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Complementary (c)DNA clones corresponding to the full‐length genome of T36CA (a Californian isolate of Citrus tristeza virus with the T36 genotype), which shares 99.1% identity with that of T36FL (a T36 isolate from Florida), were made into a vector system to express the green fluorescent protein (GFP). Agroinfiltration of two prototype T36CA‐based vectors (pT36CA) to Nicotiana benthamiana plants resulted in local but not systemic GFP expression/viral infection. This contrasted with agroinfiltration of the T36FL‐based vector (pT36FL), which resulted in both local and systemic GFP expression/viral infection. A prototype T36CA systemically infected RNA silencing‐defective N. benthamiana lines, demonstrating that a genetic basis for its defective systemic infection was RNA silencing. We evaluated the in planta bioactivity of chimeric pT36CA‐pT36FL constructs and the results suggested that nucleotide variants in several open reading frames of the prototype T36CA could be responsible for its defective systemic infection. A single amino acid substitution in each of two silencing suppressors, p20 (S107G) and p25 (G36D), of prototype T36CA facilitated its systemic infectivity in N. benthamiana (albeit with reduced titre relative to that of T36FL) but not in Citrus macrophylla plants. Enhanced virus accumulation and, remarkably, robust systemic infection of T36CA in N. benthamiana and C. macrophylla plants, respectively, required two additional amino acid substitutions engineered in p65 (N118S and S158L), a putative closterovirus movement protein. The availability of pT36CA provides a unique opportunity for comparative analysis to identify viral coding and noncoding nucleotides or sequences involved in functions that are vital for in planta infection. Differential bioactivity of citrus tristeza virus (CTV), T36CA, in two plant hosts is delineated by specific amino acid residues in two viral suppressors of RNA silencing and a putative CTV movement protein.

For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scoring is based on subjective microscopic examination of tumor morphology and suffers from poor reproducibility. Here we present a deep learning system (DLS) for Gleason scoring whole-slide images of prostatectomies. Our system was developed using 112 million pathologist-annotated image patches from 1226 slides, and evaluated on an independent validation dataset of 331 slides. Compared to a reference standard provided by genitourinary pathology experts, the mean accuracy among 29 general pathologists was 0.61 on the validation set. The DLS achieved a significantly higher diagnostic accuracy of 0.70 ( p  = 0.002) and trended towards better patient risk stratification in correlations to clinical follow-up data. Our approach could improve the accuracy of Gleason scoring and subsequent therapy decisions, particularly where specialist expertise is unavailable. The DLS also goes beyond the current Gleason system to more finely characterize and quantitate tumor morphology, providing opportunities for refinement of the Gleason system itself.

