James D. Shemilt, Alex Horsley, Jim M. Wild, Oliver E. Jensen, Alice B. Thompson, Carl A. Whitfield
Airway constriction and blockage in obstructive lung diseases create barriers to effective drug deposition by altering how different regions of the lungs are ventilated. Established computational particle deposition models have not accounted for these impacts of disease. We present a new particle deposition model that calculates ventilation based on the resistance of each airway, such that ventilation patterns respond to airway constriction. We incorporate distal airway constrictions representative of cystic fibrosis, and assess the resulting impact on deposition down to the single-airway scale. We demonstrate how constriction reduces deposition in the airways directly distal and proximal to the affected airways. When multiple constrictions are clustered together, deposition in the central airways proximal to the constrictions is more strongly reduced, and deposition in the other central airways is generally increased. This results in more uneven deposition in both the central and distal airways, even when constrictions affect only the distal airways. We use our model to calculate lung clearance index (LCI), a clinical measure of ventilation heterogeneity, in lungs with constrictions of various severities localised to one lobe. We find an increase in LCI coinciding with a significant drop in deposition throughout the affected lobe.
{"title":"Non-local impacts of distal airway constrictions on patterns of inhaled particle deposition","authors":"James D. Shemilt, Alex Horsley, Jim M. Wild, Oliver E. Jensen, Alice B. Thompson, Carl A. Whitfield","doi":"arxiv-2404.03760","DOIUrl":"https://doi.org/arxiv-2404.03760","url":null,"abstract":"Airway constriction and blockage in obstructive lung diseases create barriers\u0000to effective drug deposition by altering how different regions of the lungs are\u0000ventilated. Established computational particle deposition models have not\u0000accounted for these impacts of disease. We present a new particle deposition\u0000model that calculates ventilation based on the resistance of each airway, such\u0000that ventilation patterns respond to airway constriction. We incorporate distal\u0000airway constrictions representative of cystic fibrosis, and assess the\u0000resulting impact on deposition down to the single-airway scale. We demonstrate\u0000how constriction reduces deposition in the airways directly distal and proximal\u0000to the affected airways. When multiple constrictions are clustered together,\u0000deposition in the central airways proximal to the constrictions is more\u0000strongly reduced, and deposition in the other central airways is generally\u0000increased. This results in more uneven deposition in both the central and\u0000distal airways, even when constrictions affect only the distal airways. We use\u0000our model to calculate lung clearance index (LCI), a clinical measure of\u0000ventilation heterogeneity, in lungs with constrictions of various severities\u0000localised to one lobe. We find an increase in LCI coinciding with a significant\u0000drop in deposition throughout the affected lobe.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140585051","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}
James K Ruffle, Samia Mohinta, Kelly Pegoretti Baruteau, Rebekah Rajiah, Faith Lee, Sebastian Brandner, Parashkev Nachev, Harpreet Hyare
The VASARI MRI feature set is a quantitative system designed to standardise glioma imaging descriptions. Though effective, deriving VASARI is time-consuming and seldom used in clinical practice. This is a problem that machine learning could plausibly automate. Using glioma data from 1172 patients, we developed VASARI-auto, an automated labelling software applied to both open-source lesion masks and our openly available tumour segmentation model. In parallel, two consultant neuroradiologists independently quantified VASARI features in a subsample of 100 glioblastoma cases. We quantified: 1) agreement across neuroradiologists and VASARI-auto; 2) calibration of performance equity; 3) an economic workforce analysis; and 4) fidelity in predicting patient survival. Tumour segmentation was compatible with the current state of the art and equally performant regardless of age or sex. A modest inter-rater variability between in-house neuroradiologists was comparable to between neuroradiologists and VASARI-auto, with far higher agreement between VASARI-auto methods. The time taken for neuroradiologists to derive VASARI was substantially higher than VASARI-auto (mean time per case 317 vs. 3 seconds). A UK hospital workforce analysis forecast that three years of VASARI featurisation would demand 29,777 consultant neuroradiologist workforce hours ({pounds}1,574,935), reducible to 332 hours of computing time (and {pounds}146 of power) with VASARI-auto. The best-performing survival model utilised VASARI-auto features as opposed to those derived by neuroradiologists. VASARI-auto is a highly efficient automated labelling system with equitable performance across patient age or sex, a favourable economic profile if used as a decision support tool, and with non-inferior fidelity in downstream patient survival prediction. Future work should iterate upon and integrate such tools to enhance patient care.
{"title":"VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI","authors":"James K Ruffle, Samia Mohinta, Kelly Pegoretti Baruteau, Rebekah Rajiah, Faith Lee, Sebastian Brandner, Parashkev Nachev, Harpreet Hyare","doi":"arxiv-2404.15318","DOIUrl":"https://doi.org/arxiv-2404.15318","url":null,"abstract":"The VASARI MRI feature set is a quantitative system designed to standardise\u0000glioma imaging descriptions. Though effective, deriving VASARI is\u0000time-consuming and seldom used in clinical practice. This is a problem that\u0000machine learning could plausibly automate. Using glioma data from 1172\u0000patients, we developed VASARI-auto, an automated labelling software applied to\u0000both open-source lesion masks and our openly available tumour segmentation\u0000model. In parallel, two consultant neuroradiologists independently quantified\u0000VASARI features in a subsample of 100 glioblastoma cases. We quantified: 1)\u0000agreement across neuroradiologists and VASARI-auto; 2) calibration of\u0000performance equity; 3) an economic workforce analysis; and 4) fidelity in\u0000predicting patient survival. Tumour segmentation was compatible with the\u0000current state of the art and equally performant regardless of age or sex. A\u0000modest inter-rater variability between in-house neuroradiologists was\u0000comparable to between neuroradiologists and VASARI-auto, with far higher\u0000agreement between VASARI-auto methods. The time taken for neuroradiologists to\u0000derive VASARI was substantially higher than VASARI-auto (mean time per case 317\u0000vs. 3 seconds). A UK hospital workforce analysis forecast that three years of\u0000VASARI featurisation would demand 29,777 consultant neuroradiologist workforce\u0000hours ({pounds}1,574,935), reducible to 332 hours of computing time (and\u0000{pounds}146 of power) with VASARI-auto. The best-performing survival model\u0000utilised VASARI-auto features as opposed to those derived by neuroradiologists.\u0000VASARI-auto is a highly efficient automated labelling system with equitable\u0000performance across patient age or sex, a favourable economic profile if used as\u0000a decision support tool, and with non-inferior fidelity in downstream patient\u0000survival prediction. Future work should iterate upon and integrate such tools\u0000to enhance patient care.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140806614","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}
How pattern and form are generated in a reproducible manner during embryogenesis remains poorly understood. Intestinal organoid morphogenesis involves a number of mechanochemical regulators, including cell-type specific cytoskeletal forces and osmotically-driven lumen volume changes. However, whether and how these forces are coordinated in time and space via feedbacks to ensure robust morphogenesis remains unclear. Here, we propose a minimal physical model of organoid morphogenesis with local cellular mechano-sensation, where lumen volume changes can impact epithelial shape via both direct mechanical (passive) and indirect mechanosensitive (active) mechanisms. We show how mechano-sensitive feedbacks on cytoskeletal tension generically give rise to morphological bistability, where both bulged (open) and budded (closed) crypt states are possible and dependent on the history of volume changes. Such bistability can explain several paradoxical experimental observations, such as the importance of the timing of lumen shrinkage and robustness of the final morphogenetic state to mechanical perturbations. More quantitatively, we performed mechanical and pharmacological experiments to validate the key modelling assumptions and make quantitative predictions on organoid morphogenesis. This suggests that bistability arising from feedbacks between cellular tensions and fluid pressure could be a general mechanism to allow for the coordination of multicellular shape changes in developing systems.
