Grimeswelch3031

here, e.g., to other behavioral, policy, or health related topics.

Detailed county- and state-level estimates of smoke-free workplace policies and home rules can help identify coverage disparities and differential impact of smoke-free legislation and related social norms. Moreover, this estimation framework can be useful for modeling different tobacco control variables and applied elsewhere, e.g., to other behavioral, policy, or health related topics.

While numerous studies show that preoperative pain catastrophizing is a risk factor for pain following total knee arthroplasty (TKA), little is known regarding the temporal course of the association between perioperative pain catastrophizing and pain severity. The present study investigated temporal changes and their dynamic associations between pain catastrophizing and pain severity before and after TKA.

A secondary data analysis of a larger observational parent study featuring prospective repeated measurement over 12 months.

Dual-site academic hospital.

245 individuals who underwent TKA.

Participants completed pain catastrophizing and pain severity questionnaires at baseline, 6-weeks, and 3-, 6-, and 12-months post-TKA. Cross-lagged panel analysis was conducted using structural equation modeling including age, sex, race, baseline anxiety and depressive symptoms as covariates.

Reduction in pain catastrophizing from baseline to 6-week post-TKA was associated with lower pain severity at 3-month posdergoing TKA.Spruce budworm, Choristoneura fumiferana Clem. (Lepidoptera Tortricidae), is the most severe defoliator of Pinaceae in Nearctic boreal forests. Three tools widely used to guide large-scale management decisions (year-to-year defoliation maps; density of overwintering second instars [L2]; number of males at pheromone traps) were integrated to derive pheromone-based thresholds corresponding to specific intergenerational transitions in larval densities (L2i → L2i+1), taking into account the novel finding that threshold estimates decline with distance to defoliated forest stands (DIST). Estimates of thresholds were highly variable between years, both numerically and in terms of interactive effects of L2i and DIST, which limit their heuristic value. In the context of early intervention strategy (L2i+1 > 6.5 individuals per branch), however, thresholds fluctuated within relatively narrow intervals across wide ranges of L2i and DIST, and values of 40-200 males per trap may thus be used as general guideline.This paper utilizes causal time-series and panel techniques to examine the relationship between development assistance for health (DAH) and domestic health spending, both public and private, in 134 countries between 2000 and 2015. Data on 237 656 donor transactions from the Institute for Health Metrics and Evaluation's DAH and Health Expenditure datasets are merged with economic, demographic and health data from the World Bank Databank and World Health Organization's Global Health Observatory. Arellano-Bond system GMM estimation is used to assess the effect of changes in DAH on domestic health spending and health outcomes. Analyses are conducted for the entire health sector and separately for HIV, TB and malaria financing. Results show that DAH had no significant impact on overall domestic public health investment. For HIV-specific investments, a $1 increase in on-budget DAH was associated with a $0.12 increase in government spending for HIV. For the private sector, $1 in DAH is associated with a $0.60 and $0.03 increase in prepaid private spending overall and for malaria, with no significant impact on HIV spending. Results demonstrate that a 1% increase in public financing reduced under-5 mortality by 0.025%, while a 1% increase in DAH had no significant effect on reducing under-5 mortality. The relationships between DAH and public health financing suggest that malaria and HIV-specific crowding-in effects are offset by crowding-out effects in other unobserved health sectors. The results also suggest policies that crowd-in public financing will likely have larger impacts on health outcomes than DAH investments that do not crowd-in public spending.The coronavirus disease 2019 (COVID-19) outbreak continues to spread rapidly around the world. By the end of 2020, there have been nearly 80 million confirmed cases and >1.7 million deaths associated with COVID-19 globally (https//www.who.int/emergencies/diseases/novel-coronavirus-2019), with an estimated mortality rate of 0.03%-40% (Wiersinga et al., 2020). Noticeably, the COVID-19 is predicted to threaten millions of people throughout the world in the coming months and years.Assessments of sperm DNA damage are controversial because of perceived uncertainties over the relationship with pregnancy and the limited range of therapies available should positive results be returned. In this article, we highlight recent data supporting a chain of associations between oxidative stress in the male germ line, DNA damage in spermatozoa, defective DNA repair in the oocyte, the mutational load carried by the resulting embryo and the long-term health trajectory of the offspring. Any condition capable of generating oxidative damage in spermatozoa (age, obesity, smoking, prolonged abstinence, varicocele, chemical exposures, radiation etc.) is capable of influencing offspring health in this manner, creating a range of pathologies in the progeny including neuropsychiatric disorders and cancer. If sperm DNA damage is detected, there are several therapeutic interventions that can be introduced to improve DNA quality prior to the use of these cells in ART. We therefore argue that infertility specialists should be engaged in the diagnosis and remediation of sperm DNA damage as a matter of best practice, in order to minimize the risk of adverse health outcomes in children conceived using ART.

