Methods最新文献

{"title":"Imaging flow cytometry reveals LPS-induced changes to intracellular intensity and distribution of α-synuclein in a TLR4-dependent manner in STC-1 cells","authors":"Anastazja M. Gorecki ,&nbsp;Chidozie C. Anyaegbu ,&nbsp;Melinda Fitzgerald ,&nbsp;Kathryn A. Fuller ,&nbsp;Ryan S. Anderton","doi":"10.1016/j.ymeth.2024.10.009","DOIUrl":"10.1016/j.ymeth.2024.10.009","url":null,"abstract":"<div><h3>Background</h3><div>Parkinson’s disease is a chronic neurodegenerative disorder, where pathological protein aggregates largely composed of phosphorylated α-synuclein are implicated in disease pathogenesis and progression. Emerging evidence suggests that the interaction between pro-inflammatory microbial factors and the gut epithelium contributes to α-synuclein aggregation in the enteric nervous system. However, the cellular sources and mechanisms for α-synuclein pathology in the gut are still unclear.</div></div><div><h3>Methods</h3><div>The STC-1 cell line, which models an enteroendocrine population capable of communicating with the gut microbiota, immune and nervous systems, was treated with a TLR4 inhibitor (TAK-242) prior to microbial lipopolysaccharide (LPS) exposure to investigate the role of TLR4 signalling in α-synuclein alterations. Antibodies targeting the full-length protein (α-synuclein) and the Serine-129 phosphorylated form (pS129) were used. Complex, multi-parametric image analysis was conducted through confocal microscopy (with Zen 3.8 analysis) and imaging flow cytometry (with IDEAS® analysis).</div></div><div><h3>Results</h3><div>Confocal microscopy revealed heterogenous distribution of α-synuclein and pS129 in STC-1 cells, with prominent pS129 staining along cytoplasmic processes. Imaging flow cytometry further quantified the relationship between various α-synuclein morphometric features. Thereafter, imaging flow cytometry demonstrated a dose-specific effect of LPS, where the low (8 μg/mL), but not high dose (32 μg/mL), significantly altered measures related to α-synuclein intensity, distribution, and localisation. Pre-treatment with a TLR4 inhibitor TAK-242 alleviated some of these significant alterations.</div></div><div><h3>Conclusion</h3><div>This study demonstrates that LPS-TLR4 signalling alters the intracellular localisation of α-synuclein in enteroendocrine cells <em>in vitro</em> and showcases the utility of combining imaging flow cytometry to investigate subtle protein changes that may not be apparent through confocal microscopy alone. Further investigation is required to understand the apparent dose-dependent effects of LPS on α-synuclein in the gut epithelium in healthy states as well as conditions such as Parkinson’s disease.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 93-111"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142563953","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":"Artificial intelligence and computer-aided drug discovery: Methods development and application","authors":"Haiping Zhang,&nbsp;Yanjie Wei,&nbsp;Konda Mani Saravanan","doi":"10.1016/j.ymeth.2025.01.009","DOIUrl":"10.1016/j.ymeth.2025.01.009","url":null,"abstract":"","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 294-295"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142997924","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":"Lead-grouped multi-stage learning for myocardial infarction localization","authors":"Lin Guo ,&nbsp;Qianyun Zhan ,&nbsp;Jichao Yang ,&nbsp;Ying An ,&nbsp;Jun Long ,&nbsp;Nan Ma","doi":"10.1016/j.ymeth.2025.01.015","DOIUrl":"10.1016/j.ymeth.2025.01.015","url":null,"abstract":"<div><div>The electrocardiogram (ECG) is a ubiquitous medical diagnostic tool employed to localize myocardial infarction (MI) that is characterized by abnormal waveform patterns on the ECG. MI is a serious cardiovascular disease, and accurate, timely diagnosis is crucial for preventing severe outcomes. Current ECG analysis methods mainly rely on intra- and inter-lead feature extraction, but most models overlook the medical knowledge relevant to disease diagnosis. Moreover, existing models often fail to effectively utilize the global spatial relationships within multi-lead ECGs, limiting their ability to comprehensively understand and accurately localize the complex pathological mechanisms of MI. To address these issues, we propose a knowledge-driven overlapping lead grouping method. Based on clinical diagnostic knowledge, we group the 12 leads according to their relevance to MI localization while retaining the full set of 12 leads as a unified group. Additionally, we design a multi-stage learning network that first extracts basic features through initial convolutional layer and progressive convolutional block, followed by SE-enhanced multi-scale residual block and positional Transformer block to gradually learn deeper intra- and inter-lead features. Furthermore, we propose a branch-level weighted feature integration mechanism to effectively fuse the features extracted from each group. The proposed method was thoroughly evaluated on the publicly available multi-label PTB-XL dataset and achieved over 80% prediction accuracy for MI localization tasks. The results demonstrated significant improvements across several metrics compared to current state-of-the-art methods, confirming its exceptional performance.