Cancer Biomarkers最新文献

{"title":"Development and validation of machine learning models for early diagnosis and prognosis of lung adenocarcinoma using miRNA expression profiles.","authors":"Lin Lin, Yongxia Bao","doi":"10.1177/18758592241308756","DOIUrl":"10.1177/18758592241308756","url":null,"abstract":"<p><p>ObjectiveStudy aims to develop diagnostic and prognostic models for lung adenocarcinoma (LUAD) using Machine learning（ML）algorithms, aiming to enhance clinical decision-making accuracy.MethodsData from The Cancer Genome Atlas (TCGA) for LUAD patients were split into training (n = 196) and test sets (n = 133). Feature selection (Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Support Vector Machine (SVM)) identified miRNAs distinguishing stage I LUAD. Six ML algorithms predicted pulmonary node classification. Model performance was evaluated using Receiver Operating Characteristic (ROC) curve, Precision-Recall (PR) curves, and Error Rates (CE). A prognostic model was constructed using Lasso Cox regression. Risk score plots were generated, and model performance was assessed using Kaplan-Meier (K-M) and time-dependent ROC curves. Functional enrichment analyses investigated miRNA function and mechanism.ResultsThe feature selection results identified five miRNA molecules as distinguishing characteristics between early-stage LUAD and adjacent non-cancerous tissues. A prognostic model using 13 miRNAs predicted poorer outcomes for patients with higher risk scores, supported by time-dependent ROC curves and a nomogram. Functional enrichment analysis identified cancer-related signaling pathways for the biomarkers.ConclusionML identified a diagnostic five-miRNA signature and a prognostic 13-miRNA model for LUAD, both robust and reliable.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241308756"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143765801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial proteomics and transcriptomics characterization of tissue and multiple cancer types including decalcified marrow.","authors":"Cecilia Cs Yeung, Daniel C Jones, David W Woolston, Brandon Seaton, Elizabeth Lawless Donato, Minggang Lin, Coral Backman, Vivian Oehler, Kristin L Robinson, Kristen Shimp, Rima Kulikauskas, Annalyssa N Long, David Sowerby, Anna E Elz, Kimberly S Smythe, Evan W Newell","doi":"10.1177/18758592241308757","DOIUrl":"10.1177/18758592241308757","url":null,"abstract":"<p><p>BackgroundRecent technologies enabling the study of spatial biology include multiple high-dimensional spatial imaging methods that have rapidly emerged with different capabilities evaluating tissues at different resolutions for different sample formats. Platforms like Xenium (10x Genomics) and PhenoCycler-Fusion (Akoya Biosciences) enable single-cell resolution analysis of gene and protein expression in archival FFPE tissue slides. However, a key limitation is the absence of systematic methods to ensure tissue quality, marker integrity, and data reproducibility.ObjectiveWe seek to optimize the technical methods for spatial work by addressing preanalytical challenges with various tissue and tumor types, including a decalcification protocol for processing FFPE bone marrow core specimens to preserve nucleic acids for effective spatial proteomics and transcriptomics. This study characterizes a multicancer tissue microarray (TMA) and a molecular- and protein-friendly decalcification protocol that supports downstream spatial biology investigations.MethodsWe developed a multi-cancer tissue microarray (TMA) and processed bone marrow core samples using a molecular- and protein-friendly decalcification protocol. PhenoCycler high-plex immunohistochemistry (IHC) generated spatial proteomics data, analyzed with QuPath and single-cell analysis. Xenium provided spatial transcriptomics data, analyzed via Xenium Explorer and custom pipelines.ResultsResults showed that PhenoCycler and Xenium platforms applied to TMA sections of tonsil and various tumor types achieved good marker concordance. Bone marrow decalcification with our optimized protocol preserved mRNA and protein markers, allowing Xenium analysis to resolve all major cell types while maintaining tissue morphology.ConclusionsWe have shared our preanalytical verification of tissues and demonstrate that both the PhenoCycler-Fusion high-plex spatial proteomics and Xenium spatial transcriptomics platforms work well on various tumor types, including marrow core biopsies decalcified using a molecular- and protein-friendly decalcificationprotocol. We also demonstrate our laboratory's methods for systematic quality assessment of the spatial proteomic and transcriptomic data from these platforms, such that either platform can provide orthogonal confirmation for the other.