Notes

Protecting role as well as molecular device regarding motion of Nesfatin-1 against high glucose-induced swelling, oxidative strain and also apoptosis in retinal epithelial tissues.
We conclude that an important increase in morbidity and mortality due to SARI was observed in the FYP. More vulnerable groups and those living in the Southeast, North and Center-West regions of the country suffered the most.
In 2020, an excess of 425 054 cases and 109 682 deaths was observed, with a significant increase in the risk of falling ill and dying from SARI, with an IRAP of 200.06 and an MRAP of 51.68 cases per 100 000 inhabitants. The increase in SARI cases and deaths was particularly prominent among patients with COVID-19, the elderly, males, those self-identifying as mixed race and patients with heart disease and diabetes. We conclude that an important increase in morbidity and mortality due to SARI was observed in the FYP. More vulnerable groups and those living in the Southeast, North and Center-West regions of the country suffered the most.Hospital strikes in the Portuguese National Health Service (NHS) are becoming increasingly frequent. This paper analyses the effect of different health professionals' strikes (physicians, nurses, and diagnostic and therapeutic technicians (DTT) - DTT) on patient outcomes and hospital activity. Patient-level data, comprising all NHS hospital admissions in mainland Portugal from 2012 to 2018, is used together with a comprehensive strike dataset with almost 130 protests. Data suggests that hospital operations are partially disrupted during strikes, with sharp reductions in surgical admissions (up to 54%) and a decline on both inpatient and outpatient care admissions. The model controls for hospital characteristics, time and regional fixed effects, and case-mix changes. Results suggest a modest increase in hospital mortality limited for patients admitted during physicians' strikes, and a slight reduction in mortality for patients already at the hospital when a strike takes place. Increases in readmission rates and length of stay are also found. Results suggest that hospitals and legal minimum staffing levels defined during strikes are not flexible enough to accommodate sudden disruptions in staffing, regardless of hospital quality in periods without strikes.
In many biomedical studies, there arises the need to integrate data from multiple directly or indirectly related sources. Collective matrix factorization (CMF) and its variants are models designed to collectively learn from arbitrary collections of matrices. The latent factors learnt are rich integrative representations that can be used in downstream tasks, such as clustering or relation prediction with standard machine-learning models. Previous CMF-based methods have numerous modeling limitations. They do not adequately capture complex non-linear interactions and do not explicitly model varying sparsity and noise levels in the inputs, and some cannot model inputs with multiple datatypes. These inadequacies limit their use on many biomedical datasets.

To address these limitations, we develop Neural Collective Matrix Factorization (NCMF), the first fully neural approach to CMF. We evaluate NCMF on relation prediction tasks of gene-disease association prediction and adverse drug event prediction, using multiple datasets. In each case, data are obtained from heterogeneous publicly available databases and used to learn representations to build predictive models. NCMF is found to outperform previous CMF-based methods and several state-of-the-art graph embedding methods for representation learning in our experiments. Our experiments illustrate the versatility and efficacy of NCMF in representation learning for seamless integration of heterogeneous data.

https//github.com/ajayago/NCMF_bioinformatics.

Supplementary data are available at Bioinformatics online.
Supplementary data are available at Bioinformatics online.
The technology of high-throughput chromatin conformation capture (Hi-C) allows genome-wide measurement of chromatin interactions. Several studies have shown statistically significant relationships between gene-gene spatial contacts and their co-expression. It is desirable to uncover epigenetic mechanisms of transcriptional regulation behind such relationships using computational modeling. Existing methods for predicting gene co-expression from Hi-C data use manual feature engineering or unsupervised learning, which either limits the prediction accuracy or lacks interpretability.

To address these issues, we propose HiCoEx (Hi-C predicts gene co-expression), a novel end-to-end framework for explainable prediction of gene co-expression from Hi-C data based on graph neural network. We apply graph attention mechanism to a gene contact network inferred from Hi-C data to distinguish the importance among different neighboring genes of each gene, and learn the gene representation to predict co-expression in a supervised and task-specific manner. Then, from the trained model, we extract the learned gene embeddings as a model interpretation to distill biological insights. Experimental results show that HiCoEx can learn gene representation from 3D genomics signals automatically to improve prediction accuracy, and make the black box model explainable by capturing some biologically meaningful patterns, e.g., in a gene contact network, the common neighbors of two central genes might contribute to the co-expression of the two central genes through sharing enhancers.

The source code is freely available at https//github.com/JieZheng-ShanghaiTech/HiCoEx.

