ArXiv最新文献_第5页

Controlling tissue size by active fracture. 通过主动骨折控制组织大小。

ArXiv Pub Date : 2025-09-15

Wei Wang, Brian A Camley

{"title":"Controlling tissue size by active fracture.","authors":"Wei Wang, Brian A Camley","doi":"","DOIUrl":"","url":null,"abstract":"Groups of cells, including clusters of cancerous cells, multicellular organisms, and developing organs, may both grow and break apart. What physical factors control these fractures? In these processes, what sets the eventual size of clusters? We first develop a one-dimensional framework for understanding cell clusters that can fragment due to cell motility using an active particle model. We compute analytically how the break rate of cell-cell junctions depends on cell speed, cell persistence, and cell-cell junction properties. Next, we find the cluster size distributions, which differ depending on whether all cells can divide or only the cells on the edge of the cluster divide. Cluster size distributions depend solely on the ratio of the break rate to the growth rate - allowing us to predict how cluster size and variability depend on cell motility and cell-cell mechanics. Our results suggest that organisms can achieve better size control when cell division is restricted to the cluster boundaries or when fracture can be localized to the cluster center. Additionally, we derive a universal survival probability for an intact cluster $S(t)=mathrm{e}^{-k_d t}$ at steady state if all cells can divide, which is independent of the rupture kinetics and depends solely on the cell division rate $k_d$. Finally, we further corroborate the one-dimensional analytics with two-dimensional simulations, finding quantitative agreement with some elements of the theory across a wide range of cell motility. Our results link the general physics problem of a collective active escape over a barrier to size control, providing a quantitative measure of how motility can regulate organ or organism size.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11908369/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Engineering Spatial and Molecular Features from Cellular Niches to Inform Predictions of Inflammatory Bowel Disease. 从细胞壁龛的工程空间和分子特征告知炎症性肠病的预测。

ArXiv Pub Date : 2025-09-12

Myles Joshua Toledo Tan, Maria Kapetanaki, Panayiotis V Benos

{"title":"Engineering Spatial and Molecular Features from Cellular Niches to Inform Predictions of Inflammatory Bowel Disease.","authors":"Myles Joshua Toledo Tan, Maria Kapetanaki, Panayiotis V Benos","doi":"","DOIUrl":"","url":null,"abstract":"Differentiating between the two main subtypes of Inflammatory Bowel Disease (IBD): Crohn's disease (CD) and ulcerative colitis (UC) is a persistent clinical challenge due to overlapping presentations. This study introduces a novel computational framework that employs spatial transcriptomics (ST) to create an explainable machine learning model for IBD classification. We analyzed ST data from the colonic mucosa of healthy controls (HC), UC, and CD patients. Using Non-negative Matrix Factorization (NMF), we first identified four recurring cellular niches, representing distinct functional microenvironments within the tissue. From these niches, we systematically engineered 44 features capturing three key aspects of tissue pathology: niche composition, neighborhood enrichment, and niche-gene signals. A multilayer perceptron (MLP) classifier trained on these features achieved an accuracy of 0.774 ± 0.161 for the more challenging three-class problem (HC, UC, and CD) and 0.916±0.118 in the two-class problem of distinguishing IBD from healthy tissue. Crucially, model explainability analysis revealed that disruptions in the spatial organization of niches were the strongest predictors of general inflammation, while the classification between UC and CD relied on specific niche-gene expression signatures. This work provides a robust, proof-of-concept pipeline that transforms descriptive spatial data into an accurate and explainable predictive tool, offering not only a potential new diagnostic paradigm but also deeper insights into the distinct biological mechanisms that drive IBD subtypes.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440078/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The structure of deviations from maximum parsimony for densely-sampled data and applications for clade support estimation. 密集采样数据中最大简约性偏差的结构及其在支系支持度估计中的应用。

ArXiv Pub Date : 2025-09-12

William Howard-Snyder, Will Dumm, Mary Barker, Ognian Milanov, Claris Winston, David H Rich, Marc A Suchard, Frederick A Matsen Iv

