Large Language Models Encode Clinical Knowledge

Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but the quality bar for medical and clinical applications is high. Today, attempts to assess models' clinical knowledge typically rely on automated evaluations on limited benchmarks. There is no standard to evaluate model predictions and reasoning across a breadth of tasks. To address this, we present MultiMedQA, a benchmark combining six existing open question answering datasets spanning professional medical exams, research, and consumer queries; and HealthSearchQA, a new free-response dataset of medical questions searched online. We propose a framework for human evaluation of model answers along multiple axes including factuality, precision, possible harm, and bias. In addition, we evaluate PaLM (a 540-billion parameter LLM) and its instruction-tuned variant, Flan-PaLM, on MultiMedQA. Using a combination of prompting strategies, Flan-PaLM achieves state-of-the-art accuracy on every MultiMedQA multiple-choice dataset (MedQA, MedMCQA, PubMedQA, MMLU clinical topics), including 67.6% accuracy on MedQA (US Medical License Exam questions), surpassing prior state-of-the-art by over 17%. However, human evaluation reveals key gaps in Flan-PaLM responses. To resolve this we introduce instruction prompt tuning, a parameter-efficient approach for aligning LLMs to new domains using a few exemplars. The resulting model, Med-PaLM, performs encouragingly, but remains inferior to clinicians. We show that comprehension, recall of knowledge, and medical reasoning improve with model scale and instruction prompt tuning, suggesting the potential utility of LLMs in medicine. Our human evaluations reveal important limitations of today's models, reinforcing the importance of both evaluation frameworks and method development in creating safe, helpful LLM models for clinical applications

MUC1 Limits Helicobacter pylori Infection both by Steric Hindrance and by Acting as a Releasable Decoy

The bacterium Helicobacter pylori can cause peptic ulcer disease, gastric adenocarcinoma and MALT lymphoma. The cell-surface mucin MUC1 is a large glycoprotein which is highly expressed on the mucosal surface and limits the density of H. pylori in a murine infection model. We now demonstrate that by using the BabA and SabA adhesins, H. pylori bind MUC1 isolated from human gastric cells and MUC1 shed into gastric juice. Both H. pylori carrying these adhesins, and beads coated with MUC1 antibodies, induced shedding of MUC1 from MKN7 human gastric epithelial cells, and shed MUC1 was found bound to H. pylori. Shedding of MUC1 from non-infected cells was not mediated by the known MUC1 sheddases ADAM17 and MMP-14. However, knockdown of MMP-14 partially affected MUC1 release early in infection, whereas ADAM17 had no effect. Thus, it is likely that shedding is mediated both by proteases and by disassociation of the non-covalent interaction between the α- and β-subunits. H. pylori bound more readily to MUC1 depleted cells even when the bacteria lacked the BabA and SabA adhesins, showing that MUC1 inhibits attachment even when bacteria cannot bind to the mucin. Bacteria lacking both the BabA and SabA adhesins caused less apoptosis in MKN7 cells than wild-type bacteria, having a greater effect than deletion of the CagA pathogenicity gene. Deficiency of MUC1/Muc1 resulted in increased epithelial cell apoptosis, both in MKN7 cells in vitro, and in H. pylori infected mice. Thus, MUC1 protects the epithelium from non-MUC1 binding bacteria by inhibiting adhesion to the cell surface by steric hindrance, and from MUC1-binding bacteria by acting as a releasable decoy

Towards Generalist Biomedical AI

Medicine is inherently multimodal, with rich data modalities spanning text, imaging, genomics, and more. Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, and interpret this data at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. To enable the development of these models, we first curate MultiMedBench, a new multimodal biomedical benchmark. MultiMedBench encompasses 14 diverse tasks such as medical question answering, mammography and dermatology image interpretation, radiology report generation and summarization, and genomic variant calling. We then introduce Med-PaLM Multimodal (Med-PaLM M), our proof of concept for a generalist biomedical AI system. Med-PaLM M is a large multimodal generative model that flexibly encodes and interprets biomedical data including clinical language, imaging, and genomics with the same set of model weights. Med-PaLM M reaches performance competitive with or exceeding the state of the art on all MultiMedBench tasks, often surpassing specialist models by a wide margin. We also report examples of zero-shot generalization to novel medical concepts and tasks, positive transfer learning across tasks, and emergent zero-shot medical reasoning. To further probe the capabilities and limitations of Med-PaLM M, we conduct a radiologist evaluation of model-generated (and human) chest X-ray reports and observe encouraging performance across model scales. In a side-by-side ranking on 246 retrospective chest X-rays, clinicians express a pairwise preference for Med-PaLM M reports over those produced by radiologists in up to 40.50% of cases, suggesting potential clinical utility. While considerable work is needed to validate these models in real-world use cases, our results represent a milestone towards the development of generalist biomedical AI systems

