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Abstract Despite recommendations in the US National Research Action Plan on Long COVID, gender identity is rarely reported in research and surveillance used to guide public health programming and clinical care. We analyzed data from a cross-sectional study of COVID-19 in a nationwide sample of transgender and nonbinary (TNB) people (N = 2,134). Participants were surveyed between June 14, 2021 and May 1, 2022. Data were restricted to 817 participants who reported confirmed or suspected COVID-19 to estimate the prevalence of long COVID, defined as symptoms persisting for ≥ 3 months. Ten percent of participants with a history of COVID-19 reported symptom duration consistent with long COVID, ranging from 4.8% to 12.9% across gender identities. Long COVID was most common in transmasculine and nonbinary people assigned female sex at birth. There was no evidence of an association with reported hormone therapy, supporting current recommendations that prioritize gender-affirming care during treatment for long COVID. As a condition which profoundly impacts health and productivity, long COVID is likely to exacerbate existing disparities. Principles of equity demand that we reduce barriers to prevention, diagnosis, and care for long COVID, and ensure that research and surveillance are inclusive of TNB people and disaggregate findings by gender identity.

Abstract Cellular biology occurs through myriad interactions between diverse molecular components, many of which assemble in to specific complexes. Various techniques can provide a qualitative survey of which components are found in a given complex. However, quantitative analysis of the absolute number of molecules within a complex (known as stoichiometry) remains challenging. Here we provide a novel method that combines fluorescence microscopy and statistical modelling to derive accurate molecular counts. We have devised a system in which batches of a given biomolecule are differentially labelled with spectrally distinct fluorescent dyes (label A or B), and mixed such that B-labelled molecules are vastly outnumbered by those with label A. Complexes, containing this component, are then simply scored as either being positive or negative for label B. The frequency of positive complexes is directly related to the stoichiometry of interaction and molecular counts can be inferred by statistical modelling. We demonstrate this method using complexes of Adenovirus particles and monoclonal antibodies, achieving counts that are in excellent agreement with previous estimates. Beyond virology, this approach is readily transferable to other experimental systems and, therefore, provides a powerful tool for quantitative molecular biology.

Abstract Single-molecule localisation microscopy (SMLM) allows the localisation of fluorophores with a precision of 10–30 nm, revealing the cell’s nanoscale architecture at the molecular level. Recently, SMLM has been extended to 3D, providing a unique insight into cellular machinery. Although cluster analysis techniques have been developed for 2D SMLM data sets, few have been applied to 3D. This lack of quantification tools can be explained by the relative novelty of imaging techniques such as interferometric photo-activated localisation microscopy (iPALM). Also, existing methods that could be extended to 3D SMLM are usually subject to user defined analysis parameters, which remains a major drawback. Here, we present a new open source cluster analysis method for 3D SMLM data, free of user definable parameters, relying on a model-based Bayesian approach which takes full account of the individual localisation precisions in all three dimensions. The accuracy and reliability of the method is validated using simulated data sets. This tool is then deployed on novel experimental data as a proof of concept, illustrating the recruitment of LAT to the T-cell immunological synapse in data acquired by iPALM providing ~10 nm isotropic resolution.

The gold standard to estimate muscle mass and quality is computed tomography (CT) scan. Lower mass and density (intramuscular fat infiltration) of skeletal muscles are markers of sarcopenia, associated with increased mortality risk, impaired physical function, and poorer prognosis across various populations and medical conditions. We aimed to describe standard reference values in healthy population, prospective kidney donors, and correlate clinical parameters to muscle mass and density. Included in the cohort 384 consecutive kidney donors. Mean age was 44.6 ± 11.5 (range 18.4-74.2), 46% were female and mean BMI was 25.6 ± 3.8 kg/m 2 . Our quantified reference values for psoas cross -sectional area (CSA) index at L3 level (males/females respectively) were 6.3 ± 1.8 and 4.8 ± 1.9 cm 2 /m 2 , and density was 46.1 ± 5 and 41 ± 5 HU at that level. Older age (standardized beta coefficient - 0.12, p = 0.04), sex (- 0.32, p < 0.001) and BMI (0.17, p = 0.002) were significantly associated with CSA index of psoas at L3. Density, however, was associated with triglycerides level (- 0.21, p < 0.001), in addition to age (- 0.22, p < 0.0001), sex (- 0.27, p < 0.001) and BMI (- 0.1, p = 0.05). Our study validates the normative values of psoas muscle mass and density in healthy individuals and suggests correlations with clinical parameters. We demonstrate the significance of measuring not only the mass of the muscle, but also its density, as it has a valid association with metabolic parameters, including BMI and lipid level, even in healthy individuals and in the normal range of the tests., (© 2024. The Author(s).)

