Methods最新文献

{"title":"Multi-view contrastive clustering for cancer subtyping using fully and weakly paired multi-omics data","authors":"Yabin Kuang ,&nbsp;Minzhu Xie ,&nbsp;Zhanhong Zhao ,&nbsp;Dongze Deng ,&nbsp;Ergude Bao","doi":"10.1016/j.ymeth.2024.09.016","DOIUrl":"10.1016/j.ymeth.2024.09.016","url":null,"abstract":"<div><div>The identification of cancer subtypes is crucial for advancing precision medicine, as it facilitates the development of more effective and personalized treatment and prevention strategies. With the development of high-throughput sequencing technologies, researchers now have access to a wealth of multi-omics data from cancer patients, making computational cancer subtyping increasingly feasible. One of the main challenges in integrating multi-omics data is handling missing data, since not all biomolecules are consistently measured across all samples. Current computational models based on multi-omics data for cancer subtyping often struggle with the challenge of weakly paired omics data. To address this challenge, we propose a novel unsupervised cancer subtyping model named Subtype-MVCC. This model leverages graph convolutional networks to extract and represent low-dimensional features from each omics data type, using intra-view and inter-view contrastive learning approaches. By incorporating a weighted average fusion strategy to unify the dimension of each sample, Subtype-MVCC effectively handles weakly paired multi-omics datasets. Comprehensive evaluations on established benchmark datasets demonstrate that Subtype-MVCC outperforms nine leading models in this domain. Additionally, simulations with varying levels of missing data highlight the model's robust performance in handling weakly paired omics data. The clinical relevance and survival outcomes associated with the identified subtypes further validate the interpretability and reliability of the clustering results produced by Subtype-MVCC.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"232 ","pages":"Pages 1-8"},"PeriodicalIF":4.2,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142455004","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":"DGSIST: Clustering spatial transcriptome data based on deep graph structure Infomax","authors":"Yu-Han Xiu ,&nbsp;Si-Lin Sun ,&nbsp;Bing-Wei Zhou ,&nbsp;Ying Wan ,&nbsp;Hua Tang ,&nbsp;Hai-Xia Long","doi":"10.1016/j.ymeth.2024.10.002","DOIUrl":"10.1016/j.ymeth.2024.10.002","url":null,"abstract":"<div><div>Although spatial transcriptomics data provide valuable insights into gene expression profiles and the spatial structure of tissues, most studies rely solely on gene expression information, underutilizing the spatial data. To fully leverage the potential of spatial transcriptomics and graph neural networks, the DGSI (Deep Graph Structure Infomax) model is proposed. This innovative graph data processing model uses graph convolutional neural networks and employs an unsupervised learning approach. It maximizes the mutual information between graph-level and node-level representations, emphasizing flexible sampling and aggregation of nodes and their neighbors. This effectively captures and incorporates local information from nodes into the overall graph structure. Additionally, this paper developed the DGSIST framework, an unsupervised cell clustering method that integrates the DGSI model, SVD dimensionality reduction algorithm, and k-means++ clustering algorithm. This aims to identify cell types accurately. DGSIST fully uses spatial transcriptomics data and outperforms existing methods in accuracy. Demonstrations of DGSIST’s capability across various tissue types and technological platforms have shown its effectiveness in accurately identifying spatial domains in multiple tissue sections. Compared to other spatial clustering methods, DGSIST excels in cell clustering and effectively eliminates batch effects without needing batch correction. DGSIST excels in spatial clustering analysis, spatial variation identification, and differential gene expression detection and directly applies to graph analysis tasks, such as node classification, link prediction, or graph clustering. Anticipation lies in the contribution of the DGSIST framework to a deeper understanding of the spatial organizational structures of diseases such as cancer.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 226-236"},"PeriodicalIF":4.2,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142455003","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":"Determination of adipogenesis stages of human umbilical cord-derived mesenchymal stem cells using three-dimensional label-free holotomography","authors":"Mahesh Prakash Bhatta ,&nbsp;Gun-Woo Won ,&nbsp;Seung Hoon Lee ,&nbsp;Seung-Hyeon Choi ,&nbsp;Cheong-Hae Oh ,&nbsp;Ji Hyun Moon ,&nbsp;Hong-Hoa Hoang ,&nbsp;Jaehyeok Lee ,&nbsp;Sang Do Lee ,&nbsp;Jong-Il Park","doi":"10.1016/j.ymeth.2024.10.005","DOIUrl":"10.1016/j.ymeth.2024.10.005","url":null,"abstract":"<div><div>Adipogenesis involves complex changes in gene expression, morphology, and cytoskeletal organization. However, the quantitative analysis of live cell images to