Cystamine, a small disulfide‐containing chemical, is neuroprotective in a transgenic mouse and a Drosophila model of Huntington's disease (HD) and decreases huntingtin aggregates in an in vitro model ...of HD. The mechanism of action of cystamine in these models is widely thought to involve inhibition of transglutaminase mediated cross‐linking of mutant huntingtin in the process of aggregate formation/stabilization. In this study we show that cystamine, both in vitro and in a transgenic mouse model of HD (R6/2), increases levels of the cellular antioxidant l‐cysteine. Several oxidative stress markers increase in HD brain. We provide further evidence of oxidative stress in mouse HD by demonstrating compensatory responses in R6/2 HD brains. We found age‐dependent increases in forebrain glutathione (GSH), and increased levels of transcripts coding for proteins involved in GSH synthesis and detoxification pathways, as revealed by quantitative PCR analysis. Given the general importance of oxidative stress as a mediator of neurodegeneration we propose that an increase in brain l‐cysteine levels could be protective in HD. Furthermore, cystamine was dramatically protective against 3‐nitropropionic acid‐induced striatal injury in mice. We suggest that cystamine's neuroprotective effect in HD transgenic mice results from pleiotropic effects that include transglutaminase inhibition and antioxidant activity.
This virtual workshop was convened by the National Heart, Lung, and Blood Institute, in partnership with the Office of Strategic Coordination of the Office of the National Institutes of Health ...Director, and held September 2 to 3, 2020. The intent was to assemble a multidisciplinary group of experts in basic, translational, and clinical research in neuroscience and cardiopulmonary disorders to identify knowledge gaps, guide future research efforts, and foster multidisciplinary collaborations pertaining to autonomic neural mechanisms of cardiopulmonary regulation. The group critically evaluated the current state of knowledge of the roles that the autonomic nervous system plays in regulation of cardiopulmonary function in health and in pathophysiology of arrhythmias, heart failure, sleep and circadian dysfunction, and breathing disorders. Opportunities to leverage the Common Fund's SPARC (Stimulating Peripheral Activity to Relieve Conditions) program were characterized as related to nonpharmacologic neuromodulation and device-based therapies. Common themes discussed include knowledge gaps, research priorities, and approaches to develop novel predictive markers of autonomic dysfunction. Approaches to precisely target neural pathophysiological mechanisms to herald new therapies for arrhythmias, heart failure, sleep and circadian rhythm physiology, and breathing disorders were also detailed.
Purpose of Review
Many patients treated for cancer develop toxicities that go unaddressed, limiting their functioning, health, quality of life, and ability to work. This review describes how to ...optimize patient functioning and quality of life by preventing toxicities where possible or treating them early to reduce impairment and prevent disability.
Recent Findings
Increasing the impact of cancer rehabilitation on preventing and treating toxicity requires filling research gaps and better integrating rehabilitation with cancer care.
Summary
We must understand risk factors and the underlying biology driving impairments, disability, and individual response to intervention. Then, we need to integrate these data and implement screening of all patients throughout treatment and beyond to (1) monitor biological changes that would lead to downstream impairments and facilitate referrals for personalized rehabilitation interventions to prevent these; (2) where prevention is impossible, screen for impairments and prescribe interventions to treat them early; or (3) intervene to prevent disability resulting from impairments that cannot be prevented or treated.
•The ANS is a key regulator of cardiopulmonary health and disease and sleep/circadian pathophysiology.•Understanding cardiopulmonary sympathetic and parasympathetic nerve structure/function over ...disease time-course and cell type interactions is essential.•In vitro autonomic nervous system and experimental and computational integrative studies are necessary.•Clarifying sex-and race-specific cardiopulmonary and sleep/circadian influence on autonomic nerve function in response to neurotherapeutic interventions is critical to inform personalized strategies.