{"title":"Mechanochemical bistability of intestinal organoids enables robust morphogenesis","authors":"Shi-Lei Xue, Qiutan Yang, Prisca Liberali, Edouard Hannezo","doi":"arxiv-2403.19900","DOIUrl":"https://doi.org/arxiv-2403.19900","url":null,"abstract":"How pattern and form are generated in a reproducible manner during\u0000embryogenesis remains poorly understood. Intestinal organoid morphogenesis\u0000involves a number of mechanochemical regulators, including cell-type specific\u0000cytoskeletal forces and osmotically-driven lumen volume changes. However,\u0000whether and how these forces are coordinated in time and space via feedbacks to\u0000ensure robust morphogenesis remains unclear. Here, we propose a minimal\u0000physical model of organoid morphogenesis with local cellular mechano-sensation,\u0000where lumen volume changes can impact epithelial shape via both direct\u0000mechanical (passive) and indirect mechanosensitive (active) mechanisms. We show\u0000how mechano-sensitive feedbacks on cytoskeletal tension generically give rise\u0000to morphological bistability, where both bulged (open) and budded (closed)\u0000crypt states are possible and dependent on the history of volume changes. Such\u0000bistability can explain several paradoxical experimental observations, such as\u0000the importance of the timing of lumen shrinkage and robustness of the final\u0000morphogenetic state to mechanical perturbations. More quantitatively, we\u0000performed mechanical and pharmacological experiments to validate the key\u0000modelling assumptions and make quantitative predictions on organoid\u0000morphogenesis. This suggests that bistability arising from feedbacks between\u0000cellular tensions and fluid pressure could be a general mechanism to allow for\u0000the coordination of multicellular shape changes in developing systems.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140584709","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}
Within the context of epithelial monolayers, T1 transitions, also known as cell-intercalations, are topological rearrangements of cells that contribute to fluidity of the epithelial monolayers. We use a multi-phase field model to show that the ensemble-averaged flow profile of a T1 transition exhibits a saddle point structure, where large velocities are localised near cells undergoing T1 transitions, contributing to vortical flow. This tissue fluidisation corresponds to the dispersion of cells relative to each other. While the temporal evolution of the mean pair-separation distance between initially neighbouring cells depends on specific model details, the mean pair-separation distance increases linearly with the number of T1 transitions, in a way that is robust to model parameters.
{"title":"From cell intercalation to flow, the importance of T1 transitions","authors":"Harish P. Jain, Axel Voigt, Luiza Angheluta","doi":"arxiv-2403.20100","DOIUrl":"https://doi.org/arxiv-2403.20100","url":null,"abstract":"Within the context of epithelial monolayers, T1 transitions, also known as\u0000cell-intercalations, are topological rearrangements of cells that contribute to\u0000fluidity of the epithelial monolayers. We use a multi-phase field model to show\u0000that the ensemble-averaged flow profile of a T1 transition exhibits a saddle\u0000point structure, where large velocities are localised near cells undergoing T1\u0000transitions, contributing to vortical flow. This tissue fluidisation\u0000corresponds to the dispersion of cells relative to each other. While the\u0000temporal evolution of the mean pair-separation distance between initially\u0000neighbouring cells depends on specific model details, the mean pair-separation\u0000distance increases linearly with the number of T1 transitions, in a way that is\u0000robust to model parameters.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140584831","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}
This factorial experiment was conducted in a greenhouse during the period of May 3, 2021 to August 5, 2021 at the research farm belongs to the Horticulture Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani, Iraq. The experiment was designed to study the effect of some biostimulants, individually and their combinations, on cucumber plants performance under greenhouse conditions; in addition to compare the results with of chemical fertilizers application. The treatments consisted of control (without adding any kinds of biostimulants) recommended dose of 100% chemical fertilizers (RDCF), seaweed extracts (SE), moringa leaf extract (MLE), bacterial-based biostimulant of Fulzym-plus (FP), that contains Bacillus subtilis and Pseudomonas putida, (SE+MLE), (SE+FP), (MLE+FP), and (SE+MLE+FP). The experiment was laid out in simple RCBD with 3 replications. The results showed that the application of different biostimulants, individually and their combinations, significantly improved the root growth characteristics. However, the highest values of lateral roots number per plant, lateral root length, lateral root diameter and root system dry weight were recorded by the application of recommended dose of chemical fertilizer (RDCF). While, this treatment was not different substantially with the triple combination of the tested biostimulants (SE+FP+MLE) in all studied root characteristics. In addition, untreated plants registered the minimum value of all the mentioned characters.
