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MIT scientists break a 20-year rule and unlock never-before-seen crystal structures
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AFGHS co-signatory countries ask health care users to help fill the financing gap
Hundreds of thousands of Ugandans living with HIV on antiretrovirals could be targeted for user fees or community health insurance schemes requiring modest premium payments, according to the April 2026 version of the country’s America First Global Health Strategy implementation narrative.1 As part of the “sustainable financing for the private not for profit sector” strategy, 491 facilities will be targeted for a phased introduction of user fees and scale up of community health insurance programs.2 In the Ugandan context, PNFP facilities include faith-based hospitals and other health facilities, US missionary organizations and centers of excellence—services that are often co-located at government facilities but run with additional financial and technical resources. 402,000 people—or about 28 percent of the total Ugandan adult PLHIV population on treatment—get ART from the private not for profit sector. The selected facilities provide the majority of ART and prevention of mother to child transmission (PMTCT) services. The plan doesn’t give the total number of clients served by the 491 facilities, so it is not possible to give a precise number. But the majority of 402,000 is a figure in the hundreds of thousands—hence the estimate I’m using.3 The April draft of the Ugandan implementation plan narrative is the only one I’ve been able to review. But the government of Uganda is not alone in turning to health care users to help fill the financing gaps caused by the abrupt withdrawal of US funds. In July 2025, the Government of Liberia introduced user fees for previously free services including “registration, accommodation, patient feeding, hospitalization, and a wide range of surgical and diagnostic procedures.”4 Earlier that year, Liberia rolled out a revolving drug fund designed to stabilize drug supplies by “allowing patients to pay a small fee for standardized, quality medications,” according to a Ministry of Health press release.5 (Both of these approaches had been proposed in the National Health Policy 2022-2031; media coverage explicitly connects the launch with the US foreign aid cuts.) The health financing strategies proposed by Uganda and established in Liberia are qualitatively different from user fees officially adopted by specific health facilities to cover funding shortfalls caused by the new US approach.6 The latter is a stopgap, adhoc change. The former is a national governmental adoption of policies that pass costs on to health care users, despite evidence that such approaches can exacerbate inequities and leave deficits unfilled. Two countries does not make a pattern, but they do point to urgent questions: Have other countries, including Liberia, included user fees or community health insurance schemes in their implementation plans? If so, do any of these narratives have what Uganda’s lacks: a fall-back plan in place in case these strategies for sustainable health systems fail to deliver—as they have before? I wonder if you think about it Subscribe Predictable pitfalls Both community-based health insurance and user fees are as old as the hills. And after decades of people climbing up these hills, duking it out, climbing back down—neither strategy has shown the results the Ugandan implementation plan is counting on. This is, in fact, a hill some folks are willing to die on. (You knew I’d get there, right?) In November 2025, an African-led team of health system experts published a paper directed at low- and middle income country governments trying to figure out how to create self-sustaining health systems. The money wasn’t coming back. It had been more than nine months since the season of freezing, waivering and wood-chippering; two months since AFGHS tumbled into the world touting co-financing requirements and reductions in future US government health aid. Governments were looking for strategies for sustainable, self-financed health systems, the authors wrote. For countries considering user fees and community health insurance to fill the financing gaps, they had a simple message: Don’t. On user fees, the paper states: “Reliance on user fees is ultimately a regressive and inequitable approach. It places a disproportionate burden on the poor and undermines health system goals of equity and financial protection. […] There is overwhelming evidence that user fees mobilise very limited resources for the public health sector, making it an inefficient mechanism for revenue mobilisation.” On community health insurance: “Attempting to shift the burden of funding previously donor-funded services, such as HIV care and management, and TB treatment, onto contributory schemes would exacerbate their fragility and fail to protect the population.”7 The WHO says that community-based health insurance “cannot be expected to provide a major source of funding or coverage,” and noted that most schemes offer only moderate benefit to individuals paying into them, and exclude the poorest segment of the population.8 And yet, the US-Ugandan implementation plan says that community health insurance is “the central pillar of this [PNFP] sustainability strategy” and that this approach that will generate “pre-paid pooled funding at facility and community level [that] improves financial risk protection for households, reduces catastrophic out-of-pocket expenditure, and generates structured, transparent revenue streams that can progressively absorb recurrent costs including health worker salaries.” Unfortunately, Uganda’s own history suggests the pillar might not be able to bear this weight. Ugandans Have Been to this Rodeo Before—and Some Want Their Money Back Uganda introduced its first community health insurance scheme in 1996 with support from international donors.9 Thirty years later, somewhere between 0.2 and 0.3 percent of the population is covered by CHI; just over 1 percent has any kind of health insurance.10 User fees were universally introduced in 1993 as a condition of a World Bank loan.11 They were abandoned in 2001, and in 2004—the year I moved to Uganda to watch the free HIV program get underway—a definitive study found that the fees did not improve health systems and outcomes.12 In 2004, most clinics and hospitals had ‘free’ and ‘fee for service’ options for getting care.13 The fee for service, or “cash and carry” programs had often been established in the years prior to PEPFAR and the Global Fund to Fight AIDS, Tuberculosis and Malaria. People who could afford to paid for the drugs, often at facilities in the private-not-for-profit (PNFP) sector. When free drugs arrived, some people who’d been paying kept on doing so, perhaps because of shorter wait times, greater confidentiality, convenience or other factors. But in the year that I spent visiting the same clinics around the country week after week—including a “center of excellence” that maintained separate days for cash and carry clients and those accessing free ARVs—lots of people who had been paying tried to switch to the free option. They’d paid because they had no other choice. They’d sold pieces of family land, begged family members for loans, bought pills by the week, and sometimes by the day. Or they were just cash-strapped, like most of us, and wanted the funds for other things. 