Pub Date : 2024-10-29DOI: 10.1016/j.slast.2024.100213
Yuan Zheng , Xiaoxiao Ren , Linzhen Li
In order to understand the application of conjugated polymer nanocomposites as biosensors in the rehabilitation of ankle joint injuries in martial arts, the author proposes a study on the application of conjugated polymer nanocomposites in the rehabilitation of ankle joint injuries in martial arts. Firstly, in martial arts training, the incidence of ankle joint injuries is relatively high. In order to prevent and reduce ankle joint injuries, high-intensity martial arts training should be used to evaluate the degree of ankle joint injuries in a timely manner using an ankle joint injury assessment model. Secondly, a Firefly algorithm based modeling method for the evaluation of ankle injury in high-intensity martial arts training is proposed. Finally, 180 questionnaires were distributed and 150 were collected. Three incomplete questions were removed, resulting in 130 valid questions with a yield of 90. The firefly algorithm has been used to assess ankle injuries and to characterize different types of combat shooting in high-intensity exercise competitions. received ankle injury index assessment combat performance. A chaotic sequence is used to fire and established a standard measurement of effort for combat ankle injuries. The proposed solution has been scientifically proven to improve basketball performance levels.
{"title":"Application of conjugated polymer nanocomposite materials as biosensors in rehabilitation of ankle joint injuries in martial arts sports","authors":"Yuan Zheng , Xiaoxiao Ren , Linzhen Li","doi":"10.1016/j.slast.2024.100213","DOIUrl":"10.1016/j.slast.2024.100213","url":null,"abstract":"<div><div>In order to understand the application of conjugated polymer nanocomposites as biosensors in the rehabilitation of ankle joint injuries in martial arts, the author proposes a study on the application of conjugated polymer nanocomposites in the rehabilitation of ankle joint injuries in martial arts. Firstly, in martial arts training, the incidence of ankle joint injuries is relatively high. In order to prevent and reduce ankle joint injuries, high-intensity martial arts training should be used to evaluate the degree of ankle joint injuries in a timely manner using an ankle joint injury assessment model. Secondly, a Firefly algorithm based modeling method for the evaluation of ankle injury in high-intensity martial arts training is proposed. Finally, 180 questionnaires were distributed and 150 were collected. Three incomplete questions were removed, resulting in 130 valid questions with a yield of 90. The firefly algorithm has been used to assess ankle injuries and to characterize different types of combat shooting in high-intensity exercise competitions. received ankle injury index assessment combat performance. A chaotic sequence is used to fire and established a standard measurement of effort for combat ankle injuries. The proposed solution has been scientifically proven to improve basketball performance levels.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100213"},"PeriodicalIF":2.5,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1016/j.slast.2024.100210
Quanhong Ping , Qi Chen , Na Li
Background
N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) play a crucial role in the cancer progression and immunotherapeutic efficacy. The potential function of m6A-related lncRNAs signature in cervical cancer has not been systematically clarified.
Methods
RNA-seq and the clinical data of cervical cancer were extracted from The Cancer Genome Atlas. All of the patients were randomly classified into training and testing cohorts. The m6A-related lncRNAs prognostic model was constructed by LASSO regression using data in the training cohort.The predictive value of the signature was validated in the whole cohort and testing cohort. Cervical cancer patients were divided into low- and high-risk subgroups by the median value of risk scores. Kaplan-Meier analysis, principal-component analysis (PCA), functional enrichment annotation, and nomogram were used for further evaluation. We also examined the immune response and potential drug sensitivity targeting this model.
Results
Seventy-nine prognostic m6A-related lncRNAs were screened. The risk model comprising four m6A-related lncRNAs (AL139035.1, AC015922.2, AC073529.1, AC008124.1) was identified and verified as an independent prognostic predictor of cervical cancer. A nomogram based on age, tumor grade, clinical stage, TNM stage, and four m6A-related lncRNAs risk signatures was generated. It displayed good accuracy and reliability in predicting the overall survival of patients with CC. Based on our risk model, cervical cancer patients with potential immunotherapy benefits from the candidate drugs could be effectively screened.