{"title":"Effect of seaweed, moringa leaf extract and biofertilizer on growth, yield and fruit quality of cucumber (Cucumis sativus L.) under greenhouse condition","authors":"Roshna Faeq Kakabra","doi":"arxiv-2403.17984","DOIUrl":"https://doi.org/arxiv-2403.17984","url":null,"abstract":"This factorial experiment was conducted in a greenhouse during the period of\u0000May 3, 2021 to August 5, 2021 at the research farm belongs to the Horticulture\u0000Department, College of Agricultural Engineering Sciences, University of\u0000Sulaimani, Sulaimani, Iraq. The experiment was designed to study the effect of\u0000some biostimulants, individually and their combinations, on cucumber plants\u0000performance under greenhouse conditions; in addition to compare the results\u0000with of chemical fertilizers application. The treatments consisted of control\u0000(without adding any kinds of biostimulants) recommended dose of 100% chemical\u0000fertilizers (RDCF), seaweed extracts (SE), moringa leaf extract (MLE),\u0000bacterial-based biostimulant of Fulzym-plus (FP), that contains Bacillus\u0000subtilis and Pseudomonas putida, (SE+MLE), (SE+FP), (MLE+FP), and (SE+MLE+FP).\u0000The experiment was laid out in simple RCBD with 3 replications. The results\u0000showed that the application of different biostimulants, individually and their\u0000combinations, significantly improved the root growth characteristics. However,\u0000the highest values of lateral roots number per plant, lateral root length,\u0000lateral root diameter and root system dry weight were recorded by the\u0000application of recommended dose of chemical fertilizer (RDCF). While, this\u0000treatment was not different substantially with the triple combination of the\u0000tested biostimulants (SE+FP+MLE) in all studied root characteristics. In\u0000addition, untreated plants registered the minimum value of all the mentioned\u0000characters.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140314664","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}
The mineralized collagen fibril is the main building block of hard tissues and it directly affects the macroscopic mechanics of biological tissues such as bone. The mechanical behavior of the fibril itself is determined by its structure: the content of collagen molecules, minerals, and cross-links, and the mechanical interactions and properties of these components. Advanced-Glycation-Endproducts (AGEs) cross-linking between tropocollagen molecules within the collagen fibril is one important factor that is believed to have a major influence on the tissue. For instance, it has been shown that brittleness in bone correlates with increased AGEs densities. However, the underlying nano-scale mechanisms within the mineralized collagen fibril remain unknown. Here, we study the effect of mineral and AGEs cross-linking on fibril deformation and fracture behavior by performing destructive tensile tests using coarse-grained molecular dynamics simulations. Our results demonstrate that after exceeding a critical content of mineral, it induces stiffening of the collagen fibril at high strain levels. We show that mineral morphology and location affect collagen fibril mechanics: The mineral content at which this stiffening occurs depends on the mineral's location and morphology. Further, both, increasing AGEs density and mineral content lead to stiffening and increased peak stresses. At low mineral contents, the mechanical response of the fibril is dominated by the AGEs, while at high mineral contents, the mineral itself determines fibril mechanics.
