| 1. |
- Namkoong, H, et al.
(författare)
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DOCK2 is involved in the host genetics and biology of severe COVID-19
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 609:7928, s. 754-
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Tidskriftsartikel (refereegranskat)abstract
- Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1–5. 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.
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| 2. |
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| 3. |
- Wang, QBS, et al.
(författare)
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The whole blood transcriptional regulation landscape in 465 COVID-19 infected samples from Japan COVID-19 Task Force
- 2022
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1, s. 4830-
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 4. |
- Abe, K., et al.
(författare)
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Neutron tagging following atmospheric neutrino events in a water Cherenkov detector
- 2022
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Ingår i: Journal of Instrumentation. - : Institute of Physics (IOP). - 1748-0221. ; 17:10
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Tidskriftsartikel (refereegranskat)abstract
- We present the development of neutron-tagging techniques in Super-Kamiokande IV using a neural network analysis. The detection efficiency of neutron capture on hydrogen is estimated to be 26%, with a mis-tag rate of 0.016 per neutrino event. The uncertainty of the tagging efficiency is estimated to be 9.0%. Measurement of the tagging efficiency with data from an Americium-Beryllium calibration agrees with this value within 10%. The tagging procedure was performed on 3,244.4 days of SK-IV atmospheric neutrino data, identifying 18,091 neutrons in 26,473 neutrino events. The fitted neutron capture lifetime was measured as 218 +/- 9 mu s.
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| 5. |
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| 6. |
- Tanaka, Y. K., et al.
(författare)
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Search for eta '-mesic nuclei using (p,d) reaction with FRS/Super-FRS at GSI/FAIR
- 2020
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Ingår i: Journal of Physics, Conference Series. - : IOP Publishing. - 1742-6588 .- 1742-6596. ; 1643
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Tidskriftsartikel (refereegranskat)abstract
- We plan a semi-exclusive measurement of the C-12(p,dp) reaction to search for eta'-mesic nuclei, aiming at investigating in-medium properties of the eta'-meson. We employ a 2.5 GeV proton beam impinging on a carbon target to produce eta'-mesic C-11 nuclei via the C-12(p,d)eta'circle times C-11 reaction. Using coincidence measurements of the forward going deuterons, important for missing-mass spectroscopy, and decay protons emitted from the eta'-mesic nuclei for event selection will provide a high experimental sensitivity to observe eta'-mesic nuclei. We will perform the measurements by combining the WASA detector system with the fragment separator FRS at GSI and also with the Super-FRS at FAIR in the future. The plan of the experiments and the present status are reported.
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| 7. |
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| 8. |
- Alfaray, R. I., et al.
(författare)
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Global Antimicrobial Resistance Gene Study of Helicobacter pylori: Comparison of Detection Tools, ARG and Efflux Pump Gene Analysis, Worldwide Epidemiological Distribution, and Information Related to the Antimicrobial-Resistant Phenotype
- 2023
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Ingår i: Antibiotics-Basel. - 2079-6382. ; 12:7
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Tidskriftsartikel (refereegranskat)abstract
- We conducted a global-scale study to identify H. pylori antimicrobial-resistant genes (ARG), address their global distribution, and understand their effect on the antimicrobial resistance (AMR) phenotypes of the clinical isolates. We identified ARG using several well-known tools against extensive bacterial ARG databases, then analyzed their correlation with clinical antibiogram data from dozens of patients across countries. This revealed that combining multiple tools and databases, followed by manual selection of ARG from the annotation results, produces more conclusive results than using a single tool or database alone. After curation, the results showed that H. pylori has 42 ARG against 11 different antibiotic classes (16 genes related to single antibiotic class resistance and 26 genes related to multidrug resistance). Further analysis revealed that H. pylori naturally harbors ARG in the core genome, called the 'Set of ARG commonly found in the Core Genome of H. pylori (ARG-CORE)', while ARG-ACC-the ARG in the accessory genome-are exclusive to particular strains. In addition, we detected 29 genes of potential efflux pump-related AMR that were mostly categorized as ARG-CORE. The ARG distribution appears to be almost similar either by geographical or H. pylori populations perspective; however, some ARG had a unique distribution since they tend to be found only in a particular region or population. Finally, we demonstrated that the presence of ARG may not directly correlate with the sensitive/resistance phenotype of clinical patient isolates but may influence the minimum inhibitory concentration phenotype.
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| 9. |
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| 10. |
- Kang, JS, et al.
(författare)
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Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning
- 2020
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1, s. 20140-
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Tidskriftsartikel (refereegranskat)abstract
- Most models for predicting malignant pancreatic intraductal papillary mucinous neoplasms were developed based on logistic regression (LR) analysis. Our study aimed to develop risk prediction models using machine learning (ML) and LR techniques and compare their performances. This was a multinational, multi-institutional, retrospective study. Clinical variables including age, sex, main duct diameter, cyst size, mural nodule, and tumour location were factors considered for model development (MD). After the division into a MD set and a test set (2:1), the best ML and LR models were developed by training with the MD set using a tenfold cross validation. The test area under the receiver operating curves (AUCs) of the two models were calculated using an independent test set. A total of 3,708 patients were included. The stacked ensemble algorithm in the ML model and variable combinations containing all variables in the LR model were the most chosen during 200 repetitions. After 200 repetitions, the mean AUCs of the ML and LR models were comparable (0.725 vs. 0.725). The performances of the ML and LR models were comparable. The LR model was more practical than ML counterpart, because of its convenience in clinical use and simple interpretability.
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