ArXiv最新文献

{"title":"Using topological data analysis to compare inter-subject variability across resting state functional MRI brain representations.","authors":"Ty Easley, Kevin Freese, Elizabeth Munch, Janine Bijsterbosch","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>In neuroimaging, extensive post-processing of resting-state functional MRI (rfMRI) data is necessary for its application and investigation in relation to brain-behavior associations. Such post-processing is used to derive brain representations, lower dimensional feature sets used for brain-behavior association studies. A brain representation involves a choice of dimension reduction (a parcellation into regions or networks) and a choice of feature type, such as spatial topography, connectivity matrix, amplitude. However, widespread variability in rfMRI brain representations has hindered both reproducibility and knowledge accumulation across the field. Brain representation choice effects measurements of inter-subject variability, which muddies the comparison and integration of findings. We leveraged persistent homology on the subject-space topologies induced by 34 different brain representations to enable direct comparison of brain representations in the context of individual differences. Our findings reveal the importance of considering feature type when comparing results derived from different brain representations, suggesting best practices for assessing the replicability and generalizability of brain-behavior research in rfMRI data.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440082/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082710","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}

{"title":"Cardiac mechanics modeling: recent developments and current challenges.","authors":"Aaron L Brown, Ju Liu, Daniel B Ennis, Alison L Marsden","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Patient-specific computational models of the heart are powerful tools for cardiovascular research and medicine, with demonstrated applications in treatment planning, device evaluation, and surgical decision-making. Yet constructing such models is inherently difficult, reflecting the extraordinary complexity of the heart itself. Numerous considerations are required, including reconstructing the anatomy from medical images, representing myocardial mesostructure, capturing material behavior, defining model geometry and boundary conditions, coupling multiple physics, and selecting numerical methods. Many of these choices involve a tradeoff between physiological fidelity and modeling complexity. In this review, we summarize recent advances and unresolved questions in each of these areas, with particular emphasis on cardiac tissue mechanics. We argue that clarifying which complexities are essential, and which can be safely simplified, will be key to enabling clinical translation of these models.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082608","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}

{"title":"Finding low-complexity DNA sequences with longdust.","authors":"Heng Li, Brian Li","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Motivation: </strong>Low-complexity (LC) DNA sequences are compositionally repetitive sequences that are often associated with increased variant density and variant calling artifacts. While algorithms for identifying LC sequences exist, they either lack rigorous mathematical foundation or are inefficient with long context windows.</p><p><strong>Results: </strong>Longdust is a new algorithm that efficiently identifies long LC sequences including centromeric satellite and tandem repeats with moderately long motifs. It defines string complexity by statistically modeling the <math><mrow><mi>k</mi></mrow> </math> -mer count distribution with the parameters: the <math><mrow><mi>k</mi></mrow> </math> -mer length, the context window size and a threshold on complexity. Longdust exhibits high performance on real data and high consistency with existing methods.</p><p><strong>Availability and implementation: </strong>https://github.com/lh3/longdust.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440070/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082694","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}

{"title":"SynLlama: Generating Synthesizable Molecules and Their Analogs with Large Language Models.","authors":"Kunyang Sun, Dorian Bagni, Joseph M Cavanagh, Yingze Wang, Jacob M Sawyer, Bo Zhou, Andrew Gritsevskiy, Oufan Zhang, Teresa Head-Gordon","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Generative machine learning models for exploring chemical space have shown immense promise, but many molecules they generate are too difficult to synthesize, making them impractical for further investigation or development. In this work, we present a novel approach by fine-tuning Meta's Llama3 Large Language Models (LLMs) to create SynLlama, which generates full synthetic pathways made of commonly accessible building blocks and robust organic reaction templates. SynLlama explores a large synthesizable space using significantly less data, and offers strong performance in both forward and bottom-up synthesis planning compared to other state-of-the-art methods. We find that SynLlama, even without training on external building blocks, can effectively generalize to unseen yet purchasable building blocks, meaning that its reconstruction capabilities extend to a broader synthesizable chemical space than the training data. We also demonstrate the use of SynLlama in a pharmaceutical context for synthesis planning of analog molecules and hit expansion leads for proposed inhibitors of target proteins, offering medicinal chemists a valuable tool for discovery.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12047903/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055456","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}

