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As of October 21, 2022, a total of 27,884 monkeypox cases (confirmed and probable) have been reported in the United States. Gay, bisexual, and other men who have sex with men have constituted a majority of cases, and persons with HIV infection and those from racial and ethnic minority groups have been disproportionately affected (1,2). During previous monkeypox outbreaks, severe manifestations of disease and poor outcomes have been reported among persons with HIV infection, particularly those with AIDS (3-5). This report summarizes findings from CDC clinical consultations provided for 57 patients aged ≥18 years who were hospitalized with severe manifestations of monkeypox during August 10-October 10, 2022, and highlights three clinically representative cases. Overall, 47 (82%) patients had HIV infection, four (9%) of whom were receiving antiretroviral therapy (ART) before monkeypox diagnosis. Most patients were male (95%) and 68% were non-Hispanic Black (Black). Overall, 17 (30%) patients received intensive care unit (ICU)-level care, and 12 (21%) have died. As of this report, monkeypox was a cause of death or contributing factor in five of these deaths; six deaths remain under investigation to determine whether monkeypox was a causal or contributing factor; and in one death, monkeypox was not a cause or contributing factor.** Health care providers and public health professionals should be aware that severe morbidity and mortality associated with monkeypox have been observed during the current outbreak in the United States (6,7), particularly among highly immunocompromised persons. Providers should test all sexually active patients with suspected monkeypox for HIV at the time of monkeypox testing unless a patient is already known to have HIV infection. Providers should consider early commencement and extended duration of monkeypox-directed therapy in highly immunocompromised patients with suspected or laboratory-diagnosed monkeypox. Engaging all persons with HIV in sustained care remains a critical public health priority.

With the suspension of the lieutenant at the Hays State Prison who stated in a deposition that beatings have taken place at the prison and that Corrections Commissioner Wayne Garner participated in the abuse, every Georgian should call for Garner's immediate replacement. Garner has led tactical squads in thinly veiled contraband sweeps to intimidate and dehumanize inmates. The evidence at Hays is too strong for a civilized people to pretend they don't hear or see.

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet. Prostate cancer progression may be enhanced by a high-fat diet. Here the authors show that a diet high in saturated fats enhance the MYC-driven transcriptional program, a feature that independently predicts prostate cancer progression and death.

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance ( P  < 2.5 × 10 −6 ), including five new risk genes ( NAV3 , ITSN1 , MARK2 , SCAF1 and HNRNPUL2 ). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes ( NAV3 , ITSN1 , SCAF1 and HNRNPUL2 ; n  = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes ( CHD8, SCN2A, ADNP, FOXP1 and SHANK3 ) (59% vs 88%, P  = 1.9 × 10 −6 ). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes. An integrated analysis of de novo and inherited coding variants in 42,607 individuals with autism spectrum disorder identifies 60 risk genes of which five have not previously been associated with neurodevelopmental disorders.

This qualitative study explored the contextual, personal, and interpersonal resources that impact Black fathers involvement in early childhood education activities. Despite being highly motivated to be involved, fathers described several systemic barriers that they believed restricted their involvement and discussed the various resources that they utilized to overcome these barriers. Educators and policy-makers should acknowledge Black fathers unique approaches to involvement as well as the contextual factors that shape their efforts to support their children's academic success.

Michigan has the 17th highest adult obesity rate in the United States. Among college-aged adults between 18 and 25 years old, the rate of obesity was 11.6 %. Obesity is a key precedent for the development of metabolic syndrome. Accordingly, the purpose of this study was to examine the prevalence of metabolic syndrome and its individual components among a sample of students at Central Michigan University. A cross-sectional survey was conducted among 462 students, aged 18–25 years, in Spring 2015 and Fall/Spring 2016 semesters. Students were recruited throughout the campus via flyers, in-class, and Blackboard announcements. Biochemical, anthropometric, and blood pressure measurements were taken for all students. Prevalence of metabolic syndrome was estimated based on the National Cholesterol Education Program’s Adult Treatment Panel III guidelines. Multivariable analysis was used to assess the prevalence of metabolic risk components. To explore the association between metabolic risk factors and lifestyle behaviors, students filled out a validated online questionnaire related to their eating habits, physical activity, and sleep patterns. Metabolic syndrome was not prevalent in our sample. However, about one-third of the students had at least one metabolic abnormality, and 6.0% had two metabolic abnormalities. The most common metabolic abnormalities were low HDL-cholesterol levels (22.0%) and high waist circumference (12.6%), and elevated serum triglyceride (5.8%). Adjusting for other factors, excess adiposity and high visceral fat scores were associated with increased risk of metabolic risk factors, whereas healthy lifestyle practices such as daily breakfast consumption, eating three meals a day, being active, and not smoking were associated with lower risks for MetS. Given the adverse consequences of undiagnosed metabolic abnormalities, efforts to identify and manage MetS among asymptomatic college students, particularly women, is essential and warrants further research.

