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Uncharted territory: the role of mitochondrial DNA variation in macrophage-mediated host susceptibility to tuberculosis

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Tuberculosis 2025年 153卷 102650-102650页

作者： Croock, Dayna Swart, Yolandi Sanko, Tomasz Janusz Mavumengwana, Vuyo Möller, Marlo Uren, Caitlin Petersen, Desiree C. South African Medical Research Council (SAMRC) Centre for Tuberculosis Research (CTR) Division of Molecular Biology and Human Genetics (MBHG) Department of Biomedical Sciences Faculty of Medicine and Health Sciences Stellenbosch University Cape Town South Africa Centre for Epidemic Response and Innovation (CERI) School of Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa Centre for Bioinformatics and Computational Biology Stellenbosch University Cape Town South Africa Genomics for Health in Africa (GHA) Africa-Europe Cluster of Research Excellence (CoRE) South Africa National Institute for Theoretical and Computational Sciences (NITheCS) South Africa South Africa

Mitochondria form an integral, yet frequently underappreciated, part of the immune response to Mycobacterium tuberculosis (***), particularly within macrophages. Despite growing recognition for their role in infection and immunity, studies investigating how mitochondrial DNA (mtDNA) variation influences host susceptibility to tuberculosis (TB) are limited. Notably, there are no studies in african-based populations, although africans possess unparalleled human genetic diversity, including the earliest diverged mitochondrial haplogroups, and a high TB burden. This underrepresentation limits the discovery of novel ancestry-specific genetic loci associated with TB. In this review article, we describe the unique characteristics of mtDNA, highlight key mitochondrial functions relevant to macrophage responses during *** infection, and summarise published studies that investigate the role of host mtDNA variation in TB susceptibility. We further advocate for the inclusion of african populations in future studies to identify novel TB susceptibility genetic risk loci and expand the current knowledgebase on host TB susceptibility. © 2025 The Authors

关键词： Mitochondria Mitochondrial DNA (mtDNA) variation Mycobacterium tuberculosis (M.tb) Tuberculosis (TB) susceptibility

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Intra-datacenter Load Balancing in a Federated Cloud with Throttled Algorithm

Intra-Datacenter Load Balancing in a Federated Cloud with Th...

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2024 International Conference on science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Akinola, Damola Gideon Adetiba, Emmanuel Abayomi, Abdultaofeek Nnaji, Uche Thakur, Surendra Moyo, Sibusiso Covenant University Covenant Applied Informatics and Communications African Center of Excellence Department of Electrical and Information Engineering Ota Nigeria Durban University of Technology HRA Institute for Systems Science Durban South Africa Mangosuthu University of Technology Department of Information and Communication Technology Durban South Africa Covenant University Dept. of Computer and Information Science Covenant Applied Informatics and Communications African Center of Excellence Ota Nigeria Durban University of Technology KZN E-Skills CoLab Durban South Africa Stellenbosch University School for Data Science and Computational Thinking Department of Mathematical Sciences Stellenbosch7602 South Africa

ISBN: (纸本)9798350358155

The emergence of cloud computing technology has motivated a very high number of users in different organizations to access its services in running and delivering their various operations and services. However, this surge of cloud users has led to the problem of uneven load sharing among the cloud computing infrastructures. As a result, federated cloud infrastructure was initiated to provide more cloud computing resources to accommodate more cloud users' requests and also to provide equal requests mapping with the available cloud resources. Nevertheless, the issue of unequal allocation of requests within the datacenter(s) that makes up the federated cloud environment still persists. This research work presents an intra-datacenter load balancing algorithm in a federated cloud environment named;the intra-balancer adapted throttled algorithm to evenly distribute requests in each datacenter that formulate the federated cloud infrastructures. The simulation of the intra-balancer was carried out in CloudAnalyst, the results of the implementation showed that the intra-balancer outperformed the Round-Robin and ESCE with 98.93ms and 2.26ms for the response and processing time respectively. The results assert that the intra-balancer algorithm provides a better load balancing solution in a federated cloud environment. © 2024 IEEE.

