Methods最新文献

{"title":"Cardiac titin isoforms: Practice in interpreting results of electrophoretic analysis.","authors":"Elmira I Yakupova, Polina A Abramicheva, Vadim V Rogachevsky, Elena A Shishkova, Alexey D Bocharnikov, Egor Y Plotnikov, Ivan M Vikhlyantsev","doi":"10.1016/j.ymeth.2025.02.007","DOIUrl":"https://doi.org/10.1016/j.ymeth.2025.02.007","url":null,"abstract":"<p><p>The sarcomeric giant protein titin affects the passive elasticity of the heart muscle and is crucial for proper cardiac function, including diastolic relaxation of the left ventricle. A useful common method for studying titin is electrophoretic analysis which can be used to examine the distribution of its isoforms in the heart. There are 5 titin parameters that can be analyzed: the N2BA/N2B isoforms ratio, the T2/T1 bands ratio, Cronos isoform content, NT isoform content, the total titin-to-myosin heavy chain (TT/MHC) ratio. These parameters can only be assessed through electrophoresis of giant proteins. It is known that these parameters are related to various biomolecular processes in muscle cells, such as providing of elastic properties, turnover, contraction, and maintaining a highly ordered sarcomere structure. In this review, we discuss the diagnostic potential of electrophoretic visualization of cardiac titin changes in various human heart diseases and animal models of physiological adaptations or pathologies.</p>","PeriodicalId":390,"journal":{"name":"Methods","volume":" ","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143490308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A free method for patient-specific 3D-VR anatomical modeling for presurgical planning using DICOM images and open-source software","authors":"Zachary Ells ,&nbsp;Vinicius Ludwig ,&nbsp;Adam B. Weiner ,&nbsp;Koichiro Kimura ,&nbsp;Andrea Farolfi ,&nbsp;Karim Chamie ,&nbsp;Joseph Shirk ,&nbsp;Nicholas M. Donin ,&nbsp;Robert Reiter ,&nbsp;Johannes Czernin ,&nbsp;Jeremie Calais ,&nbsp;Magnus Dahlbom","doi":"10.1016/j.ymeth.2025.02.006","DOIUrl":"10.1016/j.ymeth.2025.02.006","url":null,"abstract":"<div><h3>Introduction</h3><div>Surgeons commonly use cross sectional images to plan and prepare for surgical procedures. However, cognitively translating 2D images to surgical settings can be difficult and lead to sub-optimal resections. Lymph node dissection can be challenging due to the inability to locate small metastatic lesions, and their proximity to at-risk organ(s). 3D volume rendered (3D-VR) patient specific images can help to address these challenges. We created patient-specific 3D-VR images using freely available open-source programs.</div></div><div><h3>Methods</h3><div>This study included patients part of the clinical trial NCT04857502. Patients received a PET/CT prior to radioguided surgery. 3D Slicer was used to segment anatomy of interest (organs and tumor lesion(s)). After segmentation, the data was exported as an .OBJ file with an accompanying .MTL file. Manipulation of the .MTL file to restore model properties to the .OBJ file, were completed and both files were uploaded into Autodesk Viewer. Surgeons then received an email link to access the finished 3D-VR model on their smartphone or laptop for peri-operative preparation and/or guidance.</div></div><div><h3>Results</h3><div>The method was used in a series of 14 patients with prostate cancer undergoing pelvic lymph node dissection with PSMA-radioguided robotic surgery using pre-operative PSMA PET/CT images acquired on average 103 ± 69 days prior to resection. The creation of the 3D-VR models was successfully conducted in all 14 cases. In all cases, the lesions identified on the pre-operative PET/CT imaging 3D-VR models were successfully removed during surgery.</div></div><div><h3>Conclusion</h3><div>We created patient-specific anatomical 3D-VR models that the surgeons can use for pre-surgical planning and intraoperative tumor localization, by applying free, open-source software that could be used in any procedure requiring careful and strategical planning.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"236 ","pages":"Pages 10-16"},"PeriodicalIF":4.2,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143473927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI and Machine learning in Bioinformatics and Biomedicine.","authors":"Haiying Wang, Xiaohua Tony Hu","doi":"10.1016/j.ymeth.2025.02.005","DOIUrl":"https://doi.org/10.1016/j.ymeth.2025.02.005","url":null,"abstract":"","PeriodicalId":390,"journal":{"name":"Methods","volume":" ","pages":""},"PeriodicalIF":4.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143476048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Production of AFM wedged cantilevers for stress-relaxation experiments: Uniaxial loading of soft, spherical cells","authors":"Riccardo Campanile ,&nbsp;Jonne Helenius ,&nbsp;Cristina Scielzo ,&nbsp;Lydia Scarfò ,&nbsp;Domenico Salerno ,&nbsp;Mario Bossi ,&nbsp;Marta Falappi ,&nbsp;Alessia Saponara ,&nbsp;Daniel J. Müller ,&nbsp;Francesco Mantegazza ,&nbsp;Valeria Cassina","doi":"10.1016/j.ymeth.2025.02.004","DOIUrl":"10.1016/j.ymeth.2025.02.004","url":null,"abstract":"<div><div>The fabrication of wedge-shaped cantilevers for Atomic Force Microscopy (AFM) remains a critical yet challenging task, particularly when precision and efficiency are required. In this study, we present a streamlined protocol for producing these wedges using NOA63 UV-curing polymer, which simplifies the process and eliminates the need for dedicated equipment. Our method reduces preparation time while maintaining the mechanical properties of the cantilevers, in line with the manufacturer's specifications. We demonstrate the effectiveness of our wedged cantilevers in stress-relaxation experiments performed by means of AFM and confocal microscopy on primary Chronic Lymphocytic Leukemia cells and the MEC1 cell line. These experiments highlight the effectiveness of using modified cantilevers to consistently apply precise uniaxial loading to soft, spherical cells. This technique offers a marked improvement in fabrication speed and operational ease compared to traditional methods, without compromising the accuracy or performance of the measurements. This protocol is not only time-saving, but also adaptable for use in a wide range of biological applications, making it a valuable tool for AFM-based research in cellular mechanics.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"236 ","pages":"Pages 1-9"},"PeriodicalIF":4.2,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Latest trends & strategies in ocular drug delivery","authors":"Nishant S. Kulkarni ,&nbsp;Alexander Josowitz ,&nbsp;Roshan James ,&nbsp;Yang Liu ,&nbsp;Bindhu Rayaprolu ,&nbsp;Botir Sagdullaev ,&nbsp;Amardeep S. Bhalla ,&nbsp;Mohammed Shameem","doi":"10.1016/j.ymeth.2025.02.003","DOIUrl":"10.1016/j.ymeth.2025.02.003","url":null,"abstract":"<div><div>Ocular drug delivery is one of the most challenging routes of administration, and this may be attributed to the complex interplay of ocular barriers and clearance mechanisms that restrict therapeutic payload residence. Most of the currently approved products that ameliorate ocular disease conditions are topical, i.e., delivering therapeutics to the outside anterior segment of the eye. This site of administration works well for certain conditions such as local infections but due to the presence of numerous ocular barriers, the permeation of therapeutics to the posterior segment of the eye is limited. Conditions such as age-related macular degeneration and diabetic retinopathy that contribute to an extreme deterioration of vision acuity require therapeutic interventions at the posterior segment of the eye. This necessitates development of intraocular delivery systems such as intravitreal injections, implants, and specialized devices that deliver therapeutics to the posterior segment of the eye. Frequent dosing regimens and high concentration formulations have been strategized and developed to achieve desired therapeutic outcomes by overcoming some of the challenges of drug clearance and efficacy. Correspondingly, development of suitable delivery platforms such as biodegradable and non-biodegradable implants, nano delivery systems, and implantable devices have been explored. This article provides an overview of the current trends in the development of suitable formulations &amp; delivery systems for ocular drug delivery with an emphasis on late-stage clinical and approved product. Moreover, this work aims to summarize current challenges and highlights exciting pre-clinical developments, and future opportunities in cell and gene therapies that may be explored for effective ocular therapeutic outcomes.