Good afternoon, everyone. I'm Christine Mitchell, the Executive Director of the Center for Bioethics at Harvard Medical School. Welcome to our third of four webinars during Black History Month. This work grew out of a collaboration between the National Center for Bioethics at Tuskegee University and our Center for Bioethics at Harvard, especially a collaboration between Ruben Warren and Bob Trug, our director, and people involved in each of these two centers. We've changed the title a little bit from what you see on our screen. This webinar is going to be entitled Repairing the Past, Understanding and Leveraging the Political Determinance of Health. Before I turn this over to my colleague Ruben Warren, I want to take just one minute to acknowledge him. Many of you already know Professor Ruben Warren, both by his work and reputation, and if you have attended our previous seminars for Black History Month. However, you might also want to know that he has a pretty impressive background, both because he has a dental degree from a Harry Medical College, as well as a master of Divinity degree from the Interdenominational Theological Center in Atlanta, and an MPH and PhD degrees from the Harvard School of Public Health. Back in the 90s, he was the Associate Director for Minority Health at the Centers for Disease Control before going to direct the National Center for Bioethics and Research and Health Care at Tuskegee University. A couple days ago, I was taking someone on an errand to get their vaccine, and I heard a familiar voice on NPR. And it was Ruben Warren talking to a reporter about the Tuskegee United States Public Health Service syphilis study at Tuskegee. And if you don't know, you should know about the book that he co-edited of reflective essays on that study. So it's been a great pleasure to begin to get to know Ruben Warren and some of his colleagues at the National Center for Bioethics at Tuskegee. And I'm going to turn this over to Ruben now. Oh, no, I need to ask Ashley, without whom this would not be working, if she will just give us the rules for how people can ask questions. Thank you, Christina. And thank everyone for joining us today. We are recording this event, and it will be posted to the Center for Bioethics, Facebook, and YouTube pages. We ask that you submit questions at any time during the presentation using the Q&A feature found at the meeting controls at the bottom of your screen. Select questions will be discussed after the presentation. And you can also use the chat feature to share comments or any technical issues. I would recommend using all panelists and all attendees to submit any comments so that everyone can do them. And if you're interested in upcoming events, please visit the Center for Bioethics website and sign up to get the invitation. Thanks so much, Ashley. And now, Ruben. Thank you so, so very much. I'm excited about this event where this is our third of four events and the relationship that we've developed over time with the Harvard Bioethics Center is an exciting opportunity to do things right and do things the right way. We're really in great collaboration. And the most important thing for my context is that we are working into generation. So our two students are colleagues. And they have as much to say and probably more to think about than we do. So we're engaged together to turn it over to them to make things better than they are. Now, what I also want to be clear is that this is the third session, our first session dealt with the kind of issues that impact upon the health delivery system, particularly as the impact upon people of color and also health care delivery and research. The second issue dealt with this thing called the Tuskegee Syphilis Study, the misnamed and misnomer. And we had a family member, as well as a professor of ethics and biology, kind of clear up the issues. And now we're moving on. We're looking back to move forward. And today's session is so exciting. But let me pause a moment and have our two colleagues that are joining us, joining me and Christina, moderators, to introduce themselves. And tell us a spot about them so you'll know who's controlling and managing this session, our two new colleagues. Thank you so much for such a lovely and honorable introduction. My name is Keona J. Nguyen. I am a PhD student at Harvard Chan School of Public Health. I completed my master's of bioethics at Harvard University, the Center for Bioethics in 2019. So almost two years ago now, that's quite hard to believe. And I'm very excited to be here and to moderate this very insightful and really necessary, really cutting edge discussion. Hello, everyone. My name is Chloe Adams. Why I'm an undergraduate student at Tuskegee University studying animal science with hopes to become a veterinarian. I'm very excited to be here today and to introduce the amazing Dr. Daniel Dawes. Attorney Daniel E. Dawes is a nationally recognized leader in the health equity movement and has led numerous efforts to address health policy issues impacting vulnerable, underserved, and marginalized populations. He received his law degree from University of Nebraska Lincoln and is a health care attorney and administrator. Attorney Dawes serves as the executive director of government affairs and health policy at Morehouse School of Medicine, is a lecturer of health law and policy at the Statue of Health Leadership Institute and serves on several boards, commissions, and councils focused on health equity and health reform. Thank you, Attorney Dawes, for joining us today and sharing your insight. I'm very excited to learn from you today. Well, let me also add my gratitude and thank you, Chloe and Kiona, for that very generous introduction. I also want to thank my dear friend, Ruben Warren, Dr. Warren, as well as Professor Christine Mitchell for the opportunity for this platform to share my thoughts about how we can move beyond merely nibbling around the edges of the problem of health inequities in America. We're going to talk tonight about how inequities have been concretized in our structures and system, in our communities over time, looking at this through, of course, a political determinants of health lens. And I wanted to start off our conversation by showing a short video called Jessica's Story. So Ashley, if we can bring that back to the beginning and then we're going to start our conversation. To best grasp the political determinants of health, let's examine a hypothetical example that combines experiences of real people in urban and rural communities. Imagine a 19-year-old woman, we'll call her Jessica. After enduring several miscarriages, she barely survives giving birth to an infant nine weeks early, the baby weighing only three pounds. Her son is placed in the neonatal intensive care unit, the blood from his umbilical cord, revealing over 200 toxins. Where did the system fail Jessica and her baby? How and why did these results occur? Three years earlier, Jessica had left her parents' house. Access to treatment for her dad's substance use disorder had been eliminated when policymakers closed three of the city's public community health centers to save money. Contending with his wife's lack of education, neither of Jessica's parents could secure a job with a livable wage, prompting serious and substantial mental health conditions. Jessica moved to a low-income neighborhood in the city. She never knew of the extent of how the appalling conditions of her neighborhood were politically determined. For example, determined to keep housing segregation in place, politicians expended very few resources to build sidewalks, parks or recreational facilities. Healthcare providers refused to operate in Jessica's community due to poor reimbursement rates for Medicaid. Because they resisted creating bus routes, lawmakers dissuaded grocery stores from operating in the community, preventing residents access to fresh fruit, vegetables and meat. Simultaneously, policymakers altered zoning laws to permit development of a dump site and a chemical plant, switching the community's water source from a clean river 10 miles away to a nearby polluted river to save money. This water was used to drink, bathe and wash clothes. It also irrigated the lawn at Jessica's apartment building, adding to the list of pollutants and environmental hazards in her neighborhood. And because her district lacked established tenant rights, her landlord had no interest in improving unhealthy housing practices. Jessica found work as a cashier at the corner convenience store, a job with no employee benefits, including health or disability insurance. Because policymakers rejected proposals to increase minimum wage to a livable income, Jessica often substituted her