SDN-based time-domain error correction for in-network video QoE estimation in wireless networks

Our previous study proposed a channel utilization method in Software-Defined Networking (SDN) enabled multi-channel wireless mesh network (SD-WMN), which utilizes all of channel resources efficiently. However, when different types of applications are transferred together, their QoE cannot be maintained because of differences in important factors affecting QoE among these applications. Therefore, in order to handle application flows more efficiently based on QoE, this paper focuses on QoE estimation for every ongoing flows through SD-WMN. Since some parameters required for QoE calculation cannot be obtained from OpenFlow, we estimate QoE based on not only the results from SDN-based measurement but also the estimated values of parameters. Finally, we showed that our proposed method is effective for video QoE estimation, especially in a case where there is no packet loss.11th International Conference on Intelligent Networking and Collaborative Systems(INCoS 2019), September 5-7, 2019, Oita, Japa

Fate of Polycyclic Aromatic Hydrocarbons and Radionuclides through Loess over Pan-Japan Sea Area -Reaction, Transportation and Deposition-

金沢大学大学院自然科学研究科金沢大学工学部Nankai, UniversityChinese Academy of SciencesScedule:17-18 March 2003, Vemue: Kanazawa, Japan, Kanazawa Citymonde Hotel, Project Leader : Hayakawa, Kazuichi, Symposium Secretariat: XO kamata, Naoto, Edited by:Kamata, Naoto

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

SDN-Based Time-Domain Error Correction for In-Network Video QoE Estimation in Wireless Networks

Our previous study proposed a channel utilization method in Software-Defined Networking (SDN) enabled multi-channel wireless mesh network (SD-WMN), which utilizes all of channel resources efficiently. However, when different types of applications are transferred together, their QoE cannot be maintained because of differences in important factors affecting QoE among these applications. Therefore, in order to handle application flows more efficiently based on QoE, this paper focuses on QoE estimation for every ongoing flows through SD-WMN. Since some parameters required for QoE calculation cannot be obtained from OpenFlow, we estimate QoE based on not only the results from SDN-based measurement but also the estimated values of parameters. Finally, we showed that our proposed method is effective for video QoE estimation, especially in a case where there is no packet loss.11th International Conference on Intelligent Networking and Collaborative Systems(INCoS 2019), September 5-7, 2019, Oita, Japa