{"title":"The structure of deviations from maximum parsimony for densely-sampled data and applications for clade support estimation.","authors":"William Howard-Snyder, Will Dumm, Mary Barker, Ognian Milanov, Claris Winston, David H Rich, Marc A Suchard, Frederick A Matsen Iv","doi":"","DOIUrl":"","url":null,"abstract":"How do phylogenetic reconstruction algorithms go astray when they return incorrect trees? This simple question has not been answered in detail, even for maximum parsimony (MP), the simplest phylogenetic criterion. Understanding MP has recently gained relevance in the regime of extremely dense sampling, where each virus sample commonly differs by zero or one mutation from another previously sampled virus. Although recent research shows that evolutionary histories in this regime are close to being maximally parsimonious, the structure of their deviations from MP is not yet understood. In this paper, we develop algorithms to understand how the correct tree deviates from being MP in the densely sampled case. By applying these algorithms to simulations that realistically mimic the evolution of SARS-CoV-2, we find that simulated trees frequently only deviate from maximally parsimonious trees locally, through simple structures consisting of the same mutation appearing independently on sister branches. We leverage this insight to design approaches for sampling near-MP trees and using them to efficiently estimate clade supports.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultra-low field 13C MRI of hyperpolarized pyruvate. 超极化丙酮酸的超低场13C MRI。

ArXiv Pub Date : 2025-09-12

Thomas Boele, Stephen J McBride, Megan Pike, Erica Curran, Patrick TomHon, Hester Braaksma, Sheng Shen, Neha Koonjoo, David E Korenchan, Eduard Chekmenev, Thomas Theis, David E J Waddington, Matthew S Rosen

{"title":"Ultra-low field 13C MRI of hyperpolarized pyruvate.","authors":"Thomas Boele, Stephen J McBride, Megan Pike, Erica Curran, Patrick TomHon, Hester Braaksma, Sheng Shen, Neha Koonjoo, David E Korenchan, Eduard Chekmenev, Thomas Theis, David E J Waddington, Matthew S Rosen","doi":"","DOIUrl":"","url":null,"abstract":"Medicine is evolving beyond therapy largely predicated on anatomical information and towards incorporating patient-specific molecular biomarkers of disease for more accurate diagnosis and effective treatment. The complementary combination of hyperpolarization by spin-lock induced crossing signal amplification by reversible exchange (SLIC SABRE) and low field magnetic resonance imaging (MRI) can enable accessible metabolic imaging to advance personalized medicine. Hyperpolarized 13C-enriched pyruvate has demonstrated utility for MRI of metabolism in cancer, heart disease and neurodegenerative disorders but has been restricted from widespread clinical adoption by a lack of access to affordable technology. Parahydrogen-based polarization techniques, paired with low-cost high-performance MRI at millitesla fields, offer a means of broadening the reach of metabolic imaging. Here we show results demonstrating in situ hyperpolarization of pyruvate at 6.5 mT by SLIC SABRE, followed by immediate readout without field cycling or sample shuttling. We achieve 13C signal enhancements several million times above thermal equilibrium at 6.5 mT, corresponding to polarization levels of approximately 3%. Leveraging this enhancement, we perform 13C MRI and acquire NMR spectra with resolution sufficient to distinguish chemical shifts between pyruvate isotopomers. These results show a viable pathway towards accessible metabolic imaging with hyperpolarized 13C MRI at ultra-low field.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated Tuning for Diffusion Inverse Problem Solvers without Generative Prior Retraining. 无生成先验再训练的扩散逆问题求解器的自动调谐。

ArXiv Pub Date : 2025-09-11

Yaşar Utku Alçalar, Junno Yun, Mehmet Akçakaya

{"title":"Automated Tuning for Diffusion Inverse Problem Solvers without Generative Prior Retraining.","authors":"Yaşar Utku Alçalar, Junno Yun, Mehmet Akçakaya","doi":"","DOIUrl":"","url":null,"abstract":"Diffusion/score-based models have recently emerged as powerful generative priors for solving inverse problems, including accelerated MRI reconstruction. While their flexibility allows decoupling the measurement model from the learned prior, their performance heavily depends on carefully tuned data fidelity weights, especially under fast sampling schedules with few denoising steps. Existing approaches often rely on heuristics or fixed weights, which fail to generalize across varying measurement conditions and irregular timestep schedules. In this work, we propose Zero-shot Adaptive Diffusion Sampling (ZADS), a test-time optimization method that adaptively tunes fidelity weights across arbitrary noise schedules without requiring retraining of the diffusion prior. ZADS treats the denoising process as a fixed unrolled sampler and optimizes fidelity weights in a self-supervised manner using only undersampled measurements. Experiments on the fastMRI knee dataset demonstrate that ZADS consistently outperforms both traditional compressed sensing and recent diffusion-based methods, showcasing its ability to deliver high-fidelity reconstructions across varying noise schedules and acquisition settings.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule Generation. 基于ADSeqGAN的小样本分子生成辅助鉴别器序列生成对抗网络。

