arXiv - QuanBio - Tissues and Organs最新文献

{"title":"Air-blood interface engineered microfluidic device to mimic shear rate gradient induced human bleeding model","authors":"Shobhit Das, Shilpi Pandey, Oliver Hayden","doi":"arxiv-2407.21356","DOIUrl":"https://doi.org/arxiv-2407.21356","url":null,"abstract":"Microfluidic technology has emerged as a powerful tool for studying complex\u0000biological processes with enhanced precision and control. A microfluidic chip\u0000was designed to emulate human-like microvascular networks with precise control\u0000over channel geometry and flow conditions. By simulating blood flow dynamics\u0000during bleeding events, we successfully observed the real-time interactions of\u0000platelets and their aggregation induced by shear rate gradient at the wound\u0000site. Platelet dynamics is primarily influenced by physico-mechanical condition\u0000of blood vessels with pathophysiological condition of blood at close proximity\u0000of vascular injury site. This microfluidic platform facilitated the\u0000investigation of platelet adhesion, activation, and clot formation, providing a\u0000unique opportunity to study the spatiotemporal dynamics of platelet aggregation\u0000and blood clot. Our findings shed light on the intricate mechanisms underlying\u0000thrombus formation and platelet-mediated aggregation, offering a more accurate\u0000and dynamic representation of human haemostasis compared to traditional animal\u0000models. In the conventional approach, the human bleeding model is tried on\u0000mouse due to anatomy and pathological similarities between mouse and humans.\u0000This study will simplify and standardize the blood and vasculature conditions.\u0000The microfluidic-based replication of the bleeding model holds significant\u0000promise in advancing our understanding of clotting disorders and wound healing\u0000processes. Furthermore, it paves the way for targeted therapeutic interventions\u0000in managing bleeding disorders and enhancing clinical strategies for promoting\u0000efficient wound closure. Ultimately, this study demonstrates the potential of\u0000microfluidics to revolutionize haemostasis research and opens up new avenues\u0000for the development of personalized medicine approaches in the field of\u0000clotting disorders.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141873269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dimeric Drug Polymeric Micelles with Acid-Active Tumor Targeting and FRET-indicated Drug Release","authors":"Xing Guo, Lin Wang, Kayla Duval, Jing Fan, Shaobing Zhou, Zi Chen","doi":"arxiv-2407.20538","DOIUrl":"https://doi.org/arxiv-2407.20538","url":null,"abstract":"Trans-activating transcriptional activator (TAT), a cell-penetrating peptide,\u0000has been extensively used for facilitating cellular uptake and nuclear\u0000targeting of drug delivery systems. However, the positively charged TAT peptide\u0000usually strongly interacts with serum components and undergoes substantial\u0000phagocytosis by the reticuloendothelial system, causing a short blood\u0000circulation in vivo. In this work, an acid-active tumor targeting nanoplatform\u0000DA-TAT-PECL was developed to effectively inhibit the nonspecific interactions\u0000of TAT in the bloodstream. 2,3-dimethylmaleic anhydride (DA) was first used to\u0000convert the TAT amines to carboxylic acid, the resulting DA-TAT was further\u0000conjugated to get DA-TAT-PECL. After self-assembly into polymeric micelles,\u0000they were capable of circulating in the physiological condition for a long time\u0000and promoting cell penetration upon accumulation at the tumor site and\u0000de-shielding the DA group. Moreover, camptothecin (CPT) was used as the\u0000anticancer drug and modified into a dimer (CPT)2-ss-Mal, in which two CPT\u0000molecules were connected by a reduction-labile maleimide thioether bond. The\u0000FRET signal between CPT and maleimide thioether bond was monitored to visualize\u0000the drug release process and effective targeted delivery of antitumor drugs was\u0000demonstrated. This pH/reduction dual-responsive micelle system provides a new\u0000platform for high fidelity cancer therapy.