Advancements in the Epsilon Launch Vehicle\u27s Rideshare Capability and Future Missions

Fifth Epsilon launch vehicle (Epsilon-5) with Innovative Satellite Technology Demonstration-2 was successfully launched from JAXA Uchinoura Space Center in Kagoshima, Japan on November 9, 2021. Successful injection of nine satellites with high accuracy demonstrated the capability of Epsilon launch vehicle for rideshare missions of various satellite sizes. The new Epsilon Satellite Mount Structure-II (ESMS-II) and an adapter was developed to launch more satellites. In the paper, we first introduce Epsilon launch vehicle and its multi-launch capability. Then, we describe the mission design of Epsilon-5 and rideshare specific configuration. Finally, we mention the rideshare opportunity provided by Epsilon launch vehicle in the future

JRAB/MICAL-L2 undergoes liquid–liquid phase separation to form tubular recycling endosomes

Elongated tubular endosomes play essential roles in diverse cellular functions. Multiple molecules have been implicated in tubulation of recycling endosomes, but the mechanism of endosomal tubule biogenesis has remained unclear. In this study, we found that JRAB/MICAL-L2 induces endosomal tubulation via activated Rab8A. In association with Rab8A, JRAB/MICAL-L2 adopts its closed form, which functions in the tubulation of recycling endosomes. Moreover, JRAB/MICAL-L2 induces liquid–liquid phase separation, initiating the formation of tubular recycling endosomes upon overexpression. Between its N-terminal and C-terminal globular domains, JRAB/MICAL-L2 contains an intrinsically disordered region, which contributes to the formation of JRAB/MICAL-L2 condensates. Based on our findings, we propose that JRAB/MICAL-L2 plays two sequential roles in the biogenesis of tubular recycling endosomes: first, JRAB/MICAL-L2 organizes phase separation, and then the closed form of JRAB/MICAL-L2 formed by interaction with Rab8A promotes endosomal tubulation

Population pharmacokinetic modeling of GS‐441524, the active metabolite of remdesivir, in Japanese COVID‐19 patients with renal dysfunction

腎障害患者におけるレムデシビルの薬物動態モデルを構築 --新型コロナウイルス感染症治療薬の適正使用に向けて--. 京都大学プレスリリース. 2021-11-25.Remdesivir, a prodrug of the nucleoside analog GS-441524, plays a key role in the treatment of coronavirus disease 2019 (COVID-19). However, owing to limited information on clinical trials and inexperienced clinical use, there is a lack of pharmacokinetic (PK) data in patients with COVID-19 with special characteristics. In this study, we aimed to measure serum GS-441524 concentrations and develop a population PK (PopPK) model. Remdesivir was administered at a 200 mg loading dose on the first day followed by 100 mg from day 2, based on the package insert, in patients with an estimated glomerular filtration rate (eGFR) greater than or equal to 30 ml/min. In total, 190 concentrations from 37 Japanese patients were used in the analysis. The GS-441524 trough concentrations were significantly higher in the eGFR less than 60 ml/min group than in the eGFR greater than or equal to 60 ml/min group. Extracorporeal membrane oxygenation in four patients hardly affected the total body clearance (CL) and volume of distribution (Vd) of GS-441524. A one-compartment model described serum GS-441524 concentration data. The CL and Vd of GS-441524 were significantly affected by eGFR readjusted by individual body surface area and age, respectively. Simulations proposed a dose regimen of 200 mg on day 1 followed by 100 mg once every 2 days from day 2 in patients with an eGFR of 30 ml/min or less. In conclusion, we successfully established a PopPK model of GS-441524 using retrospectively obtained serum GS-441524 concentrations in Japanese patients with COVID-19, which would be helpful for optimal individualized therapy of remdesivir

Combined landscape of single-nucleotide variants and copy number alterations in clonal hematopoiesis

クローン性造血の臨床予後への影響を解明 --遺伝子変異とコピー数異常の統合的な知見--. 京都大学プレスリリース. 2021-07-09.Clonal hematopoiesis (CH) in apparently healthy individuals is implicated in the development of hematological malignancies (HM) and cardiovascular diseases. Previous studies of CH analyzed either single-nucleotide variants and indels (SNVs/indels) or copy number alterations (CNAs), but not both. Here, using a combination of targeted sequencing of 23 CH-related genes and array-based CNA detection of blood-derived DNA, we have delineated the landscape of CH-related SNVs/indels and CNAs in 11, 234 individuals without HM from the BioBank Japan cohort, including 672 individuals with subsequent HM development, and studied the effects of these somatic alterations on mortality from HM and cardiovascular disease, as well as on hematological and cardiovascular phenotypes. The total number of both types of CH-related lesions and their clone size positively correlated with blood count abnormalities and mortality from HM. CH-related SNVs/indels and CNAs exhibited statistically significant co-occurrence in the same individuals. In particular, co-occurrence of SNVs/indels and CNAs affecting DNMT3A, TET2, JAK2 and TP53 resulted in biallelic alterations of these genes and was associated with higher HM mortality. Co-occurrence of SNVs/indels and CNAs also modulated risks for cardiovascular mortality. These findings highlight the importance of detecting both SNVs/indels and CNAs in the evaluation of CH

Integrating Statistical Predictions and Experimental Verifications for Enhancing Protein-Chemical Interaction Predictions in Virtual Screening

Predictions of interactions between target proteins and potential leads are of great benefit in the drug discovery process. We present a comprehensively applicable statistical prediction method for interactions between any proteins and chemical compounds, which requires only protein sequence data and chemical structure data and utilizes the statistical learning method of support vector machines. In order to realize reasonable comprehensive predictions which can involve many false positives, we propose two approaches for reduction of false positives: (i) efficient use of multiple statistical prediction models in the framework of two-layer SVM and (ii) reasonable design of the negative data to construct statistical prediction models. In two-layer SVM, outputs produced by the first-layer SVM models, which are constructed with different negative samples and reflect different aspects of classifications, are utilized as inputs to the second-layer SVM. In order to design negative data which produce fewer false positive predictions, we iteratively construct SVM models or classification boundaries from positive and tentative negative samples and select additional negative sample candidates according to pre-determined rules. Moreover, in order to fully utilize the advantages of statistical learning methods, we propose a strategy to effectively feedback experimental results to computational predictions with consideration of biological effects of interest. We show the usefulness of our approach in predicting potential ligands binding to human androgen receptors from more than 19 million chemical compounds and verifying these predictions by in vitro binding. Moreover, we utilize this experimental validation as feedback to enhance subsequent computational predictions, and experimentally validate these predictions again. This efficient procedure of the iteration of the in silico prediction and in vitro or in vivo experimental verifications with the sufficient feedback enabled us to identify novel ligand candidates which were distant from known ligands in the chemical space

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

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

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049