{"title":"Mineral and cross-linking in collagen fibrils: The mechanical behavior of bone tissue at the nano-scale","authors":"Julia Kamml, Claire Acevedo, David Kammer","doi":"arxiv-2403.11753","DOIUrl":"https://doi.org/arxiv-2403.11753","url":null,"abstract":"The mineralized collagen fibril is the main building block of hard tissues\u0000and it directly affects the macroscopic mechanics of biological tissues such as\u0000bone. The mechanical behavior of the fibril itself is determined by its\u0000structure: the content of collagen molecules, minerals, and cross-links, and\u0000the mechanical interactions and properties of these components.\u0000Advanced-Glycation-Endproducts (AGEs) cross-linking between tropocollagen\u0000molecules within the collagen fibril is one important factor that is believed\u0000to have a major influence on the tissue. For instance, it has been shown that\u0000brittleness in bone correlates with increased AGEs densities. However, the\u0000underlying nano-scale mechanisms within the mineralized collagen fibril remain\u0000unknown. Here, we study the effect of mineral and AGEs cross-linking on fibril\u0000deformation and fracture behavior by performing destructive tensile tests using\u0000coarse-grained molecular dynamics simulations. Our results demonstrate that\u0000after exceeding a critical content of mineral, it induces stiffening of the\u0000collagen fibril at high strain levels. We show that mineral morphology and\u0000location affect collagen fibril mechanics: The mineral content at which this\u0000stiffening occurs depends on the mineral's location and morphology. Further,\u0000both, increasing AGEs density and mineral content lead to stiffening and\u0000increased peak stresses. At low mineral contents, the mechanical response of\u0000the fibril is dominated by the AGEs, while at high mineral contents, the\u0000mineral itself determines fibril mechanics.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140165832","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}
Adam A. Malik, Cecilia Krona, Soumi Kundu, Philip Gerlee, Sven Nelander
Patient-derived cells (PDC) mouse xenografts are increasingly important tools in glioblastoma (GBM) research, essential to investigate case-specific growth patterns and treatment responses. Despite the central role of xenograft models in the field, few good simulation models are available to probe the dynamics of tumor growth and to support therapy design. We therefore propose a new framework for the patient-specific simulation of GBM in the mouse brain. Unlike existing methods, our simulations leverage a high-resolution map of the mouse brain anatomy to yield patient-specific results that are in good agreement with experimental observations. To facilitate the fitting of our model to histological data, we use Approximate Bayesian Computation. Because our model uses few parameters, reflecting growth, invasion and niche dependencies, it is well suited for case comparisons and for probing treatment effects. We demonstrate how our model can be used to simulate different treatment by perturbing the different model parameters. We expect in silico replicates of mouse xenograft tumors can improve the assessment of therapeutic outcomes and boost the statistical power of preclinical GBM studies.
{"title":"Anatomically aware simulation of patient-specific glioblastoma xenografts","authors":"Adam A. Malik, Cecilia Krona, Soumi Kundu, Philip Gerlee, Sven Nelander","doi":"arxiv-2403.09182","DOIUrl":"https://doi.org/arxiv-2403.09182","url":null,"abstract":"Patient-derived cells (PDC) mouse xenografts are increasingly important tools\u0000in glioblastoma (GBM) research, essential to investigate case-specific growth\u0000patterns and treatment responses. Despite the central role of xenograft models\u0000in the field, few good simulation models are available to probe the dynamics of\u0000tumor growth and