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141870224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TMA-Grid: An open-source, zero-footprint web application for FAIR Tissue MicroArray De-arraying","authors":"Aaron Ge, Monjoy Saha, Maire A. Duggan, Petra Lenz, Mustapha Abubakar, Montserrat García-Closas, Jeya Balasubramanian, Jonas S. Almeida, Praphulla MS Bhawsar","doi":"arxiv-2407.21233","DOIUrl":"https://doi.org/arxiv-2407.21233","url":null,"abstract":"Background: Tissue Microarrays (TMAs) significantly increase analytical efficiency in\u0000histopathology and large-scale epidemiologic studies by allowing multiple\u0000tissue cores to be scanned on a single slide. The individual cores can be\u0000digitally extracted and then linked to metadata for analysis in a process known\u0000as de-arraying. However, TMAs often contain core misalignments and artifacts\u0000due to assembly errors, which can adversely affect the reliability of the\u0000extracted cores during the de-arraying process. Moreover, conventional\u0000approaches for TMA de-arraying rely on desktop solutions.Therefore, a robust\u0000yet flexible de-arraying method is crucial to account for these inaccuracies\u0000and ensure effective downstream analyses. Results: We developed TMA-Grid, an in-browser, zero-footprint, interactive web\u0000application for TMA de-arraying. This web application integrates a\u0000convolutional neural network for precise tissue segmentation and a grid\u0000estimation algorithm to match each identified core to its expected location.\u0000The application emphasizes interactivity, allowing users to easily adjust\u0000segmentation and gridding results. Operating entirely in the web-browser,\u0000TMA-Grid eliminates the need for downloads or installations and ensures data\u0000privacy. Adhering to FAIR principles (Findable, Accessible, Interoperable, and\u0000Reusable), the application and its components are designed for seamless\u0000integration into TMA research workflows. Conclusions: TMA-Grid provides a robust, user-friendly solution for TMA dearraying on the\u0000web. As an open, freely accessible platform, it lays the foundation for\u0000collaborative analyses of TMAs and similar histopathology imaging data.\u0000Availability: Web application: https://episphere.github.io/tma-grid Code:\u0000https://github.com/episphere/tma-grid Tutorial: https://youtu.be/miajqyw4BVk","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141870105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GP-VLS: A general-purpose vision language model for surgery","authors":"Samuel Schmidgall, Joseph Cho, Cyril Zakka, William Hiesinger","doi":"arxiv-2407.19305","DOIUrl":"https://doi.org/arxiv-2407.19305","url":null,"abstract":"Surgery requires comprehensive medical knowledge, visual assessment skills,\u0000and procedural expertise. While recent surgical AI models have focused on\u0000solving task-specific problems, there is a need for general-purpose systems\u0000that can understand surgical scenes and interact through natural language. This\u0000paper introduces GP-VLS, a general-purpose vision language model for surgery\u0000that integrates medical and surgical knowledge with visual scene understanding.\u0000For comprehensively evaluating general-purpose surgical models, we propose\u0000SurgiQual, which evaluates across medical and surgical knowledge benchmarks as\u0000well as surgical vision-language questions. To train GP-VLS, we develop six new\u0000datasets spanning medical knowledge, surgical textbooks, and vision-language\u0000pairs for tasks like phase recognition and tool identification. We show that\u0000GP-VLS significantly outperforms existing open- and closed-source models on\u0000surgical vision-language tasks, with 8-21% improvements in accuracy across\u0000SurgiQual benchmarks. GP-VLS also demonstrates strong performance on medical\u0000and surgical knowledge tests compared to open-source alternatives. Overall,\u0000GP-VLS provides an open-source foundation for developing AI assistants to\u0000support surgeons across a wide range of tasks and scenarios.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141870226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The IBEX Knowledge-Base: Achieving more together with open science","authors":"Andrea J. RadtkeLymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Ifeanyichukwu AnidiCritical Care Medicine and Pulmonary Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA, Leanne ArakkalLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Armando Arroyo-MejiasLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Rebecca T. BeuschelLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Katy BornerDepartment of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA, Colin J. ChuUCL Institute of Ophthalmology and NIHR Moorfields Biomedical Research Centre, London, UK, Beatrice ClarkLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Menna R. ClatworthyCambridge Institute for Therapeutic Immunology and Infectious Diseases, University of Cambridge Department of Medicine, Molecular Immunity Unit, Laboratory of Molecular Biology, Cambridge, UK, Jake ColauttiMcMaster Immunology Research Centre, Schroeder Allergy and Immunology Research Institute, Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada, Joshua CroteauDepartment of Business Development, BioLegend Inc., San Diego, CA, USA, Saven DenhaMcMaster Immunology Research Centre, Schroeder Allergy and Immunology Research Institute, Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada, Rose DeverFunctional Immunogenomics Unit, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, USA, Walderez