identify their stages through morphological markers is limited. Distinct adipogenesis markers on human umbilical cord-derived mesenchymal stem cells (UC-MSCs) were identified through holotomography, a label-free live cell imaging technique. In the MSC-to-preadipocyte transition, the nucleus-to-cytoplasm ratio (0.080 vs. 0.052) and lipid droplet (LD) refractive index variation decreased (0.149 % vs. 0.061 %), whereas the LD number (20 vs. 65) increased. This event was also accompanied by the downregulation and upregulation of THY1 and Preadipocyte Factor-1 (PREF-1), respectively. In the preadipocyte to immature adipocyte shift, cell sphericity (0.20 vs. 0.43) and LD number (65 vs. 200) surged, large LDs (&gt;10 μm³) appeared, and the major axis of the cell was reduced (143.7 μm vs. 83.12 μm). These findings indicate features of preadipocyte and immature adipocyte stages, alongside the downregulation of PREF-1 and upregulation of Peroxisome Proliferator-Activated Receptor gamma (PPARγ). In adipocyte maturation, along with PPARγ and Fatty Acid-Binding Protein 4 upregulation, cell compactness (0.15 vs. 0.29) and sphericity (0.43 vs. 0.59) increased, and larger LDs (&gt;30 μm³) formed, marking immature and mature adipocyte stages. The study highlights the distinct adipogenic morphological biomarkers of adipogenesis stages in UC-MSCs, providing potential applications in biomedical and clinical settings, such as fostering innovative medical strategies for treating metabolic disease.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 204-214"},"PeriodicalIF":4.2,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441517","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":"Multi-kernel clustering with tensor fusion on Grassmann manifold for high-dimensional genomic data","authors":"Fei Qi ,&nbsp;Jin Guo ,&nbsp;Junyu Li ,&nbsp;Yi Liao ,&nbsp;Wenxiong Liao ,&nbsp;Hongmin Cai ,&nbsp;Jiazhou Chen","doi":"10.1016/j.ymeth.2024.09.015","DOIUrl":"10.1016/j.ymeth.2024.09.015","url":null,"abstract":"<div><div>The high dimensionality and noise challenges in genomic data make it difficult for traditional clustering methods. Existing multi-kernel clustering methods aim to improve the quality of the affinity matrix by learning a set of base kernels, thereby enhancing clustering performance. However, directly learning from the original base kernels presents challenges in handling errors and redundancies when dealing with high-dimensional data, and there is still a lack of feasible multi-kernel fusion strategies. To address these issues, we propose a Multi-Kernel Clustering method with Tensor fusion on Grassmann manifolds, called MKCTM. Specifically, we maximize the clustering consensus among base kernels by imposing tensor low-rank constraints to eliminate noise and redundancy. Unlike traditional kernel fusion approaches, our method fuses learned base kernels on the Grassmann manifold, resulting in a final consensus matrix for clustering. We integrate tensor learning and fusion processes into a unified optimization model and propose an effective iterative optimization algorithm for solving it. Experimental results on ten datasets, comparing against 12 popular baseline clustering methods, confirm the superiority of our approach. Our code is available at <span><span>https://github.com/foureverfei/MKCTM.git</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 215-225"},"PeriodicalIF":4.2,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446912","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":"Protocol for a pilot study: Feasibility of a web-based platform to improve nutrition, mindfulness, and physical function in people living with Post COVID-19 condition (BLEND)","authors":"Montserrat Montes-Ibarra ,&nbsp;Kristine Godziuk ,&nbsp;Richard B Thompson ,&nbsp;Catherine B. Chan ,&nbsp;Edith Pituskin ,&nbsp;Douglas P. Gross ,&nbsp;Grace Lam ,&nbsp;Mathias Schlögl ,&nbsp;João Felipe Mota ,&nbsp;D. Ian Paterson ,&nbsp;Carla M. Prado","doi":"10.1016/j.ymeth.2024.10.004","DOIUrl":"10.1016/j.ymeth.2024.10.004","url":null,"abstract":"<div><div>Individuals with Post COVID-19 condition (PCC), or long COVID, experience symptoms such as fatigue, muscle weakness, and psychological distress, including anxiety, depression, or sleep disorders that persist after recovery from COVID-19. These ongoing symptoms significantly compromise quality of life and diminish functional capacity and independence. Multimodal digital interventions targeting behavioural factors such as nutrition and mindfulness have shown promise in improving health outcomes of people with chronic health conditions and may be beneficial for those with PCC. <em>The BLEND study (weB-based pLatform to improve nutrition, mindfulnEss, and physical function, in patients with loNg COVID)</em> study is an 8-week pilot randomized controlled trial evaluating the feasibility of a digital wellness platform compared to usual care among individuals with PCC. The web-based wellness platform employed in this study, My Viva Plan (MVP)®, integrates a holistic, multicomponent approach to promote wellness. The intervention group receives access to the digital health platform for 8 weeks with encouragement for frequent interactions to improve dietary intake and mindfulness. The control group receives general content focusing on improvements in dietary intake and mindfulness. Assessments are conducted at baseline and week 8. The primary outcome is the feasibility of platform use. Secondary and exploratory outcomes include a between-group comparison of changes in body composition, nutritional status, quality of life, mindfulness, physical activity, and physical performance after 8 weeks. Findings of this study will inform the development of effective web-based wellness programs tailored for individuals with PCC to promote sustainable behavioural changes and improved health outcomes.