Conclusion
The four m6A-related lncRNAs signature may provide new targets and allow the prediction of immunotherapy response, which can assist developing individualized treatment for cervical cancer.
背景N6-甲基腺苷酸相关长非编码RNA（m6A相关lncRNAs）在癌症进展和免疫治疗效果中起着至关重要的作用。方法从癌症基因组图谱（The Cancer Genome Atlas）中提取宫颈癌的RNA-seq和临床数据。所有患者被随机分为训练组和测试组。利用训练队列中的数据，通过LASSO回归法构建了m6A相关lncRNAs预后模型，并在整个队列和测试队列中验证了该特征的预测价值。根据风险评分的中位值将宫颈癌患者分为低风险亚组和高风险亚组。卡普兰-梅耶分析、主成分分析（PCA）、功能富集注释和提名图被用于进一步评估。我们还研究了针对该模型的免疫反应和潜在的药物敏感性。由四个m6A相关lncRNA（AL139035.1、AC015922.2、AC073529.1、AC008124.1）组成的风险模型被鉴定并验证为宫颈癌的独立预后预测因子。根据年龄、肿瘤分级、临床分期、TNM 分期和四个与 m6A 相关的 lncRNAs 风险特征生成了一个提名图。它在预测宫颈癌患者的总生存率方面显示出良好的准确性和可靠性。结论 四种m6A相关lncRNAs风险特征可提供新的靶点，并可预测免疫治疗反应，有助于开发宫颈癌的个体化治疗。
{"title":"Identification of m6A-related lncRNAs prognostic signature for predicting immunotherapy response in cervical cancer","authors":"Quanhong Ping , Qi Chen , Na Li","doi":"10.1016/j.slast.2024.100210","DOIUrl":"10.1016/j.slast.2024.100210","url":null,"abstract":"<div><h3>Background</h3><div><em>N</em>6-methylandenosine-related long non-coding RNAs (m<sup>6</sup>A-related lncRNAs) play a crucial role in the cancer progression and immunotherapeutic efficacy. The potential function of m<sup>6</sup>A-related lncRNAs signature in cervical cancer has not been systematically clarified.</div></div><div><h3>Methods</h3><div>RNA-seq and the clinical data of cervical cancer were extracted from The Cancer Genome Atlas. All of the patients were randomly classified into training and testing cohorts. The m<sup>6</sup>A-related lncRNAs prognostic model was constructed by LASSO regression using data in the training cohort.The predictive value of the signature was validated in the whole cohort and testing cohort. Cervical cancer patients were divided into low- and high-risk subgroups by the median value of risk scores. Kaplan-Meier analysis, principal-component analysis (PCA), functional enrichment annotation, and nomogram were used for further evaluation. We also examined the immune response and potential drug sensitivity targeting this model.</div></div><div><h3>Results</h3><div>Seventy-nine prognostic m<sup>6</sup>A-related lncRNAs were screened. The risk model comprising four m<sup>6</sup>A-related lncRNAs (AL139035.1, AC015922.2, AC073529.1, AC008124.1) was identified and verified as an independent prognostic predictor of cervical cancer. A nomogram based on age, tumor grade, clinical stage, TNM stage, and four m<sup>6</sup>A-related lncRNAs risk signatures was generated. It displayed good accuracy and reliability in predicting the overall survival of patients with CC. Based on our risk model, cervical cancer patients with potential immunotherapy benefits from the candidate drugs could be effectively screened.</div></div><div><h3>Conclusion</h3><div>The four m<sup>6</sup>A-related lncRNAs signature may provide new targets and allow the prediction of immunotherapy response, which can assist developing individualized treatment for cervical cancer.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100210"},"PeriodicalIF":2.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.slast.2024.100212
Hong Cheng , Jing Wang , Yingjie Zhao , Xiaoli Hou , Fang Ling , Yixia Wang , Yasen Cao
Background
Heat shock proteins (HSPs) play a critical role in cellular stress responses and have been implicated in numerous diseases, including Parkinson's disease (PD) and various cancers. Understanding the differential expression and functional implications of HSPs in these conditions is crucial for identifying potential therapeutic targets and biomarkers for diagnosis and prognosis.