O. DutraLaboratory of Cell-Cell Interactions, Department of Morphology, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil, Sonja FritzscheMax-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Spencer FullamDivision of Rheumatology, Rush University Medical Center, Chicago, IL, USA, Michael Y. GernerDepartment of Immunology, University of Washington School of Medicine, Seattle, WA, USA, Anita GolaRobin Chemers Neustein Laboratory of Mammalian Cell Biology and Development, The Rockefeller University, New York, NY, USA, Kenneth J. GollobCenter for Research in Immuno-oncology, Jonathan M. HernandezSurgical Oncology Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA, Jyh Liang HorLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Hiroshi IchiseLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Zhixin JingLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Danny JonigkInstitute of Pathology, Aachen Medical University, RWTH Aachen, Aachen, Germany, Evelyn KandovLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Wolfgang KastenmuellerWurzburg Institute of Systems Immunology, Max Planck Research Group at the Julius-Maximilians-Universitat Wurzburg, Wurzburg, Germany, Joshua F. E. KoenigMcMaster Immunology Research Centre, Schroeder Allergy and Immunology Research Institute, Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada, Aanandita KothurkarUCL Institute of Ophthalmology and NIHR Moorfields Biomedical Research Centre, London, UK, Alexandra Y. KreinsInfection Immunity and Inflammation Research and Teaching Department, University College London Great Ormond Street Institute of Child Health, London, UK, Ian LambornLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Yuri LinSurgical Oncology Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA, Katia Luciano Pereira MoraisCenter for Research in Immuno-oncology, Aleksandra LunichCritical Care Medicine and Pulmonary Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA, Jean C. S. LuzViral Vector Laboratory, Cancer Institute of Sao Paulo, University of Sao Paulo, SP, Brazil, Ryan B. MacDonaldUCL Institute of Ophthalmology and NIHR Moorfields Biomedical Research Centre, London, UK, Chen MakranzNeuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA, Vivien I. MaltezDivision of Allergy, Immunology and Rheumatology, Department of Pediatrics, University of California San Diego, La Jolla, CA, USA, Ryan V. MoriatyDepartment of Cellular and Developmental Biology, Northwestern University, Chicago, IL, USA, Juan M. Ocampo-GodinezLaboratorio de Bioingenieria de Tejidos, Departamento de Estudios de Posgrado e Investigacion, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico, Vitoria M. OlynthoMcMaster Immunology Research Centre, Schroeder Allergy and Immunology Research Institute, Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada, Kartika PadhanLymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Kirsten RemmertSurgical Oncology Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA, Nathan RichozCambridge Institute for Therapeutic Immunology and Infectious Diseases, University of Cambridge Department of Medicine, Molecular Immunity Unit, Laboratory of Molecular Biology, Cambridge, UK, Edward C. SchromLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Wanjing ShangLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Lihong ShiLaboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Rochelle M. ShihLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Emily SperanzaFlorida Research and Innovation Center, Cleveland Clinic Lerner Research Institute, Port Saint Lucie, FL, USA, Salome StierliInstitute of Anatomy, University of Zurich, Zurich, Switzerland, Sarah A. TeichmannCambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Puddicombe Way, Cambridge Biomedical Campus, Cambridge, UK, Tibor Z. VeresLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Megan VierhoutMcMaster Immunology Research Centre, Schroeder Allergy and Immunology Research Institute, Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada, Brianna T. WachterLaboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Adam K. Wade-VallanceLymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Margaret WilliamsCritical Care Medicine and Pulmonary Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD, USA, Nathan ZanggerInstitute of Microbiology, ETH Zurich, Zurich, Switzerland, Ronald N. GermainLymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA and Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA, Ziv YanivBioinformatics and Computational Bioscience Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA","doi":"arxiv-2407.19059","DOIUrl":"https://doi.org/arxiv-2407.19059","url":null,"abstract":"Iterative Bleaching Extends multipleXity (IBEX) is a versatile method for\u0000highly multiplexed imaging of diverse tissues. Based on open science\u0000principles, we created the IBEX Knowledge-Base, a resource for reagents,\u0000protocols and more, to empower innovation.