14 Twenty-two years later, this hasn’t changed. Ugandans pay out of pocket for 30-40 percent of their health care costs, leading one paper to declare that “falling ill is more than a health crisis. It is a financial emergency.”15 One recent study found that up to 48.5 percent of households dealing with tuberculosis sold something, took out a loan or dug into savings to defray the costs of TB care—which is supposed to be universally free.16 The Ugandan implementation plan does anticipate challenges. It proposes a phased approach, with 187 facilities introducing user contribution systems in Year 1, 152 in Year 2, and 153 in Year 3. Willingness to pay and feasibility studies will precede roll out; fees will be tiered by region, and a waiver system is proposed to ensure that no one has to pay who is unable to. Moreover, the plan provides for quarterly reviews of epidemiological data to “ensure that user contributions do not compromise epidemic control gains, ART continuity for the client cohort, TB case management, or PMTCT services.” Alt text: A screenshot of a table included in the implementation plan narrative that is the subject of this stack. It’s got a fetching pink bar at the top. It uses the abbreviation “CHI” which is Community Health Insurance, and FBO which is Faith Based Organizations, and it details the number of facilities that will implement user fees with waivers and community health insurance schemes over the five years of the agreement. As I said in the footnote, this is a super interesting document with a lot of other rich material. Tell me what you see—and what you would have focused on. And if you’ve seen something like this, or anything else that strikes you, in another implementation plan, tell me that too. You can use the Substack message platform or try me on Signal at @endaplague_again.25 (because @mercoonfan was, weirdly, taken). But the plan doesn’t fully explain what will happen if this approach doesn’t work out. Yes, progress will be monitored, and corrective action triggered. However, there is no specified funding replacement if premium and fee revenue prove inadequate. Instead, the authors write, “Currently, COEs serve a total client cohort of over 180,000 across 28 facilities. In the initial years, the U.S. Government (USG) will provide financial support for clients; over time, user fees generated by COEs will become the primary source of funding for sustaining their services.” Failure does not really seem to be an option. Health insurance schemes are more acceptable to the Ugandan population than user fees. Members of Parliament and civil society traveled to Ethiopia to see how that country’s scheme worked. In a follow up report, a veteran civil society group recommended allowing the “health insurance ecosystem to grow organically and [to] keep reviewing the law and regulations as this growth takes root.”17 One study found that more than three-quarters of Ugandans were willing to join a health insurance program.18 However, coverage of community-based health insurance is minimal, as is coverage of any kind of insurance—including private plans.19 A national health insurance scheme bill has been stalled for several years and presently sits with President Yoweri Museveni.20 Community-based health insurance scheme that do exist are expanding in number, but losing enrollees. Between 2022 and 2026, the number of community-based health financing schemes across the country increased by 42 percent, while the number of people enrolled decreased by nearly 11 percent.21 None of this means that community-based health insurance should not happen in Uganda—or that people do not want insurance. It doesn’t even mean that user fees and waivers won’t ever work. But there is highly relevant evidence from Uganda and the surrounding region that it is quite optimistic to describe community health insurance and user fees as central supports for sustainable financing in any sector of the health system. And now for the best-case scenario In the best-case scenario22, the Ugandan approach does exactly what it sets out to do, and so does the Liberian fee structure and revolving pharmacy fund—though I’ve not confirmed that these are in the MoU. In one best-case scenario, Uganda is an outlier, and user fees and community health insurance are not recurrent pillars of self-sustaining financing in other countries’ implementation plans. In another best-case scenario, all countries that include these strategies enjoy success beyond anyone’s evidence-informed wildest dreams: reliable funding generated by health care users fees, great health care outcomes for everyone, no exacerbation of inequities, no crippling household debt. No sold land, repurposed school tuition or high-interest loans. In the best-case scenario, not one of the hundreds of thousands of Ugandans living with HIV receiving antiretrovirals from 491 PNFP facilities misses a refill or leaves care because of user fees or community health insurance premiums. This is the best-case scenario for these people for their own health, and for their families. It is also the best-case scenario if Uganda wants to stay on the path to eliminating HIV as a public health threat. According to the country’s most recent data, 96.5 percent of people living with HIV on antiretrovirals are virologically suppressed. Epidemic control depends ensuring that 95% of people living with HIV know their status, 95 percent of those individuals are on ART, and 95% of those individuals are virologically suppressed. Uganda is still struggling with the first “95"—a frankly abysmal 85.3 percent. If HIV epidemic control and the attendant prevention of new infections, avoidable suffering and premature death matter, the country cannot afford to lose any clients who are currently in care.23 As I write this a couple hours before the polls close for the US elections in the city I live in, I say with soul-deep sincerity: I am rooting for the best-case scenario. I think it’s safe to say that we all are.24 I think it’s also safe to say that if the US and co-signatory governments have inked plans that lead to successful expansion of community health insurance and strategic use of user fees, we all would like to know, now, so that we don’t miss the opportunity to celebrate when success happens. The implementation plan narratives have to enter the public domain. They are the fullest expression of a strategy co-created by two governments. There are assumptions and details that people living in the US and co-signatory countries need to understand that are not available in the MoUs or, to date, in the Congressional Notifications. Some of these details can help other countries that are, as I write this, still working on implementation plans. Others, like a solid count of how many other countries have plans for expanding user fees or health insurance, are important for regional and global health architecture reform initiatives. No matter how this election night turns out, there will be a slew of new Congressional member orientations, briefings and talking points papers in the next few months. Release of implementation narratives should be a bullet point in every context that AFGHS is discussed. These documents can be redacted so that procurement sensitive information isn’t disclosed. There is much more historical precedent for sharing such documents than there is for relying on user fees to fill health financing gaps. Let’s look at the information together so we can hope for the best and prepare for, you know, the other thing. Alt text: A substack first: a bicep selfie! It’s my arm - peachy-white skin, black shirt (flannel, notch neck, too hot for this appallingly balmy November weather, if you’re wondering) and a sticker that says I VOTED 2026. Beige letters on red for I voted. Beige on blue for 2026. You bet I did.25 In your wildest dreams. Subscribe 1 This is a really, really rich 95 page document. There are fascinating ideas and detailed plans in it. It is all worth reading AND I have, in this post, highlighted an instance of content that could pose challenges and certainly posits success of strategies that haven’t worked before. I would love to hear what readers’ see that’s interesting and should be lifted up as something to check for in other implementation plans. I will also shortly be adding a static page to the substack site where implementation plan documents will live. I will put the url into this footnote and it will also be there on emilybass.substack.com by the end of the week. Uganda Implementation Narrative Section 4 April 22 2026 Draft 1.51MB ∙ PDF file Download Download 2 User fees are costs charged for visits, labs, medicines or other health services, usually at the time they are provided. Community health insurance, or community-based health insurance, is what the World Health Organization calls “micro insurance,” which is health insurance targeted at low-income people. 3 As usual (by which I mean always), please prove me wrong. 