employer's free snacks policy as a meal, never realizing the effect that high-fat, high-sodium food would eventually have on her or her baby's health. With local politicians striking down an effort to ban smoking in convenience stores, Jessica was constantly subjected to a barrage of secondhand smoke. And when she discovered she was pregnant, no attempt at receiving health insurance coverage was successful. Her non-ACA compliant plan denied her maternity coverage because they viewed her pregnancy as a preexisting condition. Medicaid, the government's health insurance program for low-income families, denied her coverage for not being poor enough. After finding a ride to the free clinic, Jessica waited more than half a day to be seen by a second-rate physician, a doctor who was condescending and offensive. Realizing she could not afford to take more days off from work, she never went back. At 31 weeks, a neighbor drove Jessica to a hospital ER 20 miles away. Seeing that Jessica was experiencing excessive swelling in her face and ankles as well as seizures, the emergency team decided to deliver her premature son immediately. Due to complications, her newborn son was sent to the neonatal intensive care unit. Once his organs were deemed mature enough, he was taken off the machines and sent home with severe cognitive defects. And in their apartment, Jessica and the baby were exposed to mildew and cockroaches, causing her son to develop respiratory problems. The landlord refused to remedy the poor conditions, telling her to move if she didn't like it there. Jessica struggled to find early childhood care and access to schools with educational assistance, healthy food options, and other resources needed to thrive. Because their school and community lacked the resources to enable Jessica's son to even barely reach his potential, he dropped out of school after entering eighth grade, just as his grandmother had done, repeating what is surely the ongoing rule of poverty. Jessica's story shows the compounding effect of political determinants over personal responsibility. No matter how reliably Jessica tried to act, structural, institutional, intrapersonal, and interpersonal obstacles stood in her way. Political determinants were pulling strings that prevented Jessica and her family from achieving optimal health and their full potential. What does this mean for all of us? What can we do to improve and mend our community's most damaged systems? I am, let me make sure you all can see this, okay. So can you see the slides? Yes, all right, wonderful. So, you know, they say that a picture is worth 1,000 words and I'm hoping this video is worth much more than that, right, when we try to grapple with the concept of the political determinants of health. You know, when I say that, what I'm referring to are the upstream factors, right, that impact our health, going to the instigators of the causes of health inequities in America. You know, most everybody I think by now understands either explicitly or implicitly what social determinants of health are. You know, those structural conditions in which we are born in, right? We live and we work and we play and we pray and we die in that affect all aspects of our health and the quality of our lives on this earth, right? But what's important to realize is that for every social determinant of health or environmental determinant health or behavioral health or healthcare, right? There was some preceding legislative, regulatory, legal or other policy decision that resulted in that determinant. And those are the political determinants of health. So just to ensure that we're all on the same page, I define this to mean it's a systematic process, right? Of structuring relationships, of distributing resources and administering power. And they operate simultaneously in ways that mutually reinforce one another to shape opportunities that are either going to advance health equity or hinder health equity, right? So now that we know that these determinants can have a negative impact on health outcomes for vulnerable and marginalized populations, I wanna get started into how we came to be or how this came to be, right? So as you can see on your screen, this is Lady Columbia or Lady Justice representing our great country. And as we know for too long, many racial and ethnic minorities and other vulnerable and marginalized groups have found themselves in a precarious situation. Their health, their lives have literally been hanging into balance, right? Many of them have been falling through the cracks of our health system, educational system, our human services system, behavioral health, housing, you name it. These communities struggle to live in a society that has intentionally erected barrier after barrier to weaken their bodies and hasten their deaths. So we know for over 400 years, these groups have experienced inequities throughout the life course, right? The inequities and health status and healthcare are widely documented. When in fact, we have over 7,000 peer review journal articles highlighting that. And today I chose seven tombstones to highlight the terrible impact that these inequities have had on communities of color. Today we know that blacks are three times more likely to know someone who has died from COVID-19. Only 6.1% of the vaccinated populations today are minorities. We know that when you think about the death rates of COVID in terms of children, three quarters of the children who have died from COVID are racial and ethnic minorities. And the list goes on and on as we know. So we know that these groups, racial and ethnic minorities, people with disabilities, lower socioeconomic status individuals, LGBTQ plus individuals, and individuals living in rural communities are dying disproportionately each year. And the toll that it has taken is unconscionable, right? But the one thing that I hope we remember tonight is that we must always remember this, that the United States' health is not an organic outcome. It is not a coincidence that certain groups of Americans experience higher premature death rates or poor health outcomes than others. Why? Why has this been happening, right? Today, of course, we recognize, as you just saw from Jessica's story, that there are a variety of forces that are impacting our health, right? And determine the extent of our lives on this earth. We know that it's true, air pollution, climate change, toxic waste sites, unclean water, a lack of fresh fruits and vegetables, unsafe, unsecure and unstable housing, poor quality education, inaccessible transportation, a lack of blue and green zones or parks and other recreational areas. And of course, other factors play an outsized role on our overall health and wellbeing. They increase our stress. They expose us to harmful elements and they limit our opportunities to thrive. These multiple determinants of health, but especially the social determinants of health, play an outsized role in these human-made pre-existing inequities. But underlying each one is a political determinant that we can no longer ignore. You see, we've been stopping, I think, too often at the social drivers of inequities, failing to look back, right? And dig even further to see the depths of the problem and understand their root causes and distribution. And as a result, we've been missing the link between the social determinants of health and their political roots. So this pandemic, I think, illustrates or demonstrates the inconvenient and harsh truth about the impact of social determinants of health and how collectively these factors significantly contribute to our society's health and equities. It shows, as you saw from the video, the compounding effects of political determinants over personal responsibility, because no matter how much many African-Americans, Native Americans, Native Hawaiians, Latinx Americans, Pacific Islander Americans, and lower socioeconomic status individuals try to act responsibly, they are always structural, institutional, interpersonal, and yes, even intrapersonal obstacles hindering them. And beneath these communities' notice have been political determinants that have pulled and continued to pull strings that prevent them from achieving their optimal health. We all know that the inequities that predate COVID did not suddenly appear, right? Nor are they inapplicable. All of these individuals, these marginalized groups still contend with neighborhoods that are largely devoid of necessary health protective and health sustaining resources. And they're still contending with the political determinants or drivers that created, perpetuated, and exacerbated these health inequities over time. And so is it any wonder why COVID-19 has not been striking all groups