关键词： Cloud platforms

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Selection for Cheaper Amino Acids Drives Nucleotide Usage at the Start of Translation in Eukaryotic Genes

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Genomics, Proteomics & bioinformatics 2021年第6期19卷 949-957页

作者： Na L.Gao Zilong He Qianhui Zhu Puzi Jiang Songnian Hu Wei-Hua Chen Key Laboratory of Molecular Biophysics of the Ministry of Education Hubei Key Laboratory of Bioinformatics and Molecular-imagingDepartment of Bioinformatics and Systems BiologyCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Institute for Computer Science and Cluster of Excellence on Plant Sciences Heinrich Heine UniversityD-40225 DuesseldorfGermany CAS Key Laboratory of Genome Sciences and Information Beijing Institute of GenomicsChinese Academy of SciencesBeijing 100101China State Key Laboratory of Microbial Resources Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Interdisciplinary Innovation Institute of Medicine and EngineeringBeihang UniversityBeijing 100191China University of Chinese Academy of Sciences Beijing 100049China

Coding regions have complex interactions among multiple selective forces,which are manifested as biases in nucleotide *** studies have revealed a decreasing GC gradient from the 5′-end to 3′-end of coding regions in various *** confirmed that this gradient is universal in eukaryotic genes,but the decrease only starts from the~25th *** trend is mostly found in nonsynonymous(ns)sites at which the GC gradient is universal across the eukaryotic *** GC contents at ns sites result in cheaper amino acids,indicating a universal selection for energy efficiency toward the N-termini of encoded *** a genome,the decreasing GC gradient is intensified from lowly to highly expressed genes(more and more protein products),further supporting this *** reveals a conserved selective constraint for cheaper amino acids at the translation start that drives the increased GC contents at ns *** GC contents can facilitate transcription but result in a more stable local secondary structure around the start codon and subsequently impede translation ***,the GC gradients at four-fold and two-fold synonymous sites vary across *** could decrease or increase,suggesting different constraints acting at the GC contents of different codon sites in different *** study reveals that the overall GC contents at the translation start are consequences of complex interactions among several major biological processes that shape the nucleotide sequences,especially efficient energy usage.

关键词： Macroevolution Prioritization of selective forces Energy efficiency Transcription Translation initiation

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RePhine: An Integrative Method for Identification of Drug Response-related Transcriptional Regulators

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Genomics, Proteomics & bioinformatics 2021年第4期19卷 534-548页

作者： Xujun Wang Zhengtao Zhang Wenyi Qin Shiyi Liu Cong Liu Georgi ZGenchev Lijian Hui Hongyu Zhao Hui Lu SJTU-Yale Joint Center for Biostatistics and Data Science Department of Bioinformatics and BiostatisticsSchool of Life Science and BiotechnologyShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Cell Biology CAS Center for Excellence in Molecular Cell ScienceShanghai Institute of Biochemistry and Cell BiologyShanghai 200031China Department of Bioengineering University of Illinois at ChicagoIL 60607USA Department of Genetics School of MedicineYale UniversityNew HavenCT 06511USA Department of Medical Informatics Columbia UniversityNew YorkNY 10032USA Bulgarian Institute for Genomics and Precision Medicine Sofia 1000Bulgaria Department of Biostatistics Yale School of Public Health.New HavenCT 06511USA Institute of Science and Technology for Brain-Inspired Intelligence Fudan UniversityShanghai 200433China Center for Biomedical informatics Shanghai Children’s HospitalShanghai 200040China

Transcriptional regulators(TRs)participate in essential processes in cancer pathogenesis and are critical therapeutic *** of drug response-related TRs from cell line-based compound screening data is often challenging due to low m RNA abundance of TRs,protein modifications,and other confounders(CFs).In this study,we developed a regression-based pharmacogenomic and Ch IP-seq data integration method(Re Phine)to infer the impact of TRs on drug response through integrative analyses of pharmacogenomic and Ch IP-seq *** Phine was evaluated in simulation and pharmacogenomic data and was applied to pan-cancer datasets with the goal of biological *** simulation data with added noises or CFs and in pharmacogenomic data,Re Phine demonstrated an improved performance in comparison with three commonly used methods(including Pearson correlation analysis,logistic regression model,and gene set enrichment analysis).Utilizing Re Phine and Cancer Cell Line Encyclopedia data,we observed that Re Phinederived TR signatures could effectively cluster drugs with different mechanisms of *** Phine predicted that loss-offunction of EZH2/PRC2 reduces cancer cell sensitivity toward the BRAF inhibitor *** validation confirmed that pharmacological EZH2 inhibition increases the resistance of cancer cells to PLX4720 *** results support that Re Phine is a useful tool for inferring drug response-related TRs and for potential therapeutic *** source code for Re Phine is freely available at https://***/coexps/Re Phine.