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 315-323"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143027495","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":"Xenographic lenticule implantation followed by riboflavin and UV treatment: A promising alternative for corneal ectasias management","authors":"Fernanda Aparecida Silva Vieira ,&nbsp;Lays Fernanda Nunes Dourado ,&nbsp;Thomas Toshio Inoue ,&nbsp;Lutiana Amaral Melo ,&nbsp;Paulo Ferrara de Almeida Cunha ,&nbsp;Silvia Ligorio Fialho ,&nbsp;Armando Silva-Cunha","doi":"10.1016/j.ymeth.2025.01.010","DOIUrl":"10.1016/j.ymeth.2025.01.010","url":null,"abstract":"<div><div>The cornea is the primary refracting surface of the eye, requiring precise curvature to ensure optimal vision. Any distortion in its shape may result in significant visual impairment. Corneal ectasias, such as keratoconus (KC), is characterized by gradual thinning and protrusion of the thinned area, due to biomechanical weakening of the tissue, leading to astigmatism and vision loss. KC affects approximately 1 in 2000 individuals globally. While corneal transplantation is the main treatment, limited donor availability and potential immunogenic reactions have spurred the search for alternatives. Stromal lenticule implantation using decellularized porcine corneas offers a promising solution, with reduced immunogenicity and risk of rejection. Additionally, combining this approach with riboflavin and UV radiation treatment post-surgery enhances collagen fibril cross-linking, promoting tissue integration and organization. This study evaluated the efficacy of heterologous transplantation of decellularized porcine lenticules into the corneal stroma of rabbits, followed by riboflavin application and UV radiation. Results demonstrated increased stromal thickness and no signs of tissue rejection, indicating minimal immunogenicity of the lenticules. The cross-linking technique successfully improved tissue organization, suggesting that xenographic lenticule implantation, combined with riboflavin and UV light, is a promising alternative for treating corneal ectasias like KC. Further research is necessary to confirm the long-term efficacy and safety of this method in human subjects.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 296-304"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142997929","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":"Advances in machine learning for epigenetics and biomedical applications","authors":"Hao Lin,&nbsp;Hao Lv,&nbsp;Fuying Dao","doi":"10.1016/j.ymeth.2025.01.018","DOIUrl":"10.1016/j.ymeth.2025.01.018","url":null,"abstract":"","PeriodicalId":390,"journal":{"name":"Methods","volume":"235 ","pages":"Pages 53-54"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121685","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":"Low friction hydrogel with diclofenac eluting ability for dry eye therapeutic contact lenses","authors":"Diana C. Silva ,&nbsp;Margarida Oliveira ,&nbsp;Carolina Marto-Costa ,&nbsp;João Teixeira ,&nbsp;Madalena Salema Oom ,&nbsp;Carlos A. Pinto ,&nbsp;Jorge A. Saraiva ,&nbsp;Ana Clara Marques ,&nbsp;Laurence Fitzhenry ,&nbsp;Ana Paula Serro","doi":"10.1016/j.ymeth.2024.11.015","DOIUrl":"10.1016/j.ymeth.2024.11.015","url":null,"abstract":"<div><div>When placed in the eye, contact lenses (CLs) disturb the tear fluid and affect the natural tribological behaviour of the eye. The disruption in the contact mechanics between the ocular tissues can increase frictional shear stress and ocular dryness, causing discomfort. Ultimately, continuous CLs wear can trigger inflammation which is particularly critical for people suffering from dry eye. In this work, a double strategy was followed to obtain therapeutic daily disposable CLs for dry eye: a hydroxyethyl methacrylate (HEMA) based hydrogel was coated with two natural polysaccharides, chitosan (CHI) and hyaluronic acid (HA) and posteriorly loaded with an anti-inflammatory drug (diclofenac, DCF). Material sterilisation was carried out by high hydrostatic pressure (HHP) combined with moderate temperature. The friction coefficient (μ) was determined in the presence of different tear biomolecules (cholesterol, lysozyme and albumin) using a nanotribometer. Drug release experiments were performed in static and in hydrodynamic conditions. The material was extensively characterised, regarding surface morphology/topography, optical properties, water content and swelling behaviour, wettability, ionic