equally? Well, no, not really, because when you think about it, our economic and social policies have not been benefiting all groups equally. Think about it this way. Who is able to get tested? As we all saw early on in the pandemic, you know, there are many of us raising our hands saying, hey, we want to provide vaccines or testing kits to our communities. We see today the disparity in terms of vaccinations again, politically determined. Who gets care and the quality of care? Even access to the internet as we see right now, right? Walkability, public space access, even access to water and access to food are all politically determined. So we know in effect that many black, indigenous, and other communities of color show us how one political determinant after another has resulted in a continual tightening of a chokehold on these communities and the eventual disaster that brought to light the inequities we now have seen magnified, right? Plaguing it, high obesity rates, diabetes, maternal mortality, depression, and many other health issues can be firmly linked back to political action or inaction. But by understanding these political determinants of health, their origins, their impact, and their interconnection with these multiple drivers of health, we will be better equipped to develop and implement, I hope, actionable solutions to close the health gap. I think what we're seeing today is that behind virtually every health disparity and subsequent death, especially during this time of COVID-19, there were specific and insidious political determinants that led to the person's premature death. So for a moment, I wanna paint this picture of the tree of health for you. Initially, you may notice on your screens a tree, right? The fruit on this tree, the individuals or even the tombstones surrounding this tree. But actually this picture is far more representative of what our society currently has to offer some of its most vulnerable people. You see, yes, the tree represents society. There have always been co-laborers in this movement, in this fight for health equity, as we'll see. And I know many of you in fact have been co-laborers who have tended to this tree. We've worked tirelessly to feed the tree evidence-based policies, programs and practices with the hope that the tree would provide fruit that would benefit all of society. However, the reality is that, there've also been others who've been working overtime to supply the tree with that which would do it harm. These are the roots that are undergirded by racism, classism, ableism and many other deleterious motives from the bottom of the tree's base, all the way up and through to the ends of its branches. What is supplied to the tree is multiplied by the tree, right? So now due to the root causes of inequities, the fruit represents higher rates of diabetes, inaccessible safe and secure housing, a lack of nutritious food and any other number of those outcomes that we now know as the social determinants of health, right? And as that poisonous and rotted fruit falls to the ground, the tree that had the potential to provide life-giving nourishment to all who encountered it, now leaves death and destruction in its shadow from one generation to the next. But all hope is not lost, right? Now I want you to imagine what could and should have been. The roots of the tree, which anchors the tree and is supposed to absorb nutrients from the soil, represent the political determinants of health. And the detrimental factors that the tree's roots were absorbing include racism, sexism, classism and many other evils. Every political and policy decision that is made feeds into the tree, yielding fruit which permeates throughout our entire society. But if the tree is rooted in health equity, the end result is a society that is nourished, cared for and capable of achieving its full potential. You see, what we've learned from this is that many of these deaths that we have seen almost half a million deaths and even more when you compound that with all of the inequities. It's a reminder that many of these were preventable and downright avoidable if only these communities had been fed by a tree of health that bore life-sustaining fruit. So let's talk about how we got here, right? We're gonna go back, let's look at big P policy and little P policy, governmental policy and then of course, non-governmental policy or commercial interests, right? How did we get here? How does inequality get under our skin and lead to this accelerated aging that we've learned so much about, right? Dr. Arlene Geronimus and others coining the term biological weathering or let's talk about how it increases our rates of chronic diseases, right? As other researchers have identified, destroying the social and the economic fabric of many of these neighborhoods. Well, let me go back 400 years, right? Evergeneticists have identified how intergenerational trauma has impaired our ability to reach health equity. But when you think about it in this way, we've talked a lot now about the social or the structural conditions in which we live in, right? We're born in, live in, die in. Well, let's talk about how these structural conditions came to be in the first place. So in the 1600s, we know that Massachusetts became the first colony to legalize slavery. We know then that there were other colonies that followed suit, Connecticut, New York and others working in concert with economic interests, right? To legalize this horrible institution. And as if that were not enough to keep down black and indigenous populations, right? Nope, they went even further by pushing their policymakers to enact, to develop and implement and act and enforce policies that would limit their ability to move, right? Couldn't move abroad, couldn't move beyond a one mile radius of the plantation, had to carry lanterns at night if you wanted to walk around. You had to, of course, you were prohibited if you were black or an indigenous person from raising your own food, from earning your own money, from learning to read and write, right? Especially English. Many, and the list goes on and on and on. But today we've identified these as critical factors, right? In our ability to address our social determinants of health. We know then that those policies were recycled from one generation to the next into the 1700s. There was then an opportunity once we had declared independence from the UK to actually not only abolish slavery but to enact a robust health equity agenda. But as we'll soon discuss that was short lived and it would then take us decades after before the opportunity would present itself to push again a health equity agenda and federal policy. Well, that too, I hate to spoil, or to give you that spoiler alert but we know that that too was short lived.  And we now know today through of course our researchers that there is a direct link to aggressive breast cancer prevalence from that time today among African American women. They have the most deadly form of breast cancer, right? Owing again to the stressors of our society. Well, now we move into an environment where you have these racially explicit laws denying blacks the ability to rate, to realize their optimal health and their full potential. But then folks got a little savvy in policy, right? When the Supreme Court came in after there were health equity champions, civil rights leaders saying, no, no, no, that violates the Equal Protection Clause. We then saw policy makers moving from intentionally or facially intentionally discriminatory policies to what we call facially neutral policies, right? So they did not on its face explicitly deny the benefits of that policy to black and indigenous groups or others. But when they were implemented, they had the same or equal effect, right? There was a disparate impact. So let me talk about that very quickly in the short time that we have. Many of us are familiar with policies that came out of the great new deal. We know that after World War I, there was a crisis in this country where many folks were malnourished. We know that times were tough. And Franklin D. Roosevelt, of course, goes out and enacts these amazing policies, right? For the most part. But he also enacted policies that were discriminatory. And one of those is the Homeowners Loan Corporation Act that essentially sent out or authorized property appraisers in over 200 cities in the United States. And their job was to go out and essentially grade these neighborhoods on an A, B, C, or D scale and to align them with a specific color. So the green areas of the city were your affluent white communities. Your blue areas of the city were your middle class white areas. Your yellow communities were your undesirable immigrant