to support therapy design. We therefore propose a new\u0000framework for the patient-specific simulation of GBM in the mouse brain. Unlike\u0000existing methods, our simulations leverage a high-resolution map of the mouse\u0000brain anatomy to yield patient-specific results that are in good agreement with\u0000experimental observations. To facilitate the fitting of our model to\u0000histological data, we use Approximate Bayesian Computation. Because our model\u0000uses few parameters, reflecting growth, invasion and niche dependencies, it is\u0000well suited for case comparisons and for probing treatment effects. We\u0000demonstrate how our model can be used to simulate different treatment by\u0000perturbing the different model parameters. We expect in silico replicates of\u0000mouse xenograft tumors can improve the assessment of therapeutic outcomes and\u0000boost the statistical power of preclinical GBM studies.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155227","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}
Romane GrosUniversity of Bern, Institute of Tissue Medicine and Pathology, Bern, SwitzerlandUniversity of Bern, Graduate School for Cellular and Biomedical Sciences, Bern, Switzerland, Omar Rodriguez-NunezBern University Hospital, University of Bern, Department of Neurosurgery, Inselspital, Bern, Switzerland, Leonard FelgerBern University Hospital, University of Bern, Department of Neurosurgery, Inselspital, Bern, Switzerland, Stefano MoriconiUniversity of Bern, Inselspital, Bern University Hospital, University Institute of Diagnostic and Interventional Radiology, Support Center for Advanced Neuroimaging, Bern, Switzerland, Richard McKinleyUniversity of Bern, Inselspital, Bern University Hospital, University Institute of Diagnostic and Interventional Radiology, Support Center for Advanced Neuroimaging, Bern, Switzerland, Angelo PierangeloIP Paris, École Polytechnique, CNRS, LPICM, Palaiseau, France, Tatiana NovikovaIP Paris, École Polytechnique, CNRS, LPICM, Palaiseau, France, Erik VassellaUniversity of Bern, Institute of Tissue Medicine and Pathology, Bern, Switzerland, Philippe SchuchtLausanne University Hospital and University of Lausanne, Institute of Pathology, Lausanne, Switzerland, Ekkehard HewerLausanne University Hospital and University of Lausanne, Institute of Pathology, Lausanne, Switzerland, Theoni MaragkouUniversity of Bern, Institute of Tissue Medicine and Pathology, Bern, Switzerland
Neuro-oncological surgery is the primary brain cancer treatment, yet it faces challenges with gliomas due to their invasiveness and the need to preserve neurological function. Hence, radical resection is often unfeasible, highlighting the importance of precise tumor margin delineation to prevent neurological deficits and improve prognosis. Imaging Mueller polarimetry, an effective modality in various organ tissues, seems a promising approach for tumor delineation in neurosurgery. To further assess its use, we characterized the polarimetric properties by analysing 45 polarimetric measurements of 27 fresh brain tumor samples, including different tumor types with a strong focus on gliomas. Our study integrates a wide-field imaging Mueller polarimetric system and a novel neuropathology protocol, correlating polarimetric and histological data for accurate tissue identification. An image processing pipeline facilitated the alignment and overlay of polarimetric images and histological masks. Variations in depolarization values were observed for grey and white matter of brain tumor tissue, while differences in linear retardance were seen only within white matter of brain tumor tissue. Notably, we identified pronounced optical axis azimuth randomization within tumor regions. This study lays the foundation for machine learning-based brain tumor segmentation algorithms using polarimetric data, facilitating intraoperative diagnosis and decision making.
