Biophysics reports最新文献_第5页

Studying large biomolecules as sedimented solutes with solid-state NMR. 利用固态核磁共振研究作为沉积溶质的大型生物分子。

Biophysics reports Pub Date : 2024-08-31 DOI: 10.52601/bpr.2024.240014

Fan Shi, Tong Zhang, Juan Li, Chaowei Shi, Shengqi Xiang

{"title":"Studying large biomolecules as sedimented solutes with solid-state NMR.","authors":"Fan Shi, Tong Zhang, Juan Li, Chaowei Shi, Shengqi Xiang","doi":"10.52601/bpr.2024.240014","DOIUrl":"https://doi.org/10.52601/bpr.2024.240014","url":null,"abstract":"Sedimentation solid-state NMR is a novel method for sample preparation in solid-state NMR (ssNMR) studies. It involves the sedimentation of soluble macromolecules such as large protein complexes. By utilizing ultra-high centrifugal forces, the molecules in solution are driven into a high-concentrated hydrogel, resulting in a sample suitable for solid-state NMR. This technique has the advantage of avoiding the need for chemical treatment, thus minimizing the loss of sample biological activity. Sediment ssNMR has been successfully applied to a variety of non-crystalline protein solids, significantly expanding the scope of solid-state NMR research. In theory, using this method, any biological macromolecule in solution can be transferred into a sedimented solute appropriate for solid-state NMR analysis. However, specialized equipment and careful handling are essential for effectively collecting and loading the sedimented solids to solid-state NMR rotors. To improve efficiency, we have designed a series of loading tools to achieve the loading process from the solution to the rotor in one step. In this paper, we illustrate the sample preparation process of sediment NMR using the H1.4-NCP167 complex, which consists of linker histone H1.4 and nucleosome core particle, as an example.","PeriodicalId":93906,"journal":{"name":"Biophysics reports","volume":"10 4","pages":"201-212"},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11399891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303329","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 brain network hub degeneration in Alzheimer's disease. 阿尔茨海默病的大脑网络中枢退化。

Biophysics reports Pub Date : 2024-08-31 DOI: 10.52601/bpr.2024.230025

Suhui Jin, Jinhui Wang, Yong He

{"title":"The brain network hub degeneration in Alzheimer's disease.","authors":"Suhui Jin, Jinhui Wang, Yong He","doi":"10.52601/bpr.2024.230025","DOIUrl":"https://doi.org/10.52601/bpr.2024.230025","url":null,"abstract":"Alzheimer's disease (AD) has been conceptualized as a syndrome of brain network dysfunction. Recent imaging connectomics studies have provided unprecedented opportunities to map structural and functional brain networks in AD. By reviewing molecular, imaging, and computational modeling studies, we have shown that highly connected brain hubs are primarily distributed in the medial and lateral prefrontal, parietal, and temporal regions in healthy individuals and that the hubs are selectively and severely affected in AD as manifested by increased amyloid-beta deposition and regional atrophy, hypo-metabolism, and connectivity dysfunction. Furthermore, AD-related hub degeneration depends on the imaging modality with the most notable degeneration in the medial temporal hubs for morphological covariance networks, the prefrontal hubs for structural white matter networks, and in the medial parietal hubs for functional networks. Finally, the AD-related hub degeneration shows metabolic, molecular, and genetic correlates. Collectively, we conclude that the brain-network-hub-degeneration framework is promising to elucidate the biological mechanisms of network dysfunction in AD, which provides valuable information on potential diagnostic biomarkers and promising therapeutic targets for the disease.","PeriodicalId":93906,"journal":{"name":"Biophysics reports","volume":"10 4","pages":"213-229"},"PeriodicalIF":0.0,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11399886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142303330","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

Unlocking the secrets of TGR5: a new dawn in treating diabetic cardiomyopathy. 揭开 TGR5 的秘密：治疗糖尿病心肌病的新曙光。

Biophysics reports Pub Date : 2024-08-31 DOI: 10.52601/bpr.2024.240907

Jin Li, He Huang

引用次数: 0

Streamlined process for effective and strand-selective mitochondrial base editing using mitoBEs. 使用 mitoBEs 进行有效和链选择性线粒体碱基编辑的简化流程。

Biophysics reports Pub Date : 2024-08-31 DOI: 10.52601/bpr.2024.240010

Xiaoxue Zhang, Zongyi Yi, Wei Tang, Wensheng Wei

引用次数: 0

Decoder-seq: a technology for high sensitivity, high resolution, and low-cost spatial RNA sequencing. 解码器-测序：一种高灵敏度、高分辨率、低成本的空间 RNA 测序技术。

Biophysics reports Pub Date : 2024-06-30 DOI: 10.52601/bpr.2024.240903

Siquan Li, Jin Li, He Huang

引用次数: 0

Developing ChatGPT for biology and medicine: a complete review of biomedical question answering. 为生物学和医学开发 ChatGPT：生物医学问题解答完整回顾。