and oxygen permeability and mechanical properties. It was found that the coating did not impair the physico-chemical properties relevant for the material’s application in CLs. Besides, it also ensured a sustained release of DCF for 24 h in tests performed in hydrodynamic conditions that simulate those found in the eye, increasing significantly the amount of drug released. It reduced friction, improving the lubrication ability of the hydrogel, and presented antibacterial properties against <em>S. aureus</em>, <em>P. aeruginosa</em> and <em>B. Cereus</em>. The coated samples did not reveal any signs of cytotoxicity or potential eye irritation. Overall, the coating of the hydrogel may be useful to produce daily CLs able to alleviate dry eye symptoms and the discomfort of CLs wearers.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 67-84"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142765111","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":"A roadmap to cysteine specific labeling of membrane proteins for single-molecule photobleaching studies","authors":"Melanie Ernst,&nbsp;Robyn Mahoney-Kruszka,&nbsp;Nathan B. Zelt,&nbsp;Janice L. Robertson","doi":"10.1016/j.ymeth.2024.10.013","DOIUrl":"10.1016/j.ymeth.2024.10.013","url":null,"abstract":"<div><div>Single-molecule photobleaching analysis is a useful approach for quantifying reactive membrane protein oligomerization in membranes. It provides a binary readout of a fluorophore attached to a protein subunit at dilute conditions. However, quantification of protein stoichiometry from this data requires information about the subunit labeling yields and whether there is non-specific background labeling. Any increases in subunit-specific labeling improves the ability to determine oligomeric states with confidence. A common strategy for site-specific labeling is by conjugation of a fluorophore bearing a thiol-reactive maleimide group to a substituted cysteine. Yet, cysteine reactivity can be difficult to predict as it depends on many factors such as solvent accessibility and electrostatics from the surrounding protein structure. Here we report a general methodology for screening potential cysteine labeling sites on purified membrane proteins. We present the results of two example systems for which the dimerization reactions in membranes have been characterized: (1) the CLC-ec1 Cl^-/H⁺ antiporter, an <em>Escherichia coli</em> homologue of voltage-gated chloride ion channels in humans and (2) a mutant form of a member of the family of fluoride channels Fluc from <em>Bordetella pertussis</em> (Fluc-Bpe-N43S). To demonstrate how we identify such sites, we first discuss considerations of residue positions hypothesized to be suitable and then describe the specific steps to rigorously assess site-specific labeling while maintaining functional activity and robust single-molecule fluorescence signals. We find that our initial, well rationalized choices are not strong predictors of success, as rigorous testing of the labeling sites shows that only ≈ 30 % of sites end up being useful for single-molecule photobleaching studies.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 21-35"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142714807","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":"Design and characterization of hollow microneedles for localized intrascleral drug delivery of ocular formulations","authors":"Shilpkala Gade,&nbsp;Lalitkumar K. Vora,&nbsp;Raghu Raj Singh Thakur","doi":"10.1016/j.ymeth.2024.12.004","DOIUrl":"10.1016/j.ymeth.2024.12.004","url":null,"abstract":"<div><div>Effective drug delivery to the posterior segment of the eye remains a challenge owing to the limitations of conventional methods such as intravitreal injections, which are associated with significant side effects. This study explored the use of hollow microneedles (HMNs) for localized intrascleral drug delivery as a minimally invasive alternative. Stainless steel HMNs with bevel angles of 30°, 45°, 60°, and 75° were fabricated using wire electron discharge machining. The penetration force of these HMNs in ex vivo porcine sclera was assessed using a texture analyser, revealing that the 60° bevel angle required the lowest force (&lt;2N), making it optimal for scleral penetration. To ensure precision in drug delivery, 3D-printed adapters were developed to control the injection angles and volumes. The distribution of a model dye, rhodamine B, was studied via digital imaging, multiphoton microscopy, and confocal microscopy. The results showed that HMNs with a 60° bevel angle could penetrate the sclera to a depth of approximately 450 µm at a 45° injection angle, providing enhanced distribution within the scleral layers. This study confirmed that the use of HMNs enables effective and controlled intrascleral drug delivery, resulting in the formation of localized depots with minimal tissue damage. This research demonstrates the potential of HMNs as a promising alternative to traditional ocular drug delivery methods, offering improved bioavailability and the potential to reduce patient discomfort.