The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD’s Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

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Originating in the brain, glioblastoma (GBM) is a highly lethal and virtually incurable cancer, in large part because it readily develops resistance to treatments. While numerous studies have investigated mechanisms enabling GBM cells to evade chemotherapy-induced apoptosis, few have addressed how their surrounding extracellular matrix (ECM) acts to promote their survival. Here, we employed a biomaterial-based, 3D culture platform to investigate systematically how interactions between patient-derived GBM cells and the brain ECM promote resistance to alkylating chemotherapiesincluding temozolomide, which is used routinely in clinical practice. Scaffolds for 3D culture were fabricated from hyaluronic acid (HA)a major structural and bioactive component of the brain ECMand functionalized with the RGD (arginine-glycineaspartic acid) tripeptide to provide sites for integrin engagement. Data demonstrate that cooperative engagement of CD44, through HA, and integrin α V , through RGD, facilitates resistance to alkylating chemotherapies through co-activation of Src, which inhibited downstream expression of BCL-2 family pro-apoptotic factors. In sum, a bioengineered, 3D culture platform was used to gain new mechanistic insights into how ECM in the brain tumor microenvironment promotes resistance to chemotherapy and suggests potential avenues for the development of novel, matrix-targeted combination therapies designed to suppress chemotherapy resistance in GBM.

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Background: TNFR1 signaling has been intensively studied, but it remains unclear how TNFR2 transduces TNF-␣ signal under inflammatory conditions. Results: TNFR2 associates with IL-17RD, resulting in receptor aggregation and TRAF2 recruitment, leading to promotion of NF-B signaling in renal tubular epithelial cells. Conclusion: TNFR2 cooperates with IL-17RD to activate NF-B. Significance: The TNFR2⅐IL-17RD heteromer might be implicated in nephritis.

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Remyelination is limited in patients with multiple sclerosis (MS) due to the difficulties in recruiting proliferating oligodendrocyte precursors (OPCs), the inhibition of OPC differentiation and/or maturation, and/or failure in the generation of the myelin sheath. In vitro studies have revealed that miR-219 is necessary for OPC differentiation and monocarboxylate transporter 1 (MCT1) plays a vital role in oligodendrocyte maturation and myelin synthesis. Herein, we hypothesized that miR-219 might promote oligodendrocyte differentiation and attenuate demyelination in a cuprizone (CPZ)-induced demyelinated model by regulating the expression of MCT1. We found that CPZ-treated mice exhibited significantly increased anxiety in the open field test. However, miR-219 reduced anxiety as shown by an increase in the total distance, the central distance and the mean amount of time spent in the central area. miR-219 decreased the quantity of OPCs and increased the number of oligodendrocytes and the level of myelin basic protein (MBP) and cyclic nucleotide 3' phosphodiesterase (CNP) protein. Ultrastructural studies further confirmed that the extent of demyelination was attenuated by miR-219 overexpression. Meanwhile, miR-219 also greatly enhanced MCT1 expression via suppression of oligodendrocyte differentiation inhibitors, Sox6 and Hes5, treatment with the MCT1 inhibitor α-cyano-4-hydroxycinnamate (4-CIN) reduced the number of oligodendrocytes and the protein levels of MBP and CNP. Taken together, these results suggest a novel mode of action of miR-219 via MCT1 in vivo and may provide a new potential remyelination therapeutic target.

Land surface temperature (LST) is one of the key parameters in hydrology, meteorology, and the surface energy balance. The National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) Enterprise algorithm is adapted to Landsat-8 data to obtain the estimate of LST. The coefficients of the Enterprise algorithm were obtained by linear regression using the analog data produced by comprehensive radiative transfer modeling. The performance of the Enterprise algorithm was first tested by simulation data and then validated by ground measurements. In addition, the accuracy of the Enterprise algorithm was compared to the generalized split-window algorithm and the split-window algorithm of Sobrino et al. (1996). The validation results indicate the Enterprise algorithm has a comparable accuracy to the other two split-window algorithms. The biases (root mean square errors) of the Enterprise algorithm were 1.38 (3.22), 1.01 (2.32), 1.99 (3.49), 2.53 (3.46), and −0.15 K (1.11 K) at the SURFRAD, HiWATER_A, HiWATER_B, HiWATER_C sites and BanGe site, respectively, whereas those values were 1.39 (3.20), 1.0 (2.30), 1.93 (3.48), 2.53 (3.35), and −0.35 K (1.16 K) for the generalized split-window algorithm, 1.45 (3.39), 1.08 (2.41), 2.16 (3.67), 2.52 (3.58), and 0.02 K (1.12 K) for the split-window algorithm of Sobrino, respectively. This study provides an alternative method to estimate LST from Landsat-8 data.