Notes

ArcDrain: A GIS Add-In for Automatic Determination of Surface area Run-off within Metropolitan Catchments.
Facial appearance has been suggested to provide an honest cue of an individual's biological condition. However, there is little direct evidence that facial attractiveness reflects actual health. Here we tested if facial appearance is related with metabolic health biomarkers. Face photographs of 161 healthy, young women (Mage = 28.59, SDage = 2.34) were assessed in terms of perceived attractiveness and health. Metabolic health was evaluated based on levels of markers of lipid and glucose metabolism balance, liver functioning, and inflammation. BMI, testosterone (T), and estradiol (E2) levels were controlled. Facial attractiveness, but not health, was negatively related with lipid profile components detrimental to health (total cholesterol, LDL, triglycerides) but not with relatively protective for health HDL. When controlled for BMI, E2, and T, only the relationship between attractiveness and triglycerides remained significant. Facial appearance was unrelated with glucose metabolism, liver functioning, and inflammatory markers. The results suggest, that for healthy women of reproductive age, such measures as BMI and sex hormone levels may be better predictors of attractiveness, compared to measures of metabolic health. Markers of lipid, glucose homeostasis, liver functioning or low-grade inflammation may be rather indicators of future health, of lesser importance in mating context, thus only modestly reflected in facial appearance.Human language is dominantly processed in the left cerebral hemisphere in most of the population. While several studies have suggested that there are higher rates of atypical right-hemispheric language lateralization in left-/mixed-handers, an accurate estimate of this association from a large sample is still missing. In this study, we comprised data from 1,554 individuals sampled in three previous studies in which language lateralization measured via dichotic listening, handedness and footedness were assessed. Overall, we found a right ear advantage indicating typical left-hemispheric language lateralization in 82.1% of the participants. While we found significantly more left-handed individuals with atypical language lateralization on the categorical level, we only detected a very weak positive correlation between dichotic listening lateralization quotients (LQs) and handedness LQs using continuous measures. Here, only 0.4% of the variance in language lateralization were explained by handedness. We complemented these analyses with Bayesian statistics and found no evidence in favor of the hypothesis that language lateralization and handedness are related. Footedness LQs were not correlated with dichotic listening LQs, but individuals with atypical language lateralization also exhibited higher rates of atypical footedness on the categorical level. We also found differences in the extent of language lateralization between males and females with males exhibiting higher dichotic listening LQs indicating more left-hemispheric language processing. Overall, these findings indicate that the direct associations between language lateralization and motor asymmetries are much weaker than previously assumed with Bayesian correlation analyses even suggesting that they do not exist at all. Furthermore, sex differences seem to be present in language lateralization when the power of the study is adequate suggesting that endocrinological processes might influence this phenotype.The tumor microenvironment (TME) plays critical roles in tumor growth and progression, however key regulators of gene expression in the TME of cutaneous malignant peripheral nerve sheath tumor (C-MPNST) and spindle cell melanoma (SCM) have not been well elucidated. Herein, we investigate the epigenetic regulation of promoters and gene bodies and their effect on the TME composition of C-MPNSTs and SCMs. A cohort of 30 patients was analyzed using differential gene expression (DGE) and gene set enrichment analysis (GSEA) using the Nanostring platform. Methylation analysis was carried out utilizing an Infinium Methylation EPIC array targeting 866,562 methylation site (CpG) islands. DGE revealed overexpression of genes related to mast cells in the TME of SCMs, and a predominance of exhausted CD8+ T cells and macrophages in the TME of C-MPNSTs. Interestingly, we further observed promoter hypermethylation in key overexpressed genes and corresponding gene body hypomethylation. Analysis using ENCODE ChIP-sequencing data identified CTCF as the common transcription factor at the site of the hypomethylated probe. These findings support that the TME composition of C-MPNSTs and SCMs is at least partially independent on promoter methylation status, suggesting a possible relationship between gene body enhancers and expression of key TME genes in both entities.Deep learning methods for digital pathology analysis are an effective way to address multiple clinical questions, from diagnosis to prediction of treatment outcomes. These methods have also been used to predict gene mutations from pathology images, but no comprehensive evaluation of their potential for extracting molecular features from histology slides has yet been performed. Cepharanthine TNF-alpha inhibitor We show that HE2RNA, a model based on the integration of multiple data modes, can be trained to systematically predict RNA-Seq profiles from whole-slide images alone, without expert annotation. Through its interpretable design, HE2RNA provides virtual spatialization of gene expression, as validated by CD3- and CD20-staining on an independent dataset. The transcriptomic representation learned by HE2RNA can also be transferred on other datasets, even of small size, to increase prediction performance for specific molecular phenotypes. We illustrate the use of this approach in clinical diagnosis purposes such as the identification of tumors with microsatellite instability.MucA and MucB are critical negative modulators of sigma factor AlgU and regulate the mucoid conversion of Pseudomonas aeruginosa. Previous studies have revealed that lipid signals antagonize MucA-MucB binding. Here we report the crystal structure of MucB in complex with the periplasmic domain of MucA and polyethylene glycol (PEG), which unveiled an intermediate state preceding the MucA-MucB dissociation. Based on the biochemical experiments, the aliphatic side chain with a polar group was found to be of primary importance for inducing MucA cleavage. These results provide evidence that the hydrophobic cavity of MucB is a primary site for sensing lipid molecules and illustrates the detailed control of conformational switching within MucA-MucB in response to lipophilic effectors.
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