Biology Methods and Protocols最新文献_第6页

Optimization and application of digital droplet PCR for the detection of SARS-CoV-2 in saliva specimen using commercially available kit. 使用市售试剂盒优化和应用数字液滴 PCR 检测唾液样本中的 SARS-CoV-2

IF 2.5

Biology Methods and Protocols Pub Date : 2024-09-23 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae068

Maria M M Kaisar, Helen Kristin, Fajar A Wijaya, Clarissa Rachel, Felicia Anggraini, Soegianto Ali

{"title":"Optimization and application of digital droplet PCR for the detection of SARS-CoV-2 in saliva specimen using commercially available kit.","authors":"Maria M M Kaisar, Helen Kristin, Fajar A Wijaya, Clarissa Rachel, Felicia Anggraini, Soegianto Ali","doi":"10.1093/biomethods/bpae068","DOIUrl":"10.1093/biomethods/bpae068","url":null,"abstract":"The coronavirus disease-19 pandemic has resulted in a significant global health crisis, causing hundreds of millions of cases and millions of deaths. Despite being declared endemic, SARS-CoV-2 infection continues to pose a significant risk, particularly for immunocompromised individuals, highlighting the need for a more sensitive and specific detection. Reverse transcription digital droplet polymerase chain reaction (RT-ddPCR) possesses a sensitive and absolute quantification compared to the gold standard. This study is the first to optimize RT-ddPCR for detecting SARS-CoV-2 in saliva specimens using a commercially available RT-qPCR kit. Optimization involved the assessment of the RT-ddPCR reaction mixture, annealing temperature adjustments, and validation using 40 stored saliva specimens. RT-qPCR was used as a reference method in this study. Compatibility assessment revealed that ddPCR Supermix for Probes (no dUTP) was preferable with an optimal annealing temperature of 57.6°C. Although a 25% higher primer/probe concentration provides a higher amplitude in droplet separation of positive control, the number of copy numbers decreased. An inverse correlation between Ct value and copy number concentration was displayed, presenting that the lower the Ct value, the higher the concentration, for the N and E genes with r2 values of 0.98 and 0.85, respectively. However, ORF1ab was poorly correlated (r2 of 0.34). The sensitivity of targeted and E genes was 100% and 93.3%, respectively; as for the specificity, the percentage ranged from 80.8% to 91.3%. This study implicates the applicability of a modified method in the ddPCR platform for similar types of pathogens using saliva specimens.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae068"},"PeriodicalIF":2.5,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11444740/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142362248","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

An efficient protocol for the extraction of pigment-free active polyphenol oxidase and soluble proteins from plant cells. 从植物细胞中提取不含色素的活性多酚氧化酶和可溶性蛋白质的高效方案。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-09-19 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae067

Seyit Yuzuak, De-Yu Xie

{"title":"An efficient protocol for the extraction of pigment-free active polyphenol oxidase and soluble proteins from plant cells.","authors":"Seyit Yuzuak, De-Yu Xie","doi":"10.1093/biomethods/bpae067","DOIUrl":"https://doi.org/10.1093/biomethods/bpae067","url":null,"abstract":"The elimination of brownish pigments from plant protein extracts has been a challenge in plant biochemistry studies. Although numerous approaches have been developed to reduce pigments for enzyme assays, none has been able to completely remove pigments from plant protein extracts for biochemical studies. A simple and effective protocol was developed to completely remove pigments from plant protein extracts. Proteins were extracted from red anthocyanin-rich transgenic and greenish wild-type tobacco cells cultured on agar-solidified Murashige and Skoog medium. Protein extracts from these cells were brownish or dark due to the pigments. Four approaches were comparatively tested to show that the diethylaminoethyl (DEAE)-Sephadex anion exchange gel column was effective in completely removing pigments to obtain transparent pigment-free protein extracts. A Millipore Amicon® Ultra 10K cut-off filter unit was used to effectively desalt proteins. Moreover, the removal of pigments significantly improved the measurement accuracy of total soluble proteins. Furthermore, enzymatic assays using catechol as a substrate coupled with high-performance liquid chromatography analysis demonstrated that the pigment-free proteins not only showed polyphenol oxidase (PPO) activity but also enhanced the catalytic activity of PPO. Taken together, this protocol is effective for extracting pigment-free plant proteins for plant biochemistry studies. A simple and effective protocol was successfully developed to not only completely and effectively remove anthocyanin and polyphenolics-derived quinone pigments from plant protein extracts but also to decrease the effects of pigments on the measurement accuracy of total soluble proteins. This robust protocol will enhance plant biochemical studies using pigment-free native proteins, which in turn increase their reliability and sensitivity.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae067"},"PeriodicalIF":2.5,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11434163/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355761","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

A new method for quantifying glyoxalase II activity in biological samples. 量化生物样本中乙醛缩合酶 II 活性的新方法。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-09-18 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae069

Mohammed Alaa Kadhum, Mahmoud Hussein Hadwan

{"title":"A new method for quantifying glyoxalase II activity in biological samples.","authors":"Mohammed Alaa Kadhum, Mahmoud Hussein Hadwan","doi":"10.1093/biomethods/bpae069","DOIUrl":"10.1093/biomethods/bpae069","url":null,"abstract":"Glyoxalase II (Glo II) is a crucial enzyme in the glyoxalase system, and plays a vital role in detoxifying harmful metabolites and maintaining cellular redox balance. Dysregulation of Glo II has been linked to various health conditions, including cancer and diabetes. This study introduces a novel method using 2,4-dinitrophenylhydrazine (2,4-DNPH) to measure Glo II activity. The principle behind this approach is the formation of a colored hydrazone complex between 2,4-DNPH and pyruvate produced by the Glo II-catalyzed reaction. Glo II catalyzes the hydrolysis of S-D-lactoylglutathione (SLG), generating D-lactate and reduced glutathione (GSH). The D-lactate is then converted to pyruvate by lactate dehydrogenase, then reacting with 2,4-DNPH to form a brown-colored hydrazone product. The absorbance of this complex, measured at 430 nm, allows for the quantification of Glo II activity. The study rigorously validates the 2,4-DNPH method, demonstrating its stability, sensitivity, linearity, and resistance to interference from various biochemical substances. Compared to the existing UV method, this 2,4-DNPH-Glo II assay shows a strong correlation. The new protocol for measuring Glo II activity using 2,4-DNPH is simple, cost-effective, and accurate, making it a valuable tool for researchers and medical professionals. Its potential for widespread use in various laboratory settings, from academic research to clinical diagnostics, offers significant opportunities for future research and medical applications.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae069"},"PeriodicalIF":2.5,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11441573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355760","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

A modified dual preparatory method for improved isolation of nucleic acids from laser microdissected fresh-frozen human cancer tissue specimens. 一种改进的双重制备方法，用于从激光显微解剖的新鲜冷冻人体癌症组织标本中分离核酸。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-09-10 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae066

Danielle C Kimble, Tracy J Litzi, Gabrielle Snyder, Victoria Olowu, Sakiyah TaQee, Kelly A Conrads, Jeremy Loffredo, Nicholas W Bateman, Camille Alba, Elizabeth Rice, Craig D Shriver, George L Maxwell, Clifton Dalgard, Thomas P Conrads

{"title":"A modified dual preparatory method for improved isolation of nucleic acids from laser microdissected fresh-frozen human cancer tissue specimens.","authors":"Danielle C Kimble, Tracy J Litzi, Gabrielle Snyder, Victoria Olowu, Sakiyah TaQee, Kelly A Conrads, Jeremy Loffredo, Nicholas W Bateman, Camille Alba, Elizabeth Rice, Craig D Shriver, George L Maxwell, Clifton Dalgard, Thomas P Conrads","doi":"10.1093/biomethods/bpae066","DOIUrl":"https://doi.org/10.1093/biomethods/bpae066","url":null,"abstract":"A central theme in cancer research is to increase our understanding of the cancer tissue microenvironment, which is comprised of a complex and spatially heterogeneous ecosystem of malignant and non-malignant cells, both of which actively contribute to an intervening extracellular matrix. Laser microdissection (LMD) enables histology selective harvest of cellular subpopulations from the tissue microenvironment for their independent molecular investigation, such as by high-throughput DNA and RNA sequencing. Although enabling, LMD often requires a labor-intensive investment to harvest enough cells to achieve the necessary DNA and/or RNA input requirements for conventional next-generation sequencing workflows. To increase efficiencies, we sought to use a commonplace dual preparatory (DP) procedure to isolate DNA and RNA from the same LMD harvested tissue samples. While the yield of DNA from the DP protocol was satisfactory, the RNA yield from the LMD harvested tissue samples was significantly poorer compared to a dedicated RNA preparation procedure. We determined that this low yield of RNA was due to incomplete partitioning of RNA in this widely used DP protocol. Here, we describe a modified DP protocol that more equally partitions nucleic acids and results in significantly improved RNA yields from LMD-harvested cells.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae066"},"PeriodicalIF":2.5,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11486541/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142476727","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

Development and characterization of human T-cell receptor (TCR) alpha and beta clones' library as biological standards and resources for TCR sequencing and engineering. 开发和鉴定人类 T 细胞受体（TCR）α 和β 克隆库，作为 TCR 测序和工程的生物标准和资源。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-09-05 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae064