Before 2020, mental disorders were leading causes of the global health-related burden, with depressive and anxiety disorders being leading contributors to this burden. The emergence of the COVID-19 pandemic has created an environment where many determinants of poor mental health are exacerbated. The need for up-to-date information on the mental health impacts of COVID-19 in a way that informs health system responses is imperative. In this study, we aimed to quantify the impact of the COVID-19 pandemic on the prevalence and burden of major depressive disorder and anxiety disorders globally in 2020. We conducted a systematic review of data reporting the prevalence of major depressive disorder and anxiety disorders during the COVID-19 pandemic and published between Jan 1, 2020, and Jan 29, 2021. We searched PubMed, Google Scholar, preprint servers, grey literature sources, and consulted experts. Eligible studies reported prevalence of depressive or anxiety disorders that were representative of the general population during the COVID-19 pandemic and had a pre-pandemic baseline. We used the assembled data in a meta-regression to estimate change in the prevalence of major depressive disorder and anxiety disorders between pre-pandemic and mid-pandemic (using periods as defined by each study) via COVID-19 impact indicators (human mobility, daily SARS-CoV-2 infection rate, and daily excess mortality rate). We then used this model to estimate the change from pre-pandemic prevalence (estimated using Disease Modelling Meta-Regression version 2.1 [known as DisMod-MR 2.1]) by age, sex, and location. We used final prevalence estimates and disability weights to estimate years lived with disability and disability-adjusted life-years (DALYs) for major depressive disorder and anxiety disorders. We identified 5683 unique data sources, of which 48 met inclusion criteria (46 studies met criteria for major depressive disorder and 27 for anxiety disorders). Two COVID-19 impact indicators, specifically daily SARS-CoV-2 infection rates and reductions in human mobility, were associated with increased prevalence of major depressive disorder (regression coefficient [B] 0·9 [95% uncertainty interval 0·1 to 1·8; p=0·029] for human mobility, 18·1 [7·9 to 28·3; p=0·0005] for daily SARS-CoV-2 infection) and anxiety disorders (0·9 [0·1 to 1·7; p=0·022] and 13·8 [10·7 to 17·0; p<0·0001]. Females were affected more by the pandemic than males (B 0·1 [0·1 to 0·2; p=0·0001] for major depressive disorder, 0·1 [0·1 to 0·2; p=0·0001] for anxiety disorders) and younger age groups were more affected than older age groups (−0·007 [–0·009 to −0·006; p=0·0001] for major depressive disorder, −0·003 [–0·005 to −0·002; p=0·0001] for anxiety disorders). We estimated that the locations hit hardest by the pandemic in 2020, as measured with decreased human mobility and daily SARS-CoV-2 infection rate, had the greatest increases in prevalence of major depressive disorder and anxiety disorders. We estimated an additional 53·2 million (44·8 to 62·9) cases of major depressive disorder globally (an increase of 27·6% [25·1 to 30·3]) due to the COVID-19 pandemic, such that the total prevalence was 3152·9 cases (2722·5 to 3654·5) per 100 000 population. We also estimated an additional 76·2 million (64·3 to 90·6) cases of anxiety disorders globally (an increase of 25·6% [23·2 to 28·0]), such that the total prevalence was 4802·4 cases (4108·2 to 5588·6) per 100 000 population. Altogether, major depressive disorder caused 49·4 million (33·6 to 68·7) DALYs and anxiety disorders caused 44·5 million (30·2 to 62·5) DALYs globally in 2020. This pandemic has created an increased urgency to strengthen mental health systems in most countries. Mitigation strategies could incorporate ways to promote mental wellbeing and target determinants of poor mental health and interventions to treat those with a mental disorder. Taking no action to address the burden of major depressive disorder and anxiety disorders should not be an option. Queensland Health, National Health and Medical Research Council, and the Bill and Melinda Gates Foundation.

•COVID-19 vaccination coverage is among women of reproductive age (18–49 years) overall.•Pregnant women and women who were trying to become pregnant at the time of the survey had lowest COVID-19 vaccination coverage.•COVID-19 vaccination coverage among women aged 18–49 years ranged from 53.3% in HHS Region 4 to 76.5% in HHS Region 1. Pregnant and postpartum women are at increased risk for severe illness from COVID-19. We assessed COVID-19 vaccination coverage, intent, and attitudes among women of reproductive age overall and by pregnancy status in the United States. Data from the National Immunization Survey Adult COVID Module collected during April 22-November 27, 2021, were analyzed to assess COVID-19 vaccination (receipt of ≥1 dose), intent for vaccination, and attitudes towards vaccination among women aged 18–49 years overall and by pregnancy status (trying to get pregnant, currently pregnant, breastfeeding, and not trying to get pregnant or currently pregnant or breastfeeding). Logistic regression and predictive marginals were used to generate unadjusted and adjusted prevalence ratios (PRs and aPRs). Trend analyses were conducted to assess monthly changes in vaccination and intent. Our analyses included 110,925 women aged 18–49 years. COVID-19 vaccination coverage (≥1 dose) was 63.2% overall (range from 53.3% in HHS Region 4 to 76.5% in HHS Region 1). Vaccination coverage was lowest among pregnant women (45.1%), followed by women who were trying to get pregnant (49.5%), women who were breastfeeding (51.5%), and all other women (64.9%). Non-Hispanic (NH) Black women who were pregnant or breastfeeding had significantly lower vaccination coverage (aPR: 0.74 and 0.66, respectively) than NH White women. Our findings are consistent with other studies showing lower vaccination coverage among pregnant individuals, with substantially lower vaccination coverage among NH Black women who are pregnant or breastfeeding. Given the overlapping and disproportionate risks of COVID-19 and maternal mortality among Black women, it is critical that COVID-19 vaccination be strongly recommended for these populations and all women of reproductive age. Healthcare and public health providers may take advantage of every opportunity to encourage vaccination and enlist the assistance of community leaders, particularly in communities with low vaccination coverage.

Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales. Climate change will not only challenge current crop modeling techniques, but require new types of models that can account for and operate at multiple scales to measure adaptation and resilience.

T-cell-based immunotherapies are promising treatments for cancer patients. Although durable responses can be achieved in some patients, many patients fail to respond to these therapies, underscoring the need for improvement with combination therapies. From a screen of 850 bioactive compounds, we identify HSP90 inhibitors as candidates for combination with immunotherapy. We show that inhibition of HSP90 with ganetespib enhances T-cell-mediated killing of patient-derived human melanoma cells by their autologous T cells in vitro and potentiates responses to anti-CTLA4 and anti-PD1 therapy in vivo. Mechanistic studies reveal that HSP90 inhibition results in upregulation of interferon response genes, which are essential for the enhanced killing of ganetespib treated melanoma cells by T cells. Taken together, these findings provide evidence that HSP90 inhibition can potentiate T-cell-mediated anti-tumor immune responses, and rationale to explore the combination of immunotherapy and HSP90 inhibitors. Many patients fail to respond to T cell based immunotherapies. Here, the authors, through a high-throughput screening, identify HSP90 inhibitors as a class of preferred drugs for treatment combination with immunotherapy.

We assessed coronavirus disease vaccination and intent and knowledge, attitudes, and beliefs among essential workers during March–June 2021. Coverage was 67%; 18% reported no intent to get vaccinated. Primary concerns were potential side effects, safety, and lack of trust in vaccines, highlighting the importance of increasing vaccine confidence in this population.

Combination therapy with PD-1 blockade and IL-2 is highly effective during chronic lymphocytic choriomeningitis virus infection 1 . Here we examine the underlying basis for this synergy. We show that PD-1 + IL-2 combination therapy, in contrast to PD-1 monotherapy, substantially changes the differentiation program of the PD-1 + TCF1 + stem-like CD8 +  T cells and results in the generation of transcriptionally and epigenetically distinct effector CD8 +  T cells that resemble highly functional effector CD8 +  T cells seen after an acute viral infection. The generation of these qualitatively superior CD8 + T cells that mediate viral control underlies the synergy between PD-1 and IL-2. Our results show that the PD-1 + TCF1 + stem-like CD8 + T cells, also referred to as precursors of exhausted CD8 + T cells, are not fate-locked into the exhaustion program and their differentiation trajectory can be changed by IL-2 signals. These virus-specific effector CD8 + T cells emerging from the stem-like CD8 + T cells after combination therapy expressed increased levels of the high-affinity IL-2 trimeric (CD25–CD122–CD132) receptor. This was not seen after PD-1 blockade alone. Finally, we show that CD25 engagement with IL-2 has an important role in the observed synergy between IL-2 cytokine and PD-1 blockade. Either blocking CD25 with an antibody or using a mutated version of IL-2 that does not bind to CD25 but still binds to CD122 and CD132 almost completely abrogated the synergistic effects observed after PD-1 + IL-2 combination therapy. There is considerable interest in PD-1 + IL-2 combination therapy for patients with cancer 2 , 3 , and our fundamental studies defining the underlying mechanisms of how IL-2 synergizes with PD-1 blockade should inform these human translational studies. PD-1 + TCF1 + stem-like CD8 + T cells—precursors of exhausted CD8 + T cells—are not fate-locked into the exhaustion program; their differentiation trajectory can be changed by IL-2 signals.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P  < 1 × 10 −4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant ( P  < 5 × 10 −8 ) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder. Genome-wide analysis identifies 30 loci associated with bipolar disorder, allowing for comparisons of shared genes and pathways with other psychiatric disorders, including schizophrenia and depression.