Chronic kidney disease is associated with an increased risk for cardiovascular and bleeding events. Data regarding the effectiveness and risks of aspirin therapy for primary prevention in the high-risk group of patients with chronic kidney disease are scant and controversial. This retrospective study included patients with chronic kidney disease. Participants were divided according to aspirin use. Outcomes included non-fatal cardiovascular events, major bleeding events and all-cause mortality. Among 10,303 patients, 2169 met the inclusion criteria and 1818 were included after 1:1 propensity-score matching. Our final cohort included patients with mean age of 73.4 ± 11.6 years, estimated glomerular filtration rate of 31.5 ± 10.5 ml/min/1.73m 2 with follow up of 4.9 ± 1.5 years. There were no significant differences in all-cause mortality and bleeding events (odds ratio = 1.03, confidence interval [0.62, 1.84], p = .58 and odds ratio = 1.09, confidence interval [0.65, 1.72], p = .87 respectively). The incidence of cardiovascular events was higher in aspirin users versus non-users on univariate analysis (p < 0.01) and was comparable after controlling for possible risk-factors (OR = 1.05, CI [0.61, 3.14], p = .85). Chronic aspirin use for primary prevention of cardiovascular disease was not associated with lower mortality, cardiovascular events or increased bleeding among patients with chronic kidney disease. Those results were unexpected and should prompt further research in this field., (© 2022. The Author(s).)

Current research implicates pre- and probiotic supplementation as a potential tool for improving symptomology in physical and mental ailments, which makes it an attractive concept for clinicians and consumers alike. Here we focus on the transitional period of late adolescence and early adulthood during which effective interventions, such as nutritional supplementation to influence the gut microbiota, have the potential to offset health-related costs in later life. We examined multiple indices of mood and well-being in 64 healthy females in a 4-week double blind, placebo controlled galacto-oligosaccharides (GOS) prebiotic supplement intervention and obtained stool samples at baseline and follow-up for gut microbiota sequencing and analyses. We report effects of the GOS intervention on self-reported high trait anxiety, attentional bias, and bacterial abundance, suggesting that dietary supplementation with a GOS prebiotic may improve indices of pre-clinical anxiety. Gut microbiota research has captured the imagination of the scientific and lay community alike, yet we are now at a stage where this early enthusiasm will need to be met with rigorous research in humans. Our work makes an important contribution to this effort by combining a psychobiotic intervention in a human sample with comprehensive behavioural and gut microbiota measures.

The Corona virus disease has significantly affected lives of people around the world. Existing quarantine policies led to large-scale lock-downs because of the slow tracking of the infection paths, and indeed we see new waves of the disease. This can be solved by contact tracing combined with efficient testing policies. Since the number of daily tests is limited, it is crucial to exploit them efficiently to improve the outcome of contact tracing (technological or human-based epidemiological investigations). We develop a controlled testing framework to achieve this goal. The key is to test individuals with high probability of being infected to identify them before symptoms appear. These probabilities are updated based on contact tracing and test results. We demonstrate that the proposed method could reduce the quarantine and morbidity rates compared to existing methods by up to a 50%. The results clearly demonstrate the necessity of accelerating the epidemiological investigations by using technological contact tracing. Furthermore, proper use of the testing capacity using the proposed controlled testing methodology leads to significantly improved results under both small and large testing capacities. We also show that for small new outbreaks controlled testing can prevent the large spread of new waves. Author contributions statement: The authors contributed equally to this work, including conceptualization, analysis, methodology, software, and drafting the work.

Low bone mass and an increased risk of fracture are predictors of osteoporosis. Individuals who share the same bone-mineral density (BMD) vary in their fracture risk, suggesting that microstructural architecture is an important determinant of skeletal strength. Here, we utilized the rich diversity of the Collaborative Cross mice to identify putative causal genes that contribute to the risk of fractures. Using microcomputed tomography, we examined key structural features that pertain to bone quality in the femoral cortical and trabecular compartments of male and female mice. We estimated the broad-sense heritability to be 50-60% for all examined traits, and we identified five quantitative trait loci (QTL) significantly associated with six traits. We refined each QTL by combining information inferred from the ancestry of the mice, ranging from RNA-Seq data and published literature to shortlist candidate genes. We found strong evidence for new candidate genes, particularly Rhbdf2, whose close association with the trabecular bone volume fraction and number was strongly suggested by our analyses. We confirmed our findings with mRNA expression assays of Rhbdf2 in extreme-phenotype mice, and by phenotyping bones of Rhbdf2 knockout mice. Our results indicate that Rhbdf2 plays a decisive role in bone mass accrual and microarchitecture.

Ovarian cancer is a highly aggressive disease and novel treatments are required. Thyroid hormones binding to αvβ3 integrin produced growth-promoting activities in ovarian cancer and we hypothesized that natural thyroid hormone derivatives may antagonize these actions. The effect of three antagonists, tetraiodoacetic acid (tetrac), triiodothyroacetic acid (triac) and 3-iodothyronamine (T1AM), on cell proliferation, cell death and DNA damage was studied in two ovarian cancer cell lines (OVCAR3 and A2780), normal hamster ovary control cells (CHOK1) and αvβ3-deficient or transfected HEK293 cells. A differential inhibition of cell proliferation was observed in ovarian cancer cells compared to CHOK1. In OVCAR3, an induction of cell cycle regulators was further shown. Apoptosis was confirmed (annexin-PI, SubG1/cell-cycle, apoptotic genes, caspase-3 and poly ADP ribose polymerase-1 (PARP-1) cleavage) and was reversed by a pan-caspase inhibitor. Induction in apoptosis inducing factor (AIF) was observed, suggesting a parallel caspase-independent mechanism. Integrin-involvement in triac/T1AM apoptotic action was shown in αvβ3-transfected HEK293 cells. Lastly, in ovarian cancer models, key proteins that coordinate recognition of DNA damage, ataxia-telangiectasia mutated (ATM) and PARP-1, were induced. To conclude, the cytotoxic potential of thyroid hormone derivatives, tetrac, triac and T1AM, in ovarian cancer may provide a much-needed novel therapeutic approach.

The metastable-to-stable phase-transition is commonly observed in many fields of science, as an uncontrolled independent process, highly sensitive to microscopic fluctuations. In particular, self-assembled lipid suspensions exhibit phase-transitions, where the underlying driving mechanisms and dynamics are not well understood. Here we describe a study of the phase-transition dynamics of lipid-based particles, consisting of mixtures of dilauroylphosphatidylethanolamine (DLPE) and dilauroylphosphatidylglycerol (DLPG), exhibiting a metastable liquid crystalline-to-stable crystalline phase transition upon cooling from 60°C to 37°C. Surprisingly, unlike classically described metastable-to-stable phase transitions, the manner in which recrystallization is delayed by tens of hours is robust, predetermined and controllable. Our results show that the delay time can be manipulated by changing lipid stoichiometry, changing solvent salinity, adding an ionophore, or performing consecutive phase-transitions. Moreover, the delay time distribution indicates a deterministic nature. We suggest that the non-stochastic physical mechanism responsible for the delayed recrystallization involves several rate-affecting processes, resulting in a controllable, non-independent metastability. A qualitative model is proposed to describe the structural reorganization during the phase transition.