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We report a precision medicine platform that evaluates the probability of chemotherapy drug efficacy for canine lymphoma by combining ex vivo chemosensitivity and immunophenotyping assays with computational modelling. We isolated live cancer cells from fresh fine needle aspirates of affected lymph nodes and collected post‐treatment clinical responses in 261 canine lymphoma patients scheduled to receive at least 1 of 5 common chemotherapy agents (doxorubicin, vincristine, cyclophosphamide, lomustine and rabacfosadine). We used flow cytometry analysis for immunophenotyping and ex vivo chemosensitivity testing. For each drug, 70% of treated patients were randomly selected to train a random forest model to predict the probability of positive Veterinary Cooperative Oncology Group (VCOG) clinical response based on input variables including antigen expression profiles and treatment sensitivity readouts for each patient's cancer cells. The remaining 30% of patients were used to test model performance. Most models showed a test set ROC‐AUC > 0.65, and all models had overall ROC‐AUC > 0.95. Predicted response scores significantly distinguished (P <.001) positive responses from negative responses in B‐cell and T‐cell disease and newly diagnosed and relapsed patients. Patient groups with predicted response scores >50% showed a statistically significant reduction (log‐rank P <.05) in time to complete response when compared to the groups with scores <50%. The computational models developed in this study enabled the conversion of ex vivo cell‐based chemosensitivity assay results into a predicted probability of in vivo therapeutic efficacy, which may help improve treatment outcomes of individual canine lymphoma patients by providing predictive estimates of positive treatment response. [ABSTRACT FROM AUTHOR]

Hydrogenases are metalloproteins capable of catalyzing the interconversion between molecular hydrogen and protons and electrons. The iron–sulfur clusters within the enzyme enable rapid relay of electrons which are either consumed or generated at the active site. Their unparalleled catalytic efficiency has attracted attention, especially for potential use in H2 production and/or fuel cell technologies. However, there are limitations to using hydrogenases, especially due to their high O2 sensitivity. The subclass, called [FeFe] hydrogenases, are particularly more vulnerable to O2 but proficient in H2 production. In this review, we provide an overview of mechanistic and protein engineering studies focused on understanding and enhancing O2 tolerance of the enzyme. The emphasis is on ongoing studies that attempt to overcome O2 sensitivity of the enzyme while it catalyzes H2 production in an aerobic environment. We also discuss pioneering attempts to utilize the enzyme in biological H2 production and other industrial processes, as well as our own perspective on future applications. [ABSTRACT FROM AUTHOR]

Hydrogenases, ferredoxins, and ferredoxin-NADP+ reductases (FNR) are redox proteins that mediate electron metabolism in vivo, and are also potential components for biological H2 production technologies. A high-throughput H2 production assay device (H2PAD) is presented that enables simultaneous evaluation of 96 individual H2 production reactions to identify components that improve performance. Using a CCD camera and image analysis software, H2PAD senses the chemo-optical response of Pd/WO3 thin films to the H2 produced. H2PAD-enabled discovery of hydrogenase and FNR mutants that enhance biological H2 production is reported. From a library of 10 080 randomly mutated Clostridium pasteurianum [FeFe] hydrogenases, we found a mutant with nearly 3-fold higher H2 production specific activity. From a library of 400 semi-randomly mutated Oryza sativa FNR, the top hit enabled a 60 % increase in NADPH-driven H2 production rates. H2PAD can also facilitate elucidation of fundamental biochemical mechanisms within these systems. [ABSTRACT FROM AUTHOR]