communities. And then those were, of course, Mexican, Cuban, Jewish, Irish, German, et cetera communities. And then the red communities or D communities were your hazardous communities. And those were your predominantly African-American communities. And what they did was to essentially aggregate all of these reports, bring them back to D.C. and actually used it to develop further policies, right? So we had a policy create this report. This report then informed other policies which had a discriminatory impact. And essentially what they did was to prevent these red and it sometimes yellow-coated communities from getting VA or FHA mortgage loans. Again, starving these communities of the resources that they needed to thrive. Well, after that, we know then we went through another world war, right? World War II. And after that, President Truman tried to enact some robust health policies but intermingled with those again are policies that had a terrible impact on black and brown communities in this country. So infrastructure bills, such as the Housing Act that created the urban renewal program in this country, right? Displacing over half a million African-Americans throughout the nation. We know that this law was actually implemented in conjunction with state and local policy makers. And what they did was they essentially took folks's housing through their eminent domain powers, took their houses, took their apartments and then turned around and sold it cheaply to real estate developers who then created housing for more affluent communities. And as if that weren't enough. If you think about many black and brown communities today many of you might have noticed that there are oftentimes these major highways cutting right through the neighborhoods, right? Go to Overtown in Miami, go to St. Petersburg, Florida, in Atlanta, Georgia, Baltimore, New York, Newton, in Boston, go to Detroit, Omaha, Nebraska all throughout this country. You will see that a federal law, the Highway Act actually was implemented in conjunction again with state and local policy makers and they determined where to place these highways again in the neighborhoods of the folks that they deemed to have the least value, the least amount of privilege and power. Well, today we see the effects of a lot of these decisions. Whether it is in New York and Harlem and Manhattan where six of the seven bus depots were placed in Harlem now causing these children, black and brown children to have the highest rates of asthma in the entire country. We know that research today shows that many African-Americans and Latinx and other individuals live in communities that are hotter than the rest of the population and the list goes on. But again, all of this was as a result if you really go further upstream to the source of these inequities, if you tie these structural conditions to their political roots, it makes sense what instigated all of these. What is the effect today? Well, we know that it has led to a poverty tax on many of these communities, right? Again, hurting these communities one decade after the next. And today we see it in the form of higher payments for auto insurance, higher payments for mortgage loans, lower property appraisals. We see the effect it's having in terms of deserts, food, pharmacy, hospital deserts, making it more difficult to access resources to improve health and maintain health. And now we see through climate change, right? With what's going on, this phenomenon, right? Of moving away from red lining to now blue lining where we know back then there were policies, there were laws that were enacted restricting black and indigenous and other communities of color from buying property by the seashore. They were pushed further inland, which ironically now are higher elevated lands. And as these sea levels continue to rise, Miami, St. Petersburg, et cetera, you see many of these folks being pushed out again displacing thousands of minorities across the country. Well, what's the effect today? Why does this all matter? Michael Marmot, Professor Marmot, once stated that life expectancy is a measure of health. Tell us a great deal about how a society is doing, but the inequalities in that society, tell us even more. Now, once you overlay our current maps with all of these maps that were red lined maps from the 1930s, when you overlay that with other red line maps from the private corporations showing where they refuse to place hospitals or clinics, pharmacies, et cetera, and you overlay that with other social factors, it is not surprising then that these very communities, these very neighborhoods that have been marginalized are the ones with the lowest life expectancy losing on average a generation. Why does this matter? Because today we rank 43rd in terms of life expectancy, right? And if you disaggregate that by race and ethnicity, whites in this country, if you were to take all white people in this country and they became their own country, they would rank actually 50th in the world in terms of life expectancy. If we took all black people in America and they became their own country, they would rank 103rd in this occurrence. And if you took all indigenous populations in America and they became their own country, they would rank 143rd. This is really serious. The bottom line is that we all could be doing well, right? We could be doing better. And over the next 20 years, according to research published by the Lancet, prior to COVID striking actually, we were expected to drop 21 places in the ranking to 64th in the world in terms of life expectancy. And all of this happening while we are increasingly becoming a more racially diverse society, a racially pluralistic society, right? As the number of racial and ethnic minorities continues to increase, our life expectancy is expected to drop. This has tremendous economic and national security, not mentioning the moral dilemma for us moving forward. So we know that policy has been a driving force for many of these inequities in our country, right? But I want to quickly talk about the few occurrences, right? In which we had leaders, bold leaders, courageous leadership from health equity leaders starting in 1789, I'm purposely choosing that since that's when we were formally meeting as a constitutional republic. Congress convened, we had President George Washington convening as president. And at that time, there were a group of abolitionists, the group of health equity leaders, as I would call them, who cared deeply about the most vulnerable populations among us, fighting for the rights of people with mental illnesses in America, fighting for the homeless, fighting for black and indigenous groups, right? And in 1789, a group of abolitionists strategized and said, you know what? We have to leverage this moment. We need to recruit a policy influencer, right? And get that person to push this agenda within the federal government. And they did that with Benjamin Franklin. These folks basically approached him and said, Benjamin, would you use your influence and power to convince your colleagues, your peers in Congress to do the right thing by not only abolishing slavery and stopping the breakup of children from their mothers, the separation of these families and slave families, would you also advocate for them to get proper clothing and food, as well as medical care and the like, right? Education and real employment opportunities, right?  And so he did go about assigning his name to a petition. They sent it to Congress. And if you think we're having a really heated discussion over health equity in America and health reform in America, I can promise you it was probably just as equally contentious, folks were upset.  