4 https://smartnewsliberia.com/liberias-ministry-of-health-announces-2025-hospital-service-fees-for-public-facilities/?utm 5 https://moh.gov.lr/news/2025/grand-cape-mount-leaders-residents-embrace-new-community-pharmacy-program/?utm 6 https://www.christianitytoday.com/2026/09/hiv-usaid-pepfar-africa-foreign-aid-cuts-mission-hospitals/?utm 7 https://gh.bmj.com/content/10/11/e021270 8 https://www.who.int/news-room/fact-sheets/detail/community-based-health-insurance-CBHI 9 https://pmc.ncbi.nlm.nih.gov/articles/PMC2827475/ 10 https://pmc.ncbi.nlm.nih.gov/articles/PMC10861328/#b3-jpmph-23-110 11 https://pmc.ncbi.nlm.nih.gov/articles/PMC527704/ 12 Same citation as the footnote 2 - the article is called “Learning from failed health care reform in Uganda.” To which I say: If only. If. Only. 13 There is a whole taxonomy of user fees to be aware of, if not commit to memory. Out of pocket costs are everything that someone pays for themselves. In this Stack, user fees are planned and policy-supported out of pocket costs. There are also out of pocket costs that people pay to buy drugs or receive tests or health care assessments that would be free if the drugs were on the shelves, or the machines or kits were available, or the staff were on site. A user fee is usually designed to be modest, pegged to willingness to pay, and may be waiveable at the point of care for anyone who is unable to do so. The costs for things that would otherwise be free are whatever the market will bear and people either have to pay them or go without. Out of pocket costs for services and stuff that aren’t available in public facilities are different again from bribes or unofficial fees that some health workers may impose, even though most are indefatigable, tireless and tired, and devoted to their clients. 14 For the record—which really is these footnotes—I would give a whole stack of fridge magnets for a systematic analysis of the economic and social impact of the Mass Unemployment Event in AFGHS countries among the very people who used to be able to afford and cover user fees, both for themselves and vast family networks. Locally employed USAID technical staff, house cleaners, caregivers, drivers and technicians were financial anchors for cousins, friends, friends’ children, friends’ childrens’ cousins, teachers, pastors, neighbors and so many other kinds of kin. Aid recipients lost direct funding; many other people who had not been aid recipients, but parts of the elaborate care webs that function as safety nets for so many people, lost crucial support too. And that’s even before we get to the people who worked at the hotels and restaurants and bars where people employed by the US and its implementing partners used to spend disposable income. Those businesses have lost revenue; those folks have lost jobs. It will be some time coming—and someone will have to fund this work—but I do hope it happens. And I hope, as usual, to be proven wrong. 15 https://eprcug.org/blog/how-out-of-pocket-healthcare-costs-keep-driving-ugandans-into-poverty/ 16 Another straight-to-the-point journal article title. Households experiencing catastrophic costs due to tuberculosis in Uganda: magnitude and cost drivers. https://pubmed.ncbi.nlm.nih.gov/32938411 17 https://www.cehurd.org/download/technical-policy-brief-on-community-health-insurance-scheme/?wpdmdl=13661&refresh=6ae9122f5d4ed1793659439 18 https://pmc.ncbi.nlm.nih.gov/articles/PMC10125197/ 19 https://pmc.ncbi.nlm.nih.gov/articles/PMC10861328/#b3-jpmph-23-110 20 https://ugandapost.news/uganda-to-make-health-insurance-mandatory-by-2026/ 21 https://shu.org.ug/download/235 22 With a nod, tip of the stack hat, and wag of the Mercoon tail to a deeply valued reader who told me that I have a tendency to speculate about the worst-case scenarios a little too much of the time. 23 https://news.mak.ac.ug/2026/10/uphia-2025-shows-ugandas-hiv-status-awareness-gap-despite-strong-treatment-outcomes/ As you’ll see in the next footnote, I’ve already written a subSubstack on another topic, so I will be brief with regard to the study referenced in this article. The Uganda Population-Based HIV Impact Assessment, or UPHIA, will never happen in this way again. For more than a decade, PHIAs have been supported by the US government as a way to generate accurate estimates of country progress on key HIV indicators. They are a holdover from the PEPFAR program that was laser focused on ensuring US taxpayer dollars subsidized progress in pandemic control. There may be other population-level surveys and the data may even be publicly released, as the entire set of FY2026 MER data have not. But PHIAs will never happen again. If you’re wondering whether the estimates of HIV progress at country level might get less reliable….you’re not alone. 24 Ooh baby, I hate “we” in almost all forms. But sometimes I go there, when I am looking for company, which I am. Because this Stack moves into the somewhat-uncharted territory of assessing what the implementation plan narratives may suggest about co-signatory countries’ roles and responsibilities to the people living within their borders. The MoUs, specimen and data sharing agreements were templates. Countries’ answers fit into pre-specified questions that did not include, “how are you going to fill financing gaps and stabilize your health system as this plan unfolds?” In contrast, the implementation narratives are open form—the product of co-creation between the two governments. Co-creation can mean lots of things, but nothing leads me to believe that implementation plans are ghost-written by the US government, or that contents were imposed by the US counterparts. Instead, I think the parts of the plans that read like country government initiatives are endorsed, if not initiated by, those governments. For instance, the Ugandan implementation plan narrative describes plans for revenue-generation through fees charged for equipment calibration, repair and maintenance provided through Uganda’s National Equipment Calibration Laboratory, and laboratory accreditation through the Uganda National Accreditation Service (UGANAS), targeting private sector, PNFP, research and academic clients. That’s super specific and also quite ambitious. It doesn’t read like an American idea. There’s also a provision for solar panels, and other stuff that feels country owned and driven. This is where it gets interesting. If co-creation is the case, then both the US and co-signatory governments are accountable for the contents and the outcomes. Most discourse about AFGHS to date has focused on the decisions that America has made, or demanded that other countries make. The AFGHS architects have monopolized the hot seat. As they should, in so many ways. America absolutely created the conditions under which countries needed to come up with health financing strategies to fill unanticipated, catastrophic funding gaps. And with not-too-long a lens, we can look back and see that America is also on the hook for its role in the Bretton Woods institutions that made user fees and health system fiscal austerity conditions of loans during the era of structural adjustment. But in the here and now, it is not at all clear to me that the US is requiring Uganda or any other country to implement specific approaches to sustainable financing. Instead, it is as the authors of that paper up in footnote 6 suggest: African governments have agency. As implementation plans roll out—whether or not the narratives are shared—it will be important to understand what this agency looks like and what it means for people, including the poorest of the poor. And it will be important to figure out how to talk about it safely, respectfully and critically in places other than the literal and metaphorical footnotes. 25 This week’s song is “Once upon a time” by the Moody Blues. (I know, this is gonna be a weird, largely banger-free end of 2026 playlist. HMU with requests.) AND please do watch the video and appreciate the truly amazing opening sequence—a drum kit wasteland, a coupla plastic bags, a bit of sand. Sort of like the hill where fiscal austerity policies that put costs on health care users might go to perish. But then there’s a lady with amazing hair. It’s worth it.