Methods
We utilized combined datasets (GSE6613 and GSE72267) to identify and analyze the heat shock-related genes differentially expressed in PD. Gene Set Variation Analysis (GSVA) was performed to explore functional profiles, while LASSO regression was employed to screen potential PD biomarkers. In glioma, prognostic value, immune infiltration, and pathway enrichment associated with HSPA1L gene expression were assessed via Kaplan-Meier plots, ssGSEA, and enrichment analyses.
Results
In PD, we identified 17 differentially expressed HSPs. Enrichment analysis revealed significant pathways related to protein homeostasis and cellular stress responses. LASSO regression pinpointed 12 genes, including HSPA1L, as significant markers for PD, with nomogram and calibration plots indicating predictive accuracy. Stratification based on HSPA1L expression in PD highlighted differentially active biological processes, immune responses, and metabolic disruptions. In the pan-cancer analysis, HSPA1L showed variable expression across cancer types and a significant correlation with patient survival and immune infiltration. In glioma, low HSPA1L expression was associated with worse overall survival, distinct immune infiltration patterns, and altered pathway activities.
Conclusion
This integrative study reveals the substantial role of HSPs, especially HSPA1L, in the pathogenesis and prognosis of PD and glioma. Our findings offer new perspectives on the molecular mechanisms underlying these diseases and propose HSPA1L as a potential prognostic biomarker and a target for therapeutic intervention.
{"title":"Deciphering the role of heat shock protein HSPA1L: biomarker discovery and prognostic insights in Parkinson's disease and glioma","authors":"Hong Cheng , Jing Wang , Yingjie Zhao , Xiaoli Hou , Fang Ling , Yixia Wang , Yasen Cao","doi":"10.1016/j.slast.2024.100212","DOIUrl":"10.1016/j.slast.2024.100212","url":null,"abstract":"<div><h3>Background</h3><div>Heat shock proteins (HSPs) play a critical role in cellular stress responses and have been implicated in numerous diseases, including Parkinson's disease (PD) and various cancers. Understanding the differential expression and functional implications of HSPs in these conditions is crucial for identifying potential therapeutic targets and biomarkers for diagnosis and prognosis.</div></div><div><h3>Methods</h3><div>We utilized combined datasets (GSE6613 and GSE72267) to identify and analyze the heat shock-related genes differentially expressed in PD. Gene Set Variation Analysis (GSVA) was performed to explore functional profiles, while LASSO regression was employed to screen potential PD biomarkers. In glioma, prognostic value, immune infiltration, and pathway enrichment associated with HSPA1L gene expression were assessed via Kaplan-Meier plots, ssGSEA, and enrichment analyses.</div></div><div><h3>Results</h3><div>In PD, we identified 17 differentially expressed HSPs. Enrichment analysis revealed significant pathways related to protein homeostasis and cellular stress responses. LASSO regression pinpointed 12 genes, including HSPA1L, as significant markers for PD, with nomogram and calibration plots indicating predictive accuracy. Stratification based on HSPA1L expression in PD highlighted differentially active biological processes, immune responses, and metabolic disruptions. In the pan-cancer analysis, HSPA1L showed variable expression across cancer types and a significant correlation with patient survival and immune infiltration. In glioma, low HSPA1L expression was associated with worse overall survival, distinct immune infiltration patterns, and altered pathway activities.</div></div><div><h3>Conclusion</h3><div>This integrative study reveals the substantial role of HSPs, especially HSPA1L, in the pathogenesis and prognosis of PD and glioma. Our findings offer new perspectives on the molecular mechanisms underlying these diseases and propose HSPA1L as a potential prognostic biomarker and a target for therapeutic intervention.