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The role of MLH1, MSH2 and MSH6 in the development of colorectal cancer in Uganda

BMC Cancer 2025年第1期25卷 1-13页

作者： Wismayer, Richard Matthews, Rosie Whalley, Celina Kiwanuka, Julius Kakembo, Fredrick Elishama Thorn, Steve Wabinga, Henry Odida, Michael Tomlinson, Ian Department of Surgery Masaka Regional Referral Hospital Masaka Uganda Department of Surgery Faculty of Health Sciences Equator University of Science and Technology Masaka Uganda Department of Surgery Faculty of Health Sciences Habib Medical School IUIU University Kampala Uganda Department of Pathology School of Biomedical Sciences College of Health Sciences Makerere University Kampala Uganda Institute of Genetics and Cancer College of Medicine and Veterinary Medicine University of Edinburgh Edinburgh United Kingdom Institute of Cancer and Genomic Sciences College of Medical and Dental Sciences University of Birmingham Birmingham United Kingdom Department of Epidemiology and Biostatistics College of Health Sciences Makerere University Kampala Uganda Department of Immunology and Molecular Biology School of Biomedical Sciences College of Health Sciences Makerere University Kampala Uganda Department of Pathology Faculty of Medicine Gulu University Gulu Uganda Department of Oncology University of Oxford Oxford United Kingdom African Centre of Excellence in Bioinformatics and Data Intensive Sciences Infectious Diseases Institute Makerere University Kampala Uganda

Introduction: In Uganda, colorectal cancer (CRC) is steadily increasing according to the Kampala Cancer Registry. In the West, microsatellite instability is detected in 90% of hereditary nonpolyposis colon cancers (HNPCC) which account for 1–2% of all CRC, and 15% of sporadic CRC. Germline mutations in MLH1 and MSH2 account for 90% of HNPCC in the West, whilst the remainder of cases are due to mutations in MSH6 and PMS2. The aim of this study was to determine the microsatellite instability (MSI) status and determine the proportions of MLH1, MSH2, and MSH6 pathological mutations in Ugandan CRC patients. Methodology: This was a cross-sectional study carried out between 1st January 2008 to 15th September 2021. Patients were recruited prospectively from 16th September 2019 to 16th September 2021, from Masaka Regional Referral Hospital, Mulago National Referral Hospital, Uganda Martyrs’ Hospital Lubaga and Mengo Hospital. From 1st January 2008 to 15th September 2019, CRC FFPE tissue blocks were obtained from the archives of the Department of Pathology, Makerere University. data was abstracted from the medical case files for demographics, topography and stage. The histopathological subtype and grade of CRC were obtained by two consultant pathologists from the H&E slides. DNA was extracted from CRC formalin-fixed paraffin-embedded (FFPE) tissue blocks. Library preparation was completed using the Qiagen custom design panel. The custom panel represented 56 genes. The MLH-1, MSH2, MSH6, BRAF and KRAS genes were sequenced using the above library preparation and NGS sequencing. The MSI status was obtained if one of the MSI genes, MLH1, MSH2 or MSH6 was pathologically mutated. If none of the genes was pathologically mutated it was considered MSI negative, microsatellite stable (MSS). Immunohistochemistry was carried out to determine whether MLH1 and PMS2 was MMR proficient or deficient. Categorical data was summarized using frequencies and proportions corresponding to each of th

关键词： Colorectal cancer Immunohistochemistry Microsatellite instability (MSI) Microsatellite stable (MSS) Uganda

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Characterizing Emergency Department Care for Patients With Histories of Incarceration

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JACEP Open 2025年第1期6卷 100022-100022页

作者： Huang, Thomas Socrates, Vimig Ovchinnikova, Polina Faustino, Isaac Kumar, Anusha Safranek, Conrad Chi, Ling Wang, Emily A. Puglisi, Lisa Wong, Ambrose H. Wang, Karen H. Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Department for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States SEICHE Center for Health and Justice Yale School of Medicine New Haven CT United States Equity Research and Innovation Center Yale School of Medicine Yale University New Haven CT United States