Yu-Chun Wei, Mateusz Pospiech, Yiting Meng, Houda Alachkar

{"title":"Development and characterization of human T-cell receptor (TCR) alpha and beta clones' library as biological standards and resources for TCR sequencing and engineering.","authors":"Yu-Chun Wei, Mateusz Pospiech, Yiting Meng, Houda Alachkar","doi":"10.1093/biomethods/bpae064","DOIUrl":"10.1093/biomethods/bpae064","url":null,"abstract":"Characterization of T-cell receptors (TCRs) repertoire was revolutionized by next-generation sequencing technologies; however, standardization using biological controls to facilitate precision of current alignment and assembly tools remains a challenge. Additionally, availability of TCR libraries for off-the-shelf cloning and engineering TCR-specific T cells is a valuable resource for TCR-based immunotherapies. We established nine human TCR α and β clones that were evaluated using the 5'-rapid amplification of cDNA ends-like RNA-based TCR sequencing on the Illumina platform. TCR sequences were extracted and aligned using MiXCR, TRUST4, and CATT to validate their sensitivity and specificity and to validate library preparation methods. The correlation between actual and expected TCR ratios within libraries confirmed accuracy of the approach. Our findings established the development of biological standards and library of TCR clones to be leveraged in TCR sequencing and engineering. The remaining human TCR clones' libraries for a more diverse biological control will be generated.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae064"},"PeriodicalIF":2.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11540440/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142591834","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

Graph neural networks are promising for phenotypic virtual screening on cancer cell lines. 图神经网络有望用于癌症细胞系的表型虚拟筛选。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-09-03 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae065

Sachin Vishwakarma, Saiveth Hernandez-Hernandez, Pedro J Ballester

{"title":"Graph neural networks are promising for phenotypic virtual screening on cancer cell lines.","authors":"Sachin Vishwakarma, Saiveth Hernandez-Hernandez, Pedro J Ballester","doi":"10.1093/biomethods/bpae065","DOIUrl":"10.1093/biomethods/bpae065","url":null,"abstract":"Artificial intelligence is increasingly driving early drug design, offering novel approaches to virtual screening. Phenotypic virtual screening (PVS) aims to predict how cancer cell lines respond to different compounds by focusing on observable characteristics rather than specific molecular targets. Some studies have suggested that deep learning may not be the best approach for PVS. However, these studies are limited by the small number of tested molecules as well as not employing suitable performance metrics and dissimilar-molecules splits better mimicking the challenging chemical diversity of real-world screening libraries. Here we prepared 60 datasets, each containing approximately 30 000-50 000 molecules tested for their growth inhibitory activities on one of the NCI-60 cancer cell lines. We conducted multiple performance evaluations of each of the five machine learning algorithms for PVS on these 60 problem instances. To provide even a more comprehensive evaluation, we used two model validation types: the random split and the dissimilar-molecules split. Overall, about 14 440 training runs aczross datasets were carried out per algorithm. The models were primarily evaluated using hit rate, a more suitable metric in VS contexts. The results show that all models are more challenged by test molecules that are substantially different from those in the training data. In both validation types, the D-MPNN algorithm, a graph-based deep neural network, was found to be the most suitable for building predictive models for this PVS problem.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae065"},"PeriodicalIF":2.5,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11537795/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584500","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

Deep learning image analysis for filamentous fungi taxonomic classification: Dealing with small datasets with class imbalance and hierarchical grouping. 用于丝状真菌分类的深度学习图像分析：处理具有类不平衡和分层分组的小型数据集。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-08-27 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae063

Stefan Stiller, Juan F Dueñas, Stefan Hempel, Matthias C Rillig, Masahiro Ryo

{"title":"Deep learning image analysis for filamentous fungi taxonomic classification: Dealing with small datasets with class imbalance and hierarchical grouping.","authors":"Stefan Stiller, Juan F Dueñas, Stefan Hempel, Matthias C Rillig, Masahiro Ryo","doi":"10.1093/biomethods/bpae063","DOIUrl":"https://doi.org/10.1093/biomethods/bpae063","url":null,"abstract":"Deep learning applications in taxonomic classification for animals and plants from images have become popular, while those for microorganisms are still lagging behind. Our study investigated the potential of deep learning for the taxonomic classification of hundreds of filamentous fungi from colony images, which is typically a task that requires specialized knowledge. We isolated soil fungi, annotated their taxonomy using standard molecular barcode techniques, and took images of the fungal colonies grown in petri dishes (n = 606). We applied a convolutional neural network with multiple training approaches and model architectures to deal with some common issues in ecological datasets: small amounts of data, class imbalance, and hierarchically structured grouping. Model performance was overall low, mainly due to the relatively small dataset, class imbalance, and the high morphological plasticity exhibited by fungal colonies. However, our approach indicates that morphological features like color, patchiness, and colony extension rate could be used for the recognition of fungal colonies at higher taxonomic ranks (i.e. phylum, class, and order). Model explanation implies that image recognition characters appear at different positions within the colony (e.g. outer or inner hyphae) depending on the taxonomic resolution. Our study suggests the potential of deep learning applications for a better understanding of the taxonomy and ecology of filamentous fungi amenable to axenic culturing. Meanwhile, our study also highlights some technical challenges in deep learning image analysis in ecology, highlighting that the domain of applicability of these methods needs to be carefully considered.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae063"},"PeriodicalIF":2.5,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11387011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142297454","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

