF 1820 01:08:04,613 --> 01:08:05,314 OVERREPORTING AND OVERDETECTION. 1821 01:08:05,381 --> 01:08:06,148 DOES THAT ANSWER? 1822 01:08:06,215 --> 01:08:09,018 OKAY. 1823 01:08:09,084 --> 01:08:17,593 >> [OFF MICROPHONE]. 1824 01:08:24,834 --> 01:08:28,370 >> I THINK THAT MS1s, USAGE OF 1825 01:08:28,437 --> 01:08:30,272 MS1s IN THIS ARE BENEFICIAL 1826 01:08:30,339 --> 01:08:31,774 BUT DON'T SOLVE THE PROBLEM. 1827 01:08:31,841 --> 01:08:33,108 WE SEE LOTS OF CIRCUMSTANCES 1828 01:08:33,175 --> 01:08:36,378 WHERE YOU HAVE AMINO ACID FLIPS, 1829 01:08:36,445 --> 01:08:38,214 INSIDE THE HUMAN GENOME. 1830 01:08:38,280 --> 01:08:45,788 THE HUMAN GENOME IS SO MASSIVELY 1831 01:08:45,855 --> 01:08:46,622 OVERREPEATED, RIGHT? 1832 01:08:46,689 --> 01:08:47,857 EVOLUTION NOT SOME SORT OF 1833 01:08:47,923 --> 01:08:52,328 HIGHERING BEING THAT KNOWS AND 1834 01:08:52,394 --> 01:08:52,895 PLANS, RIGHT? 1835 01:08:52,962 --> 01:08:54,630 IT COPIES GENES, EDITING THEM 1836 01:08:54,697 --> 01:08:55,965 SLIGHTLY, CALLING IT A NEW 1837 01:08:56,031 --> 01:08:56,799 PROTEIN, RIGHT? 1838 01:08:56,866 --> 01:09:00,102 BECAUSE OF THAT WE GET SO MANY 1839 01:09:00,169 --> 01:09:02,071 SUBTLE CHANGES IN OUR 1840 01:09:02,137 --> 01:09:02,404 CIRCUMSTANCES. 1841 01:09:02,471 --> 01:09:05,040 WE OFTEN SEE LIKE REVERSED 1842 01:09:05,107 --> 01:09:07,009 SEQUENCES OR SEQUENCE VARIANT 1843 01:09:07,076 --> 01:09:08,978 OVER HERE REPLACED BY THE 1844 01:09:09,044 --> 01:09:10,045 DIFFERENT SEQUENCE VARIANT OVER 1845 01:09:10,112 --> 01:09:11,914 THERE WHERE THEY HAVE THE SAME 1846 01:09:11,981 --> 01:09:13,249 PRECURSOR MASS. 1847 01:09:13,315 --> 01:09:14,683 ALSO PRECURSOR SPACE IS FLOODED 1848 01:09:14,750 --> 01:09:16,552 WITH OTHER TYPES OF PEPTIDES, 1849 01:09:16,619 --> 01:09:18,220 ESPECIALLY WHEN HAVE YOU VERY 1850 01:09:18,287 --> 01:09:20,756 SMALL GRADIENTS. 1851 01:09:23,826 --> 01:09:26,028 >> [OFF MICROPHONE]. 1852 01:09:28,097 --> 01:09:30,299 >> HOW DO YOU CONTROL CARRYOVER, 1853 01:09:30,366 --> 01:09:32,101 YOU MEAN FROM ONE INJECTION TO 1854 01:09:32,167 --> 01:09:33,068 THE NEXT? 1855 01:09:33,135 --> 01:09:33,502 THAT'S A CHALLENGE. 1856 01:09:33,569 --> 01:09:36,272 I THINK PART OF THIS HAS TO DO 1857 01:09:36,338 --> 01:09:38,007 WITH LC ITSELF. 