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 186-194"},"PeriodicalIF":4.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142398994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study protocol for a single-arm pilot trial investigating the feasibility of a multimodal digital technology for managing metabolic syndrome in patients with chronic obstructive pulmonary disease","authors":"Bruna R. da Silva ,&nbsp;Amanda I. Radil ,&nbsp;Liam Collins ,&nbsp;Nathanial Maeda ,&nbsp;Carla M. Prado ,&nbsp;Martin Ferguson-Pell ,&nbsp;Doug Klein","doi":"10.1016/j.ymeth.2024.10.003","DOIUrl":"10.1016/j.ymeth.2024.10.003","url":null,"abstract":"<div><div>Individuals diagnosed with Chronic Obstructive Pulmonary Disease (COPD) are exposed to an increased risk of metabolic syndrome (MetS), which negatively affects their health outcomes and quality of life. Lifestyle interventions have shown promise in managing MetS. This study outlines the protocol for a web-based multimodal self-care program, Digital Metabolic Rehabilitation, for managing MetS in patients with COPD. The Digital Metabolic Rehabilitation is a single-arm pilot trial that integrates the Canadian Health Advanced by Nutrition and Graded Exercise (CHANGE) Program and a web-based wellness platform. The web-based wellness platform employed in this study is My Viva Plan (MVP)®, which integrates a holistic, multicomponent approach to promote wellness. The intervention will primarily focus on lifestyle changes for patients with COPD. Over 6 months, participants will use the web-based wellness platform and engage in weekly online support group sessions. Fifty patients diagnosed with stage I-II COPD and MetS will participate. Blood tests, anthropometrics, body composition, physical function, muscle strength, physical activity, energy metabolism, quality of life and mental health will be assessed at baseline, 3, and 6 months. The Digital Metabolic Rehabilitation program aims to explore whether a multimodal integrative intervention delivered through a web-based wellness platform can be implemented by patients with COPD with MetS. By combining the expertise of the CHANGE Program with the digital delivery format, the intervention seeks to enhance self-monitoring and foster better self-management practices. The protocol outlines a novel and potentially impactful intervention for managing MetS in patients with COPD.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 195-203"},"PeriodicalIF":4.2,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142398995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and validation of a stability-indicating HPLC method for assay of tonabersat in pharmaceutical formulations","authors":"Santosh Bhujbal,&nbsp;Ilva D. Rupenthal,&nbsp;Priyanka Agarwal","doi":"10.1016/j.ymeth.2024.10.001","DOIUrl":"10.1016/j.ymeth.2024.10.001","url":null,"abstract":"<div><div>A stability-indicating reversed-phase high-performance liquid chromatography (RP-HPLC) method was developed to assay tonabersat and assess its stability in pharmaceutical formulations. Chromatographic separation was achieved using a Kinetex® C18 column (2.6 µm, 150 x 3 mm, 100 Å) at 50 °C, with a 20 µL injection volume. A linear gradient of acetonitrile in water (5 – 33.5 %) was applied for 1 min, followed by a gradual increase to 100 % over 26 min at a flow rate of 0.5 mL/min. Tonabersat and its degradation products were detected at 275 nm and 210 nm, respectively. The optimized method was used to evaluate the stability of tonabersat in lipid-based pharmaceutical formulations at 5 ± 3 °C, 25 ± 2°C/60 ± 5 % RH, and 40 ± 2 °C/75 ± 5 % RH over 3 months. The method was validated as per ICH guidelines and demonstrated linearity in the range of 5 – 200 µg/mL (R² = 0.99994) with good accuracy (98.25 – 101.58 % recovery) and precision (% RSD &lt; 2.5 %). The limits of detection and quantitation were 0.8 µg/mL and 5 µg/mL, respectively. Forced degradation studies showed significant degradation on exposure to alkaline (90.33 ± 0.80 %), acidic (70.60 ± 1.57 %), and oxidative stress (33.95 ± 0.69 %) at 70 °C, but no degradation was observed on exposure to thermal or photolytic stress. No chemical degradation was observed in either formulation on storage. Thus, the method was sensitive, specific, and suitable for stability testing of tonabersat in pharmaceutical formulations.