When you know that we are a newly formed government, why would you bring up this contentious issue? And so in bullet by bullet, Congress basically made the arguments for why they couldn't stop the separation of children from their mothers. Why they could not stop the breakup of these enslaved families. Why they could not provide medical care or education or security, et cetera. Well, we deem the social determinants of health, right? Deem as critical social factors. Well, before Benjamin Franklin could address their petition, he died unfortunately three weeks later. And that was the first time in US history that the light of health equity had dimmed in federal policy. It would take us 75 years later, during a major war, the Civil War in 1863, before President Abraham Lincoln and his supporters would be able to, with the political stars aligning, be able to then negotiate a bill that those in 1789 wanted, what we call the Freedmen's Bureau Act. And with this bill, as contentious as it was, there was one provision that was even more contentious. So they wanted provisions in there to provide food and clothing, education and employment and security for newly freed people, right? Formerly enslaved black people. And poor whites would have been displaced as a result of the Civil War. But there was that one provision, the provision to provide medical care, health services to these newly freed people that just could not get over the finish line. And so in the spirit of compromise, President Lincoln decided to strike that provision from the bill. Well, we all know how history, how that story ends through history. Four weeks later, President Lincoln was assassinated. But his supporters not wanting to squander that opportunity to advance health equity, believe that upon reading, second reading of that law, the Freedmen's Bureau Act, that it actually afforded them the opportunity to provide health services to newly freed people. So that's why we see what Freedmen's hospitals and clinics around the country, we see historically black colleges and universities that were created because of this landmark law. But as we have seen in 2020 and 2021, racism does not sleep, right? And truly the forces back then worked over time to undermine that major health policy addressing the social determinants of health. And they succeeded finally on the seventh anniversary. Well, it would take us again, 150 years to realize another opportunity to provide and create a comprehensive health policy, what we call the Affordable Care Act, right? In many respects, mirrored after those provisions in the Freedmen's Bureau Act, taking a robust health equity agenda. So is it any wonder that that law has been under attack from the very minute it was negotiated up until today? No. Well, in the few minutes that I have, I just wanted to talk quickly about how we can leverage the political determinants of health. You heard me talk about how they involved the systematic process of structuring relationships. You heard me mention the Homeowners Loan Corporation Act that red-lined America, right? An act of the federal government in conjunction with state and federal policymakers. Think about structuring relationships in terms of the anti-miscegenation laws, the immigration laws, right? Steeped in racist ideology, illegitimacy being won. Secondly, we talked about how it is about distributing resources, right? Think about the appropriations process. Think about testing kits or the lack thereof and the distribution of vaccines today, right? The political determinants at play. Shouldn't be surprising. And it shouldn't be surprising then that there's been a dearth of health policies bolstering equity in America. And then thirdly, we talked about how this process involves administering power, right? This includes redistricting, gerrymandering, et cetera. And it operates in ways and operates simultaneously, right? In ways that mutually reinforce one another as we have seen. Well, I want to close by just bringing your attention to this. If you certainly want to learn more about how these levers can be pushed and pulled to affect the changes that you seek in your community, I encourage you to read the book, The Political Determinants of Health. But right now, I just want to quickly make this comment. And it's the fact that to advance health equity in America at this level, you must demonstrate the value of investing in change. You see, in our country, advocates must understand the disquieting and the harsh truth that the political determinants of health inequities have rarely been addressed unless their reduction or elimination served other purposes. The success of any health equity advocacy depends on how palatable they are to commercial interests and whether there is an investment value to the government. For the dearth of policies that we were able to realize in this country, it's very clear that the only reason why they were able to get over that finish line was they understood that notion, right? And aligned it with such. So rarely does an advocacy effort succeed if it significantly interferes or undermines commercial activities or national security. Something to think about, right? As we are being more strategic. Well, I want to talk about the good news though. So I am a cup-runner over person and I hope folks haven't heard my talk and say, oh my gosh, this is depressing. There's been a dearth of policies. Good Lord, it takes 150 years to realize this stuff. Well, I actually believe we are in a wonderful era now and sometimes we need to have experienced and witnessed what we did to shock our conscience to make sure that we don't lose focus or else we are doomed to repeat what happened in the past to undermine these laws. So the good news is that the structural barriers and the resulting inequities, they're not permanent but it will take greater action and collective agreement from individuals, from all of us committed to stopping out inequities and formulate and execute the strategies and the policies to overcome them. So unless we do these things we're gonna make little progress in keeping the social determinants in check. So here are five things that I think can help us move that needle toward health equity. The first is that we have to continue engaging in these tough conversations, right? We're in a very partisan, highly polarized time but I do think it is so important that we talk to folks about race, place and class. Whether we like it or not it's important to have these discussions and we gotta advocate for a full commitment to tackling health inequities upstream in all areas. We have to work upstream. We certainly must really venture further coming out of our comfort zones to address the social and the political determinants of health inequities. Understanding when they are at play, right? It can be a little confusing but we must dig down, drill down deep to understand that delineation. Then we have to research the history of our communities and address the past policies and programs at all levels that created and have perpetuated inequities, right? Remembering that exclusion has always been easier to realize in policy than inclusion. Then we must do a better job strengthening our networks and an engagement with the communities that have been closest to the pain and the problem, working with them to address these issues. And then lastly, just wanna leave you with this thought that we have to understand that health equity begins and it ends with the political determinants of health. Again, I wanna thank you all so much for the privilege of your time and I want to thank Professor Mitchell and Dr. Warren and all of you for the opportunity to share these thoughts with you tonight. So I will stop sharing and I believe we have a few minutes to take some questions, right? Fantastic. Overwhelming and we've moved from talking about the problem to doing something to resolve it. Let us get the first two questions from our co-moderators, either Chloe or Keona. What question burns you that you'd like to ask Professor Gawes? I can start. One of the questions that I was thinking about really overlapped with one of the questions that popped up in the chat. So to just kind of get it, knock both of these out is like, how do you see a single payer health system fitting into this picture or the resistance to a single payer health system in the United States? Yeah, that's a great, great question. I think it's very clear that when we think about single payer, there are certainly pros and cons to it, right? Pros being that it deals with the fragmentation in this country. It deals with the issues of interoperability. It provides universal health coverage to groups that have long been excluded from our health system. We've been locked out of the system, quite frankly. I certainly think that in light of all that we witnessed and I will say, having worked on the Affordable Care Act and spending almost every waking hour in grain and showing it now, as you can see from my head, that was quite an experience. And I think I was a lot more naive back then, probably more optimistic that we would be able to create that universal healthcare coverage and system that we all desire. But I will say that it was extremely difficult, even trying to get the public option, right? To compete in the health insurance exchanges, in the health insurance marketplace with these private health insurance companies. So I think for me, my goal is certainly health insurance or universal healthcare coverage to the extent that we can get it, realizing that it is an uphill battle. If you try to venture out, as I have said earlier, not aligning that policy with a commercial interest or making that government investment value case. So I hope that we will be able to realize that vision. I'm hopeful that under a Biden administration, they'll continue that trend of pushing, right? To get us closer to universal healthcare access. But again, I don't see single payer in the future for us any time soon. Question and answer, clear, Chloe, thank you. Hi, I just wanted to thank you first for a wonderful presentation and also for adding depth and context to my personal experiences as a Black woman in America. My question was more of a, what is your opinion or what would you say to those who? I'm sure you heard the term, everyone can't be at the top. So what would you say moving forward?  