{"title":"Characterization of Polarimetric Properties in Various Brain Tumor Types Using Wide-Field Imaging Mueller Polarimetry","authors":"Romane GrosUniversity of Bern, Institute of Tissue Medicine and Pathology, Bern, SwitzerlandUniversity of Bern, Graduate School for Cellular and Biomedical Sciences, Bern, Switzerland, Omar Rodriguez-NunezBern University Hospital, University of Bern, Department of Neurosurgery, Inselspital, Bern, Switzerland, Leonard FelgerBern University Hospital, University of Bern, Department of Neurosurgery, Inselspital, Bern, Switzerland, Stefano MoriconiUniversity of Bern, Inselspital, Bern University Hospital, University Institute of Diagnostic and Interventional Radiology, Support Center for Advanced Neuroimaging, Bern, Switzerland, Richard McKinleyUniversity of Bern, Inselspital, Bern University Hospital, University Institute of Diagnostic and Interventional Radiology, Support Center for Advanced Neuroimaging, Bern, Switzerland, Angelo PierangeloIP Paris, École Polytechnique, CNRS, LPICM, Palaiseau, France, Tatiana NovikovaIP Paris, École Polytechnique, CNRS, LPICM, Palaiseau, France, Erik VassellaUniversity of Bern, Institute of Tissue Medicine and Pathology, Bern, Switzerland, Philippe SchuchtLausanne University Hospital and University of Lausanne, Institute of Pathology, Lausanne, Switzerland, Ekkehard HewerLausanne University Hospital and University of Lausanne, Institute of Pathology, Lausanne, Switzerland, Theoni MaragkouUniversity of Bern, Institute of Tissue Medicine and Pathology, Bern, Switzerland","doi":"arxiv-2403.09561","DOIUrl":"https://doi.org/arxiv-2403.09561","url":null,"abstract":"Neuro-oncological surgery is the primary brain cancer treatment, yet it faces\u0000challenges with gliomas due to their invasiveness and the need to preserve\u0000neurological function. Hence, radical resection is often unfeasible,\u0000highlighting the importance of precise tumor margin delineation to prevent\u0000neurological deficits and improve prognosis. Imaging Mueller polarimetry, an\u0000effective modality in various organ tissues, seems a promising approach for\u0000tumor delineation in neurosurgery. To further assess its use, we characterized\u0000the polarimetric properties by analysing 45 polarimetric measurements of 27\u0000fresh brain tumor samples, including different tumor types with a strong focus\u0000on gliomas. Our study integrates a wide-field imaging Mueller polarimetric\u0000system and a novel neuropathology protocol, correlating polarimetric and\u0000histological data for accurate tissue identification. An image processing\u0000pipeline facilitated the alignment and overlay of polarimetric images and\u0000histological masks. Variations in depolarization values were observed for grey\u0000and white matter of brain tumor tissue, while differences in linear retardance\u0000were seen only within white matter of brain tumor tissue. Notably, we\u0000identified pronounced optical axis azimuth randomization within tumor regions.\u0000This study lays the foundation for machine learning-based brain tumor\u0000segmentation algorithms using polarimetric data, facilitating intraoperative\u0000diagnosis and decision making.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140155140","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}
Oliver M. DrozdowskiHeidelberg University, Germany, Ulrich S. SchwarzHeidelberg University, Germany
Epithelial monolayers are a central building block of complex organisms. Topological defects have emerged as important elements for single cell behavior in flat epithelia. Here we theoretically study such defects in a three-dimensional vertex model for spherical epithelia like cysts or intestinal organoids. We find that they lead to the same generic morphological instability to an icosahedral shape as it is known from spherical elastic shells like virus capsids, polymerized vesicles or buckyballs. We derive analytical expressions for the effective stretching and bending moduli as a function of the parameters of the vertex model, in excellent agreement with computer simulations. These equations accurately predict both the buckling of a flat epithelial monolayer under uniaxial compression and the faceting transition around the topological defects in spherical epithelia. We further show that localized apico-basal tension asymmetries allow them to reduce the transition threshold to small system sizes.