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141870225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying variabilities in cardiac digital twin models of the electrocardiogram","authors":"Elena Zappon, Matthias A. F. Gsell, Karli Gillette, Gernot Plank","doi":"arxiv-2407.17146","DOIUrl":"https://doi.org/arxiv-2407.17146","url":null,"abstract":"CDT of human cardiac EP are digital replicas of patient hearts that match\u0000like-for-like clinical observations. The ECG, as the most prevalent non-invasive observation of cardiac\u0000electrophysiology, is considered an ideal target for CDT calibration. Recent\u0000advanced CDT calibration methods have demonstrated their ability to minimize\u0000discrepancies between simulated and measured ECG signals, effectively\u0000replicating all key morphological features relevant to diagnostics. However,\u0000due to the inherent nature of clinical data acquisition and CDT model\u0000generation pipelines, discrepancies inevitably arise between the real physical\u0000electrophysiology in a patient and the simulated virtual electrophysiology in a\u0000CDT. In this study, we aim to qualitatively and quantitatively analyze the impact\u0000of these uncertainties on ECG morphology and diagnostic markers. We analyze\u0000residual beat-to-beat variability in ECG recordings obtained from healthy\u0000subjects and patients. Using a biophysically detailed and anatomically accurate\u0000computational model of whole-heart electrophysiology combined with a detailed\u0000torso model calibrated to closely replicate measured ECG signals, we vary\u0000anatomical factors (heart location, orientation, size), heterogeneity in\u0000electrical conductivities in the heart and torso, and electrode placements\u0000across ECG leads to assess their qualitative impact on ECG morphology. Our study demonstrates that diagnostically relevant ECG features and overall\u0000morphology appear relatively robust against the investigated uncertainties.\u0000This resilience is consistent with the narrow distribution of ECG due to\u0000residual beat-to-beat variability observed in both healthy subjects and\u0000patients.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing Truly Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning","authors":"Tianhang Nan, Yong Ding, Hao Quan, Deliang Li, Mingchen Zou, Xiaoyu Cui","doi":"arxiv-2407.17157","DOIUrl":"https://doi.org/arxiv-2407.17157","url":null,"abstract":"In the field of deep learning-driven Whole Slide Image (WSI) classification,\u0000Multiple Instance Learning (MIL) has gained significant attention due to its\u0000ability to be trained using only slide-level diagnostic labels. Previous MIL\u0000researches have primarily focused on enhancing feature aggregators for globally\u0000analyzing WSIs, but overlook a causal relationship in diagnosis: model's\u0000prediction should ideally stem solely from regions of the image that contain\u0000diagnostic evidence (such as tumor cells), which usually occupy relatively\u0000small areas. To address this limitation and establish the truly causal\u0000relationship between model predictions and diagnostic evidence regions, we\u0000propose Causal Inference Multiple Instance Learning (CI-MIL). CI-MIL integrates\u0000feature distillation with a novel patch decorrelation mechanism, employing a\u0000two-stage causal inference approach to distill and process patches with high\u0000diagnostic value. Initially, CI-MIL leverages feature distillation to identify\u0000patches likely containing tumor cells and extracts their corresponding feature\u0000representations. These features are then mapped to random Fourier feature\u0000space, where a learnable weighting scheme is employed to minimize inter-feature\u0000correlations, effectively reducing redundancy from homogenous patches and\u0000mitigating data bias. These processes strengthen the causal relationship\u0000between model predictions and diagnostically relevant regions, making the\u0000prediction more direct and reliable. Experimental results demonstrate that\u0000CI-MIL outperforms state-of-the-art methods. Additionally, CI-MIL exhibits\u0000superior interpretability, as its selected regions demonstrate high consistency\u0000with ground truth annotations, promising more reliable diagnostic assistance\u0000for pathologists.