DLKcat cannot predict meaningful k _cat values for mutants and unfamiliar enzymes. DLKcat 无法预测突变体和陌生酶的 k cat 值。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-08-24 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae061

Alexander Kroll, Martin J Lercher

引用次数: 0

Advanced image generation for cancer using diffusion models. 利用扩散模型生成先进的癌症图像。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-08-23 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae062

Benjamin L Kidder

{"title":"Advanced image generation for cancer using diffusion models.","authors":"Benjamin L Kidder","doi":"10.1093/biomethods/bpae062","DOIUrl":"https://doi.org/10.1093/biomethods/bpae062","url":null,"abstract":"Deep neural networks have significantly advanced the field of medical image analysis, yet their full potential is often limited by relatively small dataset sizes. Generative modeling, particularly through diffusion models, has unlocked remarkable capabilities in synthesizing photorealistic images, thereby broadening the scope of their application in medical imaging. This study specifically investigates the use of diffusion models to generate high-quality brain MRI scans, including those depicting low-grade gliomas, as well as contrast-enhanced spectral mammography (CESM) and chest and lung X-ray images. By leveraging the DreamBooth platform, we have successfully trained stable diffusion models utilizing text prompts alongside class and instance images to generate diverse medical images. This approach not only preserves patient anonymity but also substantially mitigates the risk of patient re-identification during data exchange for research purposes. To evaluate the quality of our synthesized images, we used the Fréchet inception distance metric, demonstrating high fidelity between the synthesized and real images. Our application of diffusion models effectively captures oncology-specific attributes across different imaging modalities, establishing a robust framework that integrates artificial intelligence in the generation of oncological medical imagery.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae062"},"PeriodicalIF":2.5,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11387006/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142297452","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

Methods in cancer research: Assessing therapy response of spheroid cultures by life cell imaging using a cost-effective live-dead staining protocol. 癌症研究方法：利用具有成本效益的活死细胞染色方案，通过生命细胞成像评估球形培养物的治疗反应。

IF 2.5

Biology Methods and Protocols Pub Date : 2024-08-22 eCollection Date: 2024-01-01 DOI: 10.1093/biomethods/bpae060

Jaison Phour, Erik Vassella

{"title":"Methods in cancer research: Assessing therapy response of spheroid cultures by life cell imaging using a cost-effective live-dead staining protocol.","authors":"Jaison Phour, Erik Vassella","doi":"10.1093/biomethods/bpae060","DOIUrl":"10.1093/biomethods/bpae060","url":null,"abstract":"Spheroid cultures of cancer cell lines or primary cells represent a more clinically relevant model for predicting therapy response compared to two-dimensional cell culture. However, current live-dead staining protocols used for treatment response in spheroid cultures are often expensive, toxic to the cells, or limited in their ability to monitor therapy response over an extended period due to reduced stability. In our study, we have developed a cost-effective method utilizing calcein-AM and Helix NP™ Blue for live-dead staining, enabling the monitoring of therapy response of spheroid cultures for up to 10 days. Additionally, we used ICY BioImage Analysis and Z-stacks projection to calculate viability, which is a more accurate method for assessing treatment response compared to traditional methods on spheroid size. Using the example of glioblastoma cell lines and primary glioblastoma cells, we show that spheroid cultures typically exhibit a green outer layer of viable cells, a turquoise mantle of hypoxic quiescent cells, and a blue core of necrotic cells when visualized using confocal microscopy. Upon treatment of spheroids with the alkylating agent temozolomide, we observed a reduction in the viability of glioblastoma cells after an incubation period of 7 days. This method can also be adapted for monitoring therapy response in different cancer systems, offering a versatile and cost-effective approach for assessing therapy efficacy in three-dimensional culture models.","PeriodicalId":36528,"journal":{"name":"Biology Methods and Protocols","volume":"9 1","pages":"bpae060"},"PeriodicalIF":2.5,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11374025/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142134110","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