Background Agent based models (ABM) are useful to explore population-level scenarios of disease spread and containment, but typically characterize infected individuals using simplified models of infection and symptoms dynamics. Adding more realistic models of individual infections and symptoms may help to create more realistic population level epidemic dynamics. Methods Using an equation-based, host-level mathematical model of influenza A virus infection, we develop a function that expresses the dependence of infectivity and symptoms of an infected individual on initial viral load, age, and viral strain phenotype. We incorporate this response function in a population-scale agent-based model of influenza A epidemic to create a hybrid multiscale modeling framework that reflects both population dynamics and individualized host response to infection. Results At the host level, we estimate parameter ranges using experimental data of H1N1 viral titers and symptoms measured in humans. By linearization of symptoms responses of the host-level model we obtain a map of the parameters of the model that characterizes clinical phenotypes of influenza infection and immune response variability over the population. At the population-level model, we analyze the effect of individualizing viral response in agent-based model by simulating epidemics across Allegheny County, Pennsylvania under both age-specific and age-independent severity assumptions. Conclusions We present a framework for multi-scale simulations of influenza epidemics that enables the study of population-level effects of individual differences in infections and symptoms, with minimal additional computational cost compared to the existing population-level simulations.

Commercial potato ( Solanum tuberosum ) in North America is a clonal autotetraploid crop, which complicates breeding. Efforts are underway to convert potato to a diploid inbred‐hybrid crop, allowing breeders to more quickly meet market and environmental demands. With the goal of preserving haplotypes developed over 200 years of selection, diploid potato breeding in the United States started with the creation of diploids from tetraploid commercial varieties and advanced breeding lines through prickle pollination. This is an effective but slow method, which presents a barrier to entry for individual breeding programs. Therefore, we developed 97 publicly available dihaploids (diploids from prickle pollination of tetraploids) as a resource for diploid breeding in the United States. These clones contain the majority of alleles in the US breeding population for three market classes: chips, russets, and fresh market reds. To facilitate genomic informed breeding, all clones have been resequenced, and we have developed de novo assemblies for 20 individuals. As an illustration of how these data will be used in breeding, we explored the maturity locus ( StCDF1 ) and identified 15 different alleles. The majority of dihaploids were heterozygous for early and late alleles, resulting in intermediate maturity. Beyond informing breeding, these data facilitate investigations into potato genomics. The dihaploid population is both highly heterozygous and incredibly diverse on a population level. In particular, there is extensive structural diversity segregating within the population. This contrasts with a relatively low genome‐wide historical recombination rate ( ρ ), indicating that much of potato's high diversity is found within long linkage blocks. Potato breeding is complicated due to their clonal propagation and multiple copies of each of their chromosomes, that is, a tetraploid. While this makes breeding difficult, US potato breeders have created cultivars with traits tuned for different market classes such as chip processing, frozen fry, and fresh table. To accelerate and improve their breeding efforts, potato breeders are working to reduce the potato genome to two copies of each chromosome (diploid) and propagate it by true seed. In an effort to maintain those traits, we generated diploids from existing potato cultivars with half of the genome of the tetraploid parent. In total, we developed a set of 97 diploids that represent the majority of US potato market classes and have made these publicly available. To facilitate breeding, we sequenced the genomes of these diploids, providing insight into US potato cultivar germplasm.