Methods最新文献

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A high-throughput and time-efficient Nanopore full-length 16S rRNA gene sequencing protocol for synthetic microbial communities 用于合成微生物群落的高通量、高时效 Nanopore 全长 16S rRNA 基因测序方案

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-04-07 DOI: 10.1016/j.ymeth.2025.04.003

Xingjian Zhou, Karoline Faust

Next-generation sequencing (NGS) has transitioned from primarily research-focused applications to a mature technology. However, resolving microbial community composition on the species level based on the 16S rRNA gene is impeded by several critical bottlenecks that limit the efficiency and scalability of analyses. Specifically, standard MiSeq sequencing suffers from read-length limitation; library preparation requires multiple labour-intensive steps from DNA isolation to amplification and barcoding; and prolonged turnaround times delay results. These challenges underscore the need for improved methods, which our study aims to address. Recent advances in Oxford Nanopore long-read sequencing technology (ONT), including a smaller and cheaper benchtop instrument and support for diverse sample types, have enabled faster sequencing in-house with reduced costs. To address the need for standardized, reproducible workflows, we present an optimized and state-of-the-art protocol for full-length 16S rRNA gene sequencing using the ONT MinION sequencing device. Furthermore, we quantified the reproducibility and accuracy of our protocol and compared it with previous MiSeq results. The results showed that the accuracy of our sequencing pipeline for synthetic communities is significantly higher than for MiSeq pipeline. In summary, our protocol elucidates the composition of synthetic microbial communities in an easy, fast and accurate manner while ensuring reproducible results.

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引用次数: 0

Transforming breast cancer diagnosis and treatment with large language Models: A comprehensive survey

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-04-06 DOI: 10.1016/j.ymeth.2025.04.001

Mohsen Ghorbian , Mostafa Ghobaei-Arani , Saied Ghorbian

Breast cancer (BrCa), being one of the most prevalent forms of cancer in women, poses many challenges in the field of treatment and diagnosis due to its complex biological mechanisms. Early and accurate diagnosis plays a fundamental role in improving survival rates, but the limitations of existing imaging methods and clinical data interpretation often prevent optimal results. Large Language Models (LLMs), which are developed based on advanced architectures such as transformers, have brought about a significant revolution in data processing and medical decision-making. By analyzing a large volume of medical and clinical data, these models enable early diagnosis by identifying patterns in images and medical records and provide personalized treatment strategies by integrating genetic markers and clinical guidelines. Despite the transformative potential of these models, their use in BrCa management faces challenges such as data sensitivity, algorithm transparency, ethical considerations, and model compatibility with the details of medical applications that need to be addressed to achieve reliable results. This review systematically reviews the impact of LLMs on BrCa treatment and diagnosis. This study’s objectives include analyzing the role of LLM technology in diagnosing and treating this disease. The findings indicate that the application of LLMs has resulted in significant improvements in various aspects of BrCa management, such as a 35% increase in the Efficiency of Diagnosis and BrCa Treatment (EDBC), a 30% enhancement in the System’s Clinical Trust and Reliability (SCTR), and a 20% improvement in the quality of patient education and information (IPEI). Ultimately, this study demonstrates the importance of LLMs in advancing precision medicine for BrCa and paves the way for effective patient-centered care solutions.

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引用次数: 0

RNA aptamer-induced fluorescence enhancement for NADH monitoring in cellular environment

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-04-05 DOI: 10.1016/j.ymeth.2025.04.002

Mohammad Faysal Al Mazid , Syafira Rizqi Eskasalam , Jun-Seok Lee

Cellular redox homeostasis is tightly regulated by the oxidation–reduction reactions of nicotinamide metabolites, including NAD(H) and NADP(H), which serve as essential cofactors in enzymatic processes related to energy metabolism. Monitoring intracellular NADH levels is therefore of significant interest. Most chemosensor designs to date rely on fluorescence turn-on mechanisms triggered by NADH oxidation, but these reaction-based sensors are inherently limited by NADH concentration and reaction kinetics. While NADH exhibits intrinsic fluorescence, its low quantum yield has led to the development of redox-sensitive substrates that emit fluorescence upon NADH oxidation. Here, we report an alternative fluorescence enhancement strategy based on an NADH-binding RNA aptamer. The interaction between NADH and a 49-base-pair RNA aptamer induces a 1.4-fold increase in fluorescence emission in vitro and an 1.8-fold increase in live-cell imaging. This fluorescence enhancement arises from aptamer-induced structural rigidity, analogous to the mechanism by which 4-(p-hydroxybenzylidene)-5-imidazolidinone (HBI) enhances fluorescence in green fluorescent protein. Using our aptamer-based assay, we established a live-cell fluorescence emission assay for real-time monitoring of cellular NADH dynamics.