Biophysics reports Pub Date : 2024-06-30 DOI: 10.52601/bpr.2024.240004

Qing Li, Lei Li, Yu Li

{"title":"Developing ChatGPT for biology and medicine: a complete review of biomedical question answering.","authors":"Qing Li, Lei Li, Yu Li","doi":"10.52601/bpr.2024.240004","DOIUrl":"10.52601/bpr.2024.240004","url":null,"abstract":"ChatGPT explores a strategic blueprint of question answering (QA) to deliver medical diagnoses, treatment recommendations, and other healthcare support. This is achieved through the increasing incorporation of medical domain data via natural language processing (NLP) and multimodal paradigms. By transitioning the distribution of text, images, videos, and other modalities from the general domain to the medical domain, these techniques have accelerated the progress of medical domain question answering (MDQA). They bridge the gap between human natural language and sophisticated medical domain knowledge or expert-provided manual annotations, handling large-scale, diverse, unbalanced, or even unlabeled data analysis scenarios in medical contexts. Central to our focus is the utilization of language models and multimodal paradigms for medical question answering, aiming to guide the research community in selecting appropriate mechanisms for their specific medical research requirements. Specialized tasks such as unimodal-related question answering, reading comprehension, reasoning, diagnosis, relation extraction, probability modeling, and others, as well as multimodal-related tasks like vision question answering, image captioning, cross-modal retrieval, report summarization, and generation, are discussed in detail. Each section delves into the intricate specifics of the respective method under consideration. This paper highlights the structures and advancements of medical domain explorations against general domain methods, emphasizing their applications across different tasks and datasets. It also outlines current challenges and opportunities for future medical domain research, paving the way for continued innovation and application in this rapidly evolving field. This comprehensive review serves not only as an academic resource but also delineates the course for future probes and utilization in the field of medical question answering.","PeriodicalId":93906,"journal":{"name":"Biophysics reports","volume":"10 3","pages":"152-171"},"PeriodicalIF":0.0,"publicationDate":"2024-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11252240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141725294","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

Unfolding rates of 1:1 and 2:1 complex of CX-5461 and c-MYC promoter G-quadruplexes revealed by single-molecule force spectroscopy. 单分子力谱法揭示了 CX-5461 与 c-MYC 启动子 G-四链体的 1:1 和 2:1 复合物的展开率。

Biophysics reports Pub Date : 2024-06-30 DOI: 10.52601/bpr.2024.240018

Hui Peng, Yashuo Zhang, Qun Luo, Xinyu Wang, Huijuan You

{"title":"Unfolding rates of 1:1 and 2:1 complex of CX-5461 and c-MYC promoter G-quadruplexes revealed by single-molecule force spectroscopy.","authors":"Hui Peng, Yashuo Zhang, Qun Luo, Xinyu Wang, Huijuan You","doi":"10.52601/bpr.2024.240018","DOIUrl":"10.52601/bpr.2024.240018","url":null,"abstract":"CX-5461, also known as pidnarulex, is a strong G4 stabilizer and has received FDA fast-track designation for BRCA1- and BRCA2- mutated cancers. However, quantitative measurements of the unfolding rates of CX-5461-G4 complexes which are important for the regulation function of G4s, remain lacking. Here, we employ single-molecule magnetic tweezers to measure the unfolding force distributions of c-MYC G4s in the presence of different concentrations of CX-5461. The unfolding force distributions exhibit three discrete levels of unfolding force peaks, corresponding to three binding modes. In combination with a fluorescent quenching assay and molecular docking to previously reported ligand-c-MYC G4 structure, we assigned the ~69 pN peak corresponding to the 1:1 (ligand:G4) complex where CX-5461 binds at the G4's 5'-end. The ~84 pN peak is attributed to the 2:1 complex where CX-5461 occupies both the 5' and 3'. Furthermore, using the Bell-Arrhenius model to fit the unfolding force distributions, we determined the zero-force unfolding rates of 1:1, and 2:1 complexes to be (2.4 ± 0.9) × 10-8 s-1 and (1.4 ± 1.0) × 10-9 s-1 respectively. These findings provide valuable insights for the development of G4-targeted ligands to combat c-MYC-driven cancers.","PeriodicalId":93906,"journal":{"name":"Biophysics reports","volume":"10 3","pages":"180-189"},"PeriodicalIF":0.0,"publicationDate":"2024-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11252239/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141725298","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

Digital counting of force accumulation during mechanotransduction. 对机械传导过程中的力积累进行数字计数。

Biophysics reports Pub Date : 2024-06-30 DOI: 10.52601/bpr.2024.240905

Xinyu Zhang, Bei Liu

引用次数: 0

Foundation models in molecular biology. 分子生物学基础模型

Biophysics reports Pub Date : 2024-06-30 DOI: 10.52601/bpr.2024.240006

Yunda Si, Jiawei Zou, Yicheng Gao, Guohui Chuai, Qi Liu, Luonan Chen

引用次数: 0

The gut-liver axis calibrates PEDF production for ISC homeostasis. 肠道-肝脏轴为 ISC 的平衡校准 PEDF 的产生。

Biophysics reports Pub Date : 2024-06-30 DOI: 10.52601/bpr.2024.240904

Ying Huang, Xinran Wang, Lulu Sun

引用次数: 0