ArXiv Pub Date : 2025-09-11

Haocheng Tang, Jing Long, Beihong Ji, Junmei Wang

{"title":"Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule Generation.","authors":"Haocheng Tang, Jing Long, Beihong Ji, Junmei Wang","doi":"","DOIUrl":"","url":null,"abstract":"In this work, we introduce Auxiliary Discriminator Sequence Generative Adversarial Networks (ADSeqGAN), a novel approach for molecular generation in small-sample datasets. Traditional generative models often struggle with limited training data, particularly in drug discovery, where molecular datasets for specific therapeutic targets, such as nucleic acids binders and central nervous system (CNS) drugs, are scarce. ADSeqGAN addresses this challenge by integrating an auxiliary random forest classifier as an additional discriminator into the GAN framework, significantly improves molecular generation quality and class specificity. Our method incorporates pretrained generator and Wasserstein distance to enhance training stability and diversity. We evaluate ADSeqGAN across three representative cases. First, on nucleic acid- and protein-targeting molecules, ADSeqGAN shows superior capability in generating nucleic acid binders compared to baseline models. Second, through oversampling, it markedly improves CNS drug generation, achieving higher yields than traditional de novo models. Third, in cannabinoid receptor type 1 (CB1) ligand design, ADSeqGAN generates novel druglike molecules, with 32.8% predicted actives surpassing hit rates of CB1-focused and general-purpose libraries when assessed by a target-specific LRIP-SF scoring function. Overall, ADSeqGAN offers a versatile framework for molecular design in data-scarce scenarios, with demonstrated applications in nucleic acid binders, CNS drugs, and CB1 ligands.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440062/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable AI for Accelerated Microstructure Imaging: A SHAP-Guided Protocol on the Connectome 2.0 scanner. 加速微结构成像的可解释人工智能：连接体2.0扫描仪上的shap引导协议。

ArXiv Pub Date : 2025-09-11

Quentin Uhl, Tommaso Pavan, Julianna Gerold, Kwok-Shing Chan, Yohan Jun, Shohei Fujita, Aneri Bhatt, Yixin Ma, Qiaochu Wang, Hong-Hsi Lee, Susie Y Huang, Berkin Bilgic, Ileana Jelescu

{"title":"Explainable AI for Accelerated Microstructure Imaging: A SHAP-Guided Protocol on the Connectome 2.0 scanner.","authors":"Quentin Uhl, Tommaso Pavan, Julianna Gerold, Kwok-Shing Chan, Yohan Jun, Shohei Fujita, Aneri Bhatt, Yixin Ma, Qiaochu Wang, Hong-Hsi Lee, Susie Y Huang, Berkin Bilgic, Ileana Jelescu","doi":"","DOIUrl":"","url":null,"abstract":"The diffusion MRI Neurite Exchange Imaging model offers a promising framework for probing gray matter microstructure by estimating parameters such as compartment sizes, diffusivities, and inter-compartmental water exchange time. However, existing protocols require long scan times. This study proposes a reduced acquisition scheme for the Connectome 2.0 scanner that preserves model accuracy while substantially shortening scan duration. We developed a data-driven framework using explainable artificial intelligence with a guided recursive feature elimination strategy to identify an optimal 8-feature subset from a 15-feature protocol. The performance of this optimized protocol was validated in vivo and benchmarked against the full acquisition and alternative reduction strategies. Parameter accuracy, preservation of anatomical contrast, and test-retest reproducibility were assessed. The reduced protocol yielded parameter estimates and cortical maps comparable to the full protocol, with low estimation errors in synthetic data and minimal impact on test-retest variability. Compared to theory-driven and heuristic reduction schemes, the optimized protocol demonstrated superior robustness, reducing the deviation in water exchange time estimates by over two-fold. In conclusion, this hybrid optimization framework enables viable imaging of neurite exchange in 14 minutes without loss of parameter fidelity. This approach supports the broader application of exchange-sensitive diffusion magnetic resonance imaging in neuroscience and clinical research, and offers a generalizable method for designing efficient acquisition protocols in biophysical parameter mapping.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What do the fundamental constants of physics tell us about life? 关于生命，物理学的基本常数告诉了我们什么？

