Characterization, Proximate Composition and Evaluation of Antimicrobial Activity of Seed Oil of Bauhinia tomentosa

Background: This study was carried out to investigate proximate composition, phytochemical profile and antimicrobial activity of the spectroscopically characterized seed oil of Bauhinia tomentosa . Materials and method: The characterization was carried out using FT-IR, mass spectra, 1H- and 13C-NMR. Results: The results from the proximate analysis showed the presence of crude protein 30.36±0.98%, crude fibre 26.00±0.69%, carbohydrate 25.32±0.57%, moisture content 12.04±0.39%, ash content 4.00±0.15% and fat content 2.28±0.09%. The phytochemical screening revealed the presence of alkaloids, flavonoids, saponins, terpenes, cardiac glycosides, sterols, anthraquinones and tannins in varying degrees. The mineral determination showed that the seed oil contained iron (3.10±0.01 mg kgG1), manganese (0.38±0.01 mg kgG1), while cadmium (0.0 mg kgG1), lead (0.0 mg kgG1) and nickel (0.0 mg kgG1) were not detected. The extracted seed oil was investigated for antimicrobial efficiency against four bacterial isolates and two fungal, wherein gentamicin and clotrimazole were the clinical standard antibiotic and antifungal agents, respectively. Conclusion: The antimicrobial activity result revealed the sample to be bioactive and of great pharmaceutical potential with MIC value of 6.25 and <3.625 mg mLG1 against Escherichia coli and Candida albican, respectively. Due to high nutritional values and broad antimicrobial properties, the seed oil of Bauhinia tomentosa has nutraceutical potentials, which might pave way for its use as an alternative nutrient source for mankind or for industrial purpose

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Detection of the significant impact of source clustering on higher-order statistics with DES Year 3 weak gravitational lensing data

We measure the impact of source galaxy clustering on higher-order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show this effect can exceed measurement uncertainties for common higher-order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey Year 3 data we construct null tests for the source-clustering-free case, finding a p-value of p = 4 × 10−3 (2.6σ) using third-order map moments and p = 3 × 10−11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either be included in the model or minimized through ad-hoc procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher-order gravitational lensing statistics, e.g. higher-order N-point functions, wavelet-moment observables, and deep learning or field level summary statistics of weak lensing maps

Beyond the 3rd moment: a practical study of using lensing convergence CDFs for cosmology with DES Y3

Widefield surveys probe clustered scalar fields – such as galaxy counts, lensing potential, etc. – which are sensitive to different cosmological and astrophysical processes. Constraining such processes depends on the statistics that summarize the field. We explore the cumulative distribution function (CDF) as a summary of the galaxy lensing convergence field. Using a suite of N-body light-cone simulations, we show the CDFs’ constraining power is modestly better than the second and third moments, as CDFs approximately capture information from all moments. We study the practical aspects of applying CDFs to data, using the Dark Energy Survey (DES Y3) data as an example, and compute the impact of different systematics on the CDFs. The contributions from the pointspread function and reduced shear approximation are 1 per cent of the totalsignal. Source clustering effects and baryon imprints contribute 1–10 per cent. Enforcing scale cutsto limitsystematics-driven biasesin parameter constraints degrade these constraints a noticeable amount, and this degradation is similar for the CDFs and the moments. We detect correlations between the observed convergence field and the shape noise field at 13σ. The non-Gaussian correlations in the noise field must be modelled accurately to use the CDFs, or other statistics sensitive to all moments, as a rigorous cosmology tool

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

An overview of the utilisation of microalgae biomass derived from nutrient recycling of wet market wastewater and slaughterhouse wastewater

Microalgae have high nutritional values for aquatic organisms compared to fish meal, because microalgae cells are rich in proteins, lipids, and carbohydrates. However, the high cost for the commercial production of microalgae biomass using fresh water or artificial media limits its use as fish feed. Few studies have investigated the potential of wet market wastewater and slaughterhouse wastewater for the production of microalgae biomass. Hence, this study aims to highlight the potential of these types of wastewater as an alternative superior medium for microalgae biomass as they contain high levels of nutrients required for microalgae growth. This paper focuses on the benefits of microalgae biomass produced during the phycore-mediation of wet market wastewater and slaughterhouse wastewater as fish feed. The extraction techniques for lipids and proteins as well as the studies conducted on the use of microalgae biomass as fish feed were reviewed. The results showed that microalgae biomass can be used as fish feed due to feed utilisation efficiency, physiological activity, increased resistance for several diseases, improved stress response, and improved protein retention

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts