Pub Date : 2024-08-03DOI: 10.1101/2024.07.31.24311304
Alexandre Matov
Methods for personalizing medical treatment are the focal point of contemporary biomedical research. In cancer care, we can analyze the effects of therapies at the level of individual cells. Quantitative characterization of treatment efficacy and evaluation of why some individuals respond to specific regimens, whereas others do not, requires additional approaches to genetic sequencing at single time points. Methods for the analysis of changes in phenotype, such as in vivo and ex vivo morphology and localization of cellular proteins and organelles can provide important insights into patient treatment options. Novel therapies are needed to extend survival in metastatic castration-resistant prostate cancer (mCRPC). Prostate-specific membrane antigen (PSMA), a cell surface glycoprotein that is commonly overexpressed by prostate cancer (PC) cells relative to normal prostate cells, provides a validated target. We developed a software for image analysis designed to identify PSMA expression on the surface of epithelial cells in order to extract prognostic metrics. In addition, our software can deliver predictive information and inform clinicians regarding the efficacy of PC therapy. We can envisage additional applications of our software system, beyond PC, as PSMA is expressed in a variety of tissues. Our method is based on image denoising, topologic partitioning, and edge detection. These three steps allow to segment the area of each PSMA spot in an image of a coverslip with epithelial cells. Our objective has been to present the community with an integrated, easy to use by all, tool for resolving the complex cytoskeletal organization and it is our goal to have such software system approved for use in the clinical practice.
个性化医疗方法是当代生物医学研究的焦点。在癌症治疗中，我们可以从单个细胞层面分析治疗效果。要定量分析治疗效果，评估为什么有些人对特定的治疗方案有反应，而另一些人则没有，这就需要在单个时间点进行基因测序的基础上采取更多的方法。分析表型变化的方法，如体内和体外形态学以及细胞蛋白质和细胞器的定位，可以为患者的治疗方案提供重要的见解。延长转移性耐受性前列腺癌（mCRPC）患者的生存期需要新的疗法。前列腺特异性膜抗原（PSMA）是一种细胞表面糖蛋白，与正常前列腺细胞相比，前列腺癌（PC）细胞通常过度表达这种糖蛋白。我们开发了一款图像分析软件，旨在识别上皮细胞表面的 PSMA 表达，从而提取预后指标。此外，我们的软件还能提供预测信息，让临床医生了解 PC 治疗的疗效。我们可以设想我们的软件系统在 PC 以外的其他应用，因为 PSMA 在多种组织中都有表达。我们的方法基于图像去噪、拓扑分割和边缘检测。通过这三个步骤，就能在带有上皮细胞的盖玻片图像中分割出每个 PSMA 点的区域。我们的目标是向社会提供一种易于使用的综合工具，用于解析复杂的细胞骨架组织，我们的目标是让这种软件系统获得批准，用于临床实践。
{"title":"Quantitative Microscopy in Medicine","authors":"Alexandre Matov","doi":"10.1101/2024.07.31.24311304","DOIUrl":"https://doi.org/10.1101/2024.07.31.24311304","url":null,"abstract":"Methods for personalizing medical treatment are the focal point of contemporary biomedical research. In cancer care, we can analyze the effects of therapies at the level of individual cells. Quantitative characterization of treatment efficacy and evaluation of why some individuals respond to specific regimens, whereas others do not, requires additional approaches to genetic sequencing at single time points. Methods for the analysis of changes in phenotype, such as in vivo and ex vivo morphology and localization of cellular proteins and organelles can provide important insights into patient treatment options. Novel therapies are needed to extend survival in metastatic castration-resistant prostate cancer (mCRPC). Prostate-specific membrane antigen (PSMA), a cell surface glycoprotein that is commonly overexpressed by prostate cancer (PC) cells relative to normal prostate cells, provides a validated target. We developed a software for image analysis designed to identify PSMA expression on the surface of epithelial cells in order to extract prognostic metrics. In addition, our software can deliver predictive information and inform clinicians regarding the efficacy of PC therapy. We can envisage additional applications of our software system, beyond PC, as PSMA is expressed in a variety of tissues. Our method is based on image denoising, topologic partitioning, and edge detection. These three steps allow to segment the area of each PSMA spot in an image of a coverslip with epithelial cells. Our objective has been to present the community with an integrated, easy to use by all, tool for resolving the complex cytoskeletal organization and it is our goal to have such software system approved for use in the clinical practice.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"164 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
"Molecular characterization of disease is essential for precision medicine due to novel predictive biomarkers. Multiple next-generation sequencing (NGS) platforms are available, but their expense and clinical utility vary. Even if a targetable mutation is detected, corresponding drugs may not be available or affordable. No prior studies in Pakistan have focused on integrating NGS results into patient care to assist with therapeutic decision-making and survival outcomes. This retrospective study aimed to evaluate the molecular profiling and therapeutic implications of NGS testing across solid tumors. It included all patients with histologically proven malignancy (metastatic or non-metastatic) who had NGS analysis at Aga Khan University Hospital (AKUH) from June 1, 2020, to June 1, 2023. Foundation One was the NGS platform used. From 2020 to 2023, 192 patients underwent NGS. The majority were male (55.2%) and aged over 50 years (71.9%). The most common indications for NGS were carcinoma of unknown primary (CUP) and lung cancers, representing 26% and 25% respectively, followed by colon (9%) and breast cancers (8%). Most patients had metastatic disease (98.4%). Common mutations in lung cancer were EGFR (16.3%) and KRAS G12C (14.3%). In unknown primary, breast, and colon cancers, the most common mutations were BRAF (8%), PIK3CA (18%), and KRAS (42.1%), respectively. Microsatellite instability (MSI) testing was performed in 95% of patients, with 6% being MSI high. Actionable alterations were detected in 31.8% of patients, but only 17.2% received genotype-matched treatment, mostly as a first-line treatment for lung cancer. The primary barriers were drug availability and affordability. Our results show that the implementation of NGS analysis supports clinical decision making. However, these results were applicable to a small percentage of patients. For better compliance and applicability, drug availability and cost of treatment needs to be addressed"
{"title":"\"PRESCRIBING PRACTICES AND CLINICAL IMPACT OF NEXT GENERATION SEQUENCING IN ROUTINE PRACTICE IN SOLID TUMORS REAL WORLD EXPERIENCE IN LMIC\"","authors":"Adeeba Zaki, Nida E Zehra Sameer, Aqsa Sohail, Zeeshan Ansar, Munira Moosajee","doi":"10.1101/2024.08.01.24311330","DOIUrl":"https://doi.org/10.1101/2024.08.01.24311330","url":null,"abstract":"\"Molecular characterization of disease is essential for precision medicine due to novel predictive biomarkers. Multiple next-generation sequencing (NGS) platforms are available, but their expense and clinical utility vary. Even if a targetable mutation is detected, corresponding drugs may not be available or affordable. No prior studies in Pakistan have focused on integrating NGS results into patient care to assist with therapeutic decision-making and survival outcomes.\u0000This retrospective study aimed to evaluate the molecular profiling and therapeutic implications of NGS testing across solid tumors. It included all patients with histologically proven malignancy (metastatic or non-metastatic) who had NGS analysis at Aga Khan University Hospital (AKUH) from June 1, 2020, to June 1, 2023. Foundation One was the NGS platform used. From 2020 to 2023, 192 patients underwent NGS. The majority were male (55.2%) and aged over 50 years (71.9%). The most common indications for NGS were carcinoma of unknown primary (CUP) and lung cancers, representing 26% and 25% respectively, followed by colon (9%) and breast cancers (8%). Most patients had metastatic disease (98.4%). Common mutations in lung cancer were EGFR (16.3%) and KRAS G12C (14.3%). In unknown primary, breast, and colon cancers, the most common mutations were BRAF (8%), PIK3CA (18%), and KRAS (42.1%), respectively. Microsatellite instability (MSI) testing was performed in 95% of patients, with 6% being MSI high. Actionable alterations were detected in 31.8% of patients, but only 17.2% received genotype-matched treatment, mostly as a first-line treatment for lung cancer. The primary barriers were drug availability and affordability.\u0000Our results show that the implementation of NGS analysis supports clinical decision making. However, these results were applicable to a small percentage of patients. For better compliance and applicability, drug availability and cost of treatment needs to be addressed\"","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"41 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-02DOI: 10.1101/2024.08.01.24311282
Manuel Pino-Gonzalez, Martin Lazaro-Quintela, Irene Alonso-Alvarez, Maria Gallardo-Gomez, Laura Juaneda-Magdalena, Alejandro Francisco-Fernandez, Silvia Calabuig-Farinas, Eloisa Jantus-Lewintre, Monica Martinez-Fernandez
Immunotherapy has opened new avenues of treatment for patients with advanced non-small cell lung cancer (NSCLC) without previous hope of survival. Unfortunately, only a small percentage of patients benefit from it, and it is still not well understood which tumor characteristics can be used to predict immunotherapy response. As the key cellular effectors of antitumor immunity, T cells are endowed with specialized T cell receptors (TCRs) to recognize and eliminate cancer cells. Here, we evaluated the potential of TCR repertoire as a predictive biomarker in patients treated with immunotherapy. With this aim, advanced NSCLC patients treated with immunotherapy at first-line were included. After obtaining peripheral blood and tissue samples at baseline, next-generation sequencing targeting TCRbeta/gamma was performed. Beyond TCR metrics, clonal space of the most frequent clones was determined. We found a positive association between uneven tumor-infiltrating TCRbeta repertoire and the immunotherapy response. Moreover, the use of various tumor-infiltrating and circulating TRBV/J genes predicted the immunotherapy response. Our results indicate the importance of evaluating tissue and circulating TCRbeta repertoire prior immunotherapy, showing it as a promising immunotherapy response biomarker in NSCLC patients.