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The Harvard Crimson (@theharvardcrimson)
49 likes, 0 comments - theharvardcrimson on October 30, 2026: "From @fmcrimson: At 7 p.m. on April 11, 2014, a panel of six sat onstage behind a long table at the University of Massachusetts Amherst, preparing to speak. They arranged their notes on the wrinkled plastic tablecloth. The panelists weren’t there to discuss their academic work. Rather, they were speaking about their time as members of the Vietnam-era movement Science for the People, a radical organization who believed science had been misused by capitalist interests. Allen S. Weinrub, who co-founded Science for the People in 1969, sat on the far end of the table. He wore a button with the organization’s emblem: a red fist beside a hand grasping an Erlenmeyer flask. The organization was part of the anti-war movement in the 1960s. Early members of Science for the People were protesting the use of sciences like chemistry and physics to develop weapons — but increasingly critiqued science as a reflection of power imbalances in capitalist society. Full story linked in bio. 🖋️: Sophie Gao 📷: Dawn Chen, Courtesy of Science for the People Archive and Courtesy of MIT Archives".
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2026-2027 Audree V. Fowler Fellows in Protein Science
Graduate students Lenka Milojević (Zhou group), Akshaya Narayanasamy (Lindert group), Sarah Singleton (Conway group), and Janet Zhong (Feigon group) have been selected as 2026–27 Fowler Fellows and shared their research at a special event on Oct. 13, 2026. 2026-27 Fowler Fellows – Sarah Singleton, Lenka Milojević, Janet Zhong, and Akshaya Narayanasamy. Akshaya Narayanasamy and Prof. Steffen Lindert. Sarah Singleton and Prof. Stuart Conway. Janet Zhong and Prof. Juli Feigon. About the 2026-27 Audree Fowler Fellows in Protein Science Lenka Milojević is a fifth-year Biophysics Ph.D. candidate in the lab of Professor Z. Hong Zhou at UCLA. As an undergraduate at Maastricht University, she studied the structural basis of Mycobacterium tuberculosis virulence and amyloid-β fibril nucleation in the lab of Professor Peter Peters. She completed her bachelor’s thesis research at UCLA in the lab of Professor David Eisenberg, focusing on amyloid disaggregation, before beginning her doctoral studies. In the Zhou lab, Lenka uses cryo-electron tomography to visualize and characterize membrane-associated protein assemblies across a range of viral and cellular systems. Akshaya Narayanasamy is a fifth-year Ph.D. student in the Department of Chemistry and Biochemistry at UCLA, mentored by Professor Steffen Lindert. She earned her B.S.-M.S. in Chemistry from the Indian Institute of Science Education and Research, Thiruvananthapuram, where she worked in Professor Mahesh Hariharan’s lab investigating how single-atom substitutions influence crystal packing and charge transport behavior. She received her M.S. in Physical Chemistry from The Ohio State University before moving with the Lindert lab to UCLA. At UCLA, Akshaya develops integrative modeling methods that combine deep learning and Rosetta with experimental data, such as ion mobility mass spectrometry and cryo-EM, to improve protein structure prediction. Her current work focuses on developing an experimentally guided diffusion model and designing de novo protein binders with potential antibacterial activity. Ultimately, she aims to bridge AI-based structure prediction and experimental data to make computational protein models more reliable for drug discovery and therapeutic design. Sarah Singleton is a 4th year BMSB student, working in Professor Stuart Conway’s lab. She earned her B.S. in Biochemistry at Simmon University (Fenway, MA). Her research is centered on drugging the previously undruggable class of proteins—transcription factors. Zinc finger (ZF)-containing transcription factor proteins typically contain multiple ZF motifs, but little is known about the principles that govern the recognition of multi-ZF arrays by immunomodulatory imide drugs (IMiDs). In a multi-ZF array that contains several potentially targetable ZFs, which will be accessible and why? How does the surrounding protein architecture inform IMiD recognition? Sarah’s research aims to utilize her findings on the fundamental principles of ZF recognition to design IMiD therapeutics for transcription factors involved in health and disease. Janet Zhong is a fourth-year BMSB student, working in Professor Juli Feigon’s laboratory. She received her BSc and MRes from Imperial College London. At UCLA, Janet combines cryo-electron microscopy (cryo-EM) and biochemical approaches to investigate how proteins and RNAs assemble into ribonucleoprotein structures. Her research focuses on telomerase, the enzyme that maintains chromosome ends, with interests in its structure, assembly, and mechanisms. She has also worked on capturing the cryo-EM structure of a small bacterial non-coding RNA called raiA motif RNA. About Dr. Audree Fowler A strong supporter of the basic sciences and medicine at UCLA, alumna Dr. Audree Fowler (B.S. ’56 chemistry, Ph.D. ’63 biochemistry) established the Audree V. Fowler Fellows in Protein Science in 2008. Fowler was Director UCLA Protein Microsequencing Facility from 1984-1999 and is a Researcher Emeritus of the UCLA Department of Biological Chemistry. She is one of the first four women to receive a Ph.D. from the UCLA Department of Chemistry & Biochemistry. In 2018, the women were awarded the department’s 2018 Alumni Legacy Awards in recognition of their achievements in life, and generous support and service to UCLA. “The sciences gave me a great life. Now I want to help others have access to the same opportunities I enjoyed,” Fowler explained when she established the Fowler Fellowships endowment. Applications for the fellowships are solicited from graduate students in the Molecular Biology Interdepartmental (MBI) Ph.D. Program, Biological Chemistry, and Chemistry & Biochemistry Departments. In addition to presenting their research at a special seminar, the recipients each receive a $5,000 award. Previous Fowler Fellows from the UCLA Department of Chemistry & Biochemistry 2025-26 – Nikki Cheung (Clubb Group), Jonathan Jih (Zhou Group), Eileen Olivares (Loo Group), and Lily Taylor (Rodriguez Group) 2024-25 – Andrew Goring (Clubb lab), Eric Pang (S. Clarke and Rodriguez labs), and Miranda Villanueva (Backus lab) 2023-24 – Alexandra Turmon (Backus lab), Cindy Wang (S. Clarke and C. Clarke labs) 2022-23 – Cody Gillman (Gonen lab), Declan Evans (Houk lab), Troy Lowe (S. Clarke lab), Ashley Julio (Backus lab), and Alex Stevens (Hong Zhou lab) 2021-22 – Weixian Deng (Wohlschlegel/Plath labs), Yi Xiao “Sean” Jiang (Eisenberg lab), Maria Flores (Rodriguez lab), Carter Lantz (Loo lab), and Logan Richards (Rodriguez lab). 