Characterizing selection on complex traits through conditional frequency spectra.

Natural selection on complex traits is difficult to study in part due to the ascertainment inherent to genome-wide association studies (GWAS). The power to detect a trait-associated variant in GWAS is a function of frequency and effect size - but for traits under selection, the effect size of a variant determines the strength of selection against it, constraining its frequency. Recognizing the biases inherent to GWAS ascertainment, we propose studying the joint distribution of allele frequencies across populations, conditional on the frequencies in the GWAS cohort.

Exploring the factors influencing the adult population's reluctance to accept the COVID-19 vaccine in Tehran.

Background: While evidence of efficacy, safety, and technical feasibility is crucial when introducing a vaccine, it is equally important to consider the psychological, social, and political factors influencing vaccine acceptance. This study aims to identify the factors contributing to COVID-19 vaccine hesitancy among adults in Tehran, Iran.

Methods: The study employed a descriptive and analytical cross-sectional design carried out from 2021 to 2022.

Essential core competencies for health policy graduates: a multi-method consensus type study.

Background: In light of the multi-faceted challenges confronting health systems worldwide and the imperative to advance towards development goals, the contribution of health policy graduates is of paramount importance, facilitating the attainment of health and well-being objectives. This paper delineates a set of core skills and competencies that are requisite for health policy graduates, with the objective of preparing these graduates for a spectrum of future roles, including both academic and non-academic positions.

Methods: The study was conducted in three phases: a scoping review, qualitative interviews and the validation of identified competencies through brainstorming with experts.

Bayesian estimation of gene constraint from an evolutionary model with gene features.

Measures of selective constraint on genes have been used for many applications, including clinical interpretation of rare coding variants, disease gene discovery and studies of genome evolution. However, widely used metrics are severely underpowered at detecting constraints for the shortest ~25% of genes, potentially causing important pathogenic mutations to be overlooked. Here we developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, s.

The influence of climate change on the future distribution of two Thymus species in Iran: MaxEnt model-based prediction.

Within a few decades, the species habitat was reshaped at an alarming rate followed by climate change, leading to mass extinction, especially for sensitive species. Species distribution models (SDMs), which estimate both present and future species distribution, have been extensively developed to investigate the impacts of climate change on species distribution and assess habitat suitability. In the West Asia essential oils of T.

The experiences and perceptions of people with chronic and rare diseases during political-economic sanctions in Iran: a qualitative study.

Background: Economic sanctions aim to exert pressure on political and economic foundations. Hypothesizing that sanctions might affect various aspects of population health, this study, as a component of a broader investigation to ascertain the trend effects of sanctions on selected health outcomes in Iran, seeks to explore the experiences of Iranian citizens associated with the imposed sanctions.

Methods: This is a qualitative study.

Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt.

Over the course of a few decades, climate change has caused a rapid and alarming reshaping of species habitats, resulting in mass extinction, particularly among sensitive species. In order to investigate the effects of climate change on species distribution and assess habitat suitability, researchers have developed species distribution models (SDMs) that estimate present and future species distribution. In West Asia, thyme species such as T.

Impact of climate change on the future distribution of three Ferulago species in Iran using the MaxEnt model.

The decline of habitats supporting medicinal plants is a consequence of climate change and human activities. In the Middle East, Ferulago angulata, Ferulago carduchorum, and Ferulago phialocarpa are widely recognized for their culinary, medicinal, and economic value. Therefore, this study models these Ferulago species in Iran using the MaxEnt model under two representative concentration pathways (RCP4.

The application of artificial intelligence in health policy: a scoping review.

Background: Policymakers require precise and in-time information to make informed decisions in complex environments such as health systems. Artificial intelligence (AI) is a novel approach that makes collecting and analyzing data in complex systems more accessible. This study highlights recent research on AI's application and capabilities in health policymaking.

Health Equity Impact Assessment (HEIA) reporting tool: developing a checklist for policymakers.

Introduction: Health Equity Impact Assessment (HEIA) is a decision support tool that shows users how a new program, policy, or innovation affects health equity in different population groups. Various HEIA reporting and dissemination tools are available, nevertheless, a practical standard tool to present the results of HEIA in an appropriate period to policymakers is lacking. This work reports the development of a tool (a checklist) for HEIA reporting at the decision-making level, aiming to promote the application of HEIA evidence for improving health equity.

