The COVID‐19 pandemic has taken a significant toll on people worldwide, and there are currently no specific antivirus drugs or vaccines. Herein it is a therapeutic based on catalase, an antioxidant enzyme that can effectively breakdown hydrogen peroxide and minimize the downstream reactive oxygen species, which are excessively produced resulting from the infection and inflammatory process, is reported. Catalase assists to regulate production of cytokines, protect oxidative injury, and repress replication of SARS‐CoV‐2, as demonstrated in human leukocytes and alveolar epithelial cells, and rhesus macaques, without noticeable toxicity. Such a therapeutic can be readily manufactured at low cost as a potential treatment for COVID‐19.

Needle-less TEA at ST36 using a watch-size stimulator is able to improve stress-induced impairment in gastric slow waves, possibly mediated via the autonomic mechanism. Home-based needle-less TEA may be a viable therapy for stress-induced impairment in gastric motility functions.

Pancreatic fistulae and abdominal infections are associated with PPH. Control of early mild upper gastrointestinal hemorrhages could be attempted by endotherapy, but angiography with intervention or surgical treatments were always required for delayed bleeding. The mortality in cases with sentinel bleedings was obviously increased.

Context: Evolutionary algorithms typically require large number of evaluations (of solutions) to converge -which can be very slow and expensive to evaluate. Objective: To solve search-based software engineering (SE) problems, using fewer evaluations than evolutionary methods. Method: Instead of mutating a small population, we build a very large initial population which is then culled using a recursive bi-clustering chop approach. We evaluate this approach on multiple SE models, unconstrained as well as constrained, and compare its performance with standard evolutionary algorithms. Results: Using just a few evaluations (under 100), we can obtain comparable results to state-of-the-art evolutionary algorithms. Conclusion: Just because something works, and is widespread use, does not necessarily mean that there is no value in seeking methods to improve that method. Before undertaking search-based SE optimization tasks using traditional EAs, it is recommended to try other techniques, like those explored here, to obtain the same results with fewer evaluations. (Tim Menzies) SE problems. However, evolutionary algorithms typically require large number of evaluations (of solutions) to converge. Real-world model-based applications may be very expensive to evaluate (with respect to computation time, resources required etc.).So, can we do better than EA for SBSE? Or, are there faster alternatives to EA? This paper experimentally evaluates one such alternative called SWAY (short for the Sampling WAY):1. Similar to a standard EA, generate an initial population; 2. Intelligently select a cluster within the population generated with best scores.SWAY runs so fast since it terminates after just O(l g N ) evaluations of N candidate solutions. SWAY's intelligent selection mechanism for exploring subsets of the population is a recursive binary chop that (i) finds and evaluates only the two most dissimilar examples, then (ii) recurses only on half of the data containing the better among its similar example. As shown later in this paper, for this process to work, it is important to have the right definition of "dissimilar". Note the differences between SWAY and standard EA:1. SWAY quits after the initial generation while EA reasons over multiple generations;2. SWAY makes no use of reproduction operators so there is no way for lessons learned to accumulate as it executes;3. Depending on the algorithm, not all members of the population will be evaluated -e.g. active learners [34] only evaluate a few representative individuals.Because of the limited nature of this search, until recently, we would have dismissed SWAY as comparatively less effective

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Marine microalgae are regarded as potential feedstock because of their multiple valuable compounds, including lipids, pigments, carbohydrates, and proteins. Some of these compounds exhibit attractive bioactivities, such as carotenoids, ω-3 polyunsaturated fatty acids, polysaccharides, and peptides. However, the production cost of bioactive compounds is quite high, due to the low contents in marine microalgae. Comprehensive utilization of marine microalgae for multiple compounds production instead of the sole product can be an efficient way to increase the economic feasibility of bioactive compounds production and improve the production efficiency. This paper discusses the metabolic network of marine microalgal compounds, and indicates their interaction in biosynthesis pathways. Furthermore, potential applications of co-production of multiple compounds under various cultivation conditions by shifting metabolic flux are discussed, and cultivation strategies based on environmental and/or nutrient conditions are proposed to improve the co-production. Moreover, biorefinery techniques for the integral use of microalgal biomass are summarized. These techniques include the co-extraction of multiple bioactive compounds from marine microalgae by conventional methods, super/subcritical fluids, and ionic liquids, as well as direct utilization and biochemical or thermochemical conversion of microalgal residues. Overall, this review sheds light on the potential of the comprehensive utilization of marine microalgae for improving bioeconomy in practical industrial application.

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