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"235 ","pages":"Pages 100-117"},"PeriodicalIF":4.2,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A high sensitivity assay of UBE3A ubiquitin ligase activity","authors":"Linna Han,&nbsp;Z. Begum Yagci,&nbsp;Albert J. Keung","doi":"10.1016/j.ymeth.2025.02.002","DOIUrl":"10.1016/j.ymeth.2025.02.002","url":null,"abstract":"<div><div>UBE3A is an E3 ubiquitin ligase associated with several neurodevelopmental disorders. The development of several preclinical therapeutic approaches involving UBE3A, such as gene therapy, enzyme replacement therapy, and epigenetic reactivation, require the detection of its ubiquitin ligase activity. Prior commercial assays leveraged Western Blotting to detect shifts in substrate size due to ubiquitination, but these suffered from long assay times and have also been discontinued. Here we develop a new assay that quantifies UBE3A activity. It measures the fluorescence intensity of ubiquitinated p53 substrates with a microplate reader, eliminating the need for Western Blot antibodies and instruments, and enables detection in just 1 h. The assay is fast, cost-effective, low noise, and uses components with long shelf lives. Importantly, it is also highly sensitive, detecting UBE3A levels as low as 1 nM, similar to that observed in human and mouse cerebrospinal fluid. It also differentiates the activity of wild-type UBE3A and catalytic mutants. We also design a p53 substrate with a triple-epitope tag HIS-HA-CMYC on the N terminus, which allows for versatile detection of UBE3A activity from diverse natural and engineered sources. This new assay provides a timely solution for growing needs in preclinical validation, quality control, endpoint measurements for clinical trials, and downstream manufacturing testing and validation.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"235 ","pages":"Pages 92-99"},"PeriodicalIF":4.2,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HybProm: An attention-assisted hybrid CNN-BiLSTM model for the interpretable prediction of DNA promoter","authors":"Rentao Luo,&nbsp;Jiawei Liu,&nbsp;Lixin Guan,&nbsp;Mengshan Li","doi":"10.1016/j.ymeth.2025.02.001","DOIUrl":"10.1016/j.ymeth.2025.02.001","url":null,"abstract":"<div><div>Promoter prediction is essential for analyzing gene structures, understanding regulatory networks, transcription mechanisms, and precisely controlling gene expression. Recently, computational and deep learning methods for promoter prediction have gained attention. However, there is still room to improve their accuracy. To address this, we propose the HybProm model, which uses DNA2Vec to transform DNA sequences into low-dimensional vectors, followed by a CNN-BiLSTM-Attention architecture to extract features and predict promoters across species, including E. coli, humans, mice, and plants. Experiments show that HybProm consistently achieves high accuracy (90%-99%) and offers good interpretability by identifying key sequence patterns and positions that drive predictions.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"235 ","pages":"Pages 71-80"},"PeriodicalIF":4.2,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A transferability-guided protein-ligand interaction prediction method","authors":"Weihong Zhang ,&nbsp;Fan Hu ,&nbsp;Peng Yin ,&nbsp;Yunpeng Cai","doi":"10.1016/j.ymeth.2025.01.019","DOIUrl":"10.1016/j.ymeth.2025.01.019","url":null,"abstract":"<div><div>Accurate prediction of protein–ligand interaction (PLI) is crucial for drug discovery and development. However, existing methods often struggle with effectively integrating heterogeneous protein and ligand data modalities and optimizing knowledge transfer from pretraining to the target task. This paper proposes a novel transferability-guided PLI prediction method that maximizes knowledge transfer by deeply integrating protein and ligand representations through a cross-attention mechanism and incorporating transferability metrics to guide fine-tuning. The cross-attention mechanism facilitates interactive information exchange between modalities, enabling the model to capture intricate interdependencies. Meanwhile, the transferability-guided strategy quantifies transferability from pretraining tasks and incorporates it into the training objective, ensuring the effective utilization of beneficial knowledge while mitigating negative transfer. Extensive experiments demonstrate significant and consistent improvements over traditional