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100212"},"PeriodicalIF":2.5,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, there has been an increasing demand for the detection of rare cells in drug discovery research, such as cells that have differentiated off-purpose or are required for immunogenicity evaluation. Since detection and quantification limits depend on the robustness of the experiment, inter-human differences in technique have a significant impact on the performance of the assay system. Here, we integrated flow cytometry into a cell experiment platform, Screening Station, to construct a robust assay system, examined each step of the flow cytometric pretreatment using Jurkat cells, and finally evaluated the overall assay performance. Cell detection rate when the experiment was performed manually was 48.8 % ± 5.7 % (CV=11.6 %) versus 73.7 %±2.0 % (CV=2.8 %) with the automated method. To further clarify the analytical performance of the automated method, 1–100 PD-1 expressing Jurkat cells were spiked with 1 × 105 Jurkat cells, and the lower limit of detection, linearity, and CV% were evaluated. Average detection rate was 69 %, decision count was 0.985, and lower limit of detection was 4 cells (0.004 %). We evaluated the CV% value of the number of detected cells per spiked cell and found our system to be highly robust, approximating a binomial distribution with a 69 % recovery rate. In conclusion, we have integrated the Novocyte flow cytometry system into an automated experimental platform, Screening Station, to create a fully automated flow cytometric assay system with high robustness. Our platform can fulfill the technology needs of drug discovery for rare cell detection, which have intensified in recent years.
{"title":"Integration of a fully automated flow cytometry system with high robustness into a Screening Station","authors":"Shingo Fujiyama , Hidemitsu Asano , Ichiji Namatame","doi":"10.1016/j.slast.2024.100215","DOIUrl":"10.1016/j.slast.2024.100215","url":null,"abstract":"<div><div>In recent years, there has been an increasing demand for the detection of rare cells in drug discovery research, such as cells that have differentiated off-purpose or are required for immunogenicity evaluation. Since detection and quantification limits depend on the robustness of the experiment, inter-human differences in technique have a significant impact on the performance of the assay system. Here, we integrated flow cytometry into a cell experiment platform, Screening Station, to construct a robust assay system, examined each step of the flow cytometric pretreatment using Jurkat cells, and finally evaluated the overall assay performance. Cell detection rate when the experiment was performed manually was 48.8 % ± 5.7 % (CV=11.6 %) versus 73.7 %±2.0 % (CV=2.8 %) with the automated method. To further clarify the analytical performance of the automated method, 1–100 PD-1 expressing Jurkat cells were spiked with 1 × 10<sup>5</sup> Jurkat cells, and the lower limit of detection, linearity, and CV% were evaluated. Average detection rate was 69 %, decision count was 0.985, and lower limit of detection was 4 cells (0.004 %). We evaluated the CV% value of the number of detected cells per spiked cell and found our system to be highly robust, approximating a binomial distribution with a 69 % recovery rate. In conclusion, we have integrated the Novocyte flow cytometry system into an automated experimental platform, Screening Station, to create a fully automated flow cytometric assay system with high robustness. Our platform can fulfill the technology needs of drug discovery for rare cell detection, which have intensified in recent years.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100215"},"PeriodicalIF":2.5,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.slast.2024.100216
Markus Stoeckli , Han Wang , Dieter Staab , Frederic Grandjean , Fabian Sesterhenn , Christian Opitz
Tracking chemical reactions by measuring incurred mass shifts upon successful binding is a direct and attractive alternative to existing assays based on chemical tags. Traditional methods use liquid chromatography-mass spectrometry (LC-MS), and because the required buffers are not amenable to direct MS injection, sample pre-treatment is needed to desalt. This leads to analysis times from ten seconds to minutes per sample, limiting throughput and preventing widespread application.