{"title":"Morphological instability at topological defects in a three-dimensional vertex model for spherical epithelia","authors":"Oliver M. DrozdowskiHeidelberg University, Germany, Ulrich S. SchwarzHeidelberg University, Germany","doi":"arxiv-2403.08954","DOIUrl":"https://doi.org/arxiv-2403.08954","url":null,"abstract":"Epithelial monolayers are a central building block of complex organisms.\u0000Topological defects have emerged as important elements for single cell behavior\u0000in flat epithelia. Here we theoretically study such defects in a\u0000three-dimensional vertex model for spherical epithelia like cysts or intestinal\u0000organoids. We find that they lead to the same generic morphological instability\u0000to an icosahedral shape as it is known from spherical elastic shells like virus\u0000capsids, polymerized vesicles or buckyballs. We derive analytical expressions\u0000for the effective stretching and bending moduli as a function of the parameters\u0000of the vertex model, in excellent agreement with computer simulations. These\u0000equations accurately predict both the buckling of a flat epithelial monolayer\u0000under uniaxial compression and the faceting transition around the topological\u0000defects in spherical epithelia. We further show that localized apico-basal\u0000tension asymmetries allow them to reduce the transition threshold to small\u0000system sizes.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140156780","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}
Michael Phillips, Giuseppe Tronci, Christopher M. Pask, Stephen J. Russell
Implantable hydrogels should ideally possess mechanical properties matched to the surrounding tissues to enable adequate mechanical function while regeneration occurs. This can be challenging, especially when degradable systems with high water content and hydrolysable chemical bonds are required in anatomical sites under constant mechanical stimulation, e.g. a foot ulcer cavity. In these circumstances, the design of hydrogel composites is a promising strategy to provide controlled structural features and macroscopic properties over time. To explore this strategy, the synthesis of a new photocurable elastomeric polymer, poly(glycerol-co-sebacic acid-co-lactic acid-co-polyethylene glycol) acrylate (PGSLPA), is investigated, along with its processing into UV-cured hydrogels, electrospun nonwovens and fibre-reinforced variants, without the need for a high temperature curing step or use of hazardous solvents. The mechanical properties of bioresorbable PGSLPA hydrogels were studied with and without electrospun nonwoven reinforcement and with varied layered configurations, aiming to determine the effects of microstructure on bulk compressive strength and elasticity. The nonwoven reinforced PGSLPA hydrogels exhibited a 60 % increase in compressive strength and an 80 % increase in elastic moduli compared to fibre-free PGSLPA samples. Mechanical properties of the fibre-reinforced hydrogels could also be modulated by altering the layering arrangement of the nonwoven and hydrogel phase. The nanofibre reinforced PGSLPA hydrogels also exhibited good elastic recovery, as evidenced by hysteresis in compression fatigue stress-strain evaluations showing a return to original dimensions.
{"title":"Nonwoven Reinforced Photocurable Poly(glycerol seba-cate)-Based Hydrogels","authors":"Michael Phillips, Giuseppe Tronci, Christopher M. Pask, Stephen J. Russell","doi":"arxiv-2403.08392","DOIUrl":"https://doi.org/arxiv-2403.08392","url":null,"abstract":"Implantable hydrogels should ideally possess mechanical properties matched to\u0000the surrounding tissues to enable adequate mechanical function while\u0000regeneration occurs. This can be challenging, especially when degradable\u0000systems with high water content and hydrolysable chemical bonds are required in\u0000anatomical sites under constant mechanical stimulation, e.g. a foot ulcer\u0000cavity. In these circumstances, the design of hydrogel composites is a\u0000promising strategy to provide controlled structural features and macroscopic\u0000properties over time. To explore this strategy, the synthesis of a new\u0000photocurable elastomeric polymer, poly(glycerol-co-sebacic acid-co-lactic\u0000acid-co-polyethylene glycol) acrylate (PGSLPA), is investigated, along with its\u0000processing into UV-cured hydrogels, electrospun nonwovens and fibre-reinforced\u0000variants, without the need for a high temperature curing step or use of\u0000hazardous solvents. The mechanical properties of bioresorbable PGSLPA hydrogels\u0000were studied with and without electrospun nonwoven reinforcement and with\u0000varied layered configurations, aiming to determine the effects of\u0000microstructure on bulk compressive strength and elasticity. The nonwoven\u0000reinforced PGSLPA hydrogels exhibited a 60 % increase in compressive strength\u0000and an 80 % increase in elastic moduli compared to fibre-free PGSLPA samples.\u0000Mechanical properties of the fibre-reinforced hydrogels could also be modulated\u0000by altering the layering arrangement of the nonwoven and hydrogel phase. The\u0000nanofibre reinforced PGSLPA hydrogels also exhibited good elastic recovery, as\u0000evidenced by hysteresis in compression fatigue stress-strain evaluations\u0000showing a return to original dimensions.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140129009","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}
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