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引用次数: 0

Predicting genes associated with ossification of the posterior longitudinal ligament using graph attention network

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-04-04 DOI: 10.1016/j.ymeth.2025.03.014

Fanyu Kong , Han Liu , Xiaoqi Liu , Lei Shi

Ossification of the posterior longitudinal ligament is a degenerative disease that severely impacts the spine, with a complex pathogenesis involving the interplay of multiple genes. This study utilizes a combination of graph neural networks and deep neural networks to systematically analyze genes associated with OPLL, leveraging genomics and bioinformatics techniques. By integrating gene data from the DisGeNET and HumanNetV2 databases, we constructed a GNN model to identify potential pathogenic genes for OPLL and validated the expression characteristics and mechanisms of these genes in different cell types. The findings indicate that the GNN model achieves remarkable accuracy and reliability in predicting genes associated with OPLL. Additionally, cellular trajectory analysis and immune cell infiltration studies uncovered distinct cellular environments and immune features in OPLL patients, emphasizing the significant roles of fibroblasts and mesenchymal stem cells in the disease's progression. Drug sensitivity analysis also sheds light on future personalized treatment options. This study not only enhances the understanding of OPLL's molecular mechanisms but also suggests new avenues for diagnostic and targeted therapy development.

后纵韧带骨化是一种严重影响脊柱的退行性疾病，其发病机制复杂，涉及多个基因的相互作用。本研究结合图神经网络和深度神经网络，利用基因组学和生物信息学技术，系统分析了与后纵韧带骨化症相关的基因。通过整合 DisGeNET 和 HumanNetV2 数据库中的基因数据，我们构建了一个 GNN 模型来识别 OPLL 的潜在致病基因，并验证了这些基因在不同细胞类型中的表达特征和机制。研究结果表明，GNN 模型在预测 OPLL 相关基因方面具有显著的准确性和可靠性。此外，细胞轨迹分析和免疫细胞浸润研究揭示了OPLL患者独特的细胞环境和免疫特征，强调了成纤维细胞和间充质干细胞在疾病进展中的重要作用。药物敏感性分析还为未来的个性化治疗方案提供了启示。这项研究不仅加深了人们对OPLL分子机制的了解，还为诊断和靶向治疗的开发提出了新的途径。

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引用次数: 0

Optimized toolkit for the manipulation of immortalized axolotl fibroblasts

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-04-03 DOI: 10.1016/j.ymeth.2025.03.019

Benjamin J. Tajer , Glory Kalu , Sarah Jay , Eric Wynn , Antoine Decaux , Paul Gilbert , Hani D. Singer , Maddeline D. Kidd , Jeffery A. Nelson , Noora Harake , Noah J. Lopez , Nathan R. Souchet , Anna G. Luong , Aaron M. Savage , Sangwon Min , Alparslan Karabacak , Sebastian Böhm , Ryan T. Kim , Tim Froitzheim , Konstantinos Sousounis , Jessica L. Whited

The axolotl salamander model has broad utility for regeneration studies, but this model is limited by a lack of efficient cell-culture-based tools. The Axolotl Limb-1 (AL-1) fibroblast line, the only available immortalized axolotl cell line, was first published over 20 years ago, but many established molecular biology techniques, such as lipofectamine transfection, CRISPR-Cas9 mutagenesis, and antibiotic selection, work poorly or remain untested in AL-1 cells. Innovating technologies to manipulate AL-1 cells in culture and study their behavior following transplantation into the axolotl will complement in-vivo studies, decrease the number of animals used, and enable the faster, more streamlined investigation of regenerative biology questions. Here, we establish transfection, mutagenesis, antibiotic selection, and in-vivo transplantation techniques in axolotl AL-1 cells. These techniques will enable efficient culture with AL-1 cells and guide future tool development for the culture and manipulation of other salamander cell lines.