Human Gastric Mucins Differently Regulate Helicobacter pylori Proliferation, Gene Expression and Interactions with Host Cells

Helicobacter pylori colonizes the mucus niche of the gastric mucosa and is a risk factor for gastritis, ulcers and cancer. The main components of the mucus layer are heavily glycosylated mucins, to which H. pylori can adhere. Mucin glycosylation differs between individuals and changes during disease. Here we have examined the H. pylori response to purified mucins from a range of tumor and normal human gastric tissue samples. Our results demonstrate that mucins from different individuals differ in how they modulate both proliferation and gene expression of H. pylori. The mucin effect on proliferation varied significantly between samples, and ranged from stimulatory to inhibitory, depending on the type of mucins and the ability of the mucins to bind to H. pylori. Tumor-derived mucins and mucins from the surface mucosa had potential to stimulate proliferation, while gland-derived mucins tended to inhibit proliferation and mucins from healthy uninfected individuals showed little effect. Artificial glycoconjugates containing H. pylori ligands also modulated H. pylori proliferation, albeit to a lesser degree than human mucins. Expression of genes important for the pathogenicity of H. pylori (babA, sabA, cagA, flaA and ureA) appeared co-regulated in response to mucins. The addition of mucins to co-cultures of H. pylori and gastric epithelial cells protected the viability of the cells and modulated the cytokine production in a manner that differed between individuals, was partially dependent of adhesion of H. pylori to the gastric cells, but also revealed that other mucin factors in addition to adhesion are important for H. pylori-induced host signaling. The combined data reveal host-specific effects on proliferation, gene expression and virulence of H. pylori due to the gastric mucin environment, demonstrating a dynamic interplay between the bacterium and its host

Disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE) in Iran and its neighboring countries, 1990–2015

BACKGROUND: Summary measures of health are essential in making estimates of health status that are comparable across time and place. They can be used for assessing the performance of health systems, informing effective policy making, and monitoring the progress of nations toward achievement of sustainable development goals. The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) provides disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) as main summary measures of health. We assessed the trends of health status in Iran and 15 neighboring countries using these summary measures. METHODS: We used the results of GBD 2015 to present the levels and trends of DALYs, life expectancy (LE), and HALE in Iran and its 15 neighboring countries from 1990 to 2015. For each country, we assessed the ratio of observed levels of DALYs and HALE to those expected based on socio-demographic index (SDI), an indicator composed of measures of total fertility rate, income per capita, and average years of schooling. RESULTS: All-age numbers of DALYs reached over 19 million years in Iran in 2015. The all-age number of DALYs has remained stable during the past two decades in Iran, despite the decreasing trends in all-age and age-standardized rates. The all-cause DALY rates decreased from 47,200 in 1990 to 28,400 per 100,000 in 2015. The share of non-communicable diseases in DALYs increased in Iran (from 42% to 74%) and all of its neighbors between 1990 and 2015; the pattern of change is similar in almost all 16 countries. The DALY rates for NCDs and injuries in Iran were higher than global rates and the average rate in High Middle SDI countries, while those for communicable, maternal, neonatal, and nutritional disorders were much lower in Iran. Among men, cardiovascular diseases ranked first in all countries of the region except for Bahrain. Among women, they ranked first in 13 countries. Life expectancy and HALE show a consistent increase in all countries. Still, there are dissimilarities indicating a generally low LE and HALE in Afghanistan and Pakistan and high expectancy in Qatar, Kuwait, and Saudi Arabia. Iran ranked 11th in terms of LE at birth and 12th in terms of HALE at birth in 1990 which improved to 9th for both metrics in 2015. Turkey and Iran had the highest increase in LE and HALE from 1990 to 2015 while the lowest increase was observed in Armenia, Pakistan, Kuwait, Kazakhstan, Russia, and Iraq. CONCLUSIONS: The levels and trends in causes of DALYs, life expectancy, and HALE generally show similarities between the 16 countries, although differences exist. The differences observed between countries can be attributed to a myriad of determinants, including social, cultural, ethnic, religious, political, economic, and environmental factors as well as the performance of the health system. Investigating the differences between countries can inform more effective health policy and resource allocation. Concerted efforts at national and regional levels are required to tackle the emerging burden of non-communicable diseases and injuries in Iran and its neighbors