Combining an acoustic ejection (AE) interface with a time-of-flight mass spectrometer (MS) removes this bottleneck, as samples can be directly introduced at rates of up to one second per sample. This article describes a complete workflow for measuring the covalent binding of compounds to proteins in real-time, from assay to data evaluation. It is noteworthy that this is the first instance of using SCIEX Echo® MS+ system with ZenoTOF 7600 system to study the kinetic regimes of covalent binding.
{"title":"Accelerating covalent binding studies: Direct mass shift measurement with acoustic ejection and TOF-MS","authors":"Markus Stoeckli , Han Wang , Dieter Staab , Frederic Grandjean , Fabian Sesterhenn , Christian Opitz","doi":"10.1016/j.slast.2024.100216","DOIUrl":"10.1016/j.slast.2024.100216","url":null,"abstract":"<div><div>Tracking chemical reactions by measuring incurred mass shifts upon successful binding is a direct and attractive alternative to existing assays based on chemical tags. Traditional methods use liquid chromatography-mass spectrometry (LC-MS), and because the required buffers are not amenable to direct MS injection, sample pre-treatment is needed to desalt. This leads to analysis times from ten seconds to minutes per sample, limiting throughput and preventing widespread application.</div><div>Combining an acoustic ejection (AE) interface with a time-of-flight mass spectrometer (MS) removes this bottleneck, as samples can be directly introduced at rates of up to one second per sample. This article describes a complete workflow for measuring the covalent binding of compounds to proteins in real-time, from assay to data evaluation. It is noteworthy that this is the first instance of using SCIEX Echo® MS+ system with ZenoTOF 7600 system to study the kinetic regimes of covalent binding.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100216"},"PeriodicalIF":2.5,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.slast.2024.100199
Nate Hoxie , David R. Calabrese , Zina Itkin , Glenn Gomba , Min Shen , Meghav Verma , John S. Janiszewski , Jonathan H. Shrimp , Kelli M. Wilson , Sam Michael , Matthew D. Hall , Lyle Burton , Tom Covey , Chang Liu
An approach is described for high-throughput quality assessment of drug candidate libraries using high-resolution acoustic ejection mass spectrometry (AEMS). Sample introduction from 1536-well plates is demonstrated for this application using 2.5 nL acoustically dispensed sample droplets into an Open Port Interface (OPI) with pneumatically assisted electrospray ionization at a rate of one second per sample. Both positive and negative ionization are shown to be essential to extend the compound coverage of this protease inhibitor-focused library. Specialized software for efficiently interpreting this data in 1536-well format is presented. A new high-throughput method for quantifying the concentration of the components (HTQuant) is proposed that neither requires adding an internal standard to each well nor further encumbers the high-throughput workflow. This approach for quantitation requires highly reproducible peak areas, which is shown to be consistent within 4.4 % CV for a 1536-well plate analysis. An approach for troubleshooting the workflow based on the background ion current signal is also presented. The AEMS data is compared to the industry standard LC/PDA/ELSD/MS approach and shows similar coverage but at 180-fold greater throughput. Despite the same ionization process, both methods confirmed the presence of a small percentage of compounds in wells that the other did not. The data for this relatively small, focused library is compared to a larger, more chemically diverse library to indicate that this approach can be more generally applied beyond this single case study. This capability is particularly timely considering the growing implementation of artificial intelligence strategies that require the input of large amounts of high-quality data to formulate predictions relevant to the drug discovery process. The molecular structures of the 872-compound library analyzed here are included to begin the process of correlating molecular structures with ionization efficiency and other parameters as an initial step in this direction.