{"title":"Contrast-Free Ultrasound Microvascular Imaging via Radiality and Similarity Weighting.","authors":"Jingyi Yin, Jingke Zhang, Lijie Huang, U-Wai Lok, Ryan M DeRuiter, Kaipeng Ji, Yanzhe Zhao, Kate M Knoll, Kendra E Petersen, Tao Wu, Xiang-Yang Zhu, James D Krier, Kathryn A Robinson, Lilach O Lerman, Andrew J Bentall, Shigao Chen, Chengwu Huang","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Microvascular imaging has advanced significantly with ultrafast data acquisition and improved clutter filtering, enhancing the sensitivity of power Doppler imaging to small vessels. However, the image quality remains limited by spatial resolution and elevated background noise, both of which impede visualization and accurate quantification. To address these limitations, this study proposes a high-resolution cross-correlation Power Doppler (HR-XPD) method that integrates spatial radiality weighting with Doppler signal coherence analysis, thereby enhancing spatial resolution while suppressing artifacts and background noise. Quantitative evaluations in simulation and in vivo experiments on healthy human liver, transplanted human kidney, and pig kidney demonstrated that HR-XPD significantly improves microvascular resolvability and contrast compared to conventional PD. In vivo results showed up to a 2 to 3-fold enhancement in spatial resolution and an increase in contrast by up to 20 dB. High-resolution vascular details were clearly depicted within a short acquisition time of only 0.3 s-1.2 s without the use of contrast agents. These findings indicate that HR-XPD provides an effective, contrast-free, and high-resolution microvascular imaging approach with broad applicability in both preclinical and clinical research.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12440064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145082727","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}

{"title":"Geometry-Dependent Defect Merging Induces Bifurcated Dynamics in Active Networks.","authors":"Fan Yang, Shichen Liu, Hao Wang, Heun Jin Lee, Rob Phillips, Matt Thomson","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Cytoskeletal networks can repair defects to maintain structural integrity. However, the mechanisms and dynamics of defect merging remain poorly understood. Here we report a geometry-tunable merging mechanism in microtubule-motor networks initiated by active crosslinking. We directly generate defects using a light-controlled microtubule-motor system in O-shaped and V-shaped networks, and observe that the defects can self-close. Combining theory and experiment, we find that the V-shaped networks must overcome internal elastic resistance in order to zip up cracks, giving rise to a bifurcation of dynamics dependent on the initial opening angle of the crack: the crack merges below a critical angle and opens up at larger angles. Simulation of a continuum model reproduces the bifurcation dynamics, revealing the importance of overlapping boundary layers where free motors and microtubules can actively crosslink and thereby merge the defects. We also formulate a simple elastic-rod model that can qualitatively predict the critical angle, which is tunable by the network geometry.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136475/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144227902","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}

{"title":"Stiffness and force production of outer hair cells in simple model systems.","authors":"Kuni H Iwasa","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Cochlear outer hair cells (OHCs) have two mechanosensitive elements: the hair bundle with mechanotrasducer channels and the piezoelectric lateral wall of the cell body. The present report examines how these elements interact with each other by incorporating OHCs into the simplest local cochlear models. In the frequency range, typically above 1 kHz, where capacitive conductance is greater than the ionic conductance, hair bundle (HB) conductance drives the piezoelectric cell body and amplified oscillation by countering viscous drag, while the cell body increases its stiffness owing to strain-induced polarization, elevating the resonance frequency. Since HB sensitivity is essential for amplification, the resonance is not pure piezoelectric, but semi-piezoelectric. In the lower frequency range, typically lower than 100 Hz, strain induced polarization contributes to drag and the HB sensitivity increases cell body stiffness.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12306812/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144746519","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}

{"title":"Minibeam-pLATTICE: A novel proton LATTICE modality using minibeams.","authors":"Nimita Shinde, Weijie Zhang, Yuting Lin, Hao Gao","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Background: </strong>LATTICE, a form of spatially fractionated radiation therapy (SFRT) that delivers high-dose peaks and low-dose valleys within the target volume, has been clinically utilized for treating bulky tumors. However, its application to small-to-medium-sized target volumes remains challenging due to beam size limitations.</p><p><strong>Purpose: </strong>To address the challenge of applying LATTICE radiation therapy to small-to-medium-sized targets, this work proposes a novel proton LATTICE (pLATTICE) modality using minibeams, namely minibeam-pLATTICE, that can extend the LATTICE approach for small-to-medium target volumes.</p><p><strong>Methods: </strong>Three minibeam-pLATTICE methods are introduced. (1) M0: a fixed minibeam aperture orientation (e.g., 0°) for all beam angles; (2) M1: alternated minibeam aperture orientations (e.g., between 0° and 90°), for consecutive beam angles; (3) M2: multiple minibeam aperture orientations (e.g., 0° and 90°) for each beam angle. The purpose of M1 or M2 is to correct anisotropic dose distribution at lattice peaks due to the planar spatial modulation of minibeams. For each minibeam-pLATTICE method, an optimization problem is formulated to optimize dose uniformity in target peaks and valleys, as well as dose-volume-histogram-based objectives. This optimization problem is solved using iterative convex relaxation and alternating direction method of multipliers (ADMM).</p><p><strong>Results: </strong>Three minibeam-pLATTICE methods are validated to demonstrate the feasibility of minibeam-pLATTICE for two clinical head-and-neck (HN), one abdominal and one brain case. The advantages of this modality over conventional beam (CONV) pLATTICE are evaluated by comparing peak-to-valley dose ratio (PVDR) and dose delivered to organs at risk (OAR). All three minibeam-pLATTICE modalities achieved improved plan quality compared to CONV, with M2 yielding the best results. For instance, in one HN case, the following improvements were observed: PVDR increased to 3.73 (M2), compared to 3.27 (CONV), 3.72 (M0), and 3.49 (M1), while the mean dose to the mandible was reduced to 0.18 Gy (M2), compared to 0.33 Gy (CONV), 0.17 Gy (M0), and 0.14 Gy (M1).</p><p><strong>Conclusions: </strong>A novel minibeam-pLATTICE modality is proposed that can generate lattice dose patterns for small-to-medium target volumes, which are not achievable with conventional pLATTICE due to beam size limitations. Peak dose anisotropy due to 1D planar minibeam apertures is corrected through inverse treatment planning with alternating or multiple minibeam apertures per beam angle.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11888559/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588461","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}