This virtual workshop was convened by the National Heart, Lung, and Blood Institute, in partnership with the Office of Strategic Coordination of the Office of the National Institutes of Health Director, and held September 2 to 3, 2020. The intent was to assemble a multidisciplinary group of experts in basic, translational, and clinical research in neuroscience and cardiopulmonary disorders to identify knowledge gaps, guide future research efforts, and foster multidisciplinary collaborations pertaining to autonomic neural mechanisms of cardiopulmonary regulation. The group critically evaluated the current state of knowledge of the roles that the autonomic nervous system plays in regulation of cardiopulmonary function in health and in pathophysiology of arrhythmias, heart failure, sleep and circadian dysfunction, and breathing disorders. Opportunities to leverage the Common Fund’s SPARC (Stimulating Peripheral Activity to Relieve Conditions) program were characterized as related to nonpharmacologic neuromodulation and device-based therapies. Common themes discussed include knowledge gaps, research priorities, and approaches to develop novel predictive markers of autonomic dysfunction. Approaches to precisely target neural pathophysiological mechanisms to herald new therapies for arrhythmias, heart failure, sleep and circadian rhythm physiology, and breathing disorders were also detailed.
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New York State (NYS) is an epicenter of the SARS-CoV-2 pandemic in the United States. Reliable estimates of cumulative incidence in the population are critical to tracking the extent of transmission ...and informing policies.
We conducted a statewide seroprevalence study in a 15,101 patron convenience sample at 99 grocery stores in 26 counties throughout NYS. SARS-CoV-2 cumulative incidence was estimated from antibody reactivity by first poststratification weighting and then adjusting by antibody test characteristics. The percent diagnosed was estimated by dividing the number of diagnoses by the number of estimated infection-experienced adults.
Based on 1887 of 15,101 (12.5%) reactive results, estimated cumulative incidence through March 29 was 14.0% (95% confidence interval CI: 13.3%–14.7%), corresponding to 2,139,300 (95% CI: 2,035,800–2,242,800) infection-experienced adults. Cumulative incidence was highest in New York City 22.7% (95% CI: 21.5%–24.0%) and higher among Hispanic/Latino (29.2%), non-Hispanic black/African American (20.2%), and non-Hispanic Asian (12.4%) than non-Hispanic white adults (8.1%, P < .0001). An estimated 8.9% (95% CI: 8.4%–9.3%) of infections in NYS were diagnosed, with diagnosis highest among adults aged 55 years or older (11.3%, 95% CI: 10.4%–12.2%).
From the largest U.S. serosurvey to date, we estimated >2 million adult New York residents were infected through late March, with substantial disparities, although cumulative incidence remained less than herd immunity thresholds. Monitoring, testing, and contact tracing remain essential public health strategies.
Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect millions of people worldwide each year. This time-consuming ...task typically requires expert radiologists to read the images, leading to fatigue-based diagnostic error and lack of diagnostic expertise in areas of the world where radiologists are not available. Recently, deep learning approaches have been able to achieve expert-level performance in medical image interpretation tasks, powered by large network architectures and fueled by the emergence of large labeled datasets. The purpose of this study is to investigate the performance of a deep learning algorithm on the detection of pathologies in chest radiographs compared with practicing radiologists.
We developed CheXNeXt, a convolutional neural network to concurrently detect the presence of 14 different pathologies, including pneumonia, pleural effusion, pulmonary masses, and nodules in frontal-view chest radiographs. CheXNeXt was trained and internally validated on the ChestX-ray8 dataset, with a held-out validation set consisting of 420 images, sampled to contain at least 50 cases of each of the original pathology labels. On this validation set, the majority vote of a panel of 3 board-certified cardiothoracic specialist radiologists served as reference standard. We compared CheXNeXt's discriminative performance on the validation set to the performance of 9 radiologists using the area under the receiver operating characteristic curve (AUC). The radiologists included 6 board-certified radiologists (average experience 12 years, range 4-28 years) and 3 senior radiology residents, from 3 academic institutions. We found that CheXNeXt achieved radiologist-level performance on 11 pathologies and did not achieve radiologist-level performance on 3 pathologies. The radiologists achieved statistically significantly higher AUC performance on cardiomegaly, emphysema, and hiatal hernia, with AUCs of 0.888 (95% confidence interval CI 0.863-0.910), 0.911 (95% CI 0.866-0.947), and 0.985 (95% CI 0.974-0.991), respectively, whereas CheXNeXt's AUCs were 0.831 (95% CI 0.790-0.870), 0.704 (95% CI 0.567-0.833), and 0.851 (95% CI 0.785-0.909), respectively. CheXNeXt performed better than radiologists in detecting atelectasis, with an AUC of 0.862 (95% CI 0.825-0.895), statistically significantly higher than radiologists' AUC of 0.808 (95% CI 0.777-0.838); there were no statistically significant differences in AUCs for the other 10 pathologies. The average time to interpret the 420 images in the validation set was substantially longer for the radiologists (240 minutes) than for CheXNeXt (1.5 minutes). The main limitations of our study are that neither CheXNeXt nor the radiologists were permitted to use patient history or review prior examinations and that evaluation was limited to a dataset from a single institution.
