Nanosecond heme-to-heme electron transfer rates in a multiheme cytochrome nanowire reported by a spectrally unique His/Met-ligated heme.

Proteins achieve efficient energy storage and conversion through electron transfer along a series of redox cofactors. Multiheme cytochromes are notable examples. These proteins transfer electrons over distance scales of several nanometers to >10 μm and in so doing they couple cellular metabolism with extracellular redox partners including electrodes. Here, we report pump-probe spectroscopy that provides a direct measure of the intrinsic rates of heme-heme electron transfer in this fascinating class of proteins. Our study took advantage of a spectrally unique His/Met-ligated heme introduced at a defined site within the decaheme extracellular MtrC protein of Shewanella oneidensis We observed rates of heme-to-heme electron transfer on the order of 109 s-1 (3.7 to 4.3 Å edge-to-edge distance), in good agreement with predictions based on density functional and molecular dynamics calculations. These rates are among the highest reported for ground-state electron transfer in biology. Yet, some fall 2 to 3 orders of magnitude below the Moser-Dutton ruler because electron transfer at these short distances is through space and therefore associated with a higher tunneling barrier than the through-protein tunneling scenario that is usual at longer distances. Moreover, we show that the His/Met-ligated heme creates an electron sink that stabilizes the charge separated state on the 100-μs time scale. This feature could be exploited in future designs of multiheme cytochromes as components of versatile photosynthetic biohybrid assemblies

Ageing, adipose tissue, fatty acids and inflammation

A common feature of ageing is the alteration in tissue distribution and composition, with a shift in fat away from lower body and subcutaneous depots to visceral and ectopic sites. Redistribution of adipose tissue towards an ectopic site can have dramatic effects on metabolic function. In skeletal muscle, increased ectopic adiposity is linked to insulin resistance through lipid mediators such as ceramide or DAG, inhibiting the insulin receptor signalling pathway. Additionally, the risk of developing cardiovascular disease is increased with elevated visceral adipose distribution. In ageing, adipose tissue becomes dysfunctional, with the pathway of differentiation of preadipocytes to mature adipocytes becoming impaired; this results in dysfunctional adipocytes less able to store fat and subsequent fat redistribution to ectopic sites. Low grade systemic inflammation is commonly observed in ageing, and may drive the adipose tissue dysfunction, as proinflammatory cytokines are capable of inhibiting adipocyte differentiation. Beyond increased ectopic adiposity, the effect of impaired adipose tissue function is an elevation in systemic free fatty acids (FFA), a common feature of many metabolic disorders. Saturated fatty acids can be regarded as the most detrimental of FFA, being capable of inducing insulin resistance and inflammation through lipid mediators such as ceramide, which can increase risk of developing atherosclerosis. Elevated FFA, in particular saturated fatty acids, maybe a driving factor for both the increased insulin resistance, cardiovascular disease risk and inflammation in older adults

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p

COVID-19 and Mesenchymal Stem Cell Treatment; Mystery or Not

On December 31, 2019, novel SARS-CoV2 spread from Wuhan China to more than 200 territories around world and the World Health Organization declared a COVID-19 pandemic on January 30, 2020. At this time there is no particular therapy, drug or vaccine available to deal with COVID-19. Today actual data indicates that about 17% of closed COVID-19 cases died. Health care professionals, ministry of health in countries and the public are trying to read the runes to see when the COVID-19 pandemic will be over. Although mild cases of COVID-19 can be controlled with antiviral, anti-inflammatory and immunomodulatory treatment, severe cases may need intensive care unit support and ventilation. Cytokine storms cause high inflammatory responses and pneumonia in severe cases. Mesenchymal stem cells are immunomodulatory and they have regenerative capacity. In this sense, mesenchymal stem cells may improve the patient's clinical and immunological response to COVID-19