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241308757"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomarkers in lung cancer diagnosis and bronchoscopy: Current landscape and future directions.","authors":"Nina A Thomas, Melissa L New","doi":"10.1177/18758592241306682","DOIUrl":"10.1177/18758592241306682","url":null,"abstract":"<p><p>Lung cancer is the leading cause of cancer death world-wide. Along the entire timeline of lung cancer identification, diagnosis and treatment, clinicians and patients face challenges in clinical decision-making that could be aided by useful biomarkers. In this review, we discuss the development of biomarkers and qualities that are ideal in a biomarker candidate, types of biospecimens that can be utilized for biomarker development in lung cancer, and how biomarkers could be clinically useful at various points along lung cancer timeline. We then review biomarkers that have been validated and are clinically available to assist with the management of lung nodules and diagnosis of lung cancer, which includes blood-based biomarkers to assist with decision-making prior to an invasive diagnostic procedure, as well as specimens obtained during a bronchoscopy and applied in cases of an inconclusive biopsy result. Finally, we discuss challenges in biomarker application and recent publications relevant to future lung cancer biomarker development.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241306682"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A potential target for the future treatment of malignant pleural effusion: Monocyte chemoattractant protein-1 (MCP-1).","authors":"Fatih Tekin, Deniz Koksal, Z Gunnur Dikmen, Sevilay Karahan, Rıdvan Bayler, Burcu Ancın, Erkan Dikmen, Devrim Akinci, Sevgen Onder","doi":"10.1177/18758592241293231","DOIUrl":"10.1177/18758592241293231","url":null,"abstract":"<p><p><b>Background and Aim:</b> Malignant pleural effusion (MPE) is a common clinical problem. Management options are mainly pleurodesis and drainage, and have remained unchanged for years. Novel therapies that target the molecules responsible for fluid formation are needed to reduce the need for invasive procedures. The aim of this study is to investigate the potential role of MCP-1 in the development of MPE in patients with metastatic pleural malignancies. <b>Methods:</b> Pleural effusion samples (8-10 ml) were collected from 100 patients who were divided into three groups: Group 1 (MPE, n = 56), Group 2 (benign exudate, n = 27) and Group 3 (transudate, n = 17). The collected effusions were promptly centrifuged at 4°C, and the supernatants were stored at -80°C. MCP-1 levels were determined by ELISA kit (USCN, Wuhan). <b>Results:</b> Median MCP-1 levels were found to be significantly different between the three groups (Group 1: 1303 pg/ml, Group 2: 926 pg/ml, Group 3: 211 pg/ml) (<i>p</i> < 0.001). MCP-1 levels were markedly higher but similar in Group 1 and Group 2, as compared to Group 3. When patients from Group 1 and Group 2 were combined, a positive correlation was observed between pleural fluid MCP-1 and LDH levels (r = 0.38; <i>p</i> = 0.001). Additionally, MCP-1 levels were observed to increase significantly as the volume of pleural fluid increased (<i>p</i> = 0.007). <b>Conclusion:</b> MCP-1 levels were found to be similarly high in both Group 1 (MPE) and Group 2 (Benign exudate), indicating that inflammation accompanying the tumor could play a role in the formation of pleural effusion. This suggests that the development of biological therapies targeting MCP-1 could be a promising approach in the future management of MPE.