Systematic differences in discovery of genetic effects on gene expression and complex traits.

Most signals in genome-wide association studies (GWAS) of complex traits implicate noncoding genetic variants with putative gene regulatory effects. However, currently identified regulatory variants, notably expression quantitative trait loci (eQTLs), explain only a small fraction of GWAS signals. Here, we show that GWAS and cis-eQTL hits are systematically different: eQTLs cluster strongly near transcription start sites, whereas GWAS hits do not.

Addressing conflicts of interest regarding the vaccine in infectious disease outbreaks based on good governance for health approach: a policy brief.

Background: Infectious disease outbreaks pose a significant threat to public health, and achieving herd immunity highlights the importance of addressing conflicts of interest (COI) in vaccine development and policy-making. This policy brief aims to present policy options that address COI regarding vaccines in infectious disease outbreaks, based on good governance for health approach.

Methods: Our study used a scoping review methodology.

Scaling the discrete-time Wright-Fisher model to biobank-scale datasets.

The discrete-time Wright-Fisher (DTWF) model and its diffusion limit are central to population genetics. These models can describe the forward-in-time evolution of allele frequencies in a population resulting from genetic drift, mutation, and selection. Computing likelihoods under the diffusion process is feasible, but the diffusion approximation breaks down for large samples or in the presence of strong selection.

Bayesian estimation of gene constraint from an evolutionary model with gene features.

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ~25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, .

Scaling the Discrete-time Wright Fisher model to biobank-scale datasets.

The Discrete-Time Wright Fisher (DTWF) model and its large population diffusion limit are central to population genetics. These models describe the forward-in-time evolution of the frequency of an allele in a population and can include the fundamental forces of genetic drift, mutation, and selection. Computing like-lihoods under the diffusion process is feasible, but the diffusion approximation breaks down for large sample sizes or in the presence of strong selection.

Bayesian estimation of gene constraint from an evolutionary model with gene features.

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ∼25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, .

A booster regime of liposome-delivered live-attenuated CHIKV vaccine RNA genome protects against chikungunya virus disease in mice.

Mosquito-transmitted chikungunya virus (CHIKV) is the causal pathogen of CHIKV disease and is responsible for global epidemics of arthritic disease. CHIKV infection can lead to severe chronic and debilitating arthralgia, significantly impacting patient mobility and quality of life. Our previous studies have shown a live-attenuated CHIKV vaccine candidate, CHIKV-NoLS, to be effective in protecting against CHIKV disease in mice vaccinated with one dose.

Macrophage ACE2 is necessary for SARS-CoV-2 replication and subsequent cytokine responses that restrict continued virion release.

Macrophages are key cellular contributors to the pathogenesis of COVID-19, the disease caused by the virus SARS-CoV-2. The SARS-CoV-2 entry receptor ACE2 is present only on a subset of macrophages at sites of SARS-CoV-2 infection in humans. Here, we investigated whether SARS-CoV-2 can enter macrophages, replicate, and release new viral progeny; whether macrophages need to sense a replicating virus to drive cytokine release; and, if so, whether ACE2 is involved in these mechanisms.

Anti-inflammatory actions of Pentosan polysulfate sodium in a mouse model of influenza virus A/PR8/34-induced pulmonary inflammation.

Introduction: There is an unmet medical need for effective anti-inflammatory agents for the treatment of acute and post-acute lung inflammation caused by respiratory viruses. The semi-synthetic polysaccharide, Pentosan polysulfate sodium (PPS), an inhibitor of NF-kB activation, was investigated for its systemic and local anti-inflammatory effects in a mouse model of influenza virus A/PR8/1934 (PR8 strain) mediated infection.

Methods: Immunocompetent C57BL/6J mice were infected intranasally with a sublethal dose of PR8 and treated subcutaneously with 3 or 6 mg/kg PPS or vehicle.

Evaluation of scale development and its regeneration potency in the desert killifish under laboratory conditions.

Scale development and its regeneration potency were evaluated in a desert killifish Aphaniops hormuzensis (family Aphaniidae) in laboratory conditions by using light and scanning electron microscopy. Scale development in A. hormuzensis took 156 days at room temperature.