Helicobacter pylori Adapts to Chronic Infection and Gastric Disease via pH-Responsive BabA-Mediated Adherence

International audienceThe BabA adhesin mediates high-affinity binding of Helicobacter pylori to the ABO blood group antigen-glycosylated gastric mucosa. Here we show that BabA is acid responsive-binding is reduced at low pH and restored by acid neutralization. Acid responsiveness differs among strains; often correlates with different intragastric regions and evolves during chronic infection and disease progression; and depends on pH sensor sequences in BabA and on pH reversible formation of high-affinity binding BabA multimers. We propose that BabA's extraordinary reversible acid responsiveness enables tight mucosal bacterial adherence while also allowing an effective escape from epithelial cells and mucus that are shed into the acidic bactericidal lumen and that bio-selection and changes in BabA binding properties through mutation and recombination with babA-related genes are selected by differences among individuals and by changes in gastric acidity over time. These processes generate diverse H. pylori subpopulations, in which BabA's adaptive evolution contributes to H. pylori persistence and overt gastric disease

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Adolescent transport and unintentional injuries: a systematic analysis using the Global Burden of Disease Study 2019

Background: Globally, transport and unintentional injuries persist as leading preventable causes of mortality and morbidity for adolescents. We sought to report comprehensive trends in injury-related mortality and morbidity for adolescents aged 10–24 years during the past three decades. Methods: Using the Global Burden of Disease, Injuries, and Risk Factors 2019 Study, we analysed mortality and disability-adjusted life-years (DALYs) attributed to transport and unintentional injuries for adolescents in 204 countries. Burden is reported in absolute numbers and age-standardised rates per 100 000 population by sex, age group (10–14, 15–19, and 20–24 years), and sociodemographic index (SDI) with 95% uncertainty intervals (UIs). We report percentage changes in deaths and DALYs between 1990 and 2019. Findings: In 2019, 369 061 deaths (of which 214 337 [58%] were transport related) and 31·1 million DALYs (of which 16·2 million [52%] were transport related) among adolescents aged 10–24 years were caused by transport and unintentional injuries combined. If compared with other causes, transport and unintentional injuries combined accounted for 25% of deaths and 14% of DALYs in 2019, and showed little improvement from 1990 when such injuries accounted for 26% of adolescent deaths and 17% of adolescent DALYs. Throughout adolescence, transport and unintentional injury fatality rates increased by age group. The unintentional injury burden was higher among males than females for all injury types, except for injuries related to fire, heat, and hot substances, or to adverse effects of medical treatment. From 1990 to 2019, global mortality rates declined by 34·4% (from 17·5 to 11·5 per 100 000) for transport injuries, and by 47·7% (from 15·9 to 8·3 per 100 000) for unintentional injuries. However, in low-SDI nations the absolute number of deaths increased (by 80·5% to 42 774 for transport injuries and by 39·4% to 31 961 for unintentional injuries). In the high-SDI quintile in 2010–19, the rate per 100 000 of transport injury DALYs was reduced by 16·7%, from 838 in 2010 to 699 in 2019. This was a substantially slower pace of reduction compared with the 48·5% reduction between 1990 and 2010, from 1626 per 100 000 in 1990 to 838 per 100 000 in 2010. Between 2010 and 2019, the rate of unintentional injury DALYs per 100 000 also remained largely unchanged in high-SDI countries (555 in 2010 vs 554 in 2019; 0·2% reduction). The number and rate of adolescent deaths and DALYs owing to environmental heat and cold exposure increased for the high-SDI quintile during 2010–19. Interpretation: As other causes of mortality are addressed, inadequate progress in reducing transport and unintentional injury mortality as a proportion of adolescent deaths becomes apparent. The relative shift in the burden of injury from high-SDI countries to low and low–middle-SDI countries necessitates focused action, including global donor, government, and industry investment in injury prevention. The persisting burden of DALYs related to transport and unintentional injuries indicates a need to prioritise innovative measures for the primary prevention of adolescent injury. Funding: Bill & Melinda Gates Foundation

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe