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This study piloted the use of ACT-informed exposure as an adjunct to habit reversal training (HRT) for excoriation disorder (ExD). Using a nonconcurrent multiple baseline single case design, four participants completed sessions of exposure and HRT. Repeated measures and self-report data were collected on skin picking and psychological flexibility. Two participants completed HRT followed by exposure, and two participants completed exposure followed by HRT. Results support the effectiveness of HRT in reducing picking. Results suggest exposure may have some impact in reducing picking, but effects were weaker compared to HRT. Contrary to predictions, repeated measures and self-report data did not indicate consistent improvement in psychological flexibility during exposure phases. As any reduction in picking may be clinically meaningful and all participants maintained gains at follow-up, there is some indication that exposure may be a second-line treatment worth further study. Limitations and future areas of research are discussed.

MotivationHigh-dimension cytometry assays can simultaneously measure dozens of markers, enabling the investigation of complex phenotypes. However, as manual gating relies on previous biological knowledge, few marker combinations are often assessed. This results in complex phenotypes with potential for biological relevance being overlooked. Here we present PhenoComb, an R package that allows agnostic exploration of phenotypes by assessing all combinations of markers.DesignPhenoComb uses signal intensity thresholds to assign markers to discrete states (e.g. negative, low, high) and then counts the number of cells per sample from all possible marker combinations in a memory-safe manner. Time and disk space are the only constraints on the number of markers evaluated. PhenoComb also provides several approaches to perform statistical comparisons, evaluate the relevance of phenotypes, and assess the independence of identified phenotypes. PhenoComb allows users to guide analysis by adjusting several function arguments such as identifying parent populations of interest, filtering of low-frequency populations, and defining a maximum complexity of phenotypes to evaluate. We have designed PhenoComb to be compatible with local computer or server-based use.ResultsIn testing of PhenoComb’s performance on synthetic datasets, computation on 16 markers was completed in the scale of minutes and up to 26 markers in hours. We applied PhenoComb to two publicly available datasets: an HIV flow cytometry dataset (12 markers and 421 samples) and the COVIDome CyTOF dataset (40 markers and 99 samples). In the HIV dataset, PhenoComb identified immune phenotypes associated with HIV seroconversion, including those highlighted in the original publication. In the COVID dataset, we identified several immune phenotypes with altered frequencies in infected individuals relative to healthy individuals. Collectively, PhenoComb represents a powerful discovery tool for agnostically assessing high-dimension, single-cell data.AvailabilityThe PhenoComb R package can be downloaded from https://github.com/SciOmicsLab/PhenoComb

We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produced titles. This is the first such large-scale study we are aware of. The results challenge a number of assumptions commonly made in both qualitative literature on human dubbing and machine-learning literature on automatic dubbing, arguing for the importance of vocal naturalness and translation quality over commonly emphasized isometric (character length) and lip-sync constraints, and for a more qualified view of the importance of isochronic (timing) constraints. We also find substantial influence of the source-side audio on human dubs through channels other than the words of the translation, pointing to the need for research on ways to preserve speech characteristics, as well as semantic transfer such as emphasis/emotion, in automatic dubbing systems., Comment: Accepted at TACL. pre-MIT Press publication version

Motivation High-dimensional cytometry assays can simultaneously measure dozens of markers, enabling the investigation of complex phenotypes. However, as manual gating relies on previous biological knowledge, few marker combinations are often assessed. This results in complex phenotypes with the potential for biological relevance being overlooked. Here, we present PhenoComb, an R package that allows agnostic exploration of phenotypes by assessing all combinations of markers. PhenoComb uses signal intensity thresholds to assign markers to discrete states (e.g. negative, low, high) and then counts the number of cells per sample from all possible marker combinations in a memory-safe manner. Time and disk space are the only constraints on the number of markers evaluated. PhenoComb also provides several approaches to perform statistical comparisons, evaluate the relevance of phenotypes and assess the independence of identified phenotypes. PhenoComb allows users to guide analysis by adjusting several function arguments, such as identifying parent populations of interest, filtering of low-frequency populations and defining a maximum complexity of phenotypes to evaluate. We have designed PhenoComb to be compatible with a local computer or server-based use. Results In testing of PhenoComb’s performance on synthetic datasets, computation on 16 markers was completed in the scale of minutes and up to 26 markers in hours. We applied PhenoComb to two publicly available datasets: an HIV flow cytometry dataset (12 markers and 421 samples) and the COVIDome CyTOF dataset (40 markers and 99 samples). In the HIV dataset, PhenoComb identified immune phenotypes associated with HIV seroconversion, including those highlighted in the original publication. In the COVID dataset, we identified several immune phenotypes with altered frequencies in infected individuals relative to healthy individuals. Collectively, PhenoComb represents a powerful discovery tool for agnostically assessing high-dimensional single-cell data. Availability and implementation The PhenoComb R package can be downloaded from https://github.com/SciOmicsLab/PhenoComb. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Clinical trials during public health emergencies of novel medical products such as therapeutics and vaccines in resource-limited settings are daunting due to the limited capacity for regulatory assessment. Regulating clinical trials during the Ebola outbreak in Sierra Leone required expedited evaluation to identify medical products that could be promptly introduced to combat the epidemic in the absence of approved treatment or prevention. This article explored the decisions taken by the Pharmacy Board of Sierra Leone through its Expert Committee on Medicine Safety and Clinical Trials regarding clinical trials oversight during the Ebola epidemic and the lessons learned. This independent expert committee assessed and provided scientific opinions to the Pharmacy Board of Sierra Leone to inform approval of all clinical trials within 10–15 working days. We also requested for assisted review from the African Vaccine Regulatory Forum and support from the US Food and Drug Administration through a unilateral recognition and reliance memorandum of understanding. In addition, the Agency-ensured structures and systems were in place for reporting and reviewing adverse events and serious adverse events, management of biological samples, submission and review of progress reports, and good clinical practice inspections. Unfortunately, the Ebola epidemic revealed many weaknesses in the country’s clinical trials regulatory structure and processes. Government and partners should further offer more resources to build the clinical trial structures and systems so that the Agency will be better poised to handle future public health emergencies.

The optimum target for systolic and diastolic blood pressure remains divisive. In particular, the conflicting outcomes of the SPRINT and ACCORD trials have led to a divergence of guideline-recommended blood pressure targets for adults with diabetes.Here, we review the existing recommendations for blood pressure targets in diabetes, discussing the evidence base behind them and their limitations. We start by outlining the risks and benefits of lower systolic blood pressure targets among diabetics. We then follow with a separate appraisal of diastolic blood pressure targets, which necessitates examination of the 'J curve' and isolated diastolic hypertension.Current and emerging evidence supports, on balance, a blood pressure therapeutic target of130/90 mmHg in adults at increased risk for cardiovascular disease, including diabetics. Whether certain diabetics with systolic BPs of 120-130 and/or diastolic BPs 80-90 mmHg require drug treatment to a target of120/80 mmHg is less clear and requires more research.

To estimate the prevalence of metabolic syndrome (MS) and metabolic components and their associated factors and component combinations according to hypertension status in Tibetans living at high altitude. Multistage sampling of 1473 participants (799 hypertensive patients and 674 normotensive subjects). MS prevalence and the number of metabolic components ≥ 3 were significantly higher in the hypertensive than normotensives. In hypertensive patients, the most common component was central obesity and it combined with: high blood pressure, in those with 2 risk factors, plus fasting hyperglycemia, in those with 3 risk factors, and high triglyceride, in those with 4 risk factors. In normotensive subjects, the most common single component was low high-density-lipoprotein cholesterol, and most component combination included central obesity and hyperglycemia in those with 2 risk factors, plus high blood pressure in those with 3 risk factors, and high triglycerides in those with 4 risk factors. Body mass index and female both were associated with increased possibilities of MS in hypertensive and normotensive participants. Low incoming, and high educational levels were associated with an elevated probability of MS in normotensive Tibetans also. The priority of prevention from cardiovascular diseases by targeting metabolic components in the hypertensive was different from normotensives. Different MS components had various lifestyle and socioeconomic factors.

Recent reports have challenged the notion that the lens is immune-privileged. However, these studies have not fully identified the molecular mechanism(s) that promote immune surveillance of the lens. Using a mouse model of targeted glutathione (GSH) deficiency in ocular surface tissues, we have investigated the role of oxidative stress in upregulating cytokine expression and promoting immune surveillance of the eye. RNA-sequencing of lenses from postnatal day (P) 1-aged Gclc(f/f);Le-Cre(Tg/-) (KO) and Gclc(f/f);Le-Cre(−/−) control (CON) mice revealed upregulation of many cytokines (e.g., CCL4, GDF15, CSF1) and immune response genes in the lenses of KO mice. The eyes of KO mice had a greater number of cells in the aqueous and vitreous humors at P1, P20 and P50 than age-matched CON and Gclc(w/w);Le-Cre(Tg/-) (CRE) mice. Histological analyses revealed the presence of innate immune cells (i.e., macrophages, leukocytes) in ocular structures of the KO mice. At P20, the expression of cytokines and ROS content was higher in the lenses of KO mice than in those from age-matched CRE and CON mice, suggesting that oxidative stress may induce cytokine expression. In vitro administration of the oxidant, hydrogen peroxide, and the depletion of GSH (using buthionine sulfoximine (BSO)) in 21EM15 lens epithelial cells induced cytokine expression, an effect that was prevented by co-treatment of the cells with N-acetyl-L-cysteine (NAC), a antioxidant. The in vivo and ex vivo induction of cytokine expression by oxidative stress was associated with the expression of markers of epithelial-to-mesenchymal transition (EMT), α-SMA, in lens cells. Given that EMT of lens epithelial cells causes posterior capsule opacification (PCO), we propose that oxidative stress induces cytokine expression, EMT and the development of PCO in a positive feedback loop. Collectively these data indicate that oxidative stress induces inflammation of lens cells which promotes immune surveillance of ocular structures.