We just don't have the resources for that. So what would you say moving forward should be done or how can we make things more equitable for everyone to live knowing that we are on earth and things that aren't just gonna be completely equal? So if I could push back on that, I actually believe that we all can live in a nice neighborhood, right? And we all should be living in a nice neighborhood. We should all be afforded, right? A fair opportunity to thrive. And that's what equity is all about, right? Of course, it is about giving people what they need, when they need it in the amount that they need in order to thrive. And so I believe that the goal should be that everyone gets to live in a nice neighborhood and that they should not be disadvantaged from such. So I actually would kindly push back to say that I do believe we all should be striving for that goal and we all can. I've heard that argument that, oh, the poor will always be among us. And they use that as an excuse when we are negotiating policy to deny certain groups. I totally disagree with that. And I think we've got to push back on that sort of notion, right? Moving forward, because I do think everyone should be given that fair opportunity and we can, resources are plenty. That's why you never see me use that image of the boxes and then have folks talk about, okay, I'm gonna take the box and give to this one. No, I believe we have a lot of resources in this country and we can align them with the greatest need if there is the will to do so. Totally agree. Thank you. All right, thanks, Glory. Miss Dean, it's Mitchell. I can see a burning question coming from you. You're leading. Regrettably, we are at a time when we have to stop partly because Daniel has to teach a class. So we need to let him go, but I really wanna thank you both for your compassion and your analysis, as well as your hopefulness and optimism about what's possible. You briefly mentioned your book, but I just wanna say a lot of the summary that Daniel gave us about what has happened in United States history that politically determined what the social determinants of health have been in our country is in the second chapter of his book, along with a much more detailed analysis of how to influence those political determinants in order to improve opportunities for health. So among all of us. So thank you so much, Daniel. I want to also remind people, as some of you will have seen in the chat, that there is one more webinar coming up in our series this month. And next Wednesday, Dana Bowen Matthew will be with us to talk about the history of structural racism in Charlottesville. And our colleague, Lachlan has put a couple of links to materials that would be useful to look over if you have a chance before registering and being present next Wednesday to meet and chat with Dana Bowen Matthew. I wanna thank our two students in addition to Daniel Dawes and also encourage those of you who are going to join us in the subsequent hour for debriefing and talking about this presentation among the students at Tuskegee Institute and at Harvard. Ashley, are there more things we need to say? Nope, that's it. So thank you all so much for attending and we hope to see you next week. Thank you.


Welcome back. So this afternoon's session, the main focus is going to be functional annotation and analysis of transcripts. The lecture portion here is actually going to be kind of on the short side. We're going to have more time for the lab. The lab is a little bit more expensive. There's a lot of information to cover there. And hopefully it'll be bringing together parts of what we've learned over the last couple of days in addition to some new stuff. So for this last module, certain learning objectives, and we're going to explore the different methods that are available to glean biological function from transcript sequences and want to be able to differentiate between homology based and sequence composition based functional inference. So two major ways of going about predicting functions of your transcripts or any proteins that they might encode. So when we do a transcript assembly, we end up with a fast file containing our transcript sequences and essentially strings of nucleotides. We need to figure out why is this transcript important? Functionally, what does it represent? What is it doing? Can we gather hints of biological function from this raw sequence data? There are a couple of ways of going about doing that. The most straightforward way is to look for a sequence homology. So we take that transcript sequence and we can search it against a database of all known biological sequences and ask are there other sequences that are similar to this and are they similar enough? Such that we might infer that maybe they're related in some way. And if that protein that matches to has a known function, perhaps this transcript that we're looking at encodes a protein that has a similar function. Alternatively we might look at sequence composition itself. Are there signals within the sequence that might suggest a certain type of function? So there are neural networks, hidden Markov models, there are various types of machine learning methods that we can use such as pattern recognition algorithms for looking for sequence features that are conserved and that could be indicative of a function. Starting with database searches, the most common way of doing a database search is to use the BLAST program. If we're starting with a transcript sequence, we can use the BLAST X utility to effectively search protein database with 6 frame translation of that transcript sequence. If we have a protein encoded within our transcript, we'll detect homology that way, or we can perform BLAST P instead of BLAST X. We have the protein sequence to do a more direct search. We're sticking with the nucleotide BLAST for now. We'll search our protein database. There's a nice collection of protein sequences that are available in SwissProt. SwissProt is part of the Uniprot knowledge base, which includes Tremble, which is essentially a non-redundant database of all known sequences and translated. You can see there's 114 million sequences as of fairly recently, I just put this together or updated it within the last week, I believe. There's 114 million sequences in our protein sequences. SwissProt is a manually reviewed subset of this. It has 557,000 sequences. That was as of May 2018, last week or so. SwissProt is really one of the best resources for doing this kind of search. There's a lot of information that's tied to each one of these SwissProt records, as they've been manually curated. Just to give you an example, there's one record that we find in the SwissProt database. It tells us information about the function, the known function. We have genontology terms. Everyone familiar with genontology? It's a structure vocabulary for defining the molecular functions. It's broken down into a few different sections. They have molecular function, biological process, and cellular component. It's structured in a graph. It's basically a directed graph. We talked about directed graphs earlier this morning. Instead of having directed graphs with cameras or sequence data, this is a directed graph with terms. Each node is a description of a molecular function. There are parent terms and child terms. You have edges that are of different types. There's a part of... This one protein... There's one protein of interest, which is a fructosamine 3 kinase activity. It's also a kinase. It's part of phosphorylation. Basically, all these parent terms apply to this protein. You get more... more broad in terms of your terms as you go up the hierarchy. One of the things that's useful about genontology is once you have assignments to different products, you can look for enrichment. If you're doing something like expression analysis and you have a set of transcripts that are found to be differentially expressed, you might be interested in other certain pathways or certain functions that are enriched among that set. It'll give you more information about the biology. You basically run a statistical test or an