{"title":"Optimizing normal tissue sparing via spatiotemporal optimization under equivalent tumor-radical efficacy.","authors":"Nimita Shinde, Wangyao Li, Ronald C Chen, Hao Gao","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Objective: </strong>Spatiotemporal optimization in radiation therapy involves determining the optimal number of dose delivery fractions (temporal) and the optimal dose per fraction (spatial). Traditional approaches focus on maximizing the biologically effective dose (BED) to the target while constraining BED to organs-at-risk (OAR), which may lead to insufficient BED for complete tumor cell kill. This work proposes a formulation that ensures adequate BED delivery to the target while minimizing BED to the OAR.</p><p><strong>Approach: </strong>A spatiotemporal optimization model is developed that incorporates an inequality constraint to guarantee sufficient BED for tumor cell kill while minimizing BED to the OAR. The model accounts for tumor proliferation dynamics, including lag time (delay before proliferation begins) and doubling time (time for tumor volume to double), to optimize dose fractionation.</p><p><strong>Main results: </strong>The proposed formulation is implemented for proton modality. The performance of our method is evaluated for varying lag times and doubling times. The results show that the mean BED to the target consistently meets the minimum requirement for tumor cell kill. Additionally, the mean BED to the OAR varies based on tumor proliferation dynamics. In the prostate case with lag time of 7 days and doubling time of 2 days, it is observed that the mean BED delivered to femoral head is lowest at approximately 20 fractions, making this an optimal choice. While in the head-and-neck case, the mean BED to the OAR decreases as the number of fractions increases, suggesting that a higher number of fractions is optimal. Thus, the proposed model effectively determines the optimal fractionation strategy under different tumor proliferation conditions.</p><p><strong>Significance: </strong>A spatiotemporal optimization model is presented that minimizes BED to the OAR while ensuring sufficient BED for tumor cell kill. By incorporating tumor lag time and doubling time, the approach identifies optimal number of fractions. This model can be extended to support hyperfractionation or accelerated fractionation strategies, offering a versatile tool for clinical treatment planning.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12425019/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145066761","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}

{"title":"A quantum computing approach to beam angle optimization.","authors":"Nimita Shinde, Ya-Nan Zhu, Haozheng Shen, Hao Gao","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Background: </strong>Beam angle optimization (BAO) is a critical component of radiation therapy (RT) treatment planning, where small changes in beam configuration can significantly impact treatment quality, especially for proton RT. Mathematically, BAO is a mixed integer programming (MIP) problem, which is NP-hard due to its exponential growing search space. Traditional optimization techniques often struggle with computational efficiency, necessitating the development of novel approaches.</p><p><strong>Purpose: </strong>This study introduces QC-BAO, a hybrid quantum-classical approach that leverages quantum computing to solve the MIP formulation of BAO.</p><p><strong>Methods: </strong>The proposed approach, QC-BAO, models BAO as an MIP problem, incorporating binary variables for beam angle selection and continuous variables for optimizing spot intensities for proton therapy. The proposed approach employs a hybrid quantum-classical framework, utilizing quantum computing to solve the binary decision component while integrating classical optimization techniques, including iterative convex relaxation and alternating direction method of multipliers.</p><p><strong>Results: </strong>Computational experiments were conducted on clinical test cases to evaluate QC-BAO's performance against clinically verified angles and a heuristic approach, GS-BAO. QC-BAO demonstrated improved treatment plan quality over both clinical and GS-BAO. The method consistently increased the conformity index (CI) for target coverage while reducing mean and maximum doses to organs-at-risk (OAR). Additionally, QC-BAO produced the lowest objective function value, confirming its superior optimization capability.</p><p><strong>Conclusions: </strong>The findings highlight the potential of quantum computing to enhance the solution to BAO problem by demonstrated improvement in plan quality using the proposed method, QC-BAO. This study paves the way for future clinical implementation of quantum-accelerated optimization in RT.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12036446/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144061674","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}