In this study, we developed and validated a deep learning algorithm that classified clinically important abnormalities in chest radiographs at a performance level comparable to practicing radiologists. Once tested prospectively in clinical settings, the algorithm could have the potential to expand patient access to chest radiograph diagnostics.
: Sequential pharmacokinetic assessments were performed at five centers within the context of a multicenter, single‐blind, randomized clinical trial comparing the efficacy and safety of ...enteric‐coated mycophenolate sodium (EC‐MPS, myfortic®) and mycophenolate mofetil (MMF, CellCept®) in de novo heart transplant recipients. Patients were randomized to either EC‐MPS 1080 mg bid or MMF 1500 mg bid, as part of a triple immunosuppressive therapy including cyclosporine microemulsion. Steady‐state pharmacokinetic profiles of mycophenolic acid (MPA) and its inactive phenolic glucuronide (MPAG) were assessed at weeks 2, 12, and 52. Pharmacokinetic parameters were evaluated in 32 patients (17 on EC‐MPS and 15 on MMF). Dose‐normalized peak (Cmax,ss) and area under the curve (AUCτ,ss) of MPA and MPAG increased between week 2 and week 12 assessments for both treatments. Comparisons between EC‐MPS and MMF showed no statistically significant differences in MPA and MPAG AUCτ,ss, Cmax,ss, and trough (Cmin,ss) values (p‐values ranged from 0.225 to 0.990). Consistent with the delayed release characteristics of EC‐MPS, Cmax,ss occurred approximately one hour later compared with MMF. Inter‐subject coefficients of variation (%CV) for MPA pharmacokinetic parameters of both EC‐MPS and MMF were high (37–72% for AUCτ,ss at weeks 2 and 12). Also within patients, the pharmacokinetics of MPA varied considerably. Specifically, intra‐subject %CVs for MPA AUCτ,ss, Cmax,ss, and Cmin,ss were 28%, 63%, and 34% with EC‐MPS and 54%, 139%, and 41% with MMF respectively. These results indicate that a dose of EC‐MPS 1080 mg bid in combination with cyclosporine provides adequate systemic MPA exposure in de novo heart transplant patients, comparable with MMF 1500 mg bid. Overall, there is a large inter‐ and intra‐subject variability in MPA pharmacokinetic parameters with both treatments.
The oldest stars in the Milky Way (born in the first few billion years) are expected to have a high density in the inner few kpc, spatially overlapping with the Galactic bulge. We use spectroscopic ...data from the Pristine Inner Galaxy Survey (PIGS) to study the dynamical properties of ancient, metal-poor inner Galaxy stars. We compute distances using StarHorse, and orbital properties in a barred Galactic potential. With this paper, we release the spectroscopic AAT/PIGS catalogue (13 235 stars). We find that most PIGS stars have orbits typical for a pressure-supported population. The fraction of stars confined to the inner Galaxy decreases with decreasing metallicity, but many very metal-poor stars (VMP, Fe/H < -2.0) stay confined (~ 60% stay within 5 kpc). The azimuthal velocity v\(_\phi\) also decreases between Fe/H = -1.0 and -2.0, but is constant for VMP stars (at ~ 40 km/s). The carbon-enhanced metal-poor (CEMP) stars in PIGS appear to have similar orbital properties compared to normal VMP stars. Our results suggest a possible transition between two spheroidal components - a more metal-rich, more concentrated, faster rotating component, and a more metal-poor, more extended and slower/non-rotating component. We propose that the former may be connected to pre-disc in-situ stars (or those born in large building blocks), whereas the latter may be dominated by contributions from smaller galaxies. This is an exciting era where large metal-poor samples, such as in this work (as well as upcoming surveys, e.g., 4MOST), shed light on the earliest evolution of our Galaxy.
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