Few studies have evaluated tuberculosis control in children and adolescents. We used routine tuberculosis surveillance data to quantify age- and HIV-stratified trends over time and investigate the relationship between tuberculosis, HIV, age and sex.

All children and adolescents (0-19 years) routinely treated for drug-susceptible tuberculosis in South Africa and recorded in a de-duplicated national electronic tuberculosis treatment register (2004-2016) were included. Age- and HIV-stratified tuberculosis case notification rates (CNRs) were calculated in four age bands 0-4, 5-9, 10-14 and 15-19 years. The association between HIV infection, age and sex in children and adolescents with TB was evaluated using multivariable logistic regression.

Of 719,400 children and adolescents included, 339,112 (47%) were 0-4-year-olds. The overall tuberculosis CNR for 0-19-year-olds declined by 54% between 2009 and 2016 (incidence rate ratio [IRR]=0.46, 95% confidence interval [CI] 0.45-0.47). Trends varied by age and HIV,s. The slow decline of tuberculosis CNRs in adolescents and young HIV-positive children is concerning. Understanding how tuberculosis affects children and adolescents beyond conventional age bands and by sex, can inform targeted tuberculosis control strategies.There is growing evidence that the upper female genital tract is not sterile, harbouring its own microbial communities. However, the significance and the potential effect of endometrial microorganisms on reproductive functions remain to be fully elucidated. Analysing the endometrial microbiome, the microbes and their genetic material present in the endometrium, is an emerging area of study. The initial studies suggest it is associated with poor reproductive outcomes and with different gynaecological pathologies. Nevertheless, studying a low-biomass microbial niche as is endometrium, the challenge is to conduct well-designed and well-controlled experiments in order to avoid and adjust for the risk of contamination, especially from the lower genital tract. Herein, we aim to highlight methodological considerations and propose good practice recommendations for future endometrial microbiome studies.

Detailed mechanistic models of biological processes can pose significant challenges for analysis and parameter estimations due to the large number of equations used to track the dynamics of all distinct configurations in which each involved biochemical species can be found. Model reduction can help tame such complexity by providing a lower-dimensional model in which each macro-variable can be directly related to the original variables.

We present CLUE, an algorithm for exact model reduction of systems of polynomial differential equations by constrained linear lumping. It computes the smallest dimensional reduction as a linear mapping of the state space such that the reduced model preserves the dynamics of user-specified linear combinations of the original variables. Even though CLUE works with nonlinear differential equations, it is based on linear algebra tools, which makes it applicable to high-dimensional models. Using case studies from the literature, we show how CLUE can substantially lower model dimensionality and help extract biologically intelligible insights from the reduction.

An implementation of the algorithm and relevant resources to replicate the experiments herein reported are freely available for download at https//github.com/pogudingleb/CLUE.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.

Resolving the coronavirus disease 2019 (COVID-19) pandemic requires diagnostic testing to determine which individuals are infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The current gold standard is to perform reverse-transcription polymerase chain reaction (PCR) on nasopharyngeal samples. Best-in-class assays demonstrate a limit of detection (LoD) of approximately 100 copies of viral RNA per milliliter of transport media. However, LoDs of currently approved assays vary over 10,000-fold. Assays with higher LoDs will miss infected patients. However, the relative clinical sensitivity of these assays remains unknown.

Here we model the clinical sensitivities of assays based on their LoD. Cycle threshold (Ct) values were obtained from 4700 first-time positive patients using the Abbott RealTime SARS-CoV-2 Emergency Use Authorization test. We derived viral loads from Ct based on PCR principles and empiric analysis. A sliding scale relationship for predicting clinical sensitivity was developed from analysis of viral load distribution relative to assay LoD.

Ct values were reliably repeatable over short time testing windows, providing support for use as a tool to estimate viral load. Viral load was found to be relatively evenly distributed across log10 bins of incremental viral load. Based on these data, each 10-fold increase in LoD is expected to lower assay sensitivity by approximately 13%.

The assay LoD meaningfully impacts clinical performance of SARS-CoV-2 tests. The highest LoDs on the market will miss a majority of infected patients. Assays should therefore be benchmarked against a universal standard to allow cross-comparison of SARS-CoV-2 detection methods.

The assay LoD meaningfully impacts clinical performance of SARS-CoV-2 tests. The highest LoDs on the market will miss a majority of infected patients. Assays should therefore be benchmarked against a universal standard to allow cross-comparison of SARS-CoV-2 detection methods.