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241293231"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Apolipoprotein C1 and apoprotein E as potential therapeutic and prognostic targets for adrenocortical carcinoma.","authors":"Shaojin Li, Shuixiu Xiao, Yongli Situ","doi":"10.1177/18758592241308440","DOIUrl":"10.1177/18758592241308440","url":null,"abstract":"<p><p>BackgroundApolipoprotein C1 <b>(</b>APOC1) and Apoprotein E (APOE) play important roles in lipid transport and metabolism. In recent years, <i>APOC1</i> and <i>APOE</i> have been shown to play key roles in the occurrence and development of various cancers. However, the expression levels, gene regulatory networks, prognostic values, and target predictions of <i>APOC1</i> and <i>APOE</i> in adrenocortical carcinoma (ACC) remain unclear.MethodsVarious bioinformatics analysis methods were used, including gene expression profiling interactive analysis, the University of Alabama at Birmingham cancer data analysis portal, biomarker exploration of solid tumors software, the BioPortal for Cancer Genomics, search tool for the retrieval of interacting genes/proteins, gene multiple association network integration algorithm, Metascape, transcriptional regulatory relationships unraveled by sentence-based text-mining, LinkedOmics, and genomics of drug sensitivity in cancer analysis.Results<i>APOC1</i> and <i>APOE</i> expression were strongly downregulated in patients with ACC. <i>APOC1</i> and <i>APOE</i> expression levels were lower in male patients with ACC than those in female patients. Furthermore, <i>APOC1</i> and <i>APOE</i> expression levels affected the prognosis of patients with ACC. The main functions of <i>APOC1</i> and its altered neighboring genes (ANG) were organophosphate ester transport, rRNA processing, and positive regulation of cytokine production. Cytolysis, protein ubiquitination, and histone modification were the main functions of <i>APOE</i> and its ANGs. The transcription factor E2F1, tumor protein p53, miR-182, miR-493, Erb-B2 receptor tyrosine kinase 2, and cyclin dependent kinase 1 were key regulatory targets of <i>APOC1</i>, <i>APOE</i>, and the ANGs. <i>APOC1</i> and <i>APOE</i> expression in patients with ACC were positively associated with immune cell infiltration<i>.</i> Furthermore, anti-programmed cell death protein 1 immunotherapy strongly downregulated the expression of <i>APOC1</i> in patients with ACC. Both pilaralisib and elesclomol strongly inhibited SW13 cell growth.ConclusionsThis study preliminarily clarified that <i>APOC1</i> and <i>APOE</i> might be potential therapeutic and prognostic targets for ACC, and identified new targets and treatment strategies for ACC.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241308440"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simplified MyProstateScore2.0 for high-grade prostate cancer.","authors":"Tiffany M Tang, Yuping Zhang, Ana M Kenney, Cassie Xie, Lanbo Xiao, Javed Siddiqui, Sudhir Srivastava, Martin G Sanda, John T Wei, Ziding Feng, Jeffrey J Tosoian, Yingye Zheng, Arul M Chinnaiyan, Bin Yu","doi":"10.1177/18758592241308755","DOIUrl":"10.1177/18758592241308755","url":null,"abstract":"<p><p><b>Background:</b> The limited diagnostic accuracy of prostate-specific antigen screening for prostate cancer (PCa) has prompted innovative solutions, such as the state-of-the-art 18-gene urine test for clinically-significant PCa (MyProstateScore2.0 (MPS2)). <b>Objective:</b> We aim to develop a non-invasive biomarker test, the simplified MPS2 (sMPS2), which achieves similar state-of-the-art accuracy as MPS2 for predicting high-grade PCa but requires substantially fewer genes than the 18-gene MPS2 to improve its accessibility for routine clinical care. <b>Methods:</b> We grounded the development of sMPS2 in the Predictability, Computability, and Stability (PCS) framework for veridical data science. Under this framework, we stress-tested the development of sMPS2 across various data preprocessing and modeling choices and developed a stability-driven PCS ranking procedure for selecting the most predictive and robust genes for use in sMPS2. <b>Results:</b> The final sMPS2 model consisted of 7 genes and achieved a 0.784 AUROC (95% confidence interval, 0.742-0.825) for predicting high-grade PCa on a blinded external validation cohort. This is only 2.3% lower than the 18-gene MPS2, which is similar in magnitude to the 1-2% in uncertainty induced by different data preprocessing choices. <b>Conclusions:</b> The 7-gene sMPS2 provides a unique opportunity to expand the reach and adoption of non-invasive PCa screening.