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does EDPVR Represent Myocardial Tissue Stiffness? Toward a Better Definition","authors":"Rana Raza Mehdi, Emilio A. Mendiola, Vahid Naeini, Gaurav Choudhary, Reza Avazmohammadi","doi":"arxiv-2407.15254","DOIUrl":"https://doi.org/arxiv-2407.15254","url":null,"abstract":"Accurate assessment of myocardial tissue stiffness is pivotal for the\u0000diagnosis and prognosis of heart diseases. Left ventricular diastolic stiffness\u0000($beta$) obtained from the end-diastolic pressure-volume relationship (EDPVR)\u0000has conventionally been utilized as a representative metric of myocardial\u0000stiffness. The EDPVR can be employed to estimate the intrinsic stiffness of\u0000myocardial tissues through image-based in-silico inverse optimization. However,\u0000whether $beta$, as an organ-level metric, accurately represents the\u0000tissue-level myocardial tissue stiffness in healthy and diseased myocardium\u0000remains elusive. We developed a modeling-based approach utilizing a\u0000two-parameter material model for the myocardium (denoted by $a_f$ and $b_f$) in\u0000image-based in-silico biventricular heart models to generate EDPVRs for\u0000different material parameters. Our results indicated a variable relationship\u0000between $beta$ and the material parameters depending on the range of the\u0000parameters. Interestingly, $beta$ showed a very low sensitivity to $a_f$, once\u0000averaged across several LV geometries, and even a negative correlation with\u0000$a_f$ for small values of $a_f$. These findings call for a critical assessment\u0000of the reliability and confoundedness of EDPVR-derived metrics to represent\u0000tissue-level myocardial stiffness. Our results also underscore the necessity to\u0000explore image-based in-silico frameworks, promising to provide a high-fidelity\u0000and potentially non-invasive assessment of myocardial stiffness.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141771813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, Fabrication, and Characterization of a User-Friendly Microfluidic Device for Studying Liver Zonation-on-Chip (ZoC)","authors":"Reza Mahdavi, Sameereh Hashemi Najafabadi, Mohammad Adel Ghiass, Silmu Valaskivi, Hannu Välimäki, Joose Kreutzer, Charlotte Hamngren Blomqvist, Stefano Romeo, Pasi Kallio, Caroline Beck Adiels","doi":"arxiv-2407.12976","DOIUrl":"https://doi.org/arxiv-2407.12976","url":null,"abstract":"Liver zonation is a fundamental characteristic of hepatocyte spatial\u0000heterogeneity, which is challenging to recapitulate in traditional cell\u0000cultures. This study presents a novel microfluidic device designed to induce\u0000zonation in liver cell cultures by establishing an oxygen gradient using\u0000standard laboratory gases. The device consists of two layers; a bottom layer\u0000containing a gas channel network that delivers high and low oxygenated gases to\u0000create three distinct zones within the cell culture chamber in the layer above.\u0000Computational simulations and ratiometric oxygen sensing were employed to\u0000validate the oxygen gradient, demonstrating that stable oxygen levels were\u0000achieved within two hours. Liver zonation was confirmed using\u0000immunofluorescence staining, which showed zonated albumin production in HepG2\u0000cells directly correlating with oxygen levels and mimicking in-vivo zonation\u0000behavior. This user-friendly device supports studies on liver zonation and\u0000related metabolic disease mechanisms in vitro. It can also be utilized for\u0000experiments that necessitate precise gas concentration gradients, such as\u0000hypoxia-related research areas focused on angiogenesis and cancer development.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141742639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emergence of cellular nematic order is a conserved feature of gastrulation in animal embryos","authors":"Xin Li, Robert J. Huebner, Margot L. K. Williams, Jessica Sawyer, Mark Peifer, John B. Wallingford, D. Thirumalai","doi":"arxiv-2407.12124","DOIUrl":"https://doi.org/arxiv-2407.12124","url":null,"abstract":"Cells undergo dramatic changes in morphology during embryogenesis, yet how\u0000these changes affect the formation of ordered tissues remains elusive. Here we\u0000find that the emergence of a nematic liquid crystal phase occurs in cells\u0000during gastrulation in the development of embryos of fish, frogs, and fruit\u0000flies. Moreover, the spatial correlations in all three organisms are\u0000long-ranged and follow a similar power-law decay (y~$x^{-alpha}$ ) with\u0000$alpha$ less than unity for the nematic order parameter, suggesting a common\u0000underlying physical mechanism unifies events in these distantly related\u0000species. All three species exhibit similar propagation of the nematic phase,\u0000reminiscent of nucleation and growth phenomena. Finally, we use a theoretical\u0000model along with disruptions of cell adhesion and cell specification to\u0000characterize the minimal features required for formation of the nematic phase.\u0000Our results provide a framework for understanding a potentially universal\u0000features of metazoan embryogenesis and shed light on the advent of ordered\u0000structures during animal development.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141742640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}