Biophysical reports最新文献_第9页

An efficient EPR spin-labeling method enables insights into conformational changes in DNA. 通过高效的 EPR 自旋标记法，可以深入了解 DNA 的构象变化。

IF 2.4

Biophysical reports Pub Date : 2024-09-11 Epub Date: 2024-06-28 DOI: 10.1016/j.bpr.2024.100168

Melanie Hirsch, Lukas Hofmann, Idan Yakobov, Shirin Kahremany, Hila Sameach, Yulia Shenberger, Lada Gevorkyan-Airapetov, Sharon Ruthstein

引用次数: 0

Tunable intracellular transport on converging microtubule morphologies. 汇聚微管形态上的可调细胞内运输。

IF 2.4

Biophysical reports Pub Date : 2024-09-11 Epub Date: 2024-07-10 DOI: 10.1016/j.bpr.2024.100171

Niranjan Sarpangala, Brooke Randell, Ajay Gopinathan, Oleg Kogan

{"title":"Tunable intracellular transport on converging microtubule morphologies.","authors":"Niranjan Sarpangala, Brooke Randell, Ajay Gopinathan, Oleg Kogan","doi":"10.1016/j.bpr.2024.100171","DOIUrl":"10.1016/j.bpr.2024.100171","url":null,"abstract":"A common type of cytoskeletal morphology involves multiple microtubules converging with their minus ends at the microtubule organizing center (MTOC). The cargo-motor complex will experience ballistic transport when bound to microtubules or diffusive transport when unbound. This machinery allows for sequestering and subsequent dispersal of dynein-transported cargo. The general principles governing dynamics, efficiency, and tunability of such transport in the MTOC vicinity are not fully understood. To address this, we develop a one-dimensional model that includes advective transport toward an attractor (such as the MTOC) and diffusive transport that allows particles to reach absorbing boundaries (such as cellular membranes). We calculated the mean first passage time (MFPT) for cargo to reach the boundaries as a measure of the effectiveness of sequestering (large MFPT) and diffusive dispersal (low MFPT). We show that the MFPT experiences a dramatic growth, transitioning from a low to high MFPT regime (dispersal to sequestering) over a window of cargo on-/off-rates that is close to in vivo values. Furthermore, increasing either the on-rate (attachment) or off-rate (detachment) can result in optimal dispersal when the attractor is placed asymmetrically. Finally, we also describe a regime of rare events where the MFPT scales exponentially with motor velocity and the escape location becomes exponentially sensitive to the attractor positioning. Our results suggest that structures such as the MTOC allow for the sensitive control of the spatial and temporal features of transport and corresponding function under physiological conditions.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":" ","pages":"100171"},"PeriodicalIF":2.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11345624/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602294","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 method for assessing the specificity of developing CAR therapies. 评估开发 CAR 疗法特异性的方法。

IF 2.4

Biophysical reports Pub Date : 2024-09-11 Epub Date: 2024-07-16 DOI: 10.1016/j.bpr.2024.100172

Ivan V Prikhodko, Georgy Th Guria

{"title":"The method for assessing the specificity of developing CAR therapies.","authors":"Ivan V Prikhodko, Georgy Th Guria","doi":"10.1016/j.bpr.2024.100172","DOIUrl":"10.1016/j.bpr.2024.100172","url":null,"abstract":"The effectiveness of antitumor chimeric antigen receptor (CAR) therapy mainly dealt with an elevated sensitivity of CAR cells to target cells. However, CAR therapies are associated with nonspecific side effects: on-target off-tumor toxicity. Sensitivity and specificity of CAR cells are the most important properties of the recognition process of target cells among other cells. Current developments are mainly concentrated on exploring molecular biology methods for designing CAR cells with the highest sensitivity, while the problem of the CAR cell specificity is rarely considered. For the assessment of CAR cell specificity, we suggest that, in addition to an elevated level of CAR-antigen affinity, the ability of CARs for clustering should be taken into account. We assume that the CAR cell cytotoxicity is determined by CAR clustering. The latter is treated within the framework of nucleation theory. The master equation for the probability of CAR cell cytotoxicity is derived. The size of a critical CAR cluster is found to be one of two most essential parameters. The conditions for necessary sensitivity and sufficient specificity are explored. Relevant parametric diagrams are derived. Possible applications of the method for assessing the specificity of developing CAR therapies are discussed.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":" ","pages":"100172"},"PeriodicalIF":2.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11344002/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141725187","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

Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network. 使用基因调控神经网络的湿拟态计算非线性分类器

IF 2.4

Biophysical reports Pub Date : 2024-09-11 Epub Date: 2024-06-05 DOI: 10.1016/j.bpr.2024.100158

Adrian Ratwatte, Samitha Somathilaka, Sasitharan Balasubramaniam, Assaf A Gilad

{"title":"Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network.","authors":"Adrian Ratwatte, Samitha Somathilaka, Sasitharan Balasubramaniam, Assaf A Gilad","doi":"10.1016/j.bpr.2024.100158","DOIUrl":"10.1016/j.bpr.2024.100158","url":null,"abstract":"The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational principles resemble an artificial neural network (ANN), which can pave the way for the development of wet-neuromorphic computing systems. Genes are integrated into gene-perceptrons with transcription factors (TFs) as input, where the TF concentration relative to half-maximal RNA concentration and gene product copy number influences transcription and translation via weighted multiplication before undergoing a nonlinear activation function. This process yields protein concentration as the output, effectively turning the entire GRN into a gene regulatory neural network (GRNN). In this paper, we establish nonlinear classifiers for molecular machine learning using the inherent sigmoidal nonlinear behavior of gene expression. The eigenvalue-based stability analysis, tailored to system parameters, confirms maximum-stable concentration levels, minimizing concentration fluctuations and computational errors. Given the significance of the stabilization phase in GRNN computing and the dynamic nature of the GRN, alongside potential changes in system parameters, we utilize the Lyapunov stability theorem for temporal stability analysis. Based on this GRN-to-GRNN mapping and stability analysis, three classifiers are developed utilizing two generic multilayer sub-GRNNs and a sub-GRNN extracted from the Escherichia coli GRN. Our findings also reveal the adaptability of different sub-GRNNs to suit different application requirements.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":" ","pages":"100158"},"PeriodicalIF":2.4,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11231448/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141289011","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

TSAT: Efficient evaluation software for NGS data of phage/mirror-image phage display selections. TSAT - 用于噬菌体/镜像噬菌体展示选择的 NGS 数据的高效评估软件。

IF 2.4

Biophysical reports Pub Date : 2024-09-11 Epub Date: 2024-06-21 DOI: 10.1016/j.bpr.2024.100166

Tim Altendorf, Jeannine Mohrlüder, Dieter Willbold

引用次数: 0

In silico thermal control of spiral wave dynamics in excitable cardiac tissue. 可兴奋心脏组织螺旋波动力学的硅学热控制。

IF 2.4

Biophysical reports Pub Date : 2024-09-11 Epub Date: 2024-07-02 DOI: 10.1016/j.bpr.2024.100170

Rupamanjari Majumder

引用次数: 0

Biophysical characterization of high-confidence, small human proteins. 高可信度小型人类蛋白质的生物物理特征。

IF 2.7

Biophysical reports Pub Date : 2024-09-11 Epub Date: 2024-06-22 DOI: 10.1016/j.bpr.2024.100167

A M Whited, Irwin Jungreis, Jeffre Allen, Christina L Cleveland, Jonathan M Mudge, Manolis Kellis, John L Rinn, Loren E Hough

{"title":"Biophysical characterization of high-confidence, small human proteins.","authors":"A M Whited, Irwin Jungreis, Jeffre Allen, Christina L Cleveland, Jonathan M Mudge, Manolis Kellis, John L Rinn, Loren E Hough","doi":"10.1016/j.bpr.2024.100167","DOIUrl":"10.1016/j.bpr.2024.100167","url":null,"abstract":"Significant efforts have been made to characterize the biophysical properties of proteins. Small proteins have received less attention because their annotation has historically been less reliable. However, recent improvements in sequencing, proteomics, and bioinformatics techniques have led to the high-confidence annotation of small open reading frames (smORFs) that encode for functional proteins, producing smORF-encoded proteins (SEPs). SEPs have been found to perform critical functions in several species, including humans. While significant efforts have been made to annotate SEPs, less attention has been given to the biophysical properties of these proteins. We characterized the distributions of predicted and curated biophysical properties, including sequence composition, structure, localization, function, and disease association of a conservative list of previously identified human SEPs. We found significant differences between SEPs and both larger proteins and control sets. In addition, we provide an example of how our characterization of biophysical properties can contribute to distinguishing protein-coding smORFs from noncoding ones in otherwise ambiguous cases.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":" ","pages":"100167"},"PeriodicalIF":2.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11305224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141443861","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

Estimation of the mass density of biological matter from refractive index measurements. 通过折射率测量估算生物物质的质量密度。

IF 2.6

Biophysical reports Pub Date : 2024-06-12 Epub Date: 2024-04-24 DOI: 10.1016/j.bpr.2024.100156

Conrad Möckel, Timon Beck, Sara Kaliman, Shada Abuhattum, Kyoohyun Kim, Julia Kolb, Daniel Wehner, Vasily Zaburdaev, Jochen Guck

{"title":"Estimation of the mass density of biological matter from refractive index measurements.","authors":"Conrad Möckel, Timon Beck, Sara Kaliman, Shada Abuhattum, Kyoohyun Kim, Julia Kolb, Daniel Wehner, Vasily Zaburdaev, Jochen Guck","doi":"10.1016/j.bpr.2024.100156","DOIUrl":"10.1016/j.bpr.2024.100156","url":null,"abstract":"The quantification of physical properties of biological matter gives rise to novel ways of understanding functional mechanisms. One of the basic biophysical properties is the mass density (MD). It affects the dynamics in sub-cellular compartments and plays a major role in defining the opto-acoustical properties of cells and tissues. As such, the MD can be connected to the refractive index (RI) via the well known Lorentz-Lorenz relation, which takes into account the polarizability of matter. However, computing the MD based on RI measurements poses a challenge, as it requires detailed knowledge of the biochemical composition of the sample. Here we propose a methodology on how to account for assumptions about the biochemical composition of the sample and respective RI measurements. To this aim, we employ the Biot mixing rule of RIs alongside the assumption of volume additivity to find an approximate relation of MD and RI. We use Monte-Carlo simulations and Gaussian propagation of uncertainty to obtain approximate analytical solutions for the respective uncertainties of MD and RI. We validate this approach by applying it to a set of well-characterized complex mixtures given by bovine milk and intralipid emulsion and employ it to estimate the MD of living zebrafish (Danio rerio) larvae trunk tissue. Our results illustrate the importance of implementing this methodology not only for MD estimations but for many other related biophysical problems, such as mechanical measurements using Brillouin microscopy and transient optical coherence elastography.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":"4 2","pages":"100156"},"PeriodicalIF":2.6,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11090064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140892265","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

Philament: A filament tracking program to quickly and accurately analyze in vitro motility assays. Philament：丝状物跟踪程序，用于快速准确地分析体外运动试验。

IF 2.7

Biophysical reports Pub Date : 2024-01-30 eCollection Date: 2024-03-13 DOI: 10.1016/j.bpr.2024.100147

Ryan M Bowser, Gerrie P Farman, Carol C Gregorio

{"title":"Philament: A filament tracking program to quickly and accurately analyze in vitro motility assays.","authors":"Ryan M Bowser, Gerrie P Farman, Carol C Gregorio","doi":"10.1016/j.bpr.2024.100147","DOIUrl":"10.1016/j.bpr.2024.100147","url":null,"abstract":"In vitro motility (IVM) assays allow for the examination of the basic interaction between cytoskeletal filaments with molecular motors and the influence many physiological factors have on this interaction. Examples of factors that can be studied include changes in ADP and pH that emulate fatigue, altered phosphorylation that can occur with disease, and mutations within myofilament proteins that cause disease. While IVM assays can be analyzed manually, the main limitation is the ability to extract accurate data rapidly from videos collected without individual bias. While programs have been created in the past to enable data extraction, many are now out of date or require the use of proprietary software. Here, we report the generation of a Python-based tracking program, Philament, which automatically extracts data on instantaneous and average velocities, and allows for fully automated analysis of IVM recordings. The data generated are presented in an easily accessible spreadsheet-based, comma-separated values file. Philament also contains a novel method of quantifying the smoothness of filament motion. By fitting curves to standard deviations of velocity and average velocities, the influence of different experimental conditions can be compared relative to one another. This comparison provides a qualitative measure of protein interactions where steeper slopes indicate more unstable interactions and shallower slopes indicate more stable interactions within the myofilament. Overall, Philament's automation of IVM analysis provides easier entry into the field of cardiovascular mechanics and enables users to create a truly high-throughput experimental data analysis.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":"4 1","pages":"100147"},"PeriodicalIF":2.7,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10884813/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139974783","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

Machine learning topological defects in confluent tissues. 机器学习汇合组织中的拓扑缺陷

IF 2.6

Biophysical reports Pub Date : 2024-01-09 eCollection Date: 2024-03-13 DOI: 10.1016/j.bpr.2024.100142

Andrew Killeen, Thibault Bertrand, Chiu Fan Lee

{"title":"Machine learning topological defects in confluent tissues.","authors":"Andrew Killeen, Thibault Bertrand, Chiu Fan Lee","doi":"10.1016/j.bpr.2024.100142","DOIUrl":"10.1016/j.bpr.2024.100142","url":null,"abstract":"Active nematics is an emerging paradigm for characterizing biological systems. One aspect of particularly intense focus is the role active nematic defects play in these systems, as they have been found to mediate a growing number of biological processes. Accurately detecting and classifying these defects in biological systems is, therefore, of vital importance to improving our understanding of such processes. While robust methods for defect detection exist for systems of elongated constituents, other systems, such as epithelial layers, are not well suited to such methods. Here, we address this problem by developing a convolutional neural network to detect and classify nematic defects in confluent cell layers. Crucially, our method is readily implementable on experimental images of cell layers and is specifically designed to be suitable for cells that are not rod shaped, which we demonstrate by detecting defects on experimental data using the trained model. We show that our machine learning model outperforms current defect detection techniques and that this manifests itself in our method as requiring less data to accurately capture defect properties. This could drastically improve the accuracy of experimental data interpretation while also reducing costs, advancing the study of nematic defects in biological systems.","PeriodicalId":72402,"journal":{"name":"Biophysical reports","volume":"4 1","pages":"100142"},"PeriodicalIF":2.6,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10837480/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139681976","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