Cross-Domain Text Mining of Pathophysiological Processes Associated with Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease worldwide. This study's goal was to identify the signaling drivers and pathways that modulate glomerular endothelial dysfunction in DKD via artificial intelligence-enabled literature-based discovery. Cross-domain text mining of 33+ million PubMed articles was performed with SemNet 2.0 to identify and rank multi-scalar and multi-factorial pathophysiological concepts related to DKD. A set of identified relevant genes and proteins that regulate different pathological events associated with DKD were analyzed and ranked using normalized mean HeteSim scores. High-ranking genes and proteins intersected three domains-DKD, the immune response, and glomerular endothelial cells. The top 10% of ranked concepts were mapped to the following biological functions: angiogenesis, apoptotic processes, cell adhesion, chemotaxis, growth factor signaling, vascular permeability, the nitric oxide response, oxidative stress, the cytokine response, macrophage signaling, NFκB factor activity, the TLR pathway, glucose metabolism, the inflammatory response, the ERK/MAPK signaling response, the JAK/STAT pathway, the T-cell-mediated response, the WNT/ß-catenin pathway, the renin-angiotensin system, and NADPH oxidase activity. High-ranking genes and proteins were used to generate a protein-protein interaction network. The study results prioritized interactions or molecules involved in dysregulated signaling in DKD, which can be further assessed through biochemical network models or experiments.

A Comprehensive Evaluation of Biomedical Entity Linking Models.

Biomedical entity linking (BioEL) is the process of connecting entities referenced in documents to entries in biomedical databases such as the Unified Medical Language System (UMLS) or Medical Subject Headings (MeSH). The study objective was to comprehensively evaluate nine recent state-of-the-art biomedical entity linking models under a unified framework. We compare these models along axes of (1) accuracy, (2) speed, (3) ease of use, (4) generalization, and (5) adaptability to new ontologies and datasets. We additionally quantify the impact of various preprocessing choices such as abbreviation detection. Systematic evaluation reveals several notable gaps in current methods. In particular, current methods struggle to correctly link genes and proteins and often have difficulty effectively incorporating context into linking decisions. To expedite future development and baseline testing, we release our unified evaluation framework and all included models on GitHub at https://github.com/davidkartchner/biomedical-entity-linking.

BioSift: A Dataset for Filtering Biomedical Abstracts for Drug Repurposing and Clinical Meta-Analysis.

This work presents a new, original document classification dataset, BioSift, to expedite the initial selection and labeling of studies for drug repurposing. The dataset consists of 10,000 human-annotated abstracts from scientific articles in PubMed. Each abstract is labeled with up to eight attributes necessary to perform meta-analysis utilizing the popular patient-intervention-comparator-outcome (PICO) method: has human subjects, is clinical trial/cohort, has population size, has target disease, has study drug, has comparator group, has a quantitative outcome, and an "aggregate" label. Each abstract was annotated by 3 different annotators (i.e., biomedical students) and randomly sampled abstracts were reviewed by senior annotators to ensure quality. Data statistics such as reviewer agreement, label co-occurrence, and confidence are shown. Robust benchmark results illustrate neither PubMed advanced filters nor state-of-the-art document classification schemes (e.g., active learning, weak supervision, full supervision) can efficiently replace human annotation. In short, BioSift is a pivotal but challenging document classification task to expedite drug repurposing. The full annotated dataset is publicly available and enables research development of algorithms for document classification that enhance drug repurposing.

Peritoneal GATA6+ macrophages function as a portal for Staphylococcus aureus dissemination.

Essentially all Staphylococcus aureus (S. aureus) bacteria that gain access to the circulation are plucked out of the bloodstream by the intravascular macrophages of the liver - the Kupffer cells. It is also thought that these bacteria are disseminated via the bloodstream to other organs. Our data show that S. aureus inside Kupffer cells grew and escaped across the mesothelium into the peritoneal cavity and immediately infected GATA-binding factor 6-positive (GATA6+) peritoneal cavity macrophages. These macrophages provided a haven for S. aureus, thereby delaying the neutrophilic response in the peritoneum by 48 hours and allowing dissemination to various peritoneal and retroperitoneal organs including the kidneys. In mice deficient in GATA6+ peritoneal macrophages, neutrophils infiltrated more robustly and reduced S. aureus dissemination. Antibiotics administered i.v. did not prevent dissemination into the peritoneum or to the kidneys, whereas peritoneal administration of vancomycin (particularly liposomal vancomycin with optimized intracellular penetrance capacity) reduced kidney infection and mortality, even when administered 24 hours after infection. These data indicate that GATA6+ macrophages within the peritoneal cavity are a conduit of dissemination for i.v. S. aureus, and changing the route of antibiotic delivery could provide a more effective treatment for patients with peritonitis-associated bacterial sepsis.

Mutual reinforcement between telomere capping and canonical Wnt signalling in the intestinal stem cell niche.

Critical telomere shortening (for example, secondary to partial telomerase deficiency in the rare disease dyskeratosis congenita) causes tissue pathology, but underlying mechanisms are not fully understood. Mice lacking telomerase (for example, mTR-/- telomerase RNA template mutants) provide a model for investigating pathogenesis. In such mice, after several generations of telomerase deficiency telomeres shorten to the point of uncapping, causing defects most pronounced in high-turnover tissues including intestinal epithelium. Here we show that late-generation mTR-/- mutants experience marked downregulation of Wnt pathway genes in intestinal crypt epithelia, including crypt base columnar stem cells and Paneth cells, and in underlying stroma. The importance of these changes was revealed by rescue of crypt apoptosis and Wnt pathway gene expression upon treatment with Wnt pathway agonists. Rescue was associated with reduced telomere-dysfunction-induced foci and anaphase bridges, indicating improved telomere capping. Thus a mutually reinforcing feedback loop exists between telomere capping and Wnt signalling, and telomere capping can be impacted by extracellular cues in a fashion independent of telomerase.

Mechanistic studies of Ce(IV)-mediated oxidation of beta-dicarbonyls: solvent-dependent behavior of radical cation intermediates.

The Ce(IV)-initiated oxidation of synthetically relevant beta-diketones and beta-keto silyl enol ethers was explored in three solvents: acetonitrile, methylene chloride, and methanol. The studies presented herein show that the rate of reaction between Ce(IV) and the substrates is dependent upon the polarity of the solvent. Thermochemical studies and analysis are interpreted to be consistent with transition state stabilization by solvent being primarily responsible for the rate of substrate oxidation. Kinetic investigation of radical cations obtained from oxidations of beta-diketones reveals that a more ordered transition state for the radical cation decay is achieved through the direct involvement of methanol in the deprotonation of the intermediate. In the case of radical cations derived from beta-keto silyl enol ethers, experimental data support a mechanism involving unimolecular decay of the intermediate. Remarkably, radical cations derived from beta-diketones and beta-keto silyl enol ethers are surprisingly stable in methylene chloride.