关键词： Pharmacogenomics ChIP-seq Transcriptional regulator BRAF inhibitor resistance Drug resistance

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Performance Analysis of Vehicle to Infrastructure Network

Performance Analysis of Vehicle to Infrastructure Network

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International Conference on Advanced Communication Technologies and Networking (CommNet)

作者： Opel N. Mbanzabugabo Charles Kabiri Kayalvizhi Jayavel Louis Sibomana African Center of Excellence in Internet of Things (ACEIoT) University of Rwanda Kigali Rwanda Data Science and Artificial Intelligence Creative Computing Institute University of the Arts London London UK National Council for Science and Technology Kigali Rwanda

For improving traffic safety and the driving experience, vehicle-to-infrastructure (V2I) networks require ultra-reliable and low-latency connectivity. However, because of the increased mobility of vehicles, the channel is continuously varying, making it difficult to maintain low latency and high connectivity in V2I networks. Additionally, as the number of vehicles increases, sufficient resources is needed to maintain continuous internet access via a Base Station (BS). By introducing a three-tiered prioritization mechanism, this study aims at improving resource constraints in V2I networks. The highest priority (priority 1) is assigned to emergency communications, which include critical communications such as ambulance notifications, accident reports, and alerts regarding very important people. Priority 2 is assigned to data, such as road conditions and traffic information. data concerning entertainment, such as media and ordinary communications, come into the category of low priority (priority 3). By employing this prioritization strategy, efficient resource allocation is ensured, taking into consideration different levels of urgency within services. An Analytical Priority Resources Allocation Framework (APRAF) based on M/G/1 queuing method, is developed with an objective of enhancing connectivity in the uplink of vehicles to infrastructure networks. The proposed method is evaluated using an M/G/1 queuing method where delays on queue and system are considered as main performance metrics. Using numerical analysis, the lowest latency is obtained gradually from the highest to the lowest class. As a result, the latency (waiting delay on queue and on system) for vehicles on priority 1 is very low, and in this way the connectivity is improved comparatively to existing system without priority. The waiting delay in the system for vehicles in high priority is around 66 ms while in First Come First Served model without priority, the waiting delay is infinite. The reliability i

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Docking of Human Band 3 Anion Transporter Proteins with Their Plasmodium falciparum Interactors Based on Short Linear Motifs

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American Journal of Molecular Biology 2024年第4期14卷 187-200页

作者： Fatoumata Gniné Fofana Ayoub Ksouri Cheickna Cisse Oussema Souiai Alia Benkahla Hedmon Okella Mamadou Sangare Jeffrey G. Shaffer Seydou Doumbia Mamadou Wele African Center of Excellence in Bioinformatics University of Sciences Techniques and Technologies of Bamako (USTTB) Bamako Mali Laboratory of BioInformatics BioMathematics and BioStatistics (BIMS) Institut Pasteur de Tunis University of Tunis El Manar Tunis Tunisia School of Veterinary Medicine University of California Davis Tulare USA Department of Biostatistics and Data Science Tulane University School of Public Health and Tropical Medicine New Orleans USA University Clinical Research Centre (UCRC) USTTB Bamako Mali

Plasmodium (P.) falciparum is a pathogen that causes severe forms of malaria. Protein interactions have been shown to occur between P. falciparum and human erythrocytes in human blood. The Band 3 Anion Transporter (B3AT) protein is considered the main invasive pathway for the parasite in erythrocytes that causes clinical symptoms for malaria in humans. The interactions between P. falciparum parasites and erythrocytes along this receptor have previously been explored. Short linear motifs (SLIMs) are short linear mediator sequences that involve several biological processes, acting as mediators of protein interactions identifiable by computational tools such as SLiMFinder. For a given protein, the identification of SLIMs allows predicting its interactors. Using the SLIMs approach, protein-protein interaction network analyses between P. falciparum and its human host, were used to identify a tryptophan-rich protein, A5K5E5_PLAVS as an essential interactor of B3AT. To better understand the interaction mechanism, a guided protein-protein docking approach based on SLIM motifs was performed for human B3AT and A5K5E5_PLAVS. The highlights of this important interaction between P. falciparum and its human host have the potential to pave the way to identify new therapeutic candidates.