enrichment test given genontology terms. Typically what it'll look like is a matrix like this. It's a contingency table where we have differentially expressed one axis and genontology terms on the other axis. You just break up your terms in here. In this case you get 50 transcripts that are differentially expressed. This indicates that it's enriched. It's very similar to the classical problem where you have a jar filled with marbles. You've got two kinds of marbles. You've got green marbles and red marbles. You have drawn or not drawn. In the context of differential expressed, a drawn marble is basically a transcript that we find is differentially expressed. Instead of being green or red, it has a genontology term associated with it, or it doesn't have that genontology term associated with it. You can run it through this formula in order to calculate the probability of seeing such an event. This is useful to get probabilities for whether you're enriched for having certain types of functions. There's tools that are used. You can go seek that includes all the statistical analysis. You can combine differential expression analysis with genontology category assignments and look for terms that are statistically enriched. It could be indicative of that biology. In the case of SwissProt, if you have a match to a SwissProt record, and within that protein record in SwissProt indicates that it has certain genontology terms, you can apply those genontology terms transitively to your transcript or protein adventurous. It's a nice easy way to capture genontology terms for your transcripts if you have homology. If you don't have significant sequence homology from junior blasters, what else can you do? We can ask questions like is there an open reading frame for a potential coding region? We just scan through the sequence and see do I find store codons and stop codons. There's a nice long open reading frame that's uninterrupted. For example, here we find ATG and we can keep going on and eventually find a stop codon that's in frame. Does this look like a reasonable coding region? You can use a tool like Warffinder or you can input your transcript sequence and look for all the different possible orfs. It's just an example. Put in a long transcript sequence and then hit submit and it'll return to you a whole bunch of different open reading frames that we find within that sequence. Usually, if you have a nice long open reading frame, it's unlikely to happen by chance, but this is very much tied to the nucleotide composition. If you're GC rich then you get this opacity of stop codons and you can have really long open reading frames purely by chance. It's tied to the GC content whether you find long open read frames purely by chance or not. There are tools that can take the sequence composition and determine if it really looks like it has codon metrics that are similar to other coding sequences. There are tools such as TransDecoder, it's a tool that we developed where you'll find all open reading frames within your transcripts, but then it applies a Markov model to score each of the orfs and determine whether it looks like it's a actual coding sequence or not. You can recognize functional domains in coding regions. You do PFAM searches. It's a database of Markov profiles that are made based on conserved regions of domains. You can search your open reading frame against that collection of PFAM profiles. You see evidence for a domain that might have something to do with calcium binding or DNA binding or some specific function like glycosylase or methylase. This is one of the best tools available for characterizing functions of other sequences. Take your open reading frame, put it in this case you have a web-based interface. You can just drop your sequence into the text box and press go and it will return to you all the domains that it finds from searching this database of Markov models. Based on individual domains that you find within the sequence that could be interpreted as functional or the whole combination of domains. In this case you get a whole bunch of different domains. Based on this combination of domains you might be able to figure out what its function might be. Other types of tools like a tool called TMHMM they can use for finding transmembrane domains. You just input your protein sequence and it will try to find domains that look like they're hydrophobic regions in your protein that might cross a lipid bilayer or cross multiple times. Here's the case where you just have one membrane domain.   The tool we'll use for this is called TMHMM. Most of these tools have websites where you can just input a protein sequence. When you're doing this for many thousands of sequences you're not going to do it this way. We have a command line tool that will run and capture the information running lots of sequences through. TMHMM is what this might look like. We run it through and we get a nice picture showing individual regions within the sequence that look like they're predicted to be transmembrane domains. If we know nothing else about this protein sequence we know it has an architecture that's consistent with it being a transmembrane protein. It's just better than nothing. Does the protein have a secretion signal? Does it look like it's a secreted protein? If we know nothing else maybe we can just detect that it has a secretion protein as N-terminus. There are various tools to do this. There's some sequence context for secretion signals at the N-terminus of a protein. You've got a hydrophobic region here or hydrophilic region at the very N-terminus with positive charge, hydrophobic center, and hydrophilic polar sequence at the end. These are really short sequences. 30 to 70 amino acids at the very N-terminus. Do you need a secretion signal for transmembrane proteins? This is different. Transmembrane proteins, you run TMHMM and look for this kind of signal. This is just a secretion signal. Some of these might actually be transmembrane anchors too. It's hard to tell the difference if it's a transmembrane anchor or it's a secretion signal. A lot of times the signal peptide predictors will actually predict signal peptides when their cases are actually anchored into the membrane. It's not just secretion. The latest version of the software, SignalP is much better about that. It takes into account transmembrane domains as well as the secretion signal to do a better job at predicting just the secreted proteins. Again, just pop in your sequence. This is based on a neural network I believe and it's trained for different eukaryotes versus gram-negative or gram-positive bacteria, so you have to indicate what organism you're working with and it'll give you a few different scores. As a signal peptide score it looks for a cleavage site because the signal peptide is cleaved off as part of the secretion machinery and it generates a combined score and you basically just get a list of your predicted secreted proteins. Again, it's just one of those things that if you have no sequence homology, you don't really have a whole lot of other information to go by or domains that are showing up might be a secreted peptide. It could be useful information, particularly if the transcript for this peptide turns out to be really highly differentially expressed. It's like one of your best candidates from your differential expression screen. You know nothing else about it, but it's got a nice open reading frame and it's got a strong secretion signal at the end-term risk. It's good useful information to know. So we have a tool that we developed to try to organize all this information, the homology information and all the prediction results that you get from running tools like secretion signals or transmembrane domains and it's called Trinotate. It also includes our trans decoder software for predicting coding regions within transcripts. It integrates gene ontology as well. Essentially the way this works is that you get your transcript set. I don't think I have a slide in here that walks through the whole details. Save your transcript set we'll run it through trans decoder to predict all the coding regions within the transcripts. We'll search the transcript sequences directly against SwissPro to identify homologs. We'll also search the protein coding predictions against SwissPro using BLASP. We'll take the protein coding regions and we'll search them through TMHMM, get transmembrane domains, a signal P for secretion signals. We then organize everything into a relational database that's really structured to capture all the information from SwissPro records. So basically all SwissPro has been previously parsed and stored into this relational database and if we have a good protein match or even a