{"title":"Tissue and Peripheral T-cell Repertoire Predicts Immunotherapy Response and Progression-Free Survival in NSCLC Patients.","authors":"Manuel Pino-Gonzalez, Martin Lazaro-Quintela, Irene Alonso-Alvarez, Maria Gallardo-Gomez, Laura Juaneda-Magdalena, Alejandro Francisco-Fernandez, Silvia Calabuig-Farinas, Eloisa Jantus-Lewintre, Monica Martinez-Fernandez","doi":"10.1101/2024.08.01.24311282","DOIUrl":"https://doi.org/10.1101/2024.08.01.24311282","url":null,"abstract":"Immunotherapy has opened new avenues of treatment for patients with advanced non-small cell lung cancer (NSCLC) without previous hope of survival. Unfortunately, only a small percentage of patients benefit from it, and it is still not well understood which tumor characteristics can be used to predict immunotherapy response. As the key cellular effectors of antitumor immunity, T cells are endowed with specialized T cell receptors (TCRs) to recognize and eliminate cancer cells. Here, we evaluated the potential of TCR repertoire as a predictive biomarker in patients treated with immunotherapy. With this aim, advanced NSCLC patients treated with immunotherapy at first-line were included. After obtaining peripheral blood and tissue samples at baseline, next-generation sequencing targeting TCRbeta/gamma was performed. Beyond TCR metrics, clonal space of the most frequent clones was determined. We found a positive association between uneven tumor-infiltrating TCRbeta repertoire and the immunotherapy response. Moreover, the use of various tumor-infiltrating and circulating TRBV/J genes predicted the immunotherapy response. Our results indicate the importance of evaluating tissue and circulating TCRbeta repertoire prior immunotherapy, showing it as a promising immunotherapy response biomarker in NSCLC patients.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"56 2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Molecular characterization of disease is essential for precision medicine due to novel predictive biomarkers. Multiple next-generation sequencing (NGS) platforms are available, but their expense and clinical utility vary. Even if a targetable mutation is detected, corresponding drugs may not be available or affordable. No prior studies in Pakistan have focused on integrating NGS results into patient care to assist with therapeutic decision-making and survival outcomes. This retrospective study aimed to evaluate the molecular profiling and therapeutic implications of NGS testing across solid tumors. It included all patients with histologically proven malignancy (metastatic or non-metastatic) who had NGS analysis at Aga Khan University Hospital (AKUH) from June 1, 2020, to June 1, 2023. Foundation One was the NGS platform used. From 2020 to 2023, 192 patients underwent NGS. The majority were male (55.2%) and aged over 50 years (71.9%). The most common indications for NGS were carcinoma of unknown primary (CUP) and lung cancers, representing 26% and 25% respectively, followed by colon (9%) and breast cancers (8%). Most patients had metastatic disease (98.4%). Common mutations in lung cancer were EGFR (16.3%) and KRAS G12C (14.3%). In unknown primary, breast, and colon cancers, the most common mutations were BRAF (8%), PIK3CA (18%), and KRAS (42.1%), respectively. Microsatellite instability (MSI) testing was performed in 95% of patients, with 6% being MSI high. Actionable alterations were detected in 31.8% of patients, but only 17.2% received genotype-matched treatment, mostly as a first-line treatment for lung cancer. The primary barriers were drug availability and affordability. Our results show that the implementation of NGS analysis supports clinical decision making. However, these results were applicable to a small percentage of patients. For better compliance and applicability, drug availability and cost of treatment needs to be addressed
{"title":"PRESCRIBING PRACTICES AND CLINICAL IMPACT OF NEXT GENERATION SEQUENCING IN ROUTINE PRACTICE IN SOLID TUMORS – REAL WORLD EXPERIENCE IN LMIC","authors":"nidaezehra zehra, Nida E Zehra, Aqsa Sohail, Zeeshan Ansar, Munira Moosajee","doi":"10.1101/2024.07.31.24311267","DOIUrl":"https://doi.org/10.1101/2024.07.31.24311267","url":null,"abstract":"Molecular characterization of disease is essential for precision medicine due to novel predictive biomarkers. Multiple next-generation sequencing (NGS) platforms are available, but their expense and clinical utility vary. Even if a targetable mutation is detected, corresponding drugs may not be available or affordable. No prior studies in Pakistan have focused on integrating NGS results into patient care to assist with therapeutic decision-making and survival outcomes.\u0000This retrospective study aimed to evaluate the molecular profiling and therapeutic implications of NGS testing across solid tumors. It included all patients with histologically proven malignancy (metastatic or non-metastatic) who had NGS analysis at Aga Khan University Hospital (AKUH) from June 1, 2020, to June 1, 2023. Foundation One was the NGS platform used. From 2020 to 2023, 192 patients underwent NGS. The majority were male (55.2%) and aged over 50 years (71.9%). The most common indications for NGS were carcinoma of unknown primary (CUP) and lung cancers, representing 26% and 25% respectively, followed by colon (9%) and breast cancers (8%). Most patients had metastatic disease (98.4%). Common mutations in lung cancer were EGFR (16.3%) and KRAS G12C (14.3%). In unknown primary, breast, and colon cancers, the most common mutations were BRAF (8%), PIK3CA (18%), and KRAS (42.1%), respectively. Microsatellite instability (MSI) testing was performed in 95% of patients, with 6% being MSI high. Actionable alterations were detected in 31.8% of patients, but only 17.2% received genotype-matched treatment, mostly as a first-line treatment for lung cancer. The primary barriers were drug availability and affordability.\u0000Our results show that the implementation of NGS analysis supports clinical decision making. However, these results were applicable to a small percentage of patients. For better compliance and applicability, drug availability and cost of treatment needs to be addressed","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
BACKGROUND: Pancreatic cancer is a serious threat to human health. Ultrasound is widely used in screening or preliminary diagnosis of pancreatic cancer, and enhanced CT is widely used in the diagnosis of pancreatic cancer. However, false-positive results of ultrasound and enhanced CT will bring unnecessary mental pain, expensive examination costs, physical injuries, and even adverse consequences such as organ removal and loss of function; while false-negative results of enhanced CT bring delayed treatment, and patients will thus have to bear the adverse consequences of poor prognosis, high treatment costs, poor quality of life, and short survival period. There is an urgent need to find convenient, cost-effective and non-invasive diagnostic methods to reduce the false-positive rate of ultrasound and the false-negative and false-positive rates of enhanced CT in pancreatic tumors. The aim of this study was to evaluate the diagnostic value of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D in pancreatic cancer. MATERIALS AND METHODS: 62 subjects (malignant group, n=37; benign group, n=25) were finally included in this study. Remaining serum samples from the subjects were collected and tested by applying the YiDiXie™ all-cancer detection kit to evaluate the sensitivity and specificity of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D, respectively. RESULTS: The sensitivity of YiDiXie™-SS in pancreatic ultrasound-positive patients was 100% (95% CI: 90.6% - 100%) and the specificity was 60.0% (95% CI: 55.4% - 69.7%). Compared with enhanced CT alone, sequential use of YiDiXie™-SS and enhanced CT resulted in comparable sensitivity, but the false-positive rate decreased from 24.0% (95% CI: 11.5% - 43.4%) to 8.0% (95% CI: 1.4% - 25.0%). This means that the application of YiDiXie™-SS reduces the false-positive rate of ultrasound by 60.0% (95% CI: 55.4% - 69.7%) and reduces the false-positive rate of enhanced CT by 66.7% with essentially no increase in the leakage of malignant tumors.YiDiXie™-HS had a sensitivity of 85.7% (95% CI: 48.7% - 99.3%) and a specificity of 84.2% (95% CI: 62.4% - 92.5%) in enhanced CT-negative patients. This means that YiDiXie™-HS reduces the false-negative enhancement CT rate by 84.2% (95% CI: 62.4% - 92.5%). YiDiXie™-D has a sensitivity of 33.3% (95% CI: 19.2% - 51.2%) and a specificity of 100% (95% CI: 61.0% - 100%) in patients with positive enhancement CT. This means that YiDiXie™-D reduces the false positive rate of enhanced CT by 100% (95% CI: 61.0% - 100%). CONCLUSION: YiDiXie™-SS significantly reduces the false-positive rate of ultrasound and enhanced CT in ultrasound-positive pancreatic patients with essentially no increase in delayed treatment of malignant tumors. YiDiXie™-HS significantly reduces the false-negative rate of enhanced CT in patients with pancreatic tumors. YiDiXie™-D significantly reduces the false-positive rate of enhanced CT in patients with pancreatic tumors. The YiDiXie™ test has significant diagnostic value in pancreat
{"title":"Evaluation of the diagnostic value of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D in pancreatic cancer","authors":"Xutai Li, Pengwu Zhang, Hui Zhang, Chen Sun, Yutong Wu, Huimei Zhou, Zhenjian Ge, Shengjie Lin, Yingqi Li, Wenkang Chen, Wuping Wang, Siwei Chen, Wei Li, Fei Feng, Zewei Lin, Ling Ji, Yongqing Lai","doi":"10.1101/2024.07.30.24311246","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311246","url":null,"abstract":"BACKGROUND: Pancreatic cancer is a serious threat to human health. Ultrasound is widely used in screening or preliminary diagnosis of pancreatic cancer, and enhanced CT is widely used in the diagnosis of pancreatic cancer. However, false-positive results of ultrasound and enhanced CT will bring unnecessary mental pain, expensive examination costs, physical injuries, and even adverse consequences such as organ removal and loss of function; while false-negative results of enhanced CT bring delayed treatment, and patients will thus have to bear the adverse consequences of poor prognosis, high treatment costs, poor quality of life, and short survival period. There is an urgent need to find convenient, cost-effective and non-invasive diagnostic methods to reduce the false-positive rate of ultrasound and the false-negative and false-positive rates of enhanced CT in pancreatic tumors. The aim of this study was to evaluate the diagnostic value of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D in pancreatic cancer.\u0000MATERIALS AND METHODS: 62 subjects (malignant group, n=37; benign group, n=25) were finally included in this study. Remaining serum samples from the subjects were collected and tested by applying the YiDiXie™ all-cancer detection kit to evaluate the sensitivity and specificity of YiDiXie™-SS, YiDiXie™-HS and YiDiXie™-D, respectively. RESULTS: The sensitivity of YiDiXie™-SS in pancreatic ultrasound-positive patients was 100% (95% CI: 90.6% - 100%) and the specificity was 60.0% (95% CI: 55.4% - 69.7%). Compared with enhanced CT alone, sequential use of YiDiXie™-SS and enhanced CT resulted in comparable sensitivity, but the false-positive rate decreased from 24.0% (95% CI: 11.5% - 43.4%) to 8.0% (95% CI: 1.4% - 25.0%). This means that the application of YiDiXie™-SS reduces the false-positive rate of ultrasound by 60.0% (95% CI: 55.4% - 69.7%) and reduces the false-positive rate of enhanced CT by 66.7% with essentially no increase in the leakage of malignant tumors.YiDiXie™-HS had a sensitivity of 85.7% (95% CI: 48.7% - 99.3%) and a specificity of 84.2% (95% CI: 62.4% - 92.5%) in enhanced CT-negative patients. This means that YiDiXie™-HS reduces the false-negative enhancement CT rate by 84.2% (95% CI: 62.4% - 92.5%). YiDiXie™-D has a sensitivity of 33.3% (95% CI: 19.2% - 51.2%) and a specificity of 100% (95% CI: 61.0% - 100%) in patients with positive enhancement CT. This means that YiDiXie™-D reduces the false positive rate of enhanced CT by 100% (95% CI: 61.0% - 100%). CONCLUSION: YiDiXie™-SS significantly reduces the false-positive rate of ultrasound and enhanced CT in ultrasound-positive pancreatic patients with essentially no increase in delayed treatment of malignant tumors. YiDiXie™-HS significantly reduces the false-negative rate of enhanced CT in patients with pancreatic tumors. YiDiXie™-D significantly reduces the false-positive rate of enhanced CT in patients with pancreatic tumors. The YiDiXie™ test has significant diagnostic value in pancreat","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1101/2024.07.30.24311256
Feryal Kurdi, Yahya Kurdi, Igor Vladimirovich Reshetov
Objective: The objective of this scoping review is to evaluate the current literature on the use of Indocyanine Green (ICG) in sentinel lymph node (SLN) mapping for breast cancer patients. This review aims to assess the accuracy, efficacy, and safety of ICG in this context and to identify gaps in the existing research. The outcomes will contribute to the development of further research as part of a PhD project. Introduction: Breast cancer is the leading cause of morbidity and mortality worldwide. Accurate SLN mapping is crucial for staging and treatment planning in early-stage breast cancer. ICG has emerged as a promising agent for fluorescence imaging in SLN mapping. However, comprehensive assessment of its clinical utility, including accuracy and adverse effects, remains limited. This scoping review aims to consolidate evidence on the use of ICG in breast cancer SLN mapping. Inclusion criteria: Patients with early-stage breast cancer (T1, T2), selected T3 cases where sentinel lymph node biopsy is accurate, and clinically node-negative breast cancer. The intervention includes studies using ICG for SLN mapping and assessment of fluorescence imaging cameras. Methods: Five electronic databases will be searched (PubMed, EMBASE, MEDLINE, Web of Science, and SCOPUS) using search strategies developed in consultation with the academic supervisor. The search strategy is set to human studies published in English within the last 11 years. All retrieved citations will be imported to Zotero and then uploaded to Covidence for screening of titles, abstracts, and full text according to pre-specified inclusion criteria. Citations meeting the inclusion criteria for full-text review will have their data extracted by two independent reviewers, with disagreements resolved by discussion. A data extraction tool will be developed to capture full details about the participants, concept, and context, and findings relevant to the scoping review will be summarized. Keywords: Indocyanine Green, ICG, Sentinel Lymph Node, Breast Cancer, Fluorescence, Axillary Lymph Node Mapping, NIR
目的：本范围综述旨在评估目前有关吲哚菁绿（ICG）用于乳腺癌患者前哨淋巴结（SLN）绘图的文献。本综述旨在评估 ICG 在这方面的准确性、有效性和安全性，并找出现有研究的不足之处。作为博士项目的一部分，研究成果将有助于进一步开展研究：导言：乳腺癌是全球发病率和死亡率的主要原因。准确的SLN图谱对于早期乳腺癌的分期和治疗规划至关重要。ICG 已成为一种很有前途的用于 SLN 测绘的荧光成像剂。然而，对其临床实用性（包括准确性和不良反应）的全面评估仍然有限。本范围综述旨在整合ICG用于乳腺癌SLN绘图的证据：早期乳腺癌（T1、T2）患者、前哨淋巴结活检准确的特定 T3 病例以及临床结节阴性乳腺癌患者。干预措施包括使用 ICG 绘制 SLN 地图的研究以及对荧光成像摄像机的评估。研究方法将使用与学术导师协商制定的检索策略对五个电子数据库（PubMed、EMBASE、MEDLINE、Web of Science 和 SCOPUS）进行检索。检索策略设定为过去 11 年内以英语发表的人类研究。所有检索到的引文都将导入 Zotero，然后上传到 Covidence，根据预先规定的纳入标准筛选标题、摘要和全文。符合全文审阅纳入标准的引文将由两名独立审稿人提取数据，并通过讨论解决分歧。将开发一个数据提取工具，以获取有关参与者、概念和背景的全部细节，并总结与范围界定审查相关的结果：吲哚菁绿，ICG，前哨淋巴结，乳腺癌，荧光，腋窝淋巴结绘图，近红外
{"title":"Applications of ICG in Breast Cancer for Sentinel Lymph Node Mapping: A Scoping Review Protocol","authors":"Feryal Kurdi, Yahya Kurdi, Igor Vladimirovich Reshetov","doi":"10.1101/2024.07.30.24311256","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311256","url":null,"abstract":"Objective: The objective of this scoping review is to evaluate the current literature on the use of Indocyanine Green (ICG) in sentinel lymph node (SLN) mapping for breast cancer patients. This review aims to assess the accuracy, efficacy, and safety of ICG in this context and to identify gaps in the existing research. The outcomes will contribute to the development of further research as part of a PhD project.\u0000Introduction: Breast cancer is the leading cause of morbidity and mortality worldwide. Accurate SLN mapping is crucial for staging and treatment planning in early-stage breast cancer. ICG has emerged as a promising agent for fluorescence imaging in SLN mapping. However, comprehensive assessment of its clinical utility, including accuracy and adverse effects, remains limited. This scoping review aims to consolidate evidence on the use of ICG in breast cancer SLN mapping.\u0000Inclusion criteria: Patients with early-stage breast cancer (T1, T2), selected T3 cases where sentinel lymph node biopsy is accurate, and clinically node-negative breast cancer. The intervention includes studies using ICG for SLN mapping and assessment of fluorescence imaging cameras. Methods: Five electronic databases will be searched (PubMed, EMBASE, MEDLINE, Web of Science, and SCOPUS) using search strategies developed in consultation with the academic supervisor. The search strategy is set to human studies published in English within the last 11 years. All retrieved citations will be imported to Zotero and then uploaded to Covidence for screening of titles, abstracts, and full text according to pre-specified inclusion criteria. Citations meeting the inclusion criteria for full-text review will have their data extracted by two independent reviewers, with disagreements resolved by discussion. A data extraction tool will be developed to capture full details about the participants, concept, and context, and findings relevant to the scoping review will be summarized.\u0000Keywords: Indocyanine Green, ICG, Sentinel Lymph Node, Breast Cancer, Fluorescence, Axillary Lymph Node Mapping, NIR","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"151 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1101/2024.07.30.24311186
Alexandre Matov
The current healthcare system relies largely on a passive approach toward disease detection, which typically involves patients presenting a 'chief complaint' linked to a particular set of symptoms for diagnosis. Since all degenerative diseases occur slowly and initiate as changes in the regulation of individual cells within our organs and tissues, it is inevitable that with the current approach to medical care we are bound to discover some illnesses at a point in time when the damage is irreversible and meaningful treatments are no longer available. There exist organ-specific sets (or panels) of nucleic acids, such as microRNAs (miRNAs), which regulate and help to ensure the proper function of each of our organs and tissues. Thus, dynamic readout of their relative abundance can serve as a means to facilitate real-time health monitoring. With the advent and mass utilization of next-generation sequencing (NGS), such a proactive approach is currently feasible. Because of the computational complexity of customized analyses of 'big data', dedicated efforts to extract reliable information from longitudinal datasets is key to successful early detection of disease. Here, we present our preliminary results for the analysis of healthy donor samples and drug-naive lung cancer patients.
{"title":"Urinary Biomarkers for Disease Detection","authors":"Alexandre Matov","doi":"10.1101/2024.07.30.24311186","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311186","url":null,"abstract":"The current healthcare system relies largely on a passive approach toward disease detection, which typically involves patients presenting a 'chief complaint' linked to a particular set of symptoms for diagnosis. Since all degenerative diseases occur slowly and initiate as changes in the regulation of individual cells within our organs and tissues, it is inevitable that with the current approach to medical care we are bound to discover some illnesses at a point in time when the damage is irreversible and meaningful treatments are no longer available. There exist organ-specific sets (or panels) of nucleic acids, such as microRNAs (miRNAs), which regulate and help to ensure the proper function of each of our organs and tissues. Thus, dynamic readout of their relative abundance can serve as a means to facilitate real-time health monitoring. With the advent and mass utilization of next-generation sequencing (NGS), such a proactive approach is currently feasible. Because of the computational complexity of customized analyses of 'big data', dedicated efforts to extract reliable information from longitudinal datasets is key to successful early detection of disease. Here, we present our preliminary results for the analysis of healthy donor samples and drug-naive lung cancer patients.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1101/2024.07.28.24311114
Umair Ali
Brain tumors, which are abnormal growths of cells in the brain, represent a significant health concern, necessitating prompt and accurate detection for effective treatment. If left untreated, brain tumors can lead to severe complications, including cognitive impairment, paralysis, and even death. This study evaluates six machine learning classifiers: Support Vector Classifier (SVC), Logistic Regression Classifier, K-Nearest Neighbors (KNN) Classifier, Naive Bayes Classifier, Decision Tree Classifier, and Random Forest Classifier - on a comprehensive brain tumor dataset. Our results showed that Random Forest achieved the highest accuracy of 98.27%, demonstrating its potential in detecting brain tumors. However, Support Vector Classifier (SVC) emerged as the top performer, achieving an impressive accuracy of 97.74%, showcasing its exceptional ability to detect brain tumors accurately. This significant improvement in SVC's performance highlights its potential as a reliable tool for medical diagnostics, contributing to the development of efficient and accurate automated systems for early brain tumor diagnosis, ultimately aiming to improve patient outcomes and treatment efficacy
{"title":"Comparative Evaluation Of Machine Learning Classifiers For Brain Tumor Detection","authors":"Umair Ali","doi":"10.1101/2024.07.28.24311114","DOIUrl":"https://doi.org/10.1101/2024.07.28.24311114","url":null,"abstract":"Brain tumors, which are abnormal growths of cells in the brain, represent a significant health concern, necessitating prompt and accurate detection for effective treatment. If left untreated, brain tumors can lead to severe complications, including cognitive impairment, paralysis, and even death. This study evaluates six machine learning classifiers: Support Vector Classifier (SVC), Logistic Regression Classifier, K-Nearest Neighbors (KNN) Classifier, Naive Bayes Classifier, Decision Tree Classifier, and Random Forest Classifier - on a comprehensive brain tumor dataset. Our results showed that Random Forest achieved the highest accuracy of 98.27%, demonstrating its potential in detecting brain tumors. However, Support Vector Classifier (SVC) emerged as the top performer, achieving an impressive accuracy of 97.74%, showcasing its exceptional ability to detect brain tumors accurately. This significant improvement in SVC's performance highlights its potential as a reliable tool for medical diagnostics, contributing to the development of efficient and accurate automated systems for early brain tumor diagnosis, ultimately aiming to improve patient outcomes and treatment efficacy","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"213 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.1101/2024.07.29.24311006
Deep B Gandhi, Nastaran Khalili, Ariana Familiar, Anurag Gottipati, Neda Khalili, Wenxin Tu, Shuvanjan Haldar, Hannah Anderson, Karthik Viswanathan, Phillip B Storm, Jeffrey B Ware, Adam C Resnick, Arastoo Vossough, Ali Nabavizadeh, Anahita Fathi Kazerooni
Background: Fully-automatic skull-stripping and tumor segmentation are crucial for monitoring pediatric brain tumors (PBT). Current methods, however, often lack generalizability, particularly for rare tumors in the sellar/suprasellar regions and when applied to real-world clinical data in limited data scenarios. To address these challenges, we propose AI-driven techniques for skull-stripping and tumor segmentation. Methods: Multi-institutional, multi-parametric MRI scans from 527 pediatric patients (n=336 for skull-stripping, n=489 for tumor segmentation) with various PBT histologies were processed to train separate nnU-Net-based deep learning models for skull-stripping, whole tumor (WT), and enhancing tumor (ET) segmentation. These models utilized single (T2/FLAIR) or multiple (T1-Gd and T2/FLAIR) input imaging sequences. Performance was evaluated using Dice scores, sensitivity, and 95% Hausdorff distances. Statistical comparisons included paired or unpaired two-sample t-tests and Pearsons correlation coefficient based on Dice scores from different models and PBT histologies. Results: Dice scores for the skull-stripping models for whole brain and sellar/suprasellar region segmentation were 0.98±0.01 (median 0.98) for both multi- and single-parametric models, with significant Pearsons correlation coefficient between single- and multi-parametric Dice scores (r > 0.80; p<0.05 for all). WT Dice scores for single-input tumor segmentation models were 0.84±0.17 (median=0.90) for T2 and 0.82±0.19 (median=0.89) for FLAIR inputs. ET Dice scores were 0.65±0.35 (median=0.79) for T1-Gd+FLAIR and 0.64±0.36 (median=0.79) for T1-Gd+T2 inputs. Conclusion: Our skull-stripping models demonstrate excellent performance and include sellar/suprasellar regions, using single- or multi-parametric inputs. Additionally, our automated tumor segmentation models can reliably delineate whole lesions and enhancing tumor regions, adapting to MRI sessions with missing sequences in limited data context.