1858 01:09:38,073 --> 01:09:41,510 CARRYOVER IS CAUSED BY LC. 1859 01:09:41,577 --> 01:09:43,479 AND BY SORT OF WHATEVER IS 1860 01:09:43,546 --> 01:09:45,014 REMAINING EVEN AFTER A WASH ON 1861 01:09:45,080 --> 01:09:46,215 THE LC. 1862 01:09:46,282 --> 01:09:48,517 YOU GET CARRYOVER ON THE COLUMN 1863 01:09:48,584 --> 01:09:50,152 AS WELL SO PEPTIDES THAT COME 1864 01:09:50,219 --> 01:09:52,354 OFF LATER IN THE COLUMN, THE 1865 01:09:52,421 --> 01:09:58,661 SECOND TIME YOU RUN A GRADIENT 1866 01:09:58,727 --> 01:10:01,664 THROUGH I BOTH THINGS HAPPEN, 1867 01:10:01,730 --> 01:10:04,533 CARRYOVER AROUND 1% WE ESTIMATE. 1868 01:10:04,600 --> 01:10:07,236 SO 1/100 OF OUR MEASUREMENT. 1869 01:10:07,303 --> 01:10:09,538 SO ANY IDENTIFICATION THAT WE 1870 01:10:09,605 --> 01:10:11,607 CALL THAT IS 1/100 OF A 1871 01:10:11,674 --> 01:10:14,243 MEASUREMENT AWAY FROM WHERE IT 1872 01:10:14,310 --> 01:10:17,112 IS ON AVERAGE, WE ESSENTIALLY 1873 01:10:17,179 --> 01:10:18,847 SAY THAT'S CLOSE ENOUGH TO ZERO 1874 01:10:18,914 --> 01:10:21,350 TO BE ZERO. 1875 01:10:21,417 --> 01:10:22,985 FROM THAT PERSPECTIVE, WE'LL 1876 01:10:23,052 --> 01:10:27,590 CALCULATE A RATIO, WE KNOW THAT 1877 01:10:27,656 --> 01:10:30,192 BEYOND ESSENTIALLY 1/100 WE HAVE 1878 01:10:30,259 --> 01:10:30,593 RATIO COMPRESSION. 1879 01:10:30,659 --> 01:10:35,364 IT'S BETTER THAN EYE TRACK 1 TO 1880 01:10:35,431 --> 01:10:38,100 2 OR 1 TO 3 CHANGES. 1881 01:10:38,167 --> 01:10:41,604 HERE AS LONG AS WE'RE WITHIN 1 1882 01:10:41,670 --> 01:10:42,471 TO 100, ANYTHING OUTSIDE WE'RE 1883 01:10:42,538 --> 01:10:44,106 LIKELY TO SEE PROBLEMS WITH. 1884 01:10:44,173 --> 01:10:46,508 IN REPEATED INJECTIONS. 1885 01:10:46,575 --> 01:10:48,143 YOU CAN RUN BLANKS IN BETWEEN TO 1886 01:10:48,210 --> 01:10:49,912 CLEAN OUT COLUMNS BUT IN MANY 1887 01:10:49,979 --> 01:10:53,115 CASES WHERE THERE HAVE BEEN 1888 01:10:53,182 --> 01:10:55,484 MARKERS WE CARE ABOUT, THERE ARE 1889 01:10:55,551 --> 01:10:59,755 MANY TYPES OF PEPTIDES THAT 1890 01:10:59,822 --> 01:11:02,958 STICK TO COLUMNS, AND IN ONE 1891 01:11:03,025 --> 01:11:08,297 EXPERIMENT I RAN SIX OR SEVEN 1892 01:11:08,364 --> 01:11:15,504 BLINKS AND WAS STILL ABLE TO 1893 01:11:15,571 --> 01:11:17,272 DETECT COMING OFF THE COLUMN, 1894 01:11:17,339 --> 01:11:18,474 ELUTING OFF THE COLUMN. 1895 01:11:18,540 --> 01:11:20,643 AT THE SAME TIME WE WOULD STILL 1896 01:11:20,709 --> 01:11:22,411 HAVE TO DETECTIVE ARE THESE 1897 01:11:22,478 --> 01:11:27,016 ISSUES WITH DDA OR ANY OTHER 1898 01:11:27,082 --> 01:11:29,785 TYPE OF PROTEOMIC MEASUREMENT. 