关键词： Malaria Protein-Protein Docking Protein-Protein Interaction Short Linear Motifs

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FedMonitor: An Implementation Architecture for Monitoring of Resources and Events'Notifications on Federated Cloud Computing Infrastructures 4

FedMonitor: An Implementation Architecture for Monitoring of...

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4th International Conference on Emerging Trends in Networks and Computer Communications, ETNCC 2024

作者： Adetiba, Emmanuel Nnaji, Uche Wejin, John S. Ojesanmi, Festus Akanle, Matthew B. Ajayi, Priscilla O. Sweetwiliams, Faith O. Thakur, Surendra C. Adebiyi, Ezekiel F. Department of Electrical and Information Engineering and Covenant Applied Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Covenant University Department of Computer and Information Science & CApIC-ACE Ota Nigeria Covenant University Department of Electrical and Information Engineering & CApIC-ACE Jalingo Nigeria Tareba State University Department of Computer Science Jalingo Nigeria Ota Nigeria Covenant University & CApIC-ACE Covenant University Department of Electrical and Information Engineering Ota Nigeria Covenant University Center for Systems and Information Services & CApIC-ACE Ota Nigeria Durban University of Technology e-Skills Co-Laboratory Department of Information Technology and KZN Durban4001 South Africa Covenant University Ogun State Ota Nigeria Makerere University African Center of Excellence in Bioinformatics & Data Intensive Science Kampala10218 Uganda

ISBN: (纸本)9798350353266

In the evolving landscape of cloud computing, federated cloud infrastructures present unique challenges and opportunities for resource and application monitoring. Monitoring the diverse array of cloud resources and applications within a federated cloud environment is crucial for delivering consistent Quality of Service (QoS) and continuous oversight across various cloud applications and infrastructure. Despite the various successes documented in the literature on multi-cloud monitoring, existing frameworks have not fully explored or provided enough insights into centralized monitoring of resources, applications, and network devices in a federated cloud environment. This paper introduces FedMonitor, an implementation architecture designed to enhance the monitoring and notification capabilities in federated cloud environments by building on the theoretical ideals in our earlier work (i.e. FEDARGOS-V1). FedMonitor leverages Prometheus and Grafana to crawl, manage and visualize metrics from diverse software services, hardware resources, and network devices within a federated cloud environment. The results demonstrate hat FedMonitor improves the effectiveness of resource and application monitoring in federated cloud environments. © 2024 IEEE.

关键词： Cloud platforms

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Towards hybrid artificial neural network model in predicting long term total healthcare expenditure in Rwanda

Research Square

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Research Square 2022年

作者： Uwimana, Annie Hategekimana, Isaac Nzabanita, Joseph Habarugira, Venant Shuguang, Zhang National Bank of Rwanda Department of Statistics Rwanda African Center of Excellence in Data Science College of Business & Economics University of Rwanda Rwanda Department of Mathematics College of Science and Technology University of Rwanda Rwanda Department of Statistics & Finance School of Management University of Science and Technology of China China

For a sustainable Healthcare expenditure policy, it is important to have accurate forecasts to avoid any sort of uncertainty about the rise in Healthcare expenditures. The Auto Regressive Integrated Moving Average (ARIMA) model and the Artificial Neural Networks (ANNs) models have got attention and have been the preferred model to forecast Healthcare expenditures for decades. However, it has been found that each of the two models has weaknesses in capturing linear and nonlinear relationships in data. It is with this background that, we proposed a hybrid model, which differs in combining the advantages of Auto Regressive Integrated Moving Average and Artificial Neural Networks. The hybrid model was tested on sets of Rwanda total Healthcare expenditure actual data, and the empirical results of the forecasted values in 2027 are 552,881.33 million Rwandan francs. Our results showed the effectiveness of the hybrid model which has a higher prediction accuracy as compared to the existing models. For policymakers to better plan for future resources and estimate the amount of the budget allocated to Healthcare, there is a need of accurate estimation of Healthcare expenditure as it impact government policy and planning. © 2022, CC BY.