National rates of COVID-19 infection and fatality have varied dramatically since the onset of the pandemic. Understanding the conditions associated with this cross-country variation is essential to guiding investment in more effective preparedness and response for future pandemics. Daily SARS-CoV-2 infections and COVID-19 deaths for 177 countries and territories and 181 subnational locations were extracted from the Institute for Health Metrics and Evaluation's modelling database. Cumulative infection rate and infection-fatality ratio (IFR) were estimated and standardised for environmental, demographic, biological, and economic factors. For infections, we included factors associated with environmental seasonality (measured as the relative risk of pneumonia), population density, gross domestic product (GDP) per capita, proportion of the population living below 100 m, and a proxy for previous exposure to other betacoronaviruses. For IFR, factors were age distribution of the population, mean body-mass index (BMI), exposure to air pollution, smoking rates, the proxy for previous exposure to other betacoronaviruses, population density, age-standardised prevalence of chronic obstructive pulmonary disease and cancer, and GDP per capita. These were standardised using indirect age standardisation and multivariate linear models. Standardised national cumulative infection rates and IFRs were tested for associations with 12 pandemic preparedness indices, seven health-care capacity indicators, and ten other demographic, social, and political conditions using linear regression. To investigate pathways by which important factors might affect infections with SARS-CoV-2, we also assessed the relationship between interpersonal and governmental trust and corruption and changes in mobility patterns and COVID-19 vaccination rates. The factors that explained the most variation in cumulative rates of SARS-CoV-2 infection between Jan 1, 2020, and Sept 30, 2021, included the proportion of the population living below 100 m (5·4% [4·0–7·9] of variation), GDP per capita (4·2% [1·8–6·6] of variation), and the proportion of infections attributable to seasonality (2·1% [95% uncertainty interval 1·7–2·7] of variation). Most cross-country variation in cumulative infection rates could not be explained. The factors that explained the most variation in COVID-19 IFR over the same period were the age profile of the country (46·7% [18·4–67·6] of variation), GDP per capita (3·1% [0·3–8·6] of variation), and national mean BMI (1·1% [0·2–2·6] of variation). 44·4% (29·2–61·7) of cross-national variation in IFR could not be explained. Pandemic-preparedness indices, which aim to measure health security capacity, were not meaningfully associated with standardised infection rates or IFRs. Measures of trust in the government and interpersonal trust, as well as less government corruption, had larger, statistically significant associations with lower standardised infection rates. High levels of government and interpersonal trust, as well as less government corruption, were also associated with higher COVID-19 vaccine coverage among middle-income and high-income countries where vaccine availability was more widespread, and lower corruption was associated with greater reductions in mobility. If these modelled associations were to be causal, an increase in trust of governments such that all countries had societies that attained at least the amount of trust in government or interpersonal trust measured in Denmark, which is in the 75th percentile across these spectrums, might have reduced global infections by 12·9% (5·7–17·8) for government trust and 40·3% (24·3–51·4) for interpersonal trust. Similarly, if all countries had a national BMI equal to or less than that of the 25th percentile, our analysis suggests global standardised IFR would be reduced by 11·1%. Efforts to improve pandemic preparedness and response for the next pandemic might benefit from greater investment in risk communication and community engagement strategies to boost the confidence that individuals have in public health guidance. Our results suggest that increasing health promotion for key modifiable risks is associated with a reduction of fatalities in such a scenario. Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.