{"title":"High-resolution acoustic ejection mass spectrometry for high-throughput library screening","authors":"Nate Hoxie , David R. Calabrese , Zina Itkin , Glenn Gomba , Min Shen , Meghav Verma , John S. Janiszewski , Jonathan H. Shrimp , Kelli M. Wilson , Sam Michael , Matthew D. Hall , Lyle Burton , Tom Covey , Chang Liu","doi":"10.1016/j.slast.2024.100199","DOIUrl":"10.1016/j.slast.2024.100199","url":null,"abstract":"<div><div>An approach is described for high-throughput quality assessment of drug candidate libraries using high-resolution acoustic ejection mass spectrometry (AEMS). Sample introduction from 1536-well plates is demonstrated for this application using 2.5 nL acoustically dispensed sample droplets into an Open Port Interface (OPI) with pneumatically assisted electrospray ionization at a rate of one second per sample. Both positive and negative ionization are shown to be essential to extend the compound coverage of this protease inhibitor-focused library. Specialized software for efficiently interpreting this data in 1536-well format is presented. A new high-throughput method for quantifying the concentration of the components (HTQuant) is proposed that neither requires adding an internal standard to each well nor further encumbers the high-throughput workflow. This approach for quantitation requires highly reproducible peak areas, which is shown to be consistent within 4.4 % CV for a 1536-well plate analysis. An approach for troubleshooting the workflow based on the background ion current signal is also presented. The AEMS data is compared to the industry standard LC/PDA/ELSD/MS approach and shows similar coverage but at 180-fold greater throughput. Despite the same ionization process, both methods confirmed the presence of a small percentage of compounds in wells that the other did not. The data for this relatively small, focused library is compared to a larger, more chemically diverse library to indicate that this approach can be more generally applied beyond this single case study. This capability is particularly timely considering the growing implementation of artificial intelligence strategies that require the input of large amounts of high-quality data to formulate predictions relevant to the drug discovery process. The molecular structures of the 872-compound library analyzed here are included to begin the process of correlating molecular structures with ionization efficiency and other parameters as an initial step in this direction.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100199"},"PeriodicalIF":2.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1016/j.slast.2024.100203
Sarah A. Alzakari , Asma Aldrees , Muhammad Umer , Lucia Cascone , Nisreen Innab , Imran Ashraf
Predictive modeling is becoming increasingly popular in the context of early disease detection. The use of machine learning approaches for predictive modeling can help early detection of diseases thereby enabling medical experts to appropriate medical treatments. Stillbirth prediction is a similar domain where artificial intelligence-based predictive modeling can alleviate this significant global health challenge. Despite advancements in prenatal care, the prevention of stillbirths remains a complex issue requiring further research and interventions. The cardiotocography (CTG) dataset is used in this research work from the UCI machine learning (ML) repository to investigate the efficiency of the proposed approach regarding stillbirth prediction. This research work adopts the Tabular Prior Data Fitted Network (TabPFN) model which was originally designed to solve small tabular classification. TabPFN is used to predict the still or live birth during pregnancy with 97.91% accuracy. To address this life-saving problem with more accurate results and in-depth analysis of ML models, this research work makes use of 13 renowned ML models for performance comparison with the proposed model. The proposed model is evaluated using precision, recall, F-score, Mathews Correlation Coefficient (MCC), and the area under the curve evaluation parameters and the results are 97.87%, 98.26%, 98.05%, 96.42%, and 98.88%, respectively. The results of the proposed model are further evaluated using k-fold cross-validation and its performance comparison with other state-of-the-art studies indicating the superior performance of TabPFN model.