ArXiv Pub Date : 2025-09-11

Pankaj Mehta, Jané Kondev

引用次数: 0

A 7T fMRI dataset of synthetic images for out-of-distribution modeling of vision. 一种用于视觉非分布建模的7T fMRI合成图像数据集。

ArXiv Pub Date : 2025-09-10

Alessandro T Gifford, Radoslaw M Cichy, Thomas Naselaris, Kendrick Kay

{"title":"A 7T fMRI dataset of synthetic images for out-of-distribution modeling of vision.","authors":"Alessandro T Gifford, Radoslaw M Cichy, Thomas Naselaris, Kendrick Kay","doi":"","DOIUrl":"","url":null,"abstract":"Large-scale datasets of brain responses such as the Natural Scenes Dataset (NSD) are boosting computational neuroscience research by enabling models of the brain with performances beyond what was possible just a decade ago. However, these datasets lack out-of-distribution (OOD) components, which are crucial for the development of more robust models. Here, we address this limitation by releasing NSD-synthetic, a dataset consisting of 7T fMRI responses from the same eight NSD participants for 284 synthetic images. We show that NSD-synthetic's fMRI responses reliably encode stimulus-related information and are OOD with respect to NSD. Furthermore, we provide a proof of principle that OOD generalization tests on NSD-synthetic reveal differences between models of the brain that are not detected with the original NSD data; we demonstrate that the degree of OOD (quantified as the distance between a set of responses and the training data used for modeling) is predictive of the magnitude of model failures; and we show that the concept of OOD is not restricted to artificial stimuli but can be usefully applied even within the domain of naturalistic stimuli. These results showcase how NSD-synthetic enables OOD generalization tests that facilitate the development of more robust models of visual processing and the formulation of more accurate theories of human vision.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low-Cost and Detunable Wireless Resonator Glasses for Enhanced Eye MRI with Concurrent High-Quality Whole-Brain MRI. 低成本和可拆卸的无线共振眼镜用于增强眼部MRI和高质量全脑MRI。

ArXiv Pub Date : 2025-09-10

Ming Lu, Xiaoyue Yang, Jason Moore, Pingping Li, Adam W Anderson, John C Gore, Seth A Smith, Xinqiang Yan

{"title":"Low-Cost and Detunable Wireless Resonator Glasses for Enhanced Eye MRI with Concurrent High-Quality Whole-Brain MRI.","authors":"Ming Lu, Xiaoyue Yang, Jason Moore, Pingping Li, Adam W Anderson, John C Gore, Seth A Smith, Xinqiang Yan","doi":"","DOIUrl":"","url":null,"abstract":"Purpose: To develop and evaluate a wearable wireless resonator glasses design that enhances eye MRI signal-to-noise ratio (SNR) without compromising whole-brain image quality at 7 T.Methods: The device integrates two detunable LC loop resonators into a lightweight, 3D-printed frame positioned near the eyes. The resonators passively couple to a standard 2Tx/32Rx head coil without hardware modifications. Bench tests assessed tuning, isolation, and detuning performance. B 1 + maps were measured in a head/shoulder phantom, and SNR maps were obtained in both phantom and in vivo experiments.Results: Bench measurements confirmed accurate tuning, strong inter-element isolation, and effective passive detuning. Phantom B 1 + mapping showed negligible differences between configurations with and without the resonators. Phantom and in vivo imaging demonstrated up to a ~3-fold SNR gain in the eye region, with no measurable SNR loss in the brain.Conclusion: The wireless resonator glasses provide a low-cost, easy-to-use solution that improves ocular SNR while preserving whole-brain image quality, enabling both dedicated eye MRI and simultaneous eye-brain imaging at ultrahigh field.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440073/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0