关键词： Neural networks

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Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information

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Genomics, Proteomics & bioinformatics 2020年第1期18卷 52-64页

作者： Fuyi Li Andre Leier Quanzhong Liu Yanan Wang Dongxu Xiang Tatsuya Akutsu Geoffrey IWebb A.Ian Smith Tatiana Marquez-Lago Jian Li Jiangning Song Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology Monash UniversityMelbourneVIC 3800Australia Monash Centre for Data Science Faculty of Information TechnologyMonash UniversityMelbourneVIC 3800Australia School of Medicine University of Alabama at BirminghamBirminghamAL 35233USA College of Information Engineering Northwest A&F UniversityYangling 712100China Bioinformatics Center Institute for Chemical ResearchKyoto UniversityUjiKyoto 611-0011Japan ARC Centre of Excellence in Advanced Molecular Imaging Monash UniversityMelbourneVIC 3800Australia Biomedicine Discovery Institute and Department of Microbiology Monash UniversityMelbourneVIC 3800Australia

Proteases are enzymes that cleave and hydrolyse the peptide bonds between two specific amino acid residues of target substrate ***-controlled proteolysis plays a key role in the degradation and recycling of proteins,which is essential for various physiological ***,solving the substrate identification problem will have important implications for the precise understanding of functions and physiological roles of proteases,as well as for therapeutic target identification and pharmaceutical ***,there is a great demand for bioinformatics methods that can predict novel substrate cleavage events with high accuracy by utilizing both sequence and structural *** this study,we present Procleave,a novel bioinformatics approach for predicting protease-specific substrates and specific cleavage sites by taking into account both their sequence and 3D structural *** features of known cleavage sites were represented by discrete values using a LOWESS data-smoothing optimization method,which turned out to be critical for the performance of *** optimal approximations of all structural parameter values were encoded in a conditional random field(CRF)computational framework,alongside sequence and chemical group-based ***,we demonstrate the outstanding performance of Procleave through extensive benchmarking and independent *** is capable of correctly identifying most cleavage sites in the case ***,when applied to the human structural proteome encompassing 17,628 protein structures,Procleave suggests a number of potential novel target substrates and their corresponding cleavage sites of different *** is implemented as a webserver and is freely accessible at http://***/.

关键词： Protease Cleavage site prediction Machine learning Conditional random field Structural determinants

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Public transportation demand analysis: A case study of metropolitan lagos

arXiv

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arXiv 2021年

作者： Paul, Ozioma McSharry, Patrick Carnegie Mellon University Africa Kigali Rwanda African Center of Excellence in Data Science University of Rwanda KigaliBP 4285 RW Rwanda Oxford Man Institute of Quantitative Finance Oxford University OxfordOX2 6ED United Kingdom

Modelling, simulation, and forecasting offer a means of facilitating better planning and decision-making. These quantitative approaches can add value beyond traditional methods that do not rely on data and are particularly relevant for public transportation. Lagos is experiencing rapid urbanization and currently has a population of just under 15 million. Both long waiting times and uncertain travel times has driven many people to acquire their own vehicle or use alternative modes of transport. This has significantly increased the number of vehicles on the roads leading to even more traffic and greater traffic congestion. This paper investigates urban travel demand in Lagos and explores passenger dynamics in time and space. Using individual commuter trip data from tickets purchased from the Lagos State Bus Rapid Transit (BRT), the demand patterns through the hours of the day, days of the week and bus stations are analysed. This study aims to quantify demand from actual passenger trips and estimate the impact that dynamic scheduling could have on passenger waiting times. Station segmentation is provided to cluster stations by their demand characteristics in order to tailor specific bus schedules. Intraday public transportation demand in Lagos BRT is analysed and predictions are compared. Simulations using fixed and dynamic bus scheduling demonstrate that the average waiting time could be reduced by as much as 80%. The load curves, insights and the approach developed will be useful for informing policymaking in Lagos and similar african cities facing the challenges of rapid urbanization. © 2021, CC BY-NC-SA.

关键词： Forecasting

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