transfer level match to a SwissPro entry we can capture all that SwissPro entry attributes like gene ontology assignments. So if that entry has a molecular function assigned or a biological process we can capture that and basically apply those terms to our sequence of interest. We can sort of tie this all together with the expression information too. If we have expression information, we have differential expression results we can tie that together, get our gene ontology assignments, we can use go seek for doing the enrichment analysis or statistical enrichment analysis. So all this stuff sort of tied together and wrapped around this trinotate software. And of course there's no substitute for experimentally validating different protein functions. That goes without saying maybe. And for the workshop that we're going to be doing the practical that we're doing revolves around our trinity protocol. So the way this works is we start with a bunch of samples. These could be different experimental conditions or they could be different tissue samples. And for each one of your conditions you're going to want to have multiple replicates from R&C. You probably talked about this yesterday. For differential expression you really need to have biological replicates. So you have each sample, within each sample you've got at least a few biological replicates. And what we're going to do is we're going to do a trinity genome free de novo assembly and this requires that we combine all the reads. So combine all the reads in just one big sample and that's what we generate our trinity assembly on. There is a normalization process that's sort of baked into trinity right now. So if you end up starting out with like a billion reads, you really don't need to have a billion reads to generate transcript assembly. Because of the dynamic range of gene expression, you get low express transcripts, highly express transcripts. For highly express transcripts you really just need a moderate number of reads in order to reconstruct that transcript. You don't need a million X coverage, 100 X coverage or 50 X coverage might be just fine. So we have a process in here that actually looks at the amount of read support for each read. It does this using K-mer values and it basically will toss reads into two bins. One bin is the bin that we're going to assemble. The other bin is just the excess reads that we really don't need for assembly because we already have enough for the highly express transcripts. Just to give you an example of what you kind of see here sometimes. With our Salamander transcriptome assembly that we published last year, we started off with about 1.5 billion reads. But after normalization we ended up with less than 100 million reads. So that's a huge reduction. Less than 10% of the reads we needed for assembly. So just a lot of excess. We need to know this when we're doing quantification, but for the assembly process we don't need to have all of excess reads. We put it through Trinity, our assembly, and once we have our assembly then what we're going to do is we're going to measure expression levels for each one of our samples and more specifically for each replicate within each of our samples. Did you already say what it is normalized to when you combine the reads? The normalization is based on K-mer composition. So what it does is it first takes all the reads, it counts up all the K-mers and then basically after it has this database of K-mers, for every K-mer it knows how many times it's seen it within all the reads. It then goes through the reads again and based on the K-mer composition of the reads it can stochastically either keep the read or throw it out assuming that we want to have 50x coverage instead of it could be 10,000x coverage or something. Because we have the read and you look at how often where the K-mer is found, we just take the median K-mer abundance. Based on that you can sort of use that as a proxy for how many times you've seen that kind of read within your dataset. And if you only want it 50x, well then you just basically sample it so that on average you get 50x coverage instead of 10,000x. So it's going to compress and you do that? Yeah, it's like a data compression, sure. And it's different than just doing sub-sampling. If you start out with a billion reads and you just randomly take 100 million reads, that's very different than doing normalization. Because normalization, you're just removing the excess reads for the abundant transcripts. If you're downsampling then everything gets downsampled. A low expressed look gets downsampled, the same rate that the highly expressed. So it's a different process. Okay, so for abundance estimation we're going to use a tool called salmon for doing this. We're basically going to quantitate each replica for each sample. And that's going to give us an expression matrix. We'll have all of our transcripts as rows and we'll have all of our sample replicates as columns. Once we have that we can run a differential expression analysis. For that we'll use bioconductor tools. Yesterday you used ball gown as part of the tuxedo package. Here we'll use either EDGE-R or DEC2. So bioconductor packages are all very flexible. EDGE-R and DEC2 are also two of the most popular tools for doing differential expression. And once we have that we can cluster transcripts. And we're not going to do, I think we're going to do genontology and enrichment analysis. What we're going to do is we're going to do functional annotation next. So we're going to extract coding regions. Basically we're going to run abstract coding regions. We're going to do BLAST searches. We're going to do TMHMM, SignalP. We're going to take all those results including all of our expression analysis and our differential expression results. And we're going to put them all into our trinitate relational database. This is going to generate an annotation report. Then the fun part is that this actually comes with a little web-based navigation tool. So we can fire up a trinitate web and that provides us with a nice interactive way of exploring our functional annotations and also exploring our expression data. So that'll be the fun part that we'll finish with. And I told you this part was going to be short and I didn't lie. It's annotation lab time.


Ladies and gentlemen, dear friends, it is a pleasure to contribute to the celebration of the Safer Internet Day, which unifies governments, the private sector, civil society and international organizations to promote a safer and more responsible use of online technology and mobile phones, especially by children and young people. As you are all aware, in 2010, through the leadership of Secretary General Dr. Hamaduture, the International Telecommunications Union launched the Child Online Protection Global Initiative. I was honoured to become the first patron of this initiative. However, there was much more than an honour. This was also a call to action. Since then, we have implemented the Child Online Protection Initiative in Costa Rica through the appointment of a National Commission on Cyber Security. With the support of ITU, we are developing a national model to promote online protection involving not only government but the private sector, NGOs, schools and parents across Costa Rica. I hope we can serve as a role model for other nations. In September this year, Costa Rica will host the first ITU Global Youth Summit, which aims at mobilizing youth to join forces and create solutions for social good. Young people are the undeniable pioneers in the use of ICTs. It is our hope, truly so, to inspire them to use these technologies to change the world in a very positive way. ITU is the leading United Nations agency on ICTs and it stands ready to assist all countries in developing child online protection policies, building capacity and fostering international cooperation. Let me conclude by saying that today's celebration is another important step towards education, empowerment and protection of children online. I thank you all for your commitment and I look forward to sharing more of my country's experience in the future.


I've been working in the communications field for a little over 10 years now. A day of my job would consist of a lot of moving parts, managing the help desk tickets that I get in from the soldiers when they need assistance. We've been transitioning the clinic to better improve the overall network connectivity and the personnel space here. It actually makes for a better setting for the entire clinic, so it's a pretty big deal. I've learned a little bit more on the networking side of things, how to communicate a little bit more effectively, especially when you're working with different branches of service.