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 196-210"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880855","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":"AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus","authors":"Shaherin Basith ,&nbsp;Balachandran Manavalan ,&nbsp;Gwang Lee","doi":"10.1016/j.ymeth.2025.01.003","DOIUrl":"10.1016/j.ymeth.2025.01.003","url":null,"abstract":"<div><div>Pancreatic α-amylase breaks down starch into isomaltose and maltose, which are further hydrolyzed by α-glucosidase in the intestine into monosaccharides, rapidly raising blood sugar levels and contributing to type 2 diabetes mellitus (T2DM). Synthetic inhibitors of carbohydrate-digesting enzymes are used to manage T2DM but may harm organ function over time. Bioactive peptides offer a safer alternative, avoiding such adverse effects. Computational methods for predicting antidiabetic peptides (ADPs) can significantly reduce the time and cost of experimental testing. While machine learning (ML) has been applied to identify ADPs, advancements in data analysis and algorithms continue to drive progress in the field. To address this, we developed AntiT2DMP-Pred, the first ML-based tool specifically designed for predicting type 2 antidiabetic peptides (T2ADPs). This tool employs a feature fusion strategy, combining ten highly discriminative feature descriptors chosen from a pool of 32 descriptors and eight ML algorithms, tested across a range of baseline models. AntiT2DMP-Pred demonstrated excellent performance, surpassing both baseline and feature-optimized models, with an accuracy (ACC) and Matthews’ correlation coefficient (MCC) of 0.976 and 0.953 on the training dataset, and an ACC and MCC of 0.957 and 0.851 on the independent dataset. The web server (<span><span>https://balalab-skku.org/AntiT2DMP-Pred</span><svg><path></path></svg></span>) is freely accessible, enabling researchers worldwide to utilize it in their experimental workflows and contribute to the discovery and understanding of T2ADPs, ultimately supporting peptide-based therapeutic development for diabetes management.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 264-274"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142968895","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":"Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides","authors":"Phasit Charoenkwan ,&nbsp;Pramote Chumnanpuen ,&nbsp;Nalini Schaduangrat ,&nbsp;Watshara Shoombuatong","doi":"10.1016/j.ymeth.2024.12.005","DOIUrl":"10.1016/j.ymeth.2024.12.005","url":null,"abstract":"<div><div>Identifying angiotensin-I-converting enzyme (ACE) inhibitory peptides accurately is crucial for understanding the primary factor that regulates the renin-angiotensin system and for providing guidance in developing new potential drugs. Given the inherent experimental complexities, using computational methods for <em>in silico</em> peptide identification could be indispensable for facilitating the high-throughput characterization of ACE inhibitory peptides. In this paper, we propose a novel deep stacking-based ensemble learning framework, termed Deepstack-ACE, to precisely identify ACE inhibitory peptides. In Deepstack-ACE, the input peptide sequences are fed into the word2vec embedding technique to generate sequence representations. Then, these representations were employed to train five powerful deep learning methods, including long short-term memory, convolutional neural network, multi-layer perceptron, gated recurrent unit network, and recurrent neural network, for the construction of base-classifiers. Finally, the optimized stacked model was constructed based on the best combination of selected base-classifiers. Benchmarking experiments showed that Deepstack-ACE attained a more accurate and robust identification of ACE inhibitory peptides compared to its base-classifiers and several conventional machine learning classifiers. Remarkably, in the independent test, our proposed model significantly outperformed the current state-of-the-art methods, with a balanced accuracy of 0.916, sensitivity of 0.911, and Matthews correlation coefficient scores of 0.826. Moreover, we developed a user-friendly web server for Deepstack-ACE, which is freely available at <span><span>https://pmlabqsar.pythonanywhere.com/Deepstack-ACE</span><svg><path></path></svg></span>. We anticipate that our proposed Deepstack-ACE model can provide a faster and reasonably accurate identification of ACE inhibitory peptides.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"234 ","pages":"Pages 131-140"},"PeriodicalIF":4.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142870920","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}