{"title":"Automated Pediatric Brain Tumor Imaging Assessment Tool from CBTN: Enhancing Suprasellar Region Inclusion and Managing Limited Data with Deep Learning","authors":"Deep B Gandhi, Nastaran Khalili, Ariana Familiar, Anurag Gottipati, Neda Khalili, Wenxin Tu, Shuvanjan Haldar, Hannah Anderson, Karthik Viswanathan, Phillip B Storm, Jeffrey B Ware, Adam C Resnick, Arastoo Vossough, Ali Nabavizadeh, Anahita Fathi Kazerooni","doi":"10.1101/2024.07.29.24311006","DOIUrl":"https://doi.org/10.1101/2024.07.29.24311006","url":null,"abstract":"Background: Fully-automatic skull-stripping and tumor segmentation are crucial for monitoring pediatric brain tumors (PBT). Current methods, however, often lack generalizability, particularly for rare tumors in the sellar/suprasellar regions and when applied to real-world clinical data in limited data scenarios. To address these challenges, we propose AI-driven techniques for skull-stripping and tumor segmentation.\u0000Methods: Multi-institutional, multi-parametric MRI scans from 527 pediatric patients (n=336 for skull-stripping, n=489 for tumor segmentation) with various PBT histologies were processed to train separate nnU-Net-based deep learning models for skull-stripping, whole tumor (WT), and enhancing tumor (ET) segmentation. These models utilized single (T2/FLAIR) or multiple (T1-Gd and T2/FLAIR) input imaging sequences. Performance was evaluated using Dice scores, sensitivity, and 95% Hausdorff distances. Statistical comparisons included paired or unpaired two-sample t-tests and Pearsons correlation coefficient based on Dice scores from different models and PBT histologies. Results: Dice scores for the skull-stripping models for whole brain and sellar/suprasellar region segmentation were 0.98±0.01 (median 0.98) for both multi- and single-parametric models, with significant Pearsons correlation coefficient between single- and multi-parametric Dice scores (r > 0.80; p<0.05 for all). WT Dice scores for single-input tumor segmentation models were 0.84±0.17 (median=0.90) for T2 and 0.82±0.19 (median=0.89) for FLAIR inputs. ET Dice scores were 0.65±0.35 (median=0.79) for T1-Gd+FLAIR and 0.64±0.36 (median=0.79) for T1-Gd+T2 inputs. Conclusion: Our skull-stripping models demonstrate excellent performance and include sellar/suprasellar regions, using single- or multi-parametric inputs. Additionally, our automated tumor segmentation models can reliably delineate whole lesions and enhancing tumor regions, adapting to MRI sessions with missing sequences in limited data context.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.1101/2024.07.30.24311046
Emma West, Alain Sadoun, Kaidre Bendjama, Philippe Erbs, Cristina Smolenschi, Philippe Cassier, Thierry De Baere, Sophie Sainte-Croix, Maud Brandely, Alan Melcher, Fay Ismail, Karen Scott, Angela Bennett, Emma Banks, Ewa Gasior, Sarah Kent, Marta Kurzawa, Christopher Hammond, Jai Patel, Fiona Collinson, Chris Twelves, D Alan Anthoney, Daniel Swinson, Adel Samson
Background: Effective treatment for patients with metastatic cancer is limited, particularly for colorectal cancer patients with metastatic liver lesions (mCRC), where accessibility to numerous tumours is essential for favourable clinical outcomes. Oncolytic viruses (OVs) selectively replicate in cancer cells; however, direct targeting of inaccessible lesions is limited when using conventional intravenous (i.v.) or intratumoural (i.t.) administration routes. Methods: We conducted a multi-centre, dose-escalation, phase I study of vaccinia virus, TG6002, via intrahepatic artery (IHA) delivery in combination with the oral pro-drug 5-fluorocytosine (5-FC) to fifteen mCRC patients. Results: Successful IHA delivery of replication-competent TG6002 was achieved, as demonstrated by virus within tumour biopsies. Functional transcription of the FCU1 transgene indicates viral replication within the tumour, with higher plasma concentrations of 5-fluorouracil (5-FU) associated with patients receiving the highest dose of TG6002. IHA delivery of TG6002 correlated with a robust systemic peripheral immune response to virus with activation of peripheral blood mononuclear cells, associated with a proinflammatory cytokine response and release of calreticulin, potentially indicating immunogenic cell death. Gene Ontology analyses of differentially-expressed genes reveal a significant immune response at the transcriptional level in response to treatment. Moreover, an increase in the number and frequency of T cell receptor clones against both cancer- and neo-antigens, with elevated functional activity, may be associated with improved anti-cancer activity. Despite these findings, no clinical efficacy was observed. Conclusions: In summary, these data demonstrate delivery of OV to tumour via IHA administration, associated with viral replication and significant peripheral immune activation. Collectively, the data supports the need for future studies using IHA administration of OVs.