{"title":"Optimized toolkit for the manipulation of immortalized axolotl fibroblasts","authors":"Benjamin J. Tajer , Glory Kalu , Sarah Jay , Eric Wynn , Antoine Decaux , Paul Gilbert , Hani D. Singer , Maddeline D. Kidd , Jeffery A. Nelson , Noora Harake , Noah J. Lopez , Nathan R. Souchet , Anna G. Luong , Aaron M. Savage , Sangwon Min , Alparslan Karabacak , Sebastian Böhm , Ryan T. Kim , Tim Froitzheim , Konstantinos Sousounis , Jessica L. Whited","doi":"10.1016/j.ymeth.2025.03.019","DOIUrl":"10.1016/j.ymeth.2025.03.019","url":null,"abstract":"<div><div>The axolotl salamander model has broad utility for regeneration studies, but this model is limited by a lack of efficient cell-culture-based tools. The Axolotl Limb-1 (AL-1) fibroblast line, the only available immortalized axolotl cell line, was first published over 20 years ago, but many established molecular biology techniques, such as lipofectamine transfection, CRISPR-Cas9 mutagenesis, and antibiotic selection, work poorly or remain untested in AL-1 cells. Innovating technologies to manipulate AL-1 cells in culture and study their behavior following transplantation into the axolotl will complement <em>in-vivo</em> studies, decrease the number of animals used, and enable the faster, more streamlined investigation of regenerative biology questions. Here, we establish transfection, mutagenesis, antibiotic selection, and <em>in-vivo</em> transplantation techniques in axolotl AL-1 cells. These techniques will enable efficient culture with AL-1 cells and guide future tool development for the culture and manipulation of other salamander cell lines.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"240 ","pages":"Pages 21-34"},"PeriodicalIF":4.2,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787640","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}

引用次数: 0

3D printing of calcium doped Isomalt via custom-made Extruder: Facile approach for creating blood vascular like networks within tissue mimicking hydrogel matrix 通过定制挤出机三维打印掺钙异麦芽酮：在组织模拟水凝胶基质中创建类似血管网络的简便方法。

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-04-02 DOI: 10.1016/j.ymeth.2025.03.018

Amar Dhwaj , Nimisha Roy , Amit Prabhakar , Deepti Verma

3D printing domain has witnessed rapid advancements with immense applications in various fields ranging from aerospace to 3D printed organs. This study describes a facile biofabrication approach for creating an Artificial blood vascular network inside the Hydrogel matrix by using Isomalt sugar (Sugar Alcohol) as a sacrificial component inside a composite-Hydrogel matrix. Conventional 3D-printers have extruder and hot-end assembly, whereas Bioprinters use pneumatic-piston, and piezoelectric-driven extrusion mechanisms. In this study, we describe the design and operation of a custom-made miniature precision lead screw-based syringe-pump extruder mechanism with integrated temperature-controlled heat-block. We are currently using this integrated setup for melt Isomalt-based 3D printing, which can be easily mounted over the Z-axis and is driven using a geared stepper motor with high torque, providing controlled extrusion of highly viscous polymers where sugar structures are used as sacrificial materials for making Artificial blood vascular like networks in the microfluidics domain within the composite Hydrogel matrix. Computational studies using COMSOL Multiphysics were performed to predict the diffusion pattern of the DMEM culture medium to estimate the rate of mass flow through a porous media. Furthermore, Cell based testing is performed using Human Adipose Derived Mesenchymal Stem Cells (HAD-MSC’s) which were cultured over the vascular Hydrogel matrix perfused with culture media with defined flowrates to mimic the natural function of the Nutrient and gaseous exchange inside human tissues. The proposed can be used to produce equivalent Tissue models which could be potentially used in On-chip drug testing platforms, drug discovery and regenerative medicine domains.