fine-tuning, validated by statistical tests. Ablation studies highlight the pivotal role of cross-attention, and quantitative analysis reveals the method’s ability to reduce harmful transfer. Our guided strategy provides a paradigm for more comprehensive utilization of pretraining knowledge, offering prospects for enhancing other PLI prediction approaches. This method advances PLI prediction via innovative modality fusion and guided knowledge transfer, paving the way for accelerated drug discovery pipelines. Code and data are freely available at <span><span>https://github.com/brian-zZZ/Guided-PLI</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"235 ","pages":"Pages 64-70"},"PeriodicalIF":4.2,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ZFP-CanPred: Predicting the effect of mutations in zinc-finger proteins in cancers using protein language models","authors":"Amit Phogat ,&nbsp;Sowmya Ramaswamy Krishnan ,&nbsp;Medha Pandey ,&nbsp;M. Michael Gromiha","doi":"10.1016/j.ymeth.2025.01.020","DOIUrl":"10.1016/j.ymeth.2025.01.020","url":null,"abstract":"<div><div>Zinc-finger proteins (ZNFs) constitute the largest family of transcription factors and play crucial roles in various cellular processes. Missense mutations in ZNFs significantly alter protein-DNA interactions, potentially leading to the development of various types of cancers. This study presents ZFP-CanPred, a novel deep learning-based model for predicting cancer-associated driver mutations in ZNFs. The representations derived from protein language models (PLMs) from the structural neighbourhood of mutated sites were utilized to train ZFP-CanPred for differentiating between cancer-causing and neutral mutations. ZFP-CanPred, achieved a superior performance with an accuracy of 0.72, F1-score of 0.79, and area under the Receiver Operating Characteristics (ROC) Curve (AUC) of 0.74, on an independent test set. In a comparative analysis against 11 existing prediction tools using a curated dataset of 331 mutations, ZFP-CanPred demonstrated the highest AU-ROC of 0.74, outperforming both generic and cancer-specific methods. The model’s balanced performance across specificity and sensitivity addresses a significant limitation of current methodologies. The source code and other related files are available on GitHub at <span><span>https://github.com/amitphogat/ZFP-CanPred.git</span><svg><path></path></svg></span>. We envisage that the present study contributes to understand the oncogenic processes and developing targeted therapeutic strategies.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"235 ","pages":"Pages 55-63"},"PeriodicalIF":4.2,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143254023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring drug-target interaction prediction on cold-start scenarios via meta-learning-based graph transformer","authors":"Chengxin He ,&nbsp;Zhenjiang Zhao ,&nbsp;Xinye Wang ,&nbsp;Huiru Zheng ,&nbsp;Lei Duan ,&nbsp;Jie Zuo","doi":"10.1016/j.ymeth.2024.11.010","DOIUrl":"10.1016/j.ymeth.2024.11.010","url":null,"abstract":"<div><div>Predicting drug-target interaction (DTI) is of great importance for drug discovery and development. With the rapid development of biological and chemical technologies, computational methods for DTI prediction are becoming a promising approach. However, there are few solutions to the cold-start problem in DTI prediction scenarios, as these methods rely on existing interaction information to support their modeling. Consequently, they are unable to effectively predict DTIs for new drugs or targets with limited interaction data in the existing work. To this end, we propose a graph transformer method based on meta-learning named MGDTI (short for <u>M</u>eta-learning-based <u>G</u>raph Transformer for <u>D</u>rug-<u>T</u>arget <u>I</u>nteraction prediction) to fill this gap. Technically, we employ drug-drug similarity and target-target similarity as additional information to mitigate the scarcity of interactions. Besides, we trained MGDTI via meta-learning to be adaptive to cold-start tasks. Moreover, we employed graph transformer to prevent over-smoothing by capturing long-range dependencies. Extensive results on the benchmark dataset demonstrate that MGDTI is effective on DTI prediction under cold-start scenarios.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 10-20"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}