背景：对转移性癌症患者的有效治疗非常有限，尤其是对肝转移性病变（mCRC）的结直肠癌患者而言，要想取得良好的临床疗效，必须能够进入众多肿瘤。肿瘤溶解病毒（OV）可选择性地在癌细胞中复制；然而，如果采用传统的静脉注射（i.v.）或肿瘤内注射（i.t.）给药途径，直接靶向无法触及的病灶的效果有限。研究方法我们进行了一项多中心、剂量递增的 I 期研究，通过肝内动脉（IHA）给药与口服原药 5-氟胞嘧啶（5-FC）联合给 15 名 mCRC 患者注射疫苗病毒 TG6002。结果：肿瘤活检结果表明，IHA成功递送了具有复制能力的TG6002。FCU1转基因的功能转录表明病毒在肿瘤内复制，接受最高剂量TG6002的患者血浆中5-氟尿嘧啶（5-FU）的浓度更高。TG6002 的 IHA 给药与全身外周对病毒的强烈免疫反应相关，外周血单核细胞被激活，伴有促炎细胞因子反应和钙网蛋白的释放，这可能表明免疫性细胞死亡。基因本体论对差异表达基因的分析表明，治疗在转录水平上产生了显著的免疫反应。此外，针对癌症和新抗原的 T 细胞受体克隆数量和频率的增加以及功能活性的提高，可能与抗癌活性的改善有关。尽管有这些发现，但并没有观察到临床疗效。结论：总之，这些数据证明了通过 IHA 给药将 OV 运送到肿瘤，与病毒复制和显著的外周免疫激活有关。总之，这些数据支持了今后使用 IHA 给药 OV 进行研究的必要性。
{"title":"A phase I clinical trial of intrahepatic artery delivery of TG6002 in combination with oral 5-fluorocytosine in patients with liver-dominant metastatic colorectal cancer","authors":"Emma West, Alain Sadoun, Kaidre Bendjama, Philippe Erbs, Cristina Smolenschi, Philippe Cassier, Thierry De Baere, Sophie Sainte-Croix, Maud Brandely, Alan Melcher, Fay Ismail, Karen Scott, Angela Bennett, Emma Banks, Ewa Gasior, Sarah Kent, Marta Kurzawa, Christopher Hammond, Jai Patel, Fiona Collinson, Chris Twelves, D Alan Anthoney, Daniel Swinson, Adel Samson","doi":"10.1101/2024.07.30.24311046","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311046","url":null,"abstract":"Background: Effective treatment for patients with metastatic cancer is limited, particularly for colorectal cancer patients with metastatic liver lesions (mCRC), where accessibility to numerous tumours is essential for favourable clinical outcomes. Oncolytic viruses (OVs) selectively replicate in cancer cells; however, direct targeting of inaccessible lesions is limited when using conventional intravenous (i.v.) or intratumoural (i.t.) administration routes. Methods: We conducted a multi-centre, dose-escalation, phase I study of vaccinia virus, TG6002, via intrahepatic artery (IHA) delivery in combination with the oral pro-drug 5-fluorocytosine (5-FC) to fifteen mCRC patients. Results: Successful IHA delivery of replication-competent TG6002 was achieved, as demonstrated by virus within tumour biopsies. Functional transcription of the FCU1 transgene indicates viral replication within the tumour, with higher plasma concentrations of 5-fluorouracil (5-FU) associated with patients receiving the highest dose of TG6002. IHA delivery of TG6002 correlated with a robust systemic peripheral immune response to virus with activation of peripheral blood mononuclear cells, associated with a proinflammatory cytokine response and release of calreticulin, potentially indicating immunogenic cell death. Gene Ontology analyses of differentially-expressed genes reveal a significant immune response at the transcriptional level in response to treatment. Moreover, an increase in the number and frequency of T cell receptor clones against both cancer- and neo-antigens, with elevated functional activity, may be associated with improved anti-cancer activity. Despite these findings, no clinical efficacy was observed. Conclusions: In summary, these data demonstrate delivery of OV to tumour via IHA administration, associated with viral replication and significant peripheral immune activation. Collectively, the data supports the need for future studies using IHA administration of OVs.","PeriodicalId":501437,"journal":{"name":"medRxiv - Oncology","volume":"358 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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