Notes

Semi-Destructive and Non-Destructive Exams regarding Wooden Framework of Various Dampness Articles.
Moreover, there exists a range of densities for which the coexistence of many phenotypes persists for evolutionarily long times.Understanding the cell molecular changes occurring as a results of climatic circumstances is crucial in the current days in which climate change and global warming are one of the most serious challenges that living organisms have to face. Sperm are one of the mammals' cells most sensitive to heat, therefore evaluating the impact of seasonal changes in terms of its transcriptional activity can contribute to elucidate how these cells cope with heat stress events. We sequenced the total sperm RNA from 64 ejaculates, 28 collected in summer and 36 collected in autumn, from 40 Manchega rams. A highly rich transcriptome (11,896 different transcripts) with 90 protein coding genes that exceed an average number of 5000 counts were found. Comparing transcriptome in the summer and autumn ejaculates, 236 significant differential abundance genes were assessed, most of them (228) downregulated. The main functions that these genes are related to sexual reproduction and negative regulation of protein metabolic processes and kinase activity. Sperm response to heat stress supposes a drastic decrease of the transcriptional activity, and the upregulation of only a few genes related with the basic functions to maintain the organisms' homeostasis and surviving. Rams' spermatozoids carry remnant mRNAs which are retrospectively indicators of events occurring along the spermatogenesis process, including abiotic factors such as environmental temperature.α-glucosidase inhibitors represent an important class of type 2 antidiabetic drugs and they act by lowering postprandial hyperglycemia. Today, only three synthetic inhibitors exist on the market, and there is a need for novel, natural and more efficient molecules exhibiting this activity. In this study, we investigated the ability of Tamarix nilotica ethanolic and aqueous shoot extracts, as well as methanolic fractions prepared from aqueous crude extracts to inhibit α-glucosidase. Both, 50% ethanol and aqueous extracts inhibited α-glucosidase in a concentration-dependent manner, with IC50 values of 12.5 μg/mL and 24.8 μg/mL, respectively. Importantly, α-glucosidase inhibitory activity observed in the T. nilotica crude extracts was considerably higher than pure acarbose (IC50 = 151.1 μg/mL), the most highly prescribed α-glucosidase inhibitor on the market. When T. nilotica crude extracts were fractionated using methanol, enhanced α-glucosidase inhibitory activity was observed in general, with the highest observed α-glucosidase inhibitory activity in the 30% methanol fraction (IC50 = 5.21 μg/mL). Kinetic studies further revealed a competitive reversible mechanism of inhibition by the plant extract. The phytochemical profiles of 50% ethanol extracts, aqueous extracts, and the methanolic fractions were investigated and compared using a metabolomics approach. Statistical analysis revealed significant differences in the contents of the crude extracts and fractions and potentially identified the molecules that were most responsible for these observed variations. Higher α-glucosidase inhibitory activity was associated with an enrichment of terpenoids, fatty acids, and flavonoids. Among the identified molecules, active compounds with known α-glucosidase inhibitory activity were detected, including unsaturated fatty acids, triterpenoids, and flavonoid glycosides. These results put forward T. nilotica as a therapeutic plant for type 2 diabetes and a source of α-glucosidase inhibitors.
Men who have sex with men (MSM) living with HIV are more likely to be depressed than MSM without HIV. The AIDS epidemic will not end if the needs of people living with HIV and the determinants of health are not being addressed. Compared to HIV individuals without depression, depressed HIV individuals have worse clinical outcomes and higher mortality risk. Depression is caused by a complex combination of social, psychological, and biological variables. This systematic review, thereby motivated by the need to address this gap in the literature, aims to articulate determinants of depression among MSM living with HIV according to the biopsychosocial approach.

