On the direct evaluation of the equilibrium distribution of clusters by simulation

An expression is derived that relates the average population of a particular type of cluster in a metastable vapor phase of volume Vtot to the probability, estimated by simulation, of finding this cluster in a system of volume V taken inside Vtot, where V<<Vtot. Correct treatment of the translational free energy of the cluster is crucial for this purpose. We show that the problem reduces to one of devising the proper boundary condition for the simulation. We then verify the result obtained previously for a low vapor density limit [J. Chem. Phys. 108, 3416 (1998)]. The difficulty implicit in our recent calculation [J. Chem. Phys. 110, 5249 (1999)], in which the approach in the former was generalized to higher vapor densities, is shown to be resolved by a method already suggested in that paper

On the direct evaluation of the equilibrium distribution of clusters by simulation. II

We clarify some of the subtle issues surrounding the observational cluster method, a simulation technique for studying nucleation. The validity of the method is reaffirmed here. The condition of the compact cluster limit is quantified and its implications are elucidated in terms of the correct enumeration of configuration space

The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force

「コロナ制圧タスクフォース」COVID-19患者由来の血液細胞における遺伝子発現の網羅的解析 --重症度に応じた遺伝子発現の変化には、ヒトゲノム配列の個人差が影響する--. 京都大学プレスリリース. 2022-08-23.Coronavirus disease 2019 (COVID-19) is a recently-emerged infectious disease that has caused millions of deaths, where comprehensive understanding of disease mechanisms is still unestablished. In particular, studies of gene expression dynamics and regulation landscape in COVID-19 infected individuals are limited. Here, we report on a thorough analysis of whole blood RNA-seq data from 465 genotyped samples from the Japan COVID-19 Task Force, including 359 severe and 106 non-severe COVID-19 cases. We discover 1169 putative causal expression quantitative trait loci (eQTLs) including 34 possible colocalizations with biobank fine-mapping results of hematopoietic traits in a Japanese population, 1549 putative causal splice QTLs (sQTLs; e.g. two independent sQTLs at TOR1AIP1), as well as biologically interpretable trans-eQTL examples (e.g., REST and STING1), all fine-mapped at single variant resolution. We perform differential gene expression analysis to elucidate 198 genes with increased expression in severe COVID-19 cases and enriched for innate immune-related functions. Finally, we evaluate the limited but non-zero effect of COVID-19 phenotype on eQTL discovery, and highlight the presence of COVID-19 severity-interaction eQTLs (ieQTLs; e.g., CLEC4C and MYBL2). Our study provides a comprehensive catalog of whole blood regulatory variants in Japanese, as well as a reference for transcriptional landscapes in response to COVID-19 infection

DOCK2 is involved in the host genetics and biology of severe COVID-19

「コロナ制圧タスクフォース」COVID-19疾患感受性遺伝子DOCK2の重症化機序を解明 --アジア最大のバイオレポジトリーでCOVID-19の治療標的を発見--. 京都大学プレスリリース. 2022-08-10.Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge. Here we conducted a genome-wide association study (GWAS) involving 2, 393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3, 289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target

Molecular theory of vapor phase nucleation

An attempt has been made to establish the foundation of molecular level theory of vapor phase nucleation. We have focused on evaluating the reversible work of cluster formation and followed two major trends in this direction, namely, statistical mechanical density functional theory and molecular level simulation. We applied density functional theory to heterogeneous nucleation onto an ion. Our prime interest is to predict a sign preference of nucleation rate, which has been experimentally observed yet remained inexplicable in the classical framework. The theory indicates that asymmetry in ion-molecule interaction is directly responsible for the sign preference. The predicted sign dependence decreases as the supersaturation is increased. Our results from density functional theory agree well with the existing experimental observations. Molecular simulation offers an alternative to molecular level approach. A long-standing issue of fundamental importance in cluster simulation is the precise definition of a cluster. Thus far, all attempts of defining a cluster had introduced ad hoc criteria to determine unambiguously whether a given molecule in the system belongs to vapor or to a cluster for any instantaneous configuration of molecules. From a careful examination of the context in which a cluster should be introduced into nucleation theory, we conclude that such a criterion is unnecessary. Then, we present a new approach to cluster simulation which is free of any arbitrariness involved in the definition of a cluster. Instead, it preferentially and automatically generates the physical clusters, defined as the density fluctuations that lead to nucleation, and determines their equilibrium distribution in a single simulation. The latter feature permits one to completely bypass the computationally demanding free energy evaluation that is necessary in a conventional simulation. The method is applied first to water using the SPC/E model. We then turn to H2SO4/H2O binary system to obtain a large section of the reversible work surface. The resulting surface is markedly different from that in classical theory and indicates that the rate limiting step of stable particle formation in this system is the binary collision of the sulfuric acid hydrates

Statistical Mechanics for Engineers

The purpose of writing this book is to explain basic concepts of equilibrium statistical mechanics to the ?rst year graduate students in engineering departments. Why should an engineer care about statistical mechanics? Historically, statistical mechanics evolved out of the desire to explain thermodynamics from fundamental laws of physics governing behavior of atoms and molecules. If a microscopic interpretation of the laws of thermodynamics were the only outcome of this branch of science, statistical mechanics would not appeal to those of us who simply wish to use thermodynamics to perform practical calculations. After all, validity of thermodynamics has long been established. In thermodynamics, a concept of fundamental equations plays a prominent role. From one such equation many profound predictions follow in a completely general fashion. However, thermodynamics itself does not predict the explicit form of this function.Instead,thefundamentalequationmustbedeterminedempiricallyforeach system of our interest. Being a science built on a set of macroscopic observations, thermodynamicsdoesnotofferanysystematicwayofincorporatingmolecularlevel information, either. Thus, an approach based solely on thermodynamics is not suf?cient if we hope to achieve desired materials properties through manipulation of nanoscale features and/or molecular level architecture of materials