在早期疾病检测方面，预测建模正变得越来越流行。使用机器学习方法进行预测建模有助于疾病的早期检测，从而使医学专家能够采取适当的医疗措施。死胎预测也是一个类似的领域，基于人工智能的预测建模可以缓解这一重大的全球健康挑战。尽管产前保健取得了进步，但死胎的预防仍然是一个复杂的问题，需要进一步的研究和干预。本研究工作使用了 UCI 机器学习（ML）资源库中的心脏排卵图（CTG）数据集，以研究拟议方法在死胎预测方面的效率。这项研究工作采用了表格先验数据拟合网络（TabPFN）模型，该模型最初是为解决小表分类问题而设计的。TabPFN 用于预测孕期的死产或活产，准确率高达 97.91%。为了以更准确的结果和对 ML 模型的深入分析来解决这一挽救生命的问题，这项研究工作使用了 13 种著名的 ML 模型与所提出的模型进行性能比较。使用精确度、召回率、F-分数、马修斯相关系数（MCC）和曲线下面积等评价参数对提出的模型进行了评估，结果分别为 97.87%、98.26%、98.05%、96.42% 和 98.88%。使用 k 倍交叉验证对所提模型的结果进行了进一步评估，并将其性能与其他最先进的研究结果进行了比较，结果表明 TabPFN 模型性能优越。
{"title":"Artificial intelligence-driven predictive framework for early detection of still birth","authors":"Sarah A. Alzakari , Asma Aldrees , Muhammad Umer , Lucia Cascone , Nisreen Innab , Imran Ashraf","doi":"10.1016/j.slast.2024.100203","DOIUrl":"10.1016/j.slast.2024.100203","url":null,"abstract":"<div><div>Predictive modeling is becoming increasingly popular in the context of early disease detection. The use of machine learning approaches for predictive modeling can help early detection of diseases thereby enabling medical experts to appropriate medical treatments. Stillbirth prediction is a similar domain where artificial intelligence-based predictive modeling can alleviate this significant global health challenge. Despite advancements in prenatal care, the prevention of stillbirths remains a complex issue requiring further research and interventions. The cardiotocography (CTG) dataset is used in this research work from the UCI machine learning (ML) repository to investigate the efficiency of the proposed approach regarding stillbirth prediction. This research work adopts the Tabular Prior Data Fitted Network (TabPFN) model which was originally designed to solve small tabular classification. TabPFN is used to predict the still or live birth during pregnancy with 97.91% accuracy. To address this life-saving problem with more accurate results and in-depth analysis of ML models, this research work makes use of 13 renowned ML models for performance comparison with the proposed model. The proposed model is evaluated using precision, recall, F-score, Mathews Correlation Coefficient (MCC), and the area under the curve evaluation parameters and the results are 97.87%, 98.26%, 98.05%, 96.42%, and 98.88%, respectively. The results of the proposed model are further evaluated using k-fold cross-validation and its performance comparison with other state-of-the-art studies indicating the superior performance of TabPFN model.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100203"},"PeriodicalIF":2.5,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Transverse sinus asymmetry refers to the inconsistencies in the shape structure, size or blood flow of the intracranial transverse sinus. Intraocular pressure difference refers to the obvious difference in intraocular pressure between the two eyes. Transversal sinus asymmetry may be correlated with intraocular pressure difference, but the mechanism of correlation is still unclear. To investigate the relationship between transverse sinus asymmetry and IOP differences based on MRV examination, and to explore the possible mechanism. Patients with transverse sinus asymmetry were selected and examined using the MRV technique. At the same time, the patients' IOP was measured using standard methods of IOP measurement. Correlation analysis and statistical methods were used to evaluate the association between transverse sinus asymmetry and IOP differences. There was a statistically significant distinction observed between groups I and V (Z = 6.78, P < 0.01). Significant variations were also noted in the intraocular pressures across all groups, encompassing the average measurements of the right eye and left eye, along with the variance between the two (right eye: F = 15.43, P < 0.01; left eye: F = 4.62, P = 0.002; variance between eyes: F = 41.79, P < 0.01). The asymmetry of the transverse sinus exhibited a negative relationship with the intraocular pressure of the right eye (r = 0.51, P < 0.01) and the difference between the pressures of the two eyes (r = 0.79, P < 0.01); no significant association was found between the asymmetry and the left eye's intraocular pressure. In conclusion, a certain correlation exists between the intraocular pressures of the left and right eyes and the morphology of the transverse sinus. When the transverse sinus is thicker on one side, the corresponding drainage veins are thicker, resulting in lower intraocular pressure on that same side.