Objectives: Patients with a history of incarceration experience bias from health care team members, barriers to privacy, and a multitude of health care disparities. We aimed to assess care processes delivered in emergency departments (EDs) for people with histories of incarceration. Methods: We utilized a fine-tuned large language model to identify patient incarceration status from 480,374 notes from the ED setting. We compared socio-demographic characteristics, comorbidities, and care processes, including disposition, restraint use, and sedation, between individuals with and without a history of incarceration. We then conducted multivariable logistic regression to assess the independent correlation of incarceration history and management in the ED while adjusting for demographic characteristics, health behaviors, presentation, and past medical history. Results: We found 1734 unique patient encounters with a history of incarceration from a total of 177,987 encounters. Patients with history of incarceration were more likely to be male, Black, Hispanic, or other race/ethnicity, currently unemployed or disabled, and had smoking and substance use histories, compared with those without. This cohort demonstrated higher odds of elopement (OR: 3.59 [95% CI: 2.41–5.12]), leaving against medical advice (OR: 2.39 [95% CI: 1.46–3.67]), and being subjected to sedation (OR: 3.89 [95% CI: 3.19–4.70]) and restraint use (OR: 3.76 [95% CI: 3.06–4.57]). After adjusting for covariates, the association between incarceration and elopement remained significant (adjusted odds ratio: 1.65 [95% CI: 1.08–2.43]), while associations with other dispositions, restraint use, and sedation did not persist. Conclusion: This study identified differences in patient characteristics and care processes in the ED for patients with histories of incarceration and demonstrated the potential of using natural language processing in measuring care processes in populations that are largely hidden, but highly prev

关键词： artificial intelligence emergency medicine incarceration large language models quality of health care

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Streptophyte evolution: Auxin response born out of sensing tryptophan

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Current biology : CB 2025年第9期35卷 R333-R336页

作者： Erika Endriulaitytė Cäcilia F Kunz Jaccoline M S Zegers Jan de Vries Institute for Microbiology and Genetics Department of Applied Bioinformatics University of Göttingen 37077 Göttingen Germany. Institute for Microbiology and Genetics Department of Applied Bioinformatics University of Göttingen 37077 Göttingen Germany Göttingen Center for Molecular Biosciences (GZMB) Department of Applied Bioinformatics University of Göttingen 37077 Göttingen Germany Campus Institute Data Science (CIDAS) Department of Applied Bioinformatics University of Göttingen 37077 Göttingen Germany. Electronic address: devries.jan@uni-goettingen.de.

Auxin is the major phytohormone in land plants. A new study finds that auxin triggers proliferation and gene regulation in the streptophyte alga Penium margaritaceum, and importantly, tryptophan elicits a similar response. These findings open the possibility that auxin-like responses evolved before the emergence of auxin-specific regulatory networks.

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Molecular docking and molecular dynamics simulation studies of inhibitor candidates against Anopheles gambiae 3-hydroxykynurenine transaminase and implications on vector control

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Heliyon 2025年第1期11卷 e41633页

作者： Adedeji, Eunice O. Ogunlana, Olubanke O. Oduselu, Gbolahan O. Koenig, Rainer Adebiyi, Ezekiel Soremekun, Opeyemi S. Fatumo, Segun Covenant University Bioinformatics Research (CUBRe) Covenant University Ogun State Ota Nigeria Department of Biochemistry Covenant University Ogun State Ota Nigeria Department of Biology University of York York United Kingdom Covenant Applied Informatics and Communication Africa Centre of Excellence Covenant University Ota Nigeria Institute for Infectious Diseases and Infection Control (IIMK RG Systems Biology) Jena University Hospital Am Klinikum 1 Jena 07747 Germany African Center of Excellence in Bioinformatics & Data Intensive Science Makerere University Kampala 10218 Uganda Division of Applied Bioinformatics German Cancer Research Center (DKFZ) G200 Im Neuenheimer Feld 280 Heidelberg 69120 Germany The African Computational Genomics (TACG) Research Group MRC/UVRI and LSHTM Entebbe Uganda Precision Healthcare University Research Institute Queen Mary University of London United Kingdom Department of Non-Communicable Disease Epidemiology London School of Hygiene & Tropical Medicine United Kingdom

