Transformational machine learning: Learning how to learn from many related scientific problems.

Almost all machine learning (ML) is based on representing examples using intrinsic features. When there are multiple related ML problems (tasks), it is possible to transform these features into extrinsic features by first training ML models on other tasks and letting them each make predictions for each example of the new task, yielding a novel representation. We call this transformational ML (TML). TML is very closely related to, and synergistic with, transfer learning, multitask learning, and stacking. TML is applicable to improving any nonlinear ML method. We tested TML using the most important classes of nonlinear ML: random forests, gradient boosting machines, support vector machines, k-nearest neighbors, and neural networks. To ensure the generality and robustness of the evaluation, we utilized thousands of ML problems from three scientific domains: drug design, predicting gene expression, and ML algorithm selection. We found that TML significantly improved the predictive performance of all the ML methods in all the domains (4 to 50% average improvements) and that TML features generally outperformed intrinsic features. Use of TML also enhances scientific understanding through explainable ML. In drug design, we found that TML provided insight into drug target specificity, the relationships between drugs, and the relationships between target proteins. TML leads to an ecosystem-based approach to ML, where new tasks, examples, predictions, and so on synergistically interact to improve performance. To contribute to this ecosystem, all our data, code, and our ∼50,000 ML models have been fully annotated with metadata, linked, and openly published using Findability, Accessibility, Interoperability, and Reusability principles (∼100 Gbytes).

Leukotriene E4 induces airflow obstruction and mast cell activation through the cysteinyl leukotriene type 1 receptor.

BACKGROUND: Leukotriene (LT) E4 is the final active metabolite among the cysteinyl leukotrienes (CysLTs). Animal studies have identified a distinct LTE4 receptor, suggesting that current cysteinyl leukotriene type 1 (CysLT1) receptor antagonists can provide incomplete inhibition of CysLT responses. OBJECTIVE: We tested this hypothesis by assessing the influence of the CysLT1 antagonist montelukast on responses induced by means of inhalation of LTE4 in asthmatic patients. METHODS: Fourteen patients with mild intermittent asthma and 2 patients with aspirin-exacerbated respiratory disease received 20 mg of montelukast twice daily and placebo for 5 to 7 days in a randomized, double-blind, crossover study (NCT01841164). The PD20 value was determined at the end of each treatment period based on an increasing dose challenge. Measurements included lipid mediators in urine and sputum cells 4 hours after LTE4 challenge. RESULTS: Montelukast completely blocked LTE4-induced bronchoconstriction. Despite tolerating an at least 10 times higher dose of LTE4 after montelukast, there was no difference in the percentage of eosinophils in sputum. Urinary excretion of all major lipid mediators increased after LTE4 inhalation. Montelukast blocked release of the mast cell product prostaglandin (PG) D2, as well as release of PGF2α and thromboxane (Tx) A2, but not increased excretion of PGE2 and its metabolites or isoprostanes. CONCLUSION: LTE4 induces airflow obstruction and mast cell activation through the CysLT1 receptor.

Temperature, but not pH, compromises sea urchin fertilization and early development under near-future climate change scenarios.

Global warming is causing ocean warming and acidification. The distribution of Heliocidaris erythrogramma coincides with the eastern Australia climate change hot spot, where disproportionate warming makes marine biota particularly vulnerable to climate change. In keeping with near-future climate change scenarios, we determined the interactive effects of warming and acidification on fertilization and development of this echinoid. Experimental treatments (20-26 degrees C, pH 7.6-8.2) were tested in all combinations for the 'business-as-usual' scenario, with 20 degrees C/pH 8.2 being ambient. Percentage of fertilization was high (>89%) across all treatments. There was no difference in percentage of normal development in any pH treatment. In elevated temperature conditions, +4 degrees C reduced cleavage by 40 per cent and +6 degrees C by a further 20 per cent. Normal gastrulation fell below 4 per cent at +6 degrees C. At 26 degrees C, development was impaired. As the first study of interactive effects of temperature and pH on sea urchin development, we confirm the thermotolerance and pH resilience of fertilization and embryogenesis within predicted climate change scenarios, with negative effects at upper limits of ocean warming. Our findings place single stressor studies in context and emphasize the need for experiments that address ocean warming and acidification concurrently. Although ocean acidification research has focused on impaired calcification, embryos may not reach the skeletogenic stage in a warm ocean.

Hydrolysis of a sulfonamide by a novel elimination mechanism generated by carbanion formation in the leaving group.

The alkaline hydrolysis of N-alpha-methoxycarbonyl benzyl-beta-sultam occurs 10(3) times faster than the corresponding carboxylate and with rapid D-exchange at the alpha-carbon: the pH rate profile indicates pre-equilibirum CH ionisation and together with formation of benzoyl formate as a product this suggests a novel mechanism for hydrolysis.