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No difference in any of the OCT-A parameters was observed when comparing patients with or without interstitial lung disease (ILD). Qualitative analysis of OCT-A revealed at least one abnormality in 95% of patients.

We showed the ability of OCT-A to disclose early ocular vascular abnormalities in patients with SSc. Our results may represent a hypothesis-generating basis for exploring the potential role of OCT-A in diagnosis, monitoring and prognosis stratification in SSc.

We showed the ability of OCT-A to disclose early ocular vascular abnormalities in patients with SSc. Our results may represent a hypothesis-generating basis for exploring the potential role of OCT-A in diagnosis, monitoring and prognosis stratification in SSc.Nucleotide composition (GC content) varies across bacteria species, genome regions, and specific genes. In Xylella fastidiosa, a vector-borne fastidious plant pathogen infecting multiple crops, GC content ranges between ∼51-52%; however, these values were gathered using limited genomic data. We evaluated GC content variations across X. fastidiosa subspecies fastidiosa (N = 194), subsp. pauca (N = 107), and subsp. multiplex (N = 39). Genomes were classified based on plant host and geographic origin; individual genes within each genome were classified based on gene function, strand, length, ortholog group, Core vs. Accessory, and Recombinant vs. Non-recombinant. GC content was calculated for each gene within each evaluated genome. The effects of genome and gene level variables were evaluated with a mixed effect ANOVA, and the marginal-GC content was calculated for each gene. Also, the correlation between gene-specific GC content vs. natural selection (dN/dS) and recombination/mutation (r/m) was estimated. Our analyses show that intra-genomic changes in nucleotide composition in X. fastidiosa are small and influenced by multiple variables. Higher AT-richness is observed in genes involved in replication and translation, and genes in the leading strand. In addition, we observed a negative correlation between high-AT and dN/dS in subsp. pauca. The relationship between recombination and GC content varied between core and accessory genes. We hypothesize that distinct evolutionary forces and energetic constraints both drive and limit these small variations in nucleotide composition.Feeding is an essential part of animal life that is greatly impacted by the sense of taste. Although the characterization of taste-detection at the periphery has been extensive, higher order taste and feeding circuits are still being elucidated. Here, we use an automated closed-loop optogenetic activation screen to detect novel taste and feeding neurons in Drosophila melanogaster. Out of 122 Janelia FlyLight Project GAL4 lines preselected based on expression pattern, we identify six lines that acutely promote feeding and 35 lines that inhibit it. As proof of principle, we follow up on R70C07-GAL4, which labels neurons that strongly inhibit feeding. EG-011 chemical structure Using split-GAL4 lines to isolate subsets of the R70C07-GAL4 population, we find both appetitive and aversive neurons. Furthermore, we show that R70C07-GAL4 labels putative second-order taste interneurons that contact both sweet and bitter sensory neurons. These results serve as a resource for further functional dissection of fly feeding circuits.We treated 46 patients with multiple recurrent Clostridioides difficile infections (mrCDI) using a tapered-pulsed (T-P) fidaxomicin regimen, the majority of whom failed prior T-P vancomycin treatment. Sustained clinical response rates at 30 and 90 days were 74% (34/46) and 61% (28/46). T-P fidaxomicin shows promise for management of mrCDI.

In this article, we introduce a hierarchical clustering and Gaussian mixture model with expectation-maximization (EM) algorithm for detecting copy number variants (CNVs) using whole exome sequencing (WES) data. The R shiny package “HCMMCNVs” is also developed for processing user-provided bam files, running CNVs detection algorithm, and conducting visualization. Through applying our approach to 325 cancer cell lines in 22 tumor types from Cancer Cell Line Encyclopedia (CCLE), we show that our algorithm is competitive with other existing methods and feasible in using multiple cancer cell lines for CNVs estimation. In addition, by applying our approach to WES data of 120 oral squamous cell carcinoma (OSCC) samples, our algorithm, using the tumor sample only, exhibits more power in detecting CNVs as compared with the methods using both tumors and matched normal counterparts.

HCMMCNVs R shiny software is freely available at github repository https//github.com/lunching/HCMM_CNVs. and Zenodo https//doi.org/10.5281/zenodo.4593371.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.We evaluated whether Denver neighborhoods with elevated rates of adult laboratory-confirmed influenza hospitalization had lower adult coverage with influenza vaccine. Overall vaccine coverage was low. Hospitalization rates were associated with demographic and socioeconomic characteristics. Active immunization of at-risk neighborhoods may be necessary to address disparities in influenza hospitalization rates.

Polypharmacy side effects should be carefully considered for new drug development. However, considering all the complex drug-drug interactions that cause polypharma-cy side effects is challenging. Recently, graph neural network (GNN) models have handled these complex interactions successfully and shown great predictive perfor-mance. Nevertheless, the GNN models have difficulty providing intelligible factors of the prediction for biomedical and pharmaceutical domain experts.

A novel approach, graph feature attention network (GFAN), is presented for inter-pretable prediction of polypharmacy side effects by emphasizing target genes differ-ently. To artificially simulate polypharmacy situations, where two different drugs are taken together, we formulated a node classification problem by using the concept of line graph in graph theory.

Experiments with benchmark datasets validated interpretability of the GFAN and demonstrated competitive performance with the graph attention network in a previous work. And the specific cases in the polypharmacy side effect prediction experiments showed that the GFAN model is capable of very sensitively extracting the target genes for each side effect prediction.