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Deforestation has converted swaths of land in the southern Amazon region from rainforest to farmland. The uses of the deforested land are diverse, and activities can range from small-scale farming in rural settlements to large-scale commodity agriculture. Commercial farms in the Southern Amazon can reach hundreds of thousands of hectares in area, exporting millions of tons in grains and beef every year.

Now, a team of researchers at Osaka University has used flake-shaped Si nanopowder wrapped by ultrathin graphite sheets (GSs) to fabricate LIB electrodes with high areal capacity and current density. Generally treated as industrial waste, Si swarf is generated at a rate of 100,000 tons per year globally from Si ingots that are produced from silica through processes at 1000~1800°C. Water-based coolants and fixed abrasive grain wire saws are paving the way to the use of Si swarf as an anode active material with a high capacity at a reduced cost.

Antarctic iceberg melt could hold the key to the activation of a series of mechanisms that cause the Earth to suffer prolonged periods of global cooling, according to Francisco J. Jiménez-Espejo, a researcher at the Andalusian Earth Sciences Institute (CSIC-UGR), whose discoveries were recently published in Nature.

Now, a research group under the leadership of professor and virologist Søren Riis Paludan from the Department of Biomedicine at Aarhus University, Denmark, has identified a mechanism which is activated in the cells of the immune system when they are attacked by disease. The discovery involves the protein STING, which sends signals to the nucleus of the cell when an infection threatens.

In the flagship article, The ENCODE Project Consortium et al.5 provide a bird's-eye view of the updated encyclopedia, which contains newly added data sets from 6,000 experiments, performed on around 1,300 samples. By integrating these data sets, the consortium has created an online registry of candidate CREs. Most are classified as promoters or enhancers - CREs respectively located at or some distance from the genomic site at which transcription of a gene begins. The consortium tracked the activity of each candidate CRE, along with the proteins that bind to it in many different samples from various tissues. They used chromatin-looping data to link enhancers to genes that they might regulate. This online registry marks a true milestone, turning an overwhelming amount of genomic information into a searchable, filterable and retrievable encyclopedia of DNA elements, which is freely accessible at https://screen.encodeproject.org.

Athena Akrami's neuroscience lab reopened last month without her. Life for the 38-year-old is a pale shadow of what it was before 17 March, the day she first experienced symptoms of the novel coronavirus. At University College London (UCL), Akrami's students probe how the brain organizes memories to support learning, but at home, she struggles to think clearly and battles joint and muscle pain. "I used to go to the gym three times a week," Akrami says. Now, "My physical activity is bed to couch, maybe couch to kitchen." Her early symptoms were textbook for COVID-19: a fever and cough, followed by shortness of breath, chest pain, and extreme fatigue. For weeks, she struggled to heal at home. But rather than ebb with time, Akrami's symptoms waxed and waned without ever going away. She's had just 3 weeks since March when her body temperature was normal.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in thousands of deaths in the world. Information about prediction model of prognosis of SARS-CoV-2 infection is scarce. We used machine learning for processing laboratory findings of 110 patients with SARS-CoV-2 pneumonia (including 51 non-survivors and 59 discharged patients). The maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator logistic regression model were used for selection of laboratory features. Seven laboratory features selected in the model were: prothrombin activity, urea, white blood cell, interleukin-2 receptor, indirect bilirubin, myoglobin, and fibrinogen degradation products. The signature constructed using the seven features had 98% [93%, 100%] sensitivity and 91% [84%, 99%] specificity in predicting outcome of SARS-CoV-2 pneumonia. Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings.

For protein molecules that contribute to metabolism, interactions with other components of their metabolic pathway can be crucial. Scientists at the Max Planck Institute for Developmental Biology in Tübingen have now investigated a natural enzyme complex that comprises 10 enzymes with five distinct activities. They found that the molecular architecture is surprisingly compact, yet offers individual enzymes maximum free moving space, which opens up novel perspectives for drug discovery. The scientists have published their results in Nature Chemical Biology.

Goal: The purpose of this article is to introduce a new strategy to identify areas with high human density and mobility, which are at risk for spreading COVID-19. Crowded regions with actively moving people (called at-risk regions) are susceptible to spreading the disease, especially if they contain asymptomatic infected people together with healthy people. Methods: Our scheme identifies at-risk regions using existing cellular network functionalities-handover and cell (re)selection-used to maintain seamless coverage for mobile end-user equipment (UE). The frequency of handover and cell (re)selection events is highly reflective of the density of mobile people in the area because virtually everyone carries UEs. Results: These measurements, which are accumulated over very many UEs, allow us to identify the at-risk regions without compromising the privacy and anonymity of individuals. Conclusions: The inferred at-risk regions can then be subjected to further monitoring and risk mitigation.