Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Cytokine release syndrome (CRS) is a major cause of the multi-organ injury and fatal outcome induced by SARS-CoV-2 infection in severe COVID-19 patients. Metabolism can modulate the immune responses against infectious diseases, yet our understanding remains limited on how host metabolism correlates with inflammatory responses and affects cytokine release in COVID-19 patients. Here we perform both metabolomics and cytokine/chemokine profiling on serum samples from healthy controls, mild and severe COVID-19 patients, and delineate their global metabolic and immune response landscape. Correlation analyses show tight associations between metabolites and proinflammatory cytokines/chemokines, such as IL-6, M-CSF, IL-1α, IL-1β, and imply a potential regulatory crosstalk between arginine, tryptophan, purine metabolism and hyperinflammation. Importantly, we also demonstrate that targeting metabolism markedly modulates the proinflammatory cytokines release by peripheral blood mononuclear cells isolated from SARS-CoV-2-infected rhesus macaques ex vivo, hinting that exploiting metabolic alterations may be a potential strategy for treating fatal CRS in COVID-19.

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These effects suggest that HRV-BF, a novel behavioral neurocardiac intervention, could enhance BRS, improve the cardiac autonomic tone, and facilitate BP adjustment for individuals with prehypertension.

The development of highly active and stable earth-abundant electrocatalysts to reduce or eliminate the reliance on noble-metal based ones for hydrogen evolution reaction (HER) over a broad pH range remains a great challenge. Herein, hierarchical porous CoS/N-doped carbon@MoS (CoS/NC@MoS) polyhedrons have been synthesized by a facile hydrothermal approach using highly conductive Co/NC polyhedrons composed of cobalt nanoparticles embedded in N-doped carbon matrices as both the structural support and cobalt source. The Co/NC polyhedrons were prepared by direct carbonization of Co-based zeolitic imidazolate framework (ZIF-67) in Ar atmosphere. Benefiting from the prominent synergistic effect of N-doped carbon enhancing the conductivity of the hybrid, MoS and CoS providing abundant catalytically active sites as well as the well-defined polyhedral structure promoting mechanical stability, the as-synthesized CoS/NC@MoS shows excellent HER activity and good stability over a broad pH range, with onset overpotentials of 4, 38, and 45 mV, Tafel slopes of 60.3, 68.8, and 126.1 mV dec, and overpotentials of 67, 117, and 261 mV at 10 mA cm in 1.0 M KOH, 0.5 M HSO, and 1.0 M phosphate buffer solution (PBS), respectively. This work provides a general and promising approach for the design and synthesis of inexpensive and efficient pH-universal HER electrocatalysts.