Notes

Novel technique of microalgae mobile disruption as well as wet fat elimination by utilizing electro-Fenton method using sacrificial metal anode.
In light of the recent accumulated knowledge on SARS-CoV-2 and its mode of human cells invasion, the binding of viral spike glycoprotein to human Angiotensin Converting Enzyme 2 (hACE2) receptor plays a central role in cell entry. We designed a series of peptides mimicking the N-terminal helix of hACE2 protein which contains most of the contacting residues at the binding site, exhibiting a high helical folding propensity in aqueous solution. Our best peptide-mimics are able to block SARS-CoV-2 human pulmonary cell infection with an inhibitory concentration (IC50) in the nanomolar range upon binding to the virus spike protein with high affinity. These first-in-class blocking peptide mimics represent powerful tools that might be used in prophylactic and therapeutic approaches to fight the coronavirus disease 2019 (COVID-19).'Microbial terroir' relates to the influence of autochthonous yeasts associated with a grape cultivar on the resultant wine. Geographic region, vineyard site and topography, climate and vintage influence the biodiversity of these microbial communities. Current research focus attempts to correlate their 'microbial fingerprint' to the sensorial and chemical characteristics of varietal wines from distinct geographical wine regions. This study focuses on the minor red grape variety, Negro Saurí, which has seen a resurgence in the León Appellation of Origin in Spain as a varietal wine. An experimental vineyard at Melgarajo S.A. (42° 15' 48.68_N 5° 9' 56.66_W) was sampled over four consecutive vintages, with autochthonous yeasts being isolated from grapes, must and pilot-scale un-inoculated fermentations, and identified by ITS sequencing. Forty-nine isolates belonging to Metschnikowia pulcherrima, Lachancea thermotolerans, Hanseniaspora uvarum and Torulaspora delbrueckii were isolated from grapes and must, and early stages of fermentation dependent on seasonal variation. Saccharomyces cerevisiae predominated throughout fermentation, as a heterogeneous and dynamic population, with seven major biotypes identified amongst 110 isolates across four consecutive vintages. Twenty-four S. cerevisiae isolates representing five strains dominated in two or more vintages. PF-04418948 in vitro Their persistence through fermentation warrants further validation of their oenological properties as starter cultures.Hyperamylinemia induces amylin aggregation and toxicity in the pancreas and contributes to the development of type-2 diabetes (T2D). Cardiac amylin deposition in patients with obesity and T2D was found to accelerate heart dysfunction. Non-human primates (NHPs) have similar genetic, metabolic, and cardiovascular processes as humans. However, the underlying mechanisms of cardiac amylin in NHPs, particularly related to the hypoxia inducible factor (HIF)1α and 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) signaling pathways, are unknown. Here, we demonstrate that in NHPs, amylin deposition in heart failure (HF) contributes to cardiac dysfunction via activation of HIF1α and PFKFB3 signaling. This was confirmed in two in vitro cardiomyocyte models. Furthermore, alterations of intracellular Ca2+, reactive oxygen species, mitochondrial function, and lactate levels were observed in amylin-treated cells. Our study demonstrates a pathological role for amylin in the activation of HIF1α and PFKFB3 signaling in NHPs with HF, establishing amylin as a promising target for heart disease patients.Functional diversity rather than species richness is critical for the understanding of ecological patterns and processes. This study aimed to develop novel integrated analytical strategies for the functional characterization of fish diversity based on the quantification, prediction and integration of the chemical and physical features in fish muscles. Machine learning models with an improved random forest algorithm applied on 1867 muscle nuclear magnetic resonance spectra belonging to 249 fish species successfully predicted the mobility patterns of fishes into four categories (migratory, territorial, rockfish, and demersal) with accuracies of 90.3-95.4%. Markov blanket-based feature selection method with an ecological-chemical-physical integrated network based on the Bayesian network inference algorithm highlighted the importance of nitrogen metabolism, which is critical for environmental adaptability of fishes in nutrient-rich environments, in the functional characterization of fish biodiversity. Our study provides valuable information and analytical strategies for fish home-range assessment on the basis of the chemical and physical characterization of fish muscle, which can serve as an ecological indicator for fish ecotyping and human impact monitoring.Lung cancer is the leading cause of death worldwide. Especially, non-small cell lung cancer (NSCLC) has higher mortality rate than the other cancers. The high mortality rate is partially due to lack of efficient biomarkers for detection, diagnosis and prognosis. To find high efficient biomarkers for clinical diagnosis of NSCLC patients, we used gene differential expression and gene ontology (GO) to define a set of 26 tumor suppressor (TS) genes. link2 The 26 TS genes were down-expressed in tumor samples in cohorts GSE18842, GSE40419, and GSE21933 and at stages 2 and 3 in GSE19804, and 15 TS genes were significantly down-expressed in tumor samples of stage 1. We used S-scores and N-scores defined in correlation networks to evaluate positive and negative influences of these 26 TS genes on expression of other functional genes in the four independent cohorts and found that SASH1, STARD13, CBFA2T3 and RECK were strong TS genes that have strong accordant/discordant effects and network effects globally impacting