Isoxazole and oxadiazole derivatives inhibiting 3-hydroxykynurenine transaminase (3HKT) are potential larvicidal candidates. This study aims to identify more suited potential inhibitors of Anopheles gambiae 3HKT (Ag3HKT) through molecular docking and molecular dynamics simulation. A total of 958 compounds were docked against Anopheles gambiae 3HKT (PDB ID: 2CH2) using Autodock vina and Autodock4. The top three identified hits were subjected to 300 ns molecular dynamics simulation using AMBER 18 and ADMET analysis using SWISSADME predictor and ADMETSAR. Replacement of alkyl attachment on C5 of isoxazole or oxadiazole derivative with a cycloalkyl group yielded compounds with lower binding energy than their straight chain counterparts. The top three compounds were brominated compounds, 2‐[3‐(4‐bromophenyl)‐1,2‐oxazol‐5‐yl]cyclopentane‐1‐carboxylic acid, 2-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]cyclopentane-1-carboxylic acid, 3-[3-(4-bromo-2-methylphenyl)-1,2,4-oxadiazol-5-yl]cyclopentane-1-carboxylic acid, and they had binding energies of −8.58, −8.25, and −8.18 kcal/mol in virtual screening against 2CH2 protein target, respectively. These compounds were predicted to be less toxic than temephos, a standard larvicide and more biodegradable than previously reported inhibitors. The three compounds exhibited a greater stabilizing effect on 2CH2 protein target than 4-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]butanoic acid, a previously reported inhibitor candidate with good larvicidal activity on Aedes aegypti. Further thermodynamic calculations revealed that the top three compounds possessed total binding energies (ΔG_bind) of −26.64 kcal/mol, −24.26 kcal/mol and −14.11 kcal/mol, respectively, as compared to −12.02 kcal/mol for 4-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]butanoic acid. These compounds could be better larvicides than previously reported isoxazole or oxadiazole derivatives and safer than temephos. © 2025 The Authors

关键词： 1,2,4-Oxadiazole 3HKT Isoxazoles Larvicide Mosquito Vector control

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Solanaceae pangenomes are coming of graphical age to bring heritability back

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aBIOTECH 2022年第4期3卷 233-236页

作者： Björn Usadel Institute for Biological Data Science CEPLASHeinrich Heine UniversityDüsseldorfGermany IBG-4 Bioinformatics BioSCForschungszentrum JülichJülichGermany

Two recent articles describe a pangenome of potato and a graph-based pangenome for tomato,*** latter improves our understanding of the tomato genomics architecture even further and the use of this graph-based pangenom... 详细信息

关键词： Tomato Potato Pangenome Graph-based pangenome Heritability

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A Hydrodynamic Analysis of Water System in Dadahup Swamp Irrigation Area 1

A Hydrodynamic Analysis of Water System in Dadahup Swamp Irr...

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1st International Conference on Computer science and Artificial Intelligence, ICCSAI 2021

作者： Purboseno, Sentot Suparyanto, Teddy Hidayat, Alam Ahmad Pardamean, Bens Institute of Agriculture STIPER Department of Agricultural Engineering Yogyakarta55283 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center BINUS Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Dadahup Swamp Irrigation Area (DIR) in Kapuas Regency, Central Kalimantan is developed for agricultural activities to provide food security after the pandemic. The water system consists of various channels, gates, and a flood embankment structure, which is also connected to three different rivers: Barito River, Mangkatif River, and Kapuas Mumpung River. To quantify flood risk assessments in the area, we perform a hydrodynamic analysis using the unsteady flow method via HEC-RAS software version 4.1.0. We use geometrical profiles from topography measurements and the outer boundary of the Dadahup DIR as input for the hydrologic model. Our results estimate the maximum surface water level from both cross and longitudinal sections in the channels and find that several points near the flood embankment area are prone to flood events. Our modeling approach provides a preliminary assessment for the local government to formulate a flood mitigation plan and policy in the area. © 2021 IEEE.