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 178-185"},"PeriodicalIF":4.2,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142378942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing heterogeneous sensitivity in biomarker screening with application in NanoString nCounter data","authors":"Chang Yu,&nbsp;Zhijin Wu","doi":"10.1016/j.ymeth.2024.09.007","DOIUrl":"10.1016/j.ymeth.2024.09.007","url":null,"abstract":"<div><div>Biomarkers are measurable indicators of biological processes and have wide biomedical applications including disease screening and prognosis prediction. Candidate biomarkers can be screened in high-throughput settings, which allow simultaneous measurements of a large number of molecules. For binary biomarkers, the ability to detect a molecule may be hindered by the presence of background noise and the variable signal strength, which lower the sensitivity to a different extent for different target molecules in a sample-specific manner. This heterogeneity in detection sensitivity is often overlooked and leads to an inflated false positive rate. We propose a novel <em><u>s</u>ensitivity <u>a</u>djusted <u>l</u>ikelihood-ratio <u>t</u>est</em> (SALT), which properly controls the false positives and is more powerful than the unadjusted approach. We show that sample-and-feature-specific detection sensitivity can be well estimated from NanoString nCounter data, and using the estimated sensitivity in SALT results in improved biomarker screening.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 118-143"},"PeriodicalIF":4.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370601","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":"Temperature-jump microscopy and interaction of Hsp70 heat shock protein with a client protein in vivo","authors":"Aniket Ravan ,&nbsp;Samuel Procopio ,&nbsp;Yann R. Chemla ,&nbsp;Martin Gruebele","doi":"10.1016/j.ymeth.2024.09.019","DOIUrl":"10.1016/j.ymeth.2024.09.019","url":null,"abstract":"<div><div>Biomolecular processes such as protein–protein interactions can depend strongly on cell type and even vary within a single cell type. Here we develop a microscope with a Peltier-controlled temperature stage, a laser temperature jump to induce heat stress, and an autofocusing feature to mitigate temperature drift during experiments, to study a protein–protein interaction in a selected cell type within a live organism, the zebrafish larva. As an application of the instrument, we show that there is considerable cell-to-cell variation of the heat shock protein Hsp70 binding to one of its clients, phosphoglycerate kinase <em>in vivo</em>. We adapt a key feature from our previous folding study, rare transformation of cells within the larva, so that individual cells can be imaged and differentiated for cell-to-cell response. Our approach can be extended to other organisms and cell types than the ones demonstrated in this work.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 154-164"},"PeriodicalIF":4.2,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370602","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":"Identification of target genes co-regulated by four key histone modifications of five key regions in hepatocellular carcinoma","authors":"Yu-Xian Liu ,&nbsp;Jia-Le Song ,&nbsp;Xiao-Ming Li ,&nbsp;Hao Lin ,&nbsp;Yan-Ni Cao","doi":"10.1016/j.ymeth.2024.09.017","DOIUrl":"10.1016/j.ymeth.2024.09.017","url":null,"abstract":"<div><div>Hepatocellular carcinoma (HCC) is a cancer with high morbidity and mortality. Studies have shown that histone modification plays an important regulatory role in the occurrence and development of HCC. However, the specific regulatory effects of histone modifications on gene expression in HCC are still unclear. This study focuses on HepG2 cell lines and hepatocyte cell lines. First, the distribution of histone modification signals in the two cell lines was calculated and analyzed. Then, using the random forest algorithm, we analyzed the effects of different histone modifications and their modified regions on gene expression in the two cell lines, four key histone modifications (H3K36me3, H3K4me3, H3K79me2, and H3K9ac) and five key regions that co-regulate gene expression were obtained. Subsequently, target genes regulated by key histone modifications in key regions were screened. Combined with clinical data, Cox regression analysis and Kaplan-Meier survival analysis were performed on the target genes, and four key target genes (<em>CBX2</em>, <em>CEBPZOS</em>, <em>LDHA</em>, and <em>UMPS</em>) related to prognosis were identified. Finally, through immune infiltration analysis and drug sensitivity analysis of key target genes, the potential role of key target genes in HCC was confirmed. Our results provide a theoretical basis for exploring the occurrence of HCC and propose potential biomarkers associated with histone modifications, which may be potential drug targets for the clinical treatment of HCC.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"231 ","pages":"Pages 165-177"},"PeriodicalIF":4.2,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142338564","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}