the other genes in expression and hence can be used as specific biomarkers for diagnosis of NSCLC cancer. Weak TS genes EXT1, PTCH1, KLK10 and APC that are associated with a few genes in function or work in a special pathway were not detected to be differentially expressed and had very small S-scores and N-scores in all collected datasets and can be used as sensitive biomarkers for diagnosis of early cancer. Our findings are well consistent with functions of these TS genes. GSEA analysis found that these 26 TS genes as a gene set had high enrichment scores at stages 1, 2, 3 and all stages.Active visual scanning of the scene is a key task-element in all forms of human locomotion. In the field of driving, steering (lateral control) and speed adjustments (longitudinal control) models are largely based on drivers' visual inputs. Despite knowledge gained on gaze behaviour behind the wheel, our understanding of the sequential aspects of the gaze strategies that actively sample that input remains restricted. Here, we apply scan path analysis to investigate sequences of visual scanning in manual and highly automated simulated driving. Five stereotypical visual sequences were identified under manual driving forward polling (i.e. far road explorations), guidance, backwards polling (i.e. near road explorations), scenery and speed monitoring scan paths. Previously undocumented backwards polling scan paths were the most frequent. link3 Under highly automated driving backwards polling scan paths relative frequency decreased, guidance scan paths relative frequency increased, and automation supervision specific scan paths appeared. The results shed new light on the gaze patterns engaged while driving. Methodological and empirical questions for future studies are discussed.The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this study, we propose a new estimator with some biasing parameters to estimate the regression coefficients for the PRM when there is multicollinearity problem. Some simulation experiments are conducted to compare the estimators' performance by using the mean squared error (MSE) criterion. For illustration purposes, aircraft damage data has been analyzed. The simulation results and the real-life application evidenced that the proposed estimator performs better than the rest of the estimators.A novel motion correction algorithm for X-ray lung CT imaging has been developed recently. It was designed to perform for routine chest or thorax CT scans without gating, namely axial or helical scans with pitch around 1.0. The algorithm makes use of two conjugate partial angle reconstruction images for motion estimation via non-rigid registration which is followed by a motion compensated reconstruction. Differently from other conventional approaches, no segmentation is adopted in motion estimation. This makes motion estimation of various fine lung structures possible. The aim of this study is to explore the performance of the proposed method in correcting the lung motion artifacts which arise even under routine CT scans with breath-hold. The artifacts are known to mimic various lung diseases, so it is of great interest to address the problem. For that purpose, a moving phantom experiment and clinical study (seven cases) were conducted. We selected the entropy and positivity as figure of merits to compare the reconstructed images before and after the motion correction. Results of both phantom and clinical studies showed a statistically significant improvement by the proposed method, namely up to 53.6% (p less then 0.05) and up to 35.5% (p less then 0.05) improvement by means of the positivity measure, respectively. Images of the proposed method show significantly reduced motion artifacts of various lung structures such as lung parenchyma, pulmonary vessels, and airways which are prominent in FBP images. Results of two exemplary cases also showed great potential of the proposed method in correcting motion artifacts of the aorta which is known to mimic aortic dissection. Compared to other approaches, the proposed method provides an excellent performance and a fully automatic workflow. In addition, it has a great potential to handle motions in wide range of organs such as lung structures and the aorta. We expect that this would pave a way toward innovations in chest and thorax CT imaging.In the fight to limit the global spread of antibiotic resistance, the assembly of environmental metagenomes has the potential to provide rich contextual information (e.g., taxonomic hosts, carriage on mobile genetic elements) about antibiotic resistance genes (ARG) in the environment. However, computational challenges associated with assembly can impact the accuracy of downstream analyses. This work critically evaluates the impact of assembly leveraging short reads, nanopore MinION long-reads, and a combination of the two (hybrid) on ARG contextualization for ten environmental metagenomes using seven prominent assemblers (IDBA-UD, MEGAHIT, Canu, Flye, Opera-MS, metaSpades and HybridSpades). While short-read and hybrid assemblies produced similar patterns of ARG contextualization, raw or assembled long nanopore reads produced distinct patterns. Based on an in-silico spike-in experiment using real and simulated reads, we show that low to intermediate coverage species are more likely to be incorporated into chimeric contigs across all assemblers and sequencing technologies, while more abundant species produce assemblies with a greater frequency of inversions and insertion/deletions (indels). In sum, our analyses support hybrid assembly as a valuable technique for boosting the reliability and accuracy of assembly-based analyses of ARGs and neighboring genes at environmentally-relevant coverages, provided that sufficient short-read sequencing depth is achieved.
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