We systematically searched four databases from 2011 to 2021. We searched for observational studies on determinants of depression among MSM living with HIV. The outcome is depression based on the categorical or numerical outcome. Two reviewers independently extracted data and assessed study risks of bias. Any disagreements are consulted with the third revression with the strongest evidence across studies were enacted HIV-related stigma, unemployment, sleep disturbance, current smoker, black ethnicity, born overseas, ART initiation, and access to mental health care. Despite weaker evidence, the other relevant determinants to be included were older age, internalized stigma, self-efficacy, and social support. Efforts to improve or prevent depression among MSM living with HIV could benefit from addressing the determinants of depression based on the biopsychosocial approach immediately after HIV diagnosis. Integrating mental health screening and care into HIV treatment settings would strengthen HIV prevention and care outcomes and improve access to mental healthcare.Synthetic Lethality (SL) is currently defined as a type of genetic interaction in which the loss of function of either of two genes individually has limited effect in cell viability but inactivation of both genes simultaneously leads to cell death. Given the profound genomic aberrations acquired by tumor cells, which can be systematically identified with -omics data, SL is a promising concept in cancer research. In particular, SL has received much attention in the area of cancer metabolism, due to the fact that relevant functional alterations concentrate on key metabolic pathways that promote cellular proliferation. With the extensive prior knowledge about human metabolic networks, a number of computational methods have been developed to predict SL in cancer metabolism, including the genetic Minimal Cut Sets (gMCSs) approach. A major challenge in the application of SL approaches to cancer metabolism is to systematically integrate tumor microenvironment, given that genetic interactions and nutritional availability are interconnected to support proliferation. Here, we propose a more general definition of SL for cancer metabolism that combines genetic and environmental interactions, namely loss of gene functions and absence of nutrients in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase (DHFR) inhibition in different environments. Finally, our approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.The West African Ebola (2014-2016) epidemic caused an estimated 11.310 deaths and massive social and economic disruption. The epidemic was comprised of many local outbreaks of varying sizes. However, often local outbreaks recede before the arrival of international aid or susceptible depletion. We modeled Ebola virus transmission under the effect of behavior changes acting as a local inhibitor. A spatial model is used to simulate Ebola epidemics. Our findings suggest that behavior changes can explain why local Ebola outbreaks recede before substantial international aid was mobilized during the 2014-2016 epidemic.
Ground-glass opacity (GGO)-a hazy, gray appearing density on computed tomography (CT) of lungs-is one of the hallmark features of SARS-CoV-2 in COVID-19 patients. This AI-driven study is focused on segmentation, morphology, and distribution patterns of GGOs.

We use an AI-driven unsupervised machine learning approach called PointNet++ to detect and quantify GGOs in CT scans of COVID-19 patients and to assess the severity of the disease. We have conducted our study on the "MosMedData", which contains CT lung scans of 1110 patients with or without COVID-19 infections. We quantify the morphologies of GGOs using Minkowski tensors and compute the abnormality score of individual regions of segmented lung and GGOs.

PointNet++ detects GGOs with the highest evaluation accuracy (98%), average class accuracy (95%), and intersection over union (92%) using only a fraction of 3D data. On average, the shapes of GGOs in the COVID-19 datasets deviate from sphericity by 15% and anisotropies in GGOs are dominated by dipolelarly useful in countries severely devastated by COVID-19 such as India, where the number of cases has outstripped available resources creating delays or even breakdowns in patient care. This AI-driven approach synthesizes both the unique GGO distribution pattern and severity of the disease to allow for more efficient diagnosis, triaging and conservation of limited resources.In an era of mass extinction and biodiversity crisis, it is increasingly crucial to cultivate more just and inclusive multispecies futures. As mitigation and adaption efforts are formed in response to these crises, just transitions forward require intentional consideration of the hybrid entanglement of humans, human societies, and wider landscapes. We thus apply a critical hybridity framework to examine the entanglement of the pollinator crisis with the cultural and agricultural practice of hobbyist beekeeping. We draw on ethnographic engagements with Massachusetts beekeepers and find apiculture to be widely understood as a form of environmentalism-including as both a mitigation to and adaptation for the pollinator crisis. Illustrating how power-laden socioecological negotiations shape and reshape regional environments, we then discuss how this narrative relies on the capitalistic and instrumental logics characteristic of Capitalocene environmentalisms. These rationalities, which obscure the hybridity of landscapes, consequently increase the likelihood of problematic unintended consequences. Also present, however, is a deeper engagement with hybrid perspectives, with some beekeepers even offering pathways toward inclusive solutions. We conclude that if more just and biodiverse futures are to be realized, beekeeping communities must foster increasingly hybrid visions of apiculture as situated within socioecological and contested landscapes.Bayesian methods are widely used in the GWAS meta-analysis. But the considerable consumption in both computing time and memory space poses great challenges for large-scale meta-analyses. In this research, we propose an algorithm named SMetABF to rapidly obtain the optimal ABF in the GWAS meta-analysis, where shotgun stochastic search (SSS) is introduced to improve the Bayesian GWAS meta-analysis framework, MetABF. Simulation studies confirm that SMetABF performs well in both speed and accuracy, compared to exhaustive methods and MCMC. SMetABF is applied to real GWAS datasets to find several essential loci related to Parkinson's disease (PD) and the results support the underlying relationship between PD and other autoimmune disorders. Developed as an R package and a web tool, SMetABF will become a useful tool to integrate different studies and identify more variants associated with complex traits.
Website: