Frontiers in imaging (Lausanne, Switzerland)最新文献

筛选
英文 中文
Novel imaging approach for simultaneous tracking of cell dynamics in distinct tissue layers reveals cells involved in colonic peristalsis. 在不同组织层中同时跟踪细胞动力学的新成像方法揭示了参与结肠蠕动的细胞。
Frontiers in imaging (Lausanne, Switzerland) Pub Date : 2025-01-01 Epub Date: 2025-04-02 DOI: 10.3389/fimag.2025.1538533
Salah A Baker, Peter J Blair, Sharif Amit Kamran, Kenton M Sanders
{"title":"Novel imaging approach for simultaneous tracking of cell dynamics in distinct tissue layers reveals cells involved in colonic peristalsis.","authors":"Salah A Baker, Peter J Blair, Sharif Amit Kamran, Kenton M Sanders","doi":"10.3389/fimag.2025.1538533","DOIUrl":"10.3389/fimag.2025.1538533","url":null,"abstract":"<p><p>We have developed a novel approach for high-resolution confocal imaging across multiple tissue planes simultaneously. By combining confocal microscopy, piezo actuators, and optogenetic sensors, we can simultaneously capture images of dynamic fluorescence signals from various cell populations in different tissue layers (Z planes). This enables the decoding of cell-to-cell communication through complex tissues, offering a significant advancement in understanding how cells in distinct layers of tissue communicate and coordinate their functions and produce integrated behaviors. For example, our technique sheds light on myogenic coordination underlying colonic motility. Examining various cell types, such as interstitial cells of Cajal (ICC) and smooth muscle cells (SMC), distributed through the thickness of muscle layers, we demonstrate distinct Ca<sup>2+</sup> signaling patterns and organization that underlie complex colonic motor activities.</p>","PeriodicalId":521217,"journal":{"name":"Frontiers in imaging (Lausanne, Switzerland)","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12834056/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146069810","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
Growth Independent Morphometric Machine Learning Workflow for Single-Cell Antimicrobial Susceptibility Testing of Klebsiella pneumoniae to Meropenem. 肺炎克雷伯菌对美罗培南单细胞药敏试验的生长独立形态计量学机器学习工作流程。
Frontiers in imaging (Lausanne, Switzerland) Pub Date : 2024-01-01 Epub Date: 2024-09-25 DOI: 10.3389/fimag.2024.1418669
Kristel C Tjandra, Nikhil Ram-Mohan, Manuel Roshardt, Elizabeth Zudock, Zhaonan Qu, Kathleen E Mach, Okyaz Eminaga, Joseph C Liao, Samuel Yang, Pak Kin Wong
{"title":"Growth Independent Morphometric Machine Learning Workflow for Single-Cell Antimicrobial Susceptibility Testing of <i>Klebsiella pneumoniae</i> to Meropenem.","authors":"Kristel C Tjandra, Nikhil Ram-Mohan, Manuel Roshardt, Elizabeth Zudock, Zhaonan Qu, Kathleen E Mach, Okyaz Eminaga, Joseph C Liao, Samuel Yang, Pak Kin Wong","doi":"10.3389/fimag.2024.1418669","DOIUrl":"10.3389/fimag.2024.1418669","url":null,"abstract":"<p><p>Multidrug-resistant <i>Enterobacteriaceae</i> are among the most urgent global public health threats associated with various life-threatening infections. In the absence of a rapid method to identify antimicrobial susceptibility, empirical use of broad-spectrum antimicrobials such as carbapenem monotherapy has led to the spread of resistant organisms. Rapid determination of antimicrobial resistance is urgently needed to overcome this issue. By capturing dynamic single-cell morphological features, including growth-independent, antibiotic-induced changes, of cells from nineteen strains of <i>Klebsiella pneumoniae</i>, we evaluated strategies based on time and concentration differentials for classifying its susceptibility to a commonly used carbapenem, meropenem, and predicting their minimum inhibitory concentrations (MIC). We report morphometric antimicrobial susceptibility testing (MorphoAST), a growth independent, computer vision-based machine learning workflow, for rapid determination of antimicrobial susceptibility by single-cell morphological analysis within sub-doubling time of <i>K. pneumoniae</i>. We demonstrated the technological feasibility of predicting MIC/antimicrobial susceptibility in a fraction of the bacterial doubling time (<50 min.). The classifiers achieved as high as 97% accuracy in 20 minutes (two-fifths of the doubling time) and reached over 99% accuracy within 50 minutes (one doubling time) in predicting the antimicrobial response of the validation dataset. A regression model based on the concentration differential of individual cells from nineteen strains predicted the MIC with 100% categorical agreement and essential agreement for seven unseen strains, including two clinical samples from patients with urinary tract infections with different responsiveness to meropenem, within 50 minutes of treatment. The expansion of this innovation to other drug-bug combinations could have significant implications for the future development of rapid antimicrobial susceptibility testing.</p>","PeriodicalId":521217,"journal":{"name":"Frontiers in imaging (Lausanne, Switzerland)","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13618438/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149077519","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
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书