2020-21 – Janine Fu (Loo lab), Calina Glynn (Rodriguez lab), and Jiahui Lu (Eisenberg lab) 2019-20 – David Boyer (Eisenberg lab), Orlando Martinez (Clubb lab) and John Muroski (Loo lab) 2018-19 – Scott McConnell (Clubb lab), Kevin Murray (Eisenberg lab), Rebeccah Warmack (S. Clarke lab) 2017-18 – Michael Hughes (Eisenberg lab), Yuxi Liu (Yeates lab), Kanishk Jain (S. Clarke lab) 2016-17 – Brendan Amer (Clubb Lab) and Jeff Vinokur (Bowie Lab) 2015-16 – Henry Chan (Feigon lab), Smriti Sangwan (Eisenberg lab), Nicholas Woodall (Bowie lab) 2014-15 – Dan McNamara (Yeates lab) 2013-14 – Alex Jacobitz (Clubb lab), Alexander Patananan (S. Clarke lab), Carly Ferguson (Loo lab) 2012-13 – Letian Xie (C. Clarke lab), Anni Zhao (Eisenberg lab) 2011-12 – Timothy Anderson (Clubb lab), Soohong Kim (Weiss lab) 2010-11 – Zeynep Durer (Reiser lab), Cecilia Zurita-Lopez (S. Clarke lab) 2009-10 – Luki Goldschmidt (Eisenberg lab), Kristofer Webb (S. Clarke lab), Sheng Yin (Loo lab) 2008-09 – Nathan Joh (Bowie lab), Neil King (Yeates lab) Photos courtesy of Helen Houldsworth, the Molecular Biology Institute.
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A golden age of science is coming
It’s almost hard to remember, but just a few years ago, a lot of very smart people thought that science was in terminal decline. Respected researchers were writing papers with titles like “Are Ideas Getting Harder to Find?”, “Papers and patents are becoming less disruptive over time”, and “Slowed canonical progress in large fields of science”. In 1996, science writer John Horgan even published a book called The End Of Science: Facing The Limits Of Knowledge In The Twilight Of The Scientific Age. The fundamental idea was that the Universe only has so many insights to discover, and that we’ve picked the low-hanging fruit. It was the idea that Joseph-Louis Lagrange expressed when he said that “we cannot find more than once a system of the world to establish.” As the big ideas and the simple ideas get mined out, we’re forced to throw ever more brains at the mysteries of nature just to keep scientific progress going at a fraction of its old pace: It looked like science was hitting a wall. Then along came AI. It’s far too early to tell how much AI will eventually speed up the growth of total factor productivity. But already we can see signs of a speedup in science. Anthropic Founder Jack Clark assembled some of the hopeful data points in a recent lecture: [ Dror Poleg@drorpoleg "If you pick different parts of science, you see the same pattern show up: Progress is accelerating, and it has started to accelerate in the last two years." Jack Clark @jackclarkSF I’m speaking at the IMF in an hour about the singularity and why I believe it has begun and the choices we'll need to make. Watch live here: https://t.co/Hj9HzcXx5h 6:08 PM · Oct 18, 2026 · 21.2K Views 2 Replies · 10 Reposts · 123 Likes ](https://x.com/drorpoleg/status/2111882070376980529) Anthropic is accelerating its investment into drug discovery, and is already announcing some impressive preliminary results: [ BioTender@Junioryu136689 BREAKING: Anthropic unveils early results from six Claude-powered drug development collaborations. • 70% shorter CAR-T signaling domain • ~35,000 antibody designs • >10× tighter antibody binding • 89% less batch-record review time Still largely preclinical. Anthropic @AnthropicAI Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own. In doing so, we’ve learned much more about how Claude can support the many stages of 9:43 PM · Oct 27, 2026 · 11.2K Views 3 Replies · 24 Reposts · 205 Likes ](https://x.com/Junioryu136689/status/2115197821150495150) Claude also appears to be enabling rapid progress toward a treatment for food allergies. OpenAI, meanwhile, announced a possible breakthrough treatment for neurodegenerative disease. Meanwhile, Google Cloud Chief Scientist Pushmeet Kohli has a list of recent scientific advances that have been enabled by its new Gemini model, including breakthroughs in nuclear fusion reactor design, rare disease research, and quantum computing: [ Pushmeet Kohli@pushmeet Gemini 4 Argon is a step change in model performance. In recent weeks, it has had a transformative impact on the Science projects in our team at @GoogleDeepMind and our external collaborators, and helped make a number of remarkable advances across scientific disciplines. 🧵👇 4:47 PM · Oct 13, 2026 · 36.5K Views 8 Replies · 41 Reposts · 497 Likes ](https://x.com/pushmeet/status/2110049807385702623) But as cool as these stories sound, they’re just very minor, preliminary efforts. There are a number of reasons to think that AI is going to propel us into a golden age of scientific discovery. That age might not last forever — AI might still run into diminishing returns eventually. But the next few decades are probably going to be an absolutely amazing time for human science. The number of “effective researchers” is no longer limited The most important input into science is scientists themselves. Until this year, that meant human brains — talented, highly trained human brains. The number of trained human brains could be increased by sending more people to grad school, but only to a point — the smartest people tend to be sent into the hardest research fields first, and if you 10x the number of researchers, the average quality will go down. This constraint was already starting to bite, as Ekerdt and Wu argued in 2024: We argue that a substantial portion of the downward historical trend in U.S. research productivity is a composition effect resulting from self-selection in researcher ability and the dramatic expansion of the research sector…[W]e find that this composition effect has lowered average researcher ability by between 37% and 53%[.] And of course, low fertility was making the problem worse, because fewer children meant fewer people who were able to become future scientists. AI just blows up this constraint completely. If an AI agent can function as an autonomous researcher, there’s no constraint on the number of researchers in the world — you can just build more of them, by building more computer chips and data centers that enable the running of more AI agents. Whether or not massive hordes of agents can collaborate to solve individual problems much faster, increasing the number of agents allows them to tackle many different research questions in parallel. What’s more, these AI “researchers” can be trained incredibly quickly compared to human beings. A human scientist takes decades to train, and more years to reach the frontier of their research field by diligent reading and conversation. This is the “burden