 Okay, thank you Jane. That's it for the project updates. We'll now have a report from Rong-Ling Li, a program director. We are required once a year to prepare a report for Council on tracking of women and minorities in funded applications that involve human subjects. Okay, I'm going to present the inclusion of women and minority in HGI clinical studies. Why we should report this? From a scientific scientific point of view, it is important to include the women and the minority in the clinical research. According to NIH revitalization act of 1993, each NIH IC should give a bio-nail report on including women and minority participants in the clinical research to ensure that NIH GRI in complete compliance with NIH mandated. So we analyzed the past two years data, including FY 11 and FY 12. This presentation covers both the extramural research and the intramural research data. There were two set of data. One is called proposed or target data, which come from the grantees application. And another set of data called the actual or enrollment data that comes from annual progress report. In this presentation, we only presented the actual enrollment data. All human subjects in the clinical research should report under this law, except they have some exceptions, at least here, such as darkening research, secondary data analysis, small sample size, etc. And the target data, the enrollment data for phase three clinical trial must to be reported. In our NIH GRI studies, we have no phase three clinical trial. The process of tracking this population of the inclusion, the intramural and the intramural are slightly different. For the extramural research, we have three process to track this. And first is the under scientific review. Reviews the homeless subject. And then go to the program director, program directors review if that's appropriate for the inclusion of women and the minorities. And the last step is the grant management specialist. Before they release the grant, they have to make sure that they meet the homeless subject issue. The intramural for the monitor and the process through the intramural IRB for review the protocol and monitor the process. The demographic information in this inclusion is consistent with the U.S. census. So we have the racial categories and ethnicity gender. There were total 131 protocols in the past two years. I call here the protocols because a few studies, one study includes multiple protocols. For example, like the emergency study, one study is in Geisinger. They have different phenotypes under different projects. So each phenotype under each protocol. So for the extramural, we have 42 and the intramural is 89. The total participants are about 375,000. The extramural participants are higher, about two times higher than the intramural participant. This graph shows the size of each protocol. You can see the along the axis indicated the sample size in each protocol. The vertical axis indicates the number of studies in that category. So you can see from there that the blue bar indicates the extramural research and the red bar indicates the intramural research. Most of the research, the protocols under the sample size of 600. But we do have some few studies with a big sample size there. This graph breaks down the participants by ratio, by race. The right-hand side indicates extramural research and the left-hand side indicates intramural research. You can see from this graph that majority of participants are still white participants. However, compared to extramural research and intramural research, the extramural research recruit more diverse populations. This breaks down by ethnicity, as you expected. We have more non-Hispanic participants than the Hispanic Latino or Latino participants. Again, the extramural recruit more Hispanic or Latino participants than compared to intramural research. This one indicates the gender difference. The proportion of gender women and men are similar, but the extramural we recruit more women participants than intramural. So for the extramural research, we have total of 42 protocols in the past two years. The sample size range from five to 67,000. Most of the extramural research come from the OPG, that's the Office of Regulation Genomics' previous, under the Office of Director. All these protocols with small sample size, most of them are first research, professional study or individual already under some genetic testing. You can also see from the distribution that small studies with big sample size do drive this shifting of the demographic distribution. The intramural research, we have 89 total protocols in the past year, sample size range from one to 32,000. Among those, we saw the graph before, most of them, they sample size less than 600. The type of study in the intramural includes some social study prospective linkage study and some association study and some the pilot-owned early phase of intervention studies. This graph compares the past two years, this physical FY 11-12 to previous report. The previous report is 2010. We didn't have the 2009 data, so that's why we make a comparison to 2010 only. Comparison to 2010 data, I should point out that the past two years, we improved the data collection, data quantity. See the unknown category here, the top, we reduced the unknown, proportion of unknown a lot. Another thing I should point out is the more diverse, the participants more diverse, especially for the African-American, we have increased the proportion of the African-American. Then we'll compare the NHGRI data with NIH data here. Again, we have better quality of the data. The unknown category is significant lower than the NIH data as a whole, and also more diverse participants in the NHGRI clinical research participants. And then compare this with the U.S. census data. Again, we have better recruitment of minority participants. This one is compared to all this comparison just for acidity, and we have increased the recruitment of Hispanic or Latino compared to previous report and compared to NIH. I know that because NIH has a lot of unknowns, so there's a true increase compared to NIH or not, and we cannot see at this point. Similarly, distribution about non-Hispanic and Hispanic compared with the U.S. census data. This gender difference, we tend to recruit in this past two years more female participants, and the female participants' distribution is higher than the U.S. census. In summary of this past two years, inclusion of women and the minority in the NHGRI clinical researches, NHGRI did improve the enrollment of minority and the women participants. And also we compare NHGRI with NIH, we have more diverse participants and more women participants. We compare NHGRI with the census data, then the NHGRI had a more diverse group in the enrolled research participants. Finally, I would like to acknowledge the peer viewers. They did a good job in the scientific review and the program officials and the program, the grants management special lists, and also the team members worked on this report. Thank you. I'm happy to answer your question. Yes, Howard. So in terms of the congressional mandate or internal mandate or whatever mandate seem to be close or above the bar, I'm wondering whether this institute should also take a look maybe in closed session at things like were there a sufficient number of a particular group to answer a scientific question. And I'm not picking on NHGRI because I think you're ahead of the game. But I do worry that we check the box, we have enough of filling the bank your favorite group, but we aren't any wiser. And so I would love at some point, maybe not right now, to figure out some way of tackling the issue of are there enough people of a particular group on a study to learn something about whether we need to do things differently the same, whatever. And it's coming from my own bias with our national and cancer institute cooperative trials. We publish papers saying African Americans do differently than non-African Americans for particular outcome. But we have 9% African Americans and we're trying to make some big conclusion. And it's just a, I was going to say it's a joke, but we're in open session. So it's something that's not quite a joke. So I think we need to take this on a little bit more than just the congressional mandate. That's a good point. Thank you so much. Pity, you have something to. I would just like to make one point and that is, that is supposed to be one of the review criteria. Now we might want to look at that a little closer when it comes to the review of individual applications. But that affects the scientific quality of that application if they don't have enough. And that should be reviewed, evaluated. Well, typically it's not a primary aim. And so, but then secondary analyses get done. And we have, at least in my area, we have a larger literature of underpowered studies, which make us not really any wiser about whether we should be doing something different with underrepresented groups. So, in my experience in the peer review setting, there are projects that target certain racial ethnic groups. But there are also projects that cast a broader net. And I frequently hear the comment they're probably underpowered for their African American, Latino population. What we don't know is what does come of that study. And I would think that's something that we could gather the data on. I like what you presented. I should have given my comments last, I guess, not first. But because I love what you presented, just wondering if we could look more functionally. Thank you. Yeah, we ask this question as well. When we develop the new tracking system for the whole NIH, we ask the same question, should we just include 10 or 100 African Americans in this study that's sufficient to meet the requirement, but not sufficient for the study of power? We ask the same question or try to figure out how we can do that. Okay, thank you, Rongling. At this point, you've earned a break and the cafeteria upstairs is going to close. I'm going to beg you to be back here at 3.05. We still have many miles to go before we sleep. Okay.