{"title":"Relationship between asymmetry of transverse sinus and difference in intraocular pressure Based on MRV imaging examination","authors":"Dan Zhu , Weiguang Zhang , Dongtai Zhang , Dong Qiu , Zhenyang Yu , Yiwen Jiang","doi":"10.1016/j.slast.2024.100202","DOIUrl":"10.1016/j.slast.2024.100202","url":null,"abstract":"<div><div>Transverse sinus asymmetry refers to the inconsistencies in the shape structure, size or blood flow of the intracranial transverse sinus. Intraocular pressure difference refers to the obvious difference in intraocular pressure between the two eyes. Transversal sinus asymmetry may be correlated with intraocular pressure difference, but the mechanism of correlation is still unclear. To investigate the relationship between transverse sinus asymmetry and IOP differences based on MRV examination, and to explore the possible mechanism. Patients with transverse sinus asymmetry were selected and examined using the MRV technique. At the same time, the patients' IOP was measured using standard methods of IOP measurement. Correlation analysis and statistical methods were used to evaluate the association between transverse sinus asymmetry and IOP differences. There was a statistically significant distinction observed between groups I and V (<em>Z</em> = 6.78, <em>P</em> < 0.01). Significant variations were also noted in the intraocular pressures across all groups, encompassing the average measurements of the right eye and left eye, along with the variance between the two (right eye: <em>F</em> = 15.43, <em>P</em> < 0.01; left eye: <em>F</em> = 4.62, <em>P</em> = 0.002; variance between eyes: <em>F</em> = 41.79, <em>P</em> < 0.01). The asymmetry of the transverse sinus exhibited a negative relationship with the intraocular pressure of the right eye (<em>r</em> = 0.51, <em>P</em> < 0.01) and the difference between the pressures of the two eyes (<em>r</em> = 0.79, <em>P</em> < 0.01); no significant association was found between the asymmetry and the left eye's intraocular pressure. In conclusion, a certain correlation exists between the intraocular pressures of the left and right eyes and the morphology of the transverse sinus. When the transverse sinus is thicker on one side, the corresponding drainage veins are thicker, resulting in lower intraocular pressure on that same side.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100202"},"PeriodicalIF":2.5,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-12DOI: 10.1016/j.slast.2024.100201
Silvio Di Castro, Martin L. Svensson
In recent years, pharmaceutical research has increased its interest in novel drug modalities beyond small molecules to overcome therapeutic limitations and find more effective cures.
Compound Management teams globally are adapting their processes and equipment to handle such “new modalities” with the same quality and speed as small molecule research.
Here, we share our approach in supporting next-generation therapeutics by introducing solutions for multi-solvent workflows in Compound Management at AstraZeneca.
From sample submission to assay-ready plate generation, we describe the challenges faced and process improvements introduced so far.
Collaborating with our business partners, we are pioneering new best practices and laying solid foundations for future research to bring new efficacious drugs into the clinics.
{"title":"Challenges and opportunities of next generation therapeutics: A compound management perspective","authors":"Silvio Di Castro, Martin L. Svensson","doi":"10.1016/j.slast.2024.100201","DOIUrl":"10.1016/j.slast.2024.100201","url":null,"abstract":"<div><div>In recent years, pharmaceutical research has increased its interest in novel drug modalities beyond small molecules to overcome therapeutic limitations and find more effective cures.</div><div>Compound Management teams globally are adapting their processes and equipment to handle such “new modalities” with the same quality and speed as small molecule research.</div><div>Here, we share our approach in supporting next-generation therapeutics by introducing solutions for multi-solvent workflows in Compound Management at AstraZeneca.</div><div>From sample submission to assay-ready plate generation, we describe the challenges faced and process improvements introduced so far.</div><div>Collaborating with our business partners, we are pioneering new best practices and laying solid foundations for future research to bring new efficacious drugs into the clinics.</div></div>","PeriodicalId":54248,"journal":{"name":"SLAS Technology","volume":"29 6","pages":"Article 100201"},"PeriodicalIF":2.5,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142480665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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