关键词： Rivers

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Unveiling roles of non-coding RNAs in cancer through advanced technologies

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Quantitative Biology 2025年第4期13卷 e70005-e70005页

作者： Runhao Wang Leng Han Brown Center for Immunotherapy Indiana University School of Medicine Indianapolis Indiana USA Department of Biostatistics and Health Data Science Indiana University School of Medicine Indianapolis Indiana USA Center for Computational Biology and Bioinformatics Indiana University School of Medicine Indianapolis Indiana USA

Non-coding RNAs (ncRNAs) have emerged as key regulators in tumorigenesis. In this perspective, we briefly review the significance of ncRNA in cancer biology and highlight recent technological advancements in characterization of ncRNA in cancer research. Specifically, we discuss how these advanced approaches, such as Patho-DBiT, CRISPR screens, and snoKARR-seq, hold the potential to revolutionize ncRNA research by offering comprehensive insights into their spatial expression patterns and functional roles.

关键词： cancer CRISPR screens ncRNAs patho-DBiT snoKARR-seq spatial transcriptomics

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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A bioinformatics Analysis and Homology 3D Modeling of Dihydroxy-orotate-dehydrogenase of Plasmodium ovale

A Bioinformatics Analysis and Homology 3D Modeling of Dihydr...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Nirwantono, Rudi Assidqi, Khoirunnisa Hidayat, Alam Ahmad Pebrianto Trinugroho, Joko Pardamean, Bens Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Food Biotechnology Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Departement Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

The infection of Plasmodium vivax is relatively less virulent than the deathliest Plasmodium falciparum. However, it still can lead to a fatal case and often induces recurring malaria due to dormant parasites in the liver. Thus, the research to study the drug to treat Plasmodium vivax is essential, where the enzyme dihydroorotate dehydrogenase (DHODH) has recently become a new drug target. However, the drug-enzyme interaction study has only recently been conducted in Plasmodium falciparum (pfDHODH) due to the lack of the 3D structure of enzyme DHODH from Plasmodium vivax that is crucial for the study. Therefore, this study aimed to perform the modelling study of Plasmodium vivax DHODH (PvDHODH) to create a 3D structure as a basis for drug-protein interaction study in upcoming studies. Sequence pvDHODH (Accession: SCO68359.1) was used in homology modelling using Modeller 10.2 with the crystal structure of DHODH from DHODH (Accession: 7KZY) as a template. Overall, the model generated from the homology modelling was considered a good model, and the 3D structure was close to the native state according to several parameters, including DOPE score, GA341 score, QMEAN4 value, 3D-1D score, ERRAT2 score, and ProSA score. Ramachandran plot also revealed that almost all amino acids were distributed in the desirable and allowed area (99.1%), and only 0.9% were in generously allowed regions. Superimposition of the model with the template also indicated that the model has an almost similar structure and amino acids positioning, including in the binding pocket and active site. Therefore, the model can be used for downstream analysis in drug-protein interaction studies. Nevertheless, some improvements can still be performed to upgrade the quality of the model by deleting unaligned residues on the C-terminal and realigning the residues at the doubting site. © 2023 IEEE.

关键词： Amino acids

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Deep learning for oil palm fruit ripeness classification with densenet 6

Deep learning for oil palm fruit ripeness classification wit...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Herman, Herman Cenggoro, Tjeng Wawan Susanto, Albert Pardamean, Bens Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Program Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Oil palm fruit farming is one of the most leading agriculture industries in the South East Asia region. Unfortunately, most of the harvesting method is still done through manual labor. Multiple research has been conducted to help farmers automatically detect the ripeness level of the oil palm fruit. We conducted an experiment of detecting the ripeness level of oil palm fruit by using one of the state-of-the-art computer vision approaches, which was deep learning with a Convolutional Neural Network (CNN). The dataset used consists of 7 levels of ripeness with 400 images of oil palm fruits. The models used in this test scenario were both AlexNet and DenseNet. The result of this study showed that DenseNet has been proven to outperform AlexNet by 8.5% in terms of accuracy and 8% in F1 score. © 2021 IEEE.

关键词： Computer vision

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