of knowledge”, and it’s commonly believed to be one reason ideas have been getting harder to find — by the time human scientists can get up to speed, they’re often so old that their ideas are no longer novel. AI just annihilates this constraint — it can assimilate the entire literature and reach the frontier of research extremely quickly, and it can also tell human scientists where the frontier lies without forcing them to discover that for themselves. It can also pivot to new research directions more easily than humans can. And there’s also a self-reinforcing economic cycle here. Because scientific advances enable higher GDP, they enable more resources to be invested into the creation of yet more electronic “scientists”. Now that doesn’t mean the amount of scientific research goes to infinity — there may still be some essential bottleneck task that human researchers are still needed to perform. There are some indications that AI’s progress on open-ended conceptual research tasks is slower than in other dimensions, and it may be that humans are still needed to provide some of this long-term conceptual thinking. I’d bet against this being true for much longer, but it might be true for a long time. Even in this most “pessimistic” case, though, the amount of effective capital that scientists can use to leverage their work just went up by a lot. AI eliminates the theory bottleneck Science proceeds by an iterative process of theory and experiment. The theory part of that cycle is typically short, but non-trivial — it took a couple of years after the blackbody radiation spectrum was observed for Max Planck to come up with the quantum hypothesis to explain it, and decades longer before quantum theory as we now know it was created. It took about a year for Watson and Crick to figure out the shape of DNA after the requisite data was gathered. AI will basically eliminate the theory bottleneck entirely — or at least shorten the turnaround time between experiment and theory by an order of magnitude. AI is an absolute beast at math. Recently, an OpenAI model solved some of the most important open problems in computer science, math, and theoretical physics, and no one even batted an eyebrow because that sort of triumph is becoming increasingly commonplace. One of those solutions was a proof that the Standard Model of Particle Physics could be mathematically well-defined — a problem that human theorists had so far been unable to tackle. Not all research relies equally on theory, but understanding novel experimental results almost always involves some important component of either mathematical or spatial reasoning. That part of the task has now been made much, much faster. And on top of that, science is now open to a greater number of humans who aren’t naturally good at theorizing. AI can read the whole literature Much of the work of human scientists involves reading and understanding endless amounts of papers and going to endless conferences and seminars. The purpose of that work is to understand the existing scientific literature. Understanding the literature allows scientists to do the following things: Come up with new ideas for hypotheses to test Avoid doing research that someone else has already done Synthesize approaches from different areas or fields AI can reduce this effort to almost zero. Consider this excerpt from OpenAI’s blog post about their new research into neurodegenerative disease: The team divided the analysis among thousands of AI agents powered by GPT‑Rosalind, an approach we call distributed biological reasoning. The agents examined a whole-brain CRISPR atlas…a dataset showing how gene disruptions affect different types of cells across the mouse brain. Each agent investigated a gene disruption, analyzed cellular responses, searched scientific literature, and proposed explanations for the results. Their reports were combined into a reasoning atlas linking genes, cellular effects, relevant publications, and possible biological mechanisms. The research team estimated that comparable human analysis and literature review, conducted one perturbation at a time, would take months to a year. The agents reproduced findings from human analyses while uncovering additional leads. Their assessments of novelty and scientific value also aligned with judgments from blinded human experts. These findings help prioritize further experiments needed to test the proposed biological mechanisms. Some of these insights point to new leads for understanding brain disease. [emphasis mine] This is one case in which parallel work by a large number of agents really does make a huge difference: [ Haider.@haider1 this is actually insane openai deployed thousands of GPT-Rosalind agents to analyze millions of mouse brain cells in 32 minutes, work that could take human researchers months to a year also the agents uncovered new leads for brain diseases like Alzheimer's and Parkinson's OpenAI @OpenAI GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in 2:41 PM · Oct 21, 2026 · 51.5K Views 26 Replies · 95 Reposts · 1.26K Likes ](https://x.com/haider1/status/2112917197903540516) Not only does instantaneous literature review vastly speed up the research process, but it allows AI to make novel conceptual leaps from combining approaches from wildly different fields of research. AI regularly does this in math research, combining results, approaches, and theorems from far-flung places that no human mathematician would have thought to combine. It can do it in science, too. Much of scientific innovation, historically, has been “recombinant” innovation — scientists applying insights from one field to another. With AI, essentially all research is now cross-disciplinary — AI can read not just the literature on a particular subject, but the literature on a million other subjects that might have produced useful techniques or insights for the problem at hand. Superscience So far, all of the factors I’ve listed are ways that AI can speed up science as it’s already done. I’ve basically described how AI can send gigantic hordes of superhumanly fast, superhumanly well-read, superhumanly mathematically gifted researchers to re-accelerate scientific discovery. But it’s also possible that AI will enable types of discovery — and ways of understanding the natural world — that no network of humans, no matter how large or how brilliant it was or how long it had to work, would ever be able to discover. In a post back in July, I wrote about how that might work: What if there are lots of…aspects of the Universe that [are] too complex to understand in terms of simple laws, but not so complex that they just dissolve into unknowable chaos? It’s possible that we can reliably control these complex phenomena with AI, even if we never reduce them to the kind of principles that we can teach a grad student in a textbook… Another way of saying this is that there may be laws of the universe that humans can’t understand but AI can. I call these “cloud laws” — causal regularities that can be exploited by technology, but which are too diffuse and complex for an individual human being to either intuit or communicate… Perhaps social sciences like economics, sociology, and political science obey similarly complex regularities, and AI can help us find them. Perhaps there are physical processes — plasma, or topological materials, or aerial turbulence, etc. — that obey cloud laws instead of chaos?… [H]uman collaboration is bottlenecked — it’s limited by our ability to intuit patterns at an individual level, and to communicate these patterns from one individual to another. AI, being a computer, just doesn’t have this sort of limitation; it can work with vast, diffuse patterns without having to break them into pieces or simplify them in order to compress them into the tiny pipelines of person-to-person explanation… If much of the Universe turns out to be ruled by cloud laws, we could be on the precipice of a scientific renaissance. In order to discover cloud laws, AI will need huge amounts of data about the natural world. AI figured out human speech by assimilating essentially all of the text humans have ever written. If it’s going to figure out hidden patterns in biology, neuroscience, materials science, etc., it’s going to need similarly massive amounts of data from physical instruments. That data will be far, far more than humans — individually or collectively — would be able to parse, label, characterize, or model. But AI was built to do this. If scientists simply build huge arrays of sensors to measure complex phenomena like the brain, the cell, the economy, etc., they may be able to feed this flood of data to AI directly and bypass human cognitive intermediation entirely. AI would then learn about the world directly, and it might learn things that humans never could. This “superscience”, if you want to call it that, would actually go beyond the kind of science humans have done heretofore. Many of the technologies it yielded would be beyond human comprehension — indistinguishable from magic. But to the AIs, they would make perfect scientific sense. In any case, it seems clear that the scientific slowdown that threatened human progress will now be delayed — at least for a while. Unless humans have somehow found most of the actual exploitable regularities in our Universe, we’re about to enter a new golden age of science. Subscribe Share
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Animals Starves while the Kardashians Miss the Charts Again
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) Before we get going, I’d like to offer congratulations to Jonathan Funke, whose suggestion “midflicks” won the poll for what I should call straight-to-streaming films which aren’t big or cinematic enough to go to theaters but seem too expensive for a TV movie. It’s so useful a term, I just used it last week! Now I just need to add this term to my data dictionary! Okay, on to this week’s issue. We’re starting out looking at Netflix/Ben Affleck’s latest crime thriller, Animals. I’ll also look at Disclosure Day heading to Peacock (it did better than you’d remember in theaters...) and a new movie based on toys. Plus, a long-time streaming flop returns for its eighth season...will it finally chart? (No.) Will anyone at Disney care? Probably not. All that, plus another look at new shows landing on streaming on 1-Oct from Reelgood, what streamer hasn’t had a film make the Luminate charts since August, Reacher’s long run on the charts, M_onster: The Lizzie Borden Story’s_ short run, the top shows in 2026 according to Samba TV, all the flops, bombs and misses, and a whole lot more. And I mean that last part: putting this week’s issue together, I assembled OVER 25 images, most of which are bespoke looks I made just for this report. Really, publishing articles like this takes the work of writing two articles: one is the narrative and the other is making charts/graphs. Let’s dive right in! (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, JustWatch and Reelgood interest data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the week of October 5th to October 11th, 2026. You can find a link to my terminology here.) Subscribe Film - Netflix’s Latest Star-Studded Thriller Goes For Glory The tempting angle for anyone writing about streaming film this month, like yours truly, is to ask, “Is this why Dan Lin lost his job at Netflix?” Take Animals, the Ben Affleck-starring-and-directing, Artists Equity-produced crime thriller that opened on 9-Oct. (Kerry Washington and Gillian Anderson are also in it.) If it did really well, then one could argue that Lin has another success on his resume. If it underperformed, then it’s another example of a Netflix underperformance this year. So where did Animals fall? Kinda in the middle, but that means it’s more “not a hit” than “big hit”. On Nielsen, it opened to 12.0 million hours, and here’s how that stacks up for 2026 films so far this year: Obviously, that’s not great. It’s both under my 15 million opening bar for “fine” for a Netflix film and 20 million bar for “great” opening. It did a bit better on Samba TV, getting to first place. That’s very, very good, though again, looking at the Nielsen data, it probably means that it was a light week overall. Luminate’s data is a bit closer to Samba TV’s, tied for 17th all time for single weeks since May of 2024: To top it off, no one seemed to like it. It has a 33 on Metacritic and only a 5.7 on IMDb. Both of these numbers could have been impacted by the stories about Affleck’s comments about using AI to make the film. Given the controversy, the film might not have been as bad as the ratings suggest, but it’s also not a bullish sign. All to say…yeah, on net this film isn’t a point in Dan Lin’s favor. At this point, Netflix’s slide has been long enough—going on since February—that I’m almost tempted to lower the bar for what a “hit” is on streaming. Post-February of 2026 or so, it seems like straight-to-streaming films just haven’t hit the same heights as they did from 2022 to 2025. Before we head onto the “Quick Hits” for film, I want to shout out a fellow newsletter whose articles I’ve been loving this year, LA Material, a new LA-based news outlet. For just a highlight of my favorite articles since July... I loved this article on Ghost Town, a group on Venice that clears homeless encampments. As a Los Angeleno, obviously I adore their articles on LA parking issues. Their article on illegal