Notes

Style of Hierarchical NiCo2O4 Nanocages along with Outstanding Electrocatalytic Vibrant regarding Enhanced Methanol Oxidation.
Modern machine learning techniques (such as deep learning) offer immense opportunities in the field of human biological aging research. Aging is a complex process, experienced by all living organisms. While traditional machine learning and data mining approaches are still popular in aging research, they typically need feature engineering or feature extraction for robust performance. Explicit feature engineering represents a major challenge, as it requires significant domain knowledge. The latest advances in deep learning provide a paradigm shift in eliciting meaningful knowledge from complex data without performing explicit feature engineering. In this article, we review the recent literature on applying deep learning in biological age estimation. We consider the current data modalities that have been used to study aging and the deep learning architectures that have been applied. We identify four broad classes of measures to quantify the performance of algorithms for biological age estimation and based on these evaluate the current approaches. The paper concludes with a brief discussion on possible future directions in biological aging research using deep learning. This study has significant potentials for improving our understanding of the health status of individuals, for instance, based on their physical activities, blood samples and body shapes. Thus, the results of the study could have implications in different health care settings, from palliative care to public health. © The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email [email protected] recently showed in a proof-of-concept study that real-time modeling-based response-guided therapy (RGT) can shorten hepatitis C virus (HCV) treatment duration with sofosbuvir/velpatasvir, elbasvir/grazoprevir and sofosbuvir/ledipasvir without compromising efficacy, confirming our retrospective modeling reports in more than 200 patients. However, retrospective modeling under pibrentasvir/glecaprevir (P/G) has yet to be evaluated. In the current study modeling HCV kinetics in 44 cirrhotic and non-cirrhotic patients predicts that P/G treatment might have been reduced to 4, 6 and 7 weeks in 16%, 34% and 14% of patients, respectively. These results support the further evaluation of a modeling-based RGT approach under P/G therapy. © The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail [email protected] aegypti (L.) is an important vector of viruses causing dengue, Zika, chikungunya, and yellow fever and as such presents a serious threat to public health in tropical regions. Control programs involving 'rear and release' of modified male Ae. aegypti are underway and require effective trapping methods for surveillance of both the released insects and the impacted wild mosquito population. The BG-Sentinel trap (BGS) is widely used in Ae. aegypti surveillance but its level of efficiency, that is, what proportion of the mosquitoes encountering the trap are captured, is unknown. This is especially true for male mosquitoes, the behavior of which is incompletely understood. We tested the efficiency of two versions of the BGS for capturing male Ae. aegypti under semifield conditions with and without CO2 and a human skin odor mimic lure and with these baits combined. A navy-blue BGS trap emitting CO2 and a human skin odor mimic captured 18% of the released male Ae. aegypti, with a capture efficiency of 9 % (of the total encounters with the trap). Male Ae. aegypti had multiple encounters with the BGS that did not result in capture; they crossed over the trap entrance without being captured or landed on the sides of the trap. Swarming behavior around the BGS was also recorded, even when only a visual cue was present. Understanding male Ae. aegypti behaviors during an encounter with the BGS can inform improvement of trap design and therefore capture efficiency for surveillance in control programs. Published by Oxford University Press on behalf of Entomological Society of America 2020.AIMS Ethanol is a small molecule capable of interacting with numerous targets in the brain, the mechanisms of which are complex and still poorly understood. Studies have revealed that ethanol-induced hippocampal neuronal injury is associated with oxidative stress. Grape seed procyanidin (GSP) is a new type of antioxidant that is believed to scavenge free radicals and be anti-inflammatory. This study evaluated the ability and mechanism by which the GSP improves ethanol-induced hippocampal neuronal injury. BB-2516 datasheet METHODS Primary cultures of hippocampal neurons were exposed to ethanol (11, 33 and 66 mM, 1, 4, 8, 12 and 24 h) and the neuroprotective effects of GSP were assessed by evaluating the activity of superoxide dismutase (SOD), the levels of malondialdehyde (MDA) and lactate dehydrogenase (LDH) and cell morphology. RESULTS Our results indicated that GSP prevented ethanol-induced neuronal injury by reducing the levels of MDA and LDH, while increasing the activity of SOD. In addition, GSP increased the number of primary dendrites and total dendritic length per cell. CONCLUSION Together with previous findings, these results lend further support to the significance of developing GSP as a therapeutic tool for use in the treatment of alcohol use disorders. © The Author(s) 2020. Medical Council on Alcohol and Oxford University Press. All rights reserved. For permissions, please e-mail [email protected] current emergence of the novel coronavirus pandemic caused by SARS-CoV-2 demands the development of new therapeutic strategies to prevent rapid progress of mortalities. The coronavirus spike (S) protein, which facilitates viral attachment, entry and membrane fusion is heavily glycosylated and plays a critical role in the elicitation of the host immune response. The spike protein is comprised of two protein subunits (S1 and S2), which together possess 22 potential N-glycosylation sites. Herein, we report the glycosylation mapping on spike protein subunits S1 and S2 expressed on human cells through high resolution mass spectrometry. We have characterized the quantitative N-glycosylation profile on spike protein and interestingly, observed unexpected O-glycosylation modifications on the receptor binding domain (RBD) of spike protein subunit S1. Even though O-glycosylation has been predicted on the spike protein of SARS-CoV-2, this is the first report of experimental data for both the site of O-glycosylation and identity of the O-glycans attached on the subunit S1.
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