Supplementary data are available at Bioinformatics online.
Supplementary data are available at Bioinformatics online.Ferroelectric solid solutions with composition near the morphotropic phase boundary (MPB) have gained extensive attention recently due to their excellent ferroelectric and piezoelectric properties. Here, we have demonstrated a strategy to realize the controllable preparation of BiFeO3-BaTiO3 (BF-BT) epitaxial films near the MPB. A series of high-quality BF-BT films were fabricated by pulsed laser deposition via adjusting oxygen partial pressure (PO2) using a BF-BT ceramic target. A continuous transition from rhombohedral to tetragonal phase was observed upon increasing PO2. Particularly, the film with a pure tetragonal phase exhibited a large remnant polarization of ∼90.6 μC/cm2, while excellent piezoelectric performance with an ultrahigh strain (∼0.48%) was obtained in the film with coexisting rhombohedral and tetragonal phases. The excellent ferroelectric and piezoelectric properties endow the BF-BT system near the MPB with great application prospects in lead-free electronic devices.Impaired learning and memory ability is one of the characteristics of a variety of neurological diseases, and its molecular mechanisms are complex and diverse and are regulated by a variety of factors. It is generally believed that synaptic plasticity plays an important role in the process of learning and memory. The protein encoded by the Pax2 gene is a transcription factor involved in neuron migration and cell fate determination during neural development. Mice knocked out of BDNF in the Pax2 lineage-derived interneuron precursor exhibited learning disabilities and severe cognitive impairment. In this study, Pax2 heterozygous gene (Pax2+/- mice) deletion mice were used as the research objects and behavioral tests were used to observe the effect of Pax2 gene deletion on learning and memory ability; morphological and molecular biological methods were used to observe the effect of Pax2 gene deletion on the neural structure. Single-cell transcriptome sequencing was used to observe the cell subtypes and differentially expressed genes (DEGs) and signaling pathways affected by Pax2 gene deletion and the possible molecular mechanisms. The results showed that Pax2+/- mice had impaired learning and memory ability, abnormal synaptic structure, and significantly reduced number of microglia clusters, and DEGs were associated with pro-inflammatory chemokines. Finally, we speculate that Pax2 gene deletion may lead to abnormal chemokines and chemokine receptors by affecting microglia.Copper is essential in a host of biological processes, and disruption of its homeostasis is associated with diseases including neurodegeneration and metabolic disorders. Extracellular copper shifts in its speciation between healthy and disease states, and identifying molecular components involved in these perturbations could widen the panel of biomarkers for copper status. While there have been exciting advances in approaches for studying the extracellular proteome with mass spectrometry-based methods, the typical workflows disrupt metal-protein interactions due to the lability of these bonds either during sample preparation or in gas-phase environments. We sought to develop and apply a workflow to enrich for and identify protein populations with copper-binding propensities in extracellular fluids using an immobilized metal affinity chromatography (IMAC) resin. The strategy was optimized using human serum to allow for maximum quantity and diversity of protein enrichment. Protein populations could be differentiated based on protein load on the resin, likely on account of differences in abundance and affinity. The enrichment workflow was applied to plasma samples from patients with Wilson's disease and protein IDs and differential abundancies relative to healthy subjects were compared to those yielded from a traditional proteomic workflow. While the IMAC workflow preserved differential abundance and protein ID information from the traditional workflow, it identified several additional proteins being differentially abundant including those involved in lipid metabolism, immune system, and antioxidant pathways. Our results suggest the potential for this IMAC workflow to identify new proteins as potential biomarkers in copper-associated disease states.
Biomarkers guiding the neoadjuvant use of immune-checkpoint blockers (ICB) are needed for patients with localized muscle-invasive bladder cancers (MIBC). Profiling tumor and blood samples, we found that follicular helper CD4+ T cells (TFH) are among the best therapeutic targets of pembrolizumab correlating with progression-free survival. TFH were associated with tumoral CD8 and PD-L1 expression at baseline and the induction of tertiary lymphoid structures after pembrolizumab. Blood central memory TFH accumulated in tumors where they produce CXCL13, a chemokine found in the plasma of responders only. IgG4+CD38+ TFH residing in bladder tissues correlated with clinical benefit. Finally, TFH and IgG directed against urothelium-invasive Escherichia coli dictated clinical responses to pembrolizumab in three independent cohorts. The links between tumor infection and success of ICB immunomodulation should be prospectively assessed at a larger scale.

In patients with bladder cancer treated with neoadjuvant pembrolizumab, E. coli-specific CXCL13 producing TFH and IgG constitute biomarkers that predict clinical benefit. Beyond its role as a biomarker, such immune responses against E. coli might be harnessed for future therapeutic strategies. This article is highlighted in the In This Issue feature, p. 2221.
In patients with bladder cancer treated with neoadjuvant pembrolizumab, E. coli-specific CXCL13 producing TFH and IgG constitute biomarkers that predict clinical benefit. Beyond its role as a biomarker, such immune responses against E. Panobinostat datasheet coli might be harnessed for future therapeutic strategies. This article is highlighted in the In This Issue feature, p. 2221.
Website: https://www.selleckchem.com/products/LBH-589.html