parking tickets got the City Council to address the issue! Also check out their article on people parking in medians. Check out their deep dive on what went wrong with the LA Jazz Festival and how it fell apart, or what’s wrong with USC’s finances. Finally, they wrote up a voter guide on voter guides for the LA General Election. So meta! In search of a city? L.A. Material is an independent news outlet covering the people, politics, culture and glorious chaos shaping Los Angeles. L.A. Material brings you intel on the city you can’t get anywhere else. From exploring how Reddit short stories became Hollywood’s hottest commodity to reporting on the survival jobs keeping entertainment workers afloat. And answering, once and for all, why the AMC Burbank escalator is always broken. Through their newsletters, podcast, videos, events, and member community, L.A. Material is designed to help Angelenos connect to Los Angeles and each other. Sign up now for the free weekday newsletter. Quick Notes on Film Steven Spielberg’s latest film, Disclosure Day, came to Peacock on 9-Oct, and I’ll admit that, after pulling its stats, I did a pinch of a double take. As I wrote throughout my deep, deep, deep dive on summer box office/Obsession/Backrooms/IP/superheroes, oftentimes the film media discusses films as “flops” or “misses” or “hits” without clarifying what they specifically mean. Since Disclosure Day didn’t make $250 million in the US or $500 million globally, it was definitely a disappointment by Spielbergian standards, who is the highest-grossing director of all time, and arguably even more ahead in adjusted grosses. But it did make $245 million globally on a $115 million budget, so it isn’t as big of a miss as I remember. That’s still probably not enough to break even in the theatrical window, when you factor in marketing costs…but it’s close. And it grossed a lot more even in the US than some titles with about ten times more coverage. Anyways, lots of preamble to say this one only did 4.5 million hours according to Nielsen, so it did make the charts, but on the low end. Here’s how it stacks up to other Peacock titles: Apple TV (née +) followed up their “success for them” Mayday with Matchbox The Movie. This one doesn’t look like a success even for them, but at least it’s not a miss. Apple/Skydance clearly tried to take advantage of the success of Barbie at the box office—let’s greenlight all the toy properties!!!—but of course, this didn’t make it to theaters. And it stars John Cena, who, as I argued earlier this summer, NEEDS to get his movies back in theaters. Anyways, this one has mixed-to-bad numbers. It missed the Samba TV and Nielsen charts in its first week, but did make Luminate with 7.1 million hours. That’s just enough to not be an outright miss, and about half what Mayday did earlier this summer. Speaking of Apple Studio’s Mayday, it ended up lasting five weeks on Luminate, which isn’t bad for Apple TV. On Nielsen, it had a three-week run, racking up 13.5 million hours total. Again, like Matchbox, the issue is the budget; I doubt that this viewership earned enough to justify that budget. Also, to be clear, neither of these films are “midflicks”; both should have gone to theaters. Toy Story 5 is not hanging around on the streaming charts on Disney+, so it’s not as leggy as either Zootopia 2 or Moana 2, and definitely not in the same class as Encanto. (It did make all the money at the box office, so Disney is going to be fine…) The Breadwinner on Netflix (from Sony) is down to 3.9 million hours in its third week. It only lasted for one week on the Samba TV charts. Netflix’s Doing Life had a smaller-than-normal binge release curve bounce, only going to 7.1 million hours from 6.0 to start, but it made Samba TV at fifth place in its second week. The Netflix documentary, The Widower: Til’ Death Do Us Part, also had a small binge release curve bounce to 6.5 million hours, but did make a second week on Samba TV. Meanwhile, Netflix’s Unabomber fell off after two weeks on Nielsen—which is not great at all—and Demon Slayer fell off after just one week. Over on Luminate, the two smaller titles The Swan: Behind the Mirror and Kill. Bury. Print both fell out of the Luminate top ten charts. The story of library film at the first of the month is the arrival of the Ice Age films on Netflix. Now, here’s a small example of optimizing your library that even Netflix could do better. Say you want to rent/license a new film series from Disney**.** A streamer could pay a big paycheck and then drop each Ice Age film on the exact same day of the month, the fourth of October. That’s one choice. In contrast, the streamer could have released each film one week apart, and make each one a mini-event for folks watching Ice Age films. Or even roll them out monthly. Netflix opted for the former strategy, and as a result, only three of the films made the Nielsen charts this week. The “Miss of the Week” goes to Tubi’s YA-ish horror film_, R.L. Stine’s Pumpkinhead 2_, which didn’t even make the Luminate charts like Tubi films usually do, or, should I say, “used to”? Tubi films, most of which are straight-to-streaming, used to reliably make the Luminate film charts (which only covers straight-to-streaming films), but a Tubi film hasn’t made it since August. The first Pumpkinhead got 1.4 million hours last year according to Luminate. As I wrote about this film before, it seems to be a bit muddled in terms of age: too scary for young kids but probably not scary enough for older kids. Speaking of Luminate, Netflix’s latest doc about a comic (expect more docs about comedians all month), Who Is Martin Mull?, flopped, getting just 200K and 700K hours according to Luminate. Three other film/special misses belonged to Hulu, including a standup special, Jamie Foxx: Take Care of Yourself, Neon’s latest horror film, Hokum, which made $17 million in the US, and a Family Guy Halloween special. (That last one was only 22 minutes, so it’s not a surprise it missed.) Finally, another Netflix standup special missed the charts, Mojo Brookzz: I Know You Lying missed too. I can confirm last week’s misses, most notably Paramount+’s Jackass: Best and Last, MUBI’s Teenage Sex and Death at Camp Miasma and HBO Max’s Evil Dead Burn. Television - I Can’t Visualize Nothing: The Kardashians Story Normally, in the mini-dive essays that open the Streaming Ratings Report, I focus on shows that do well or, at the very least, make the charts. Why? Because as I’ve said time and again, I can’t visualize nothing like, say, the Kardashians’ TV shows. Here’s the TV debuts chart for this week with a missing spot for The Kardashians, whose eighth season just landed on Hulu:
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