Demixing in binary mixtures with differential diffusivity at high density

Spontaneous phase separation, or demixing, is important in biological phenomena such as cell sorting. In particle-based models, an open question is whether differences in diffusivity can drive such demixing. While differential-diffusivity-induced phase separation occurs in mixtures with a packing fraction up to $0.7$ [Weber et al. Phys Rev Lett 2016], here we investigate whether demixing persists at even higher densities relevant for cells. For particle packing fractions between $0.7$ and $1.0$ the system demixes, but at packing fractions above unity the system remains mixed, exposing re-entrant behavior in the phase diagram. We also find that a confluent Voronoi model for tissues does not phase separate, consistent with the highest-density particle-based simulations.Comment: 4 pages, plus 4 page supplemental material

Improved infrared photoluminescence characteristics from circularly ordered self-assembled Ge islands

The formation of circularly ordered Ge-islands on Si(001) has been achieved because of nonuniform strain field around the periphery of the holes patterned by focused ion beam in combination with a self-assembled growth using molecular beam epitaxy. The photoluminescence (PL) spectra obtained from patterned areas (i.e., ordered islands) show a significant signal enhancement, which sustained till 200 K, without any vertical stacking of islands. The origin of two activation energies in temperature-dependent PL spectra of the ordered islands has been explained in detail

Excess energy of an ultracold Fermi gas in a trapped geometry

We have analytically explored finite size and interparticle interaction corrections to the average energy of a harmonically trapped Fermi gas below and above the Fermi temperature, and have obtained a better fitting for the excess energy reported by DeMarco and Jin [Science $\textbf{285}$, 1703 (1999)]. We have presented a perturbative calculation within a mean field approximation.Comment: 8 pages, 4 figures; Accepted in European Physical Journal

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Synthesis, characterization, and thermal property measurement of nano-Al(95)Zn(05) dispersed nanofluid prepared by a two-step process

Nanofluids are stable suspension of nanometer sized particles and exhibit extremely attractive thermal properties that make them a potential candidate for application in heat transfer devices ranging from microelectronic gadgets to thermal power plants. In the present study, we have synthesized Al-5wt%Zn nanoparticles by mechanical alloying, characterized these nanoparticles using X-ray diffraction and scanning and transmission electron microscopy. Subsequently, these nanoparticles are dispersed to the tune of 0.01-0.10 vol% in ethylene glycol (base fluid) following a careful mixing protocol. Thermal conductivity of the nanofluids and base fluid has been measured using the transient hot-wire method. It is observed that thermal conductivity of the nanofluids strongly depend on the concentration, particle size, fluid temperature and stability of dispersed nanoparticles in the base fluid. A maximum of 16% enhancement in thermal conductivity has been recorded at a nanoparticle loading of 0.10 vol%. Unlike data reported in some articles, thermal conductivity ratio of Al-5wt%Zn dispersed ethylene glycol based nanofluids is observed to decrease with the increase in crystallite/grain size of the particles. (C) 2011 Elsevier Ltd. All rights reserved

Synthesis, characterization, and thermal property measurement of nano-Al<SUB>95</SUB>Zn<SUB>05</SUB> dispersed nanofluid prepared by a two-step process

Nanofluids are stable suspension of nanometer sized particles and exhibit extremely attractive thermal properties that make them a potential candidate for application in heat transfer devices ranging from microelectronic gadgets to thermal power plants. In the present study, we have synthesized Al-5wt%Zn nanoparticles by mechanical alloying, characterized these nanoparticles using X-ray diffraction and scanning and transmission electron microscopy. Subsequently, these nanoparticles are dispersed to the tune of 0.01-0.10 vol% in ethylene glycol (base fluid) following a careful mixing protocol. Thermal conductivity of the nanofluids and base fluid has been measured using the transient hot-wire method. It is observed that thermal conductivity of the nanofluids strongly depend on the concentration, particle size, fluid temperature and stability of dispersed nanoparticles in the base fluid. A maximum of 16% enhancement in thermal conductivity has been recorded at a nanoparticle loading of 0.10 vol%. Unlike data reported in some articles, thermal conductivity ratio of Al-5wt%Zn dispersed ethylene glycol based nanofluids is observed to decrease with the increase in crystallite/grain size of the particles