The properties of electron transport through CNT/trans-PA/CNT system

Abstract Using a tight-binding model and a tranfer-matrix technique, we numerically investigate the effects of the coupling strength, and the length of the molecule on the electronic transmission through a CNT/(single) molecule/CNT system. With trans-polyacetylene (trans-PA) as the molecule sandwiched between two semi-infinite carbon nanotube(CNT), we rely on Landauer formalism as the basis for studying the conductance properties of this system. Our calculations show that the conductance is sensitive to the CNT/molecule coupling and that it exponentially decreases with the increase in the length of the molecule, as expected

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Decreasing of the activation energy of TiO2 nanoparticles by applying ultrasound waves using the sol-gel method

 In this letter, titanium dioxide nanoparticles (TiO2) were synthesized via a sol-gel method and combining titanium tetrachloride (TiCl4) and ethanol. The activation energy was investigated on the phase transformation from anatase to rutile in the presence and absence of ultrasound waves. The anatase nanocrystallites were only crystallized up to the calcination of 500 º C. By increasing the calcination in the region after 500 º C, rutile nanocrystallites grew in samples, and mixed-phase TiO2 nanoparticles were obtained. Our results show that applying ultrasound waves decreases both onset transition temperature and the activation energy of the phase transformation from anatase to rutile. The activation energy showed a considerable reduction at about 18.5 KJ/mol by applying the ultrasound waves

The properties of electron transport through CNT/trans-PA/CNT system

Using a tight-binding model and a tranfer-matrix technique, we numerically investigate the effects of the coupling strength, and the length of the molecule on the electronic transmission through a CNT/(single) molecule/CNT system. With trans-polyacetylene (trans-PA) as the molecule sandwiched between two semi-infinite carbon nanotube(CNT), we rely on Landauer formalism as the basis for studying the conductance properties of this system. Our calculations show that the conductance is sensitive to the CNT/molecule coupling and that it exponentially decreases with the increase in the length of the molecule, as expected

Enhancing both methylene blue photocatalytic degradation and ethanol sensing performances of ZnO rGO nanocomposite through the variation of GO amount

In the present work, mesoporous ZnO reduced graphene oxide rGO nanocomposites were successfully synthesized using a facile and environment friendly hydrothermal method. The ZnO rGO nanocomposites were characterized through a broad range of characterization techniques such as X ray diffraction, field emission scanning electron microscopy, energy dispersive X ray spectroscopy, X ray photoelectron spectroscopy, Brunauer Emmett Teller analysis, Raman and photoluminescence spectroscopy. ZnO rGO nanocomposites exhibited enhanced photocatalytic activity towards decomposing methylene blue MB dye under a low power ultraviolet light 8 W . In these conditions an almost complete removal of dye 99.66 was achieved within 100 min for the sample with more value of GO compared to 78.36 for pure ZnO . We also explored the use of ZnO rGO nanocomposites deposited on gold electrodes for the fabrication of ethanol vapor sensors. An excellent sensing ability was observed in its high response for the selected sample 110.11 toward 100 ppm ethanol vapor in comparison with 14.54 for pristine ZnO , very low response recovery time below 4 s , good selectivity and ultralow estimated detection limit of about 27 ppb which makes it a prospective use in gas sensors. As a result of the overall analysis, the formation of ZnO rGO nanocomposite can considerably improve the photocatalytic and gas sensing properties of ZnO and thus can be used for various applications such as environmental consideration