1899 01:11:33,088 --> 01:11:34,223 >> [OFF MICROPHONE]. 1900 01:11:34,289 --> 01:11:34,556 >> AH, YES. 1901 01:11:34,623 --> 01:11:36,392 SO, THAT'S A GREAT QUESTION. 1902 01:11:36,458 --> 01:11:38,827 HOW DO WE DO PROTEIN EXTRACTION? 1903 01:11:38,894 --> 01:11:39,595 IT'S A CHALLENGE. 1904 01:11:39,662 --> 01:11:41,130 WE FEEL LIKE THAT'S OUR SECRET 1905 01:11:41,196 --> 01:11:43,999 CAUSE RIGHT NOW IS BEING ABLE TO 1906 01:11:44,066 --> 01:11:45,167 DO REASONABLY GOOD URINE PREPS. 1907 01:11:45,234 --> 01:11:48,671 THE FIRST THING WE DO IS ACETONE 1908 01:11:48,737 --> 01:11:49,004 PRECIPITATION. 1909 01:11:49,071 --> 01:11:52,541 SO WE TRY TO CRASH OUT THE 1910 01:11:52,608 --> 01:11:54,276 PROTEIN EARLY ON, WASH IT AS 1911 01:11:54,343 --> 01:11:56,245 MUCH AS WE CAN. 1912 01:11:56,311 --> 01:11:58,313 WE END UP HAVING TO DO SEVERAL 1913 01:11:58,380 --> 01:12:01,917 ROUNDS OF CLEANUP ON IT THOUGH 1914 01:12:01,984 --> 01:12:03,585 BEFORE WE ACTUALLY PUT A PROTEIN 1915 01:12:03,652 --> 01:12:10,592 INTO THE MASS SPECTROMETER. 1916 01:12:10,659 --> 01:12:13,195 WE'LL DO C-18 CLEANUP ON 1917 01:12:13,262 --> 01:12:18,000 PEPTIDES AND C-1 18 TRAPS AS 1918 01:12:18,067 --> 01:12:18,267 WELL. 1919 01:12:18,333 --> 01:12:19,134 WE'VE EXPERIMENTED AT DIFFERENT 1920 01:12:19,201 --> 01:12:19,968 STAGES OF PROTEIN LEVEL. 1921 01:12:20,035 --> 01:12:23,806 WE'LL DO A SERIES OF WASHES TOO. 1922 01:12:23,872 --> 01:12:29,111 WE'LL USE S-TRAPS FOR DIGESTION. 1923 01:12:29,178 --> 01:12:31,480 WE'VE BEEN EXPERIMENTS WITH SP-3 1924 01:12:31,547 --> 01:12:32,881 AS ANOTHER SOLUTION BUT FOR NOW 1925 01:12:32,948 --> 01:12:34,116 IT'S WORKING FOR US FOR THIS 1926 01:12:34,183 --> 01:12:44,126 PARTICULAR SET OF DATA. 1927 01:12:44,259 --> 01:12:46,128 >> [OFF MICROPHONE]. 1928 01:12:46,195 --> 01:12:49,531 >> SO, URINE IS CHALLENGING TO 1929 01:12:49,598 --> 01:12:51,366 NORMALIZE BECAUSE OF VARIATION 1930 01:12:51,433 --> 01:12:52,034 IN CONCENTRATION. 1931 01:12:52,101 --> 01:12:55,104 FIRST THING WE DID, I MADE A SET 1932 01:12:55,170 --> 01:12:58,707 OF SAMPLES, LAB STANDARDS, THAT 1933 01:12:58,774 --> 01:13:00,809 ARE MY URINE THAT ARE -- I WAS 1934 01:13:00,876 --> 01:13:02,544 ACTIVELY TRYING TO LIKE DRINK A 1935 01:13:02,611 --> 01:13:04,880 BUNCH OF WATER OR DEHYDRATE 1936 01:13:04,947 --> 01:13:07,249 MYSELF TO MAKE US DEAL WITH THE 1937 01:13:07,316 --> 01:13:08,450 WORST POSSIBLE PROBLEMS OF THIS, 1938 01:13:08,517 --> 01:13:10,886 TO TRY TO FIGURE THIS OUT AHEAD 1939 01:13:10,953 --> 01:13:11,954 OF TIME, RIGHT? 1940 01:13:12,020 --> 01:13:13,288 RATHER THAN WORKING WITH 1941 01:13:13,355 --> 01:13:14,690 COMMERCIAL STANDARDS, THIS WAS A 1942 01:13:14,757 --> 01:13:15,924 WAY TO ACTUALLY MAKE A STANDARD 1943 01:13:15,991 --> 01:13:17,459 FOR WHAT WE CARED ABOUT WHICH 1944 01:13:17,526 --> 01:13:19,661 WAS TRYING TO DEAL WITH THIS 1945 01:13:19,728 --> 01:13:20,863 PARTICULAR PROBLEM OF 1946 01:13:20,929 --> 01:13:21,597 VARIABILITY. 1947 01:13:21,663 --> 01:13:24,233 AND SO FROM THAT PERSPECTIVE, 1948 01:13:24,299 --> 01:13:27,302 THE IMMEDIATE CRASH IS REALLY 1949 01:13:27,369 --> 01:13:28,270 IMPORTANT, ASSESSING A PROTEIN 1950 01:13:28,337 --> 01:13:29,705 CONCENTRATION AT THAT STAGE IS 1951 01:13:29,772 --> 01:13:29,972 IMPORTANT. 1952 01:13:30,038 --> 01:13:34,009 WE FEEL LIKE WE HAVE TO DO 1953 01:13:34,076 --> 01:13:34,843 PEPTIDE-LEVEL CONCENTRATIONS AS 1954 01:13:34,910 --> 01:13:35,277 WELL. 1955 01:13:35,344 --> 01:13:37,146 TO DEAL WITH THE NORMALIZATION 1956 01:13:37,212 --> 01:13:41,116 OF HOW MUCH PROTEIN WE'RE 1957 01:13:41,183 --> 01:13:44,052 ACTUALLY PUTTING ON THE MASS 1958 01:13:44,119 --> 01:13:45,687 SPECTROMETER, THAT'S THE BIGGEST 1959 01:13:45,754 --> 01:13:47,389 WAY TO DEAL WITH NORMALIZATION 1960 01:13:47,456 --> 01:13:48,223 BETWEEN THE SAMPLES. 1961 01:13:48,290 --> 01:13:50,759 THAT GETS US UP TO THE SAME 1962 01:13:50,826 --> 01:13:51,727 PROTEIN LEVEL. 1963 01:13:51,794 --> 01:13:52,995 THAT'S ANALOGOUS TO DOING AN 1964 01:13:53,061 --> 01:13:55,898 ASSAY TO SAY WHAT IS THE OVERALL 1965 01:13:55,964 --> 01:13:57,966 PROTEIN AND NORMALIZING TO THAT, 1966 01:13:58,033 --> 01:14:01,236 IT'S ANALOGOUS TO THAT. 1967 01:14:01,303 --> 01:14:01,804 >> [OFF MICROPHONE]. 1968 01:14:01,870 --> 01:14:04,473 >> GOOD QUESTION THOUGH. 1969 01:14:12,080 --> 01:14:12,981 >> [OFF MICROPHONE]. 1970 01:14:13,048 --> 01:14:13,315 >> PERFECT. 1971 01:14:13,382 --> 01:14:15,384 >> WE'LL NOT HAVE TIME TO 1972 01:14:15,450 --> 01:14:17,119 ENTERTAIN QUESTIONS FROM THE 1973 01:14:17,186 --> 01:14:17,452 ROOM. 1974 01:14:17,519 --> 01:14:19,755 SO NEXT TIME COME OVER HERE. 1975 01:14:19,822 --> 01:14:22,057 LET'S THANK BRIAN FOR COMING OUT 1976 01:14:22,124 HERE.