3D 打印领域发展迅速，在从航空航天到 3D 打印器官等各个领域都有广泛应用。本研究介绍了一种简便的生物制造方法，通过在复合水凝胶基质中使用异麦芽糖（糖醇）作为牺牲成分，在水凝胶基质中创建人造血管网络。传统的三维打印机有挤出机和热端组件，而生物打印机则使用气动活塞和压电驱动挤出机制。在本研究中，我们介绍了一种基于注射器泵的定制微型精密导螺杆挤出机制的设计和操作，该机制集成了温控热块。目前，我们正在使用这种集成装置进行基于异麦芽酮的熔融三维打印，该装置可轻松安装在 Z 轴上，并使用具有高扭矩的齿轮步进电机进行驱动，可对高粘度聚合物进行受控挤出，其中糖结构用作牺牲材料，用于在复合水凝胶基质内的微流体域中制造类似人造血管网络的网络。使用 COMSOL Multiphysics 进行了计算研究，以预测 DMEM 培养基的扩散模式，从而估算通过多孔介质的质量流量。此外，还利用人体脂肪间充质干细胞（HAD-MSC）进行了基于细胞的测试，该细胞在血管水凝胶基质上培养，并灌注了具有确定流速的培养基，以模拟人体组织内营养物质和气体交换的自然功能。所建议的方法可用于制作等效的组织模型，这些模型可用于片上药物测试平台、药物发现和再生医学领域。

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引用次数: 0

Multi-Omics clustering by integrating clinical features from large language model

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-04-01 DOI: 10.1016/j.ymeth.2025.03.017

Xiucai Ye, Tianyi Shi, Dong Huang, Tetsuya Sakurai

Multi-omics clustering has emerged as a powerful approach for understanding complex biological systems and enabling cancer subtyping by integrating diverse omics data. Existing methods primarily focus on the integration of different types of omics data, often overlooking the value of clinical context. In this study, we propose a novel framework that incorporates clinical features extracted from large language model (LLM) to enhance multi-omics clustering. Leveraging clinical data extracted from pathology reports using a BERT-based model, our framework converts unstructured medical text into structured clinical features. These features are integrated with omics data through an autoencoder, enriching the information content of each omics layer to improve feature extraction. The extracted features are then projected into a latent subspace using singular value decomposition (SVD), followed by spectral clustering to obtain the final clustering result. We evaluate the proposed framework on six cancer datasets on three omics levels, comparing it with several state-of-the-art methods. The experimental results demonstrate that the proposed framework outperforms existing methods in multi-omics clustering for cancer subtyping. Moreover, the results highlight the efficacy of integrating clinical features derived from LLM, significantly enhancing clustering performance. This work underscores the importance of clinical context in multi-omics analysis and showcases the transformative potential of LLM in advancing precision medicine.

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引用次数: 0

Strategies for ocular drug delivery

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-03-28 DOI: 10.1016/j.ymeth.2025.03.020

Silvia L. Fialho (Guest editor)

引用次数: 0

Corrigendum to “Production of AFM wedged cantilevers for stress-relaxation experiments: Uniaxial loading of soft, spherical cells” [Methods 236 (2025) 1–9]

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-03-28 DOI: 10.1016/j.ymeth.2025.03.013

Riccardo Campanile , Jonne Helenius , Cristina Scielzo , Lydia Scarfò , Domenico Salerno , Mario Bossi , Marta Falappi , Alessia Saponara , Daniel J. Müller , Francesco Mantegazza , Valeria Cassina

引用次数: 0

A methodological comparison of synthesizing heavy metal substituted bioapatite

IF 4.2 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Methods

Pub Date : 2025-03-25 DOI: 10.1016/j.ymeth.2025.03.016

Kennedy A. Drake, Tyler A. Grubelich, Stephanie Wong, Alix C. Deymier

This study evaluates two methods—maturation and direct precipitation—for synthesizing heavy metal substituted biomimetic hydroxyapatite (HA), focusing on their efficacy in mimicking human bone composition and crystallinity. Cobalt (Co) and chromium (Cr) substitutions were investigated due to their relevance to metal-on-metal implant degradation and the potential integration of these ions into bone mineral. The maturation method involves prolonged incubation, producing amorphous and bioresorbable apatites, while the direct precipitation (DP) method achieves rapid synthesis of highly crystalline apatites through controlled titration. Both approaches were characterized using X-ray diffraction (XRD), Raman spectroscopy, and Fourier Transform Infrared (FTIR) spectroscopy, confirming the apatitic nature of the samples and lattice strain induced by metal ion substitution. This study highlights the maturation method’s adaptability for long-term biological interactions and the DP method’s mechanical stability for load-bearing applications. Comparison of the structural and chemical properties of substituted HA from each method provides insights into optimizing synthesis techniques for diverse biomedical applications, such as bone tissue engineering and mitigating the effects of heavy metal ion release on bone health. These findings contribute to advancing hydroxyapatite-based biomaterials tailored for therapeutic and regenerative medicine needs.

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引用次数: 0

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