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241308755"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimated proportion of cancer deaths not addressed by current cancer screening efforts in the United States.","authors":"Joshua J Ofman, William Dahut, Ahmedin Jemal, Ellen T Chang, Christina A Clarke, Earl Hubbell, Anuraag R Kansal, Allison W Kurian, Graham A Colditz, Alpa V Patel","doi":"10.1177/18758592241308754","DOIUrl":"10.1177/18758592241308754","url":null,"abstract":"<p><p>BackgroundIt is unclear what proportion of the population cancer burden is covered by current implementation of USPSTF A/B screening recommendations.ObjectiveWe estimated the proportion of all US cancer deaths caused by cancer types not covered by screening recommendations or cancer types covered but unaddressed by current implementation.MethodsWe used 2018-2019 National Center for Health Statistics mortality data, Surveillance, Epidemiology, and End Results registries incidence-based mortality data, and published estimates of screening eligibility and receipt.ResultsOf approximately 600,000 annual cancer deaths in the US, 31.4% were from screenable cancer types, including colorectal, female breast, cervical, and smoking-associated lung cancers. Further accounting for the low receipt of lung cancer screening reduced the proportion to 17.4%; accounting for receipt of other screening reduced it to 12.8%. Thus, we estimated that current implementation of recommended screening may not address as much as 87.2% of cancer deaths<i>-</i>including 30.4% from individually uncommon cancer types unlikely ever to be covered by dedicated screening.ConclusionsThe large proportion of cancer deaths unaddressed by current screening represents a major opportunity for improved implementation of current approaches, as well as new multi-cancer screening technologies.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241308754"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum CA19-9 as a predictor of incident metabolic syndrome in obese middle-aged and older men: A 9-year cohort study.","authors":"Chun-Wei Yu, Li-Wei Wu, Je-Ming Hu, Pi-Kai Chang","doi":"10.1177/18758592241296282","DOIUrl":"10.1177/18758592241296282","url":null,"abstract":"<p><p>BackgroundThe status of carbohydrate antigen 19-9 (CA19-9) in metabolic syndrome (MetS) is unknown.ObjectiveTo investigate the association between serum CA19-9 levels and incident metabolic syndrome in obese middle-aged and older men.MethodsFrom 2007 to 2015, 1,750 participants were retrospectively reviewed. Health checkup data were obtained, and participants were divided into three groups based on CA19-9 levels. Various parameters including BMI, waist circumference, blood pressure, and biochemical parameters were measured. Cox regression analysis was used to assess the association between CA19-9 levels and incident MetS. The MetS diagnostic criteria were based on the National Cholesterol Education Program Adult Treatment Panel III guidelines.ResultsThe highest CA19-9 tertile was associated with an increased risk of incident MetS, high systolic blood pressure, high waist circumference, high fasting plasma glucose, low high-density lipoprotein, and high triglyceride levels. The observation period was 9 years, during which 328 (18.7%) new-onset MetS cases were identified. Subgroup analysis showed increased risk among individuals in the highest CA19-9 tertile who were obese, male, and ≥ 50 years old.ConclusionsThere is a positive correlation between serum CA19-9 levels and incident metabolic syndrome in obese middle-aged and older men.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"42 1","pages":"18758592241296282"},"PeriodicalIF":2.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Glycolysis and gluconeogenesis-related model for breast cancer prognosis.","authors":"Penglu Yang, Xiong Jiao","doi":"10.1177/18758592241296278","DOIUrl":"10.1177/18758592241296278","url":null,"abstract":"<p><p>BackgroundBreast cancer is a malignant tumor with high morbidity and mortality, which seriously endangers the health of women around the world. Biomarker-based exploration will be effective for better diagnosis, prediction and targeted therapy.ObjectiveTo construct biomarker models related to glycolysis and gluconeogenesis in breast cancer.MethodsThe gene expression of 932 breast cancer patients in the Cancer Genome Atlas (TCGA) database was analyzed by Gene Set Variation Analysis (GSVA) using glycolysis and gluconeogenesis-related pathways. Differential expression genes were searched for by the T-test. Univariate Cox proportional hazards model (COX) regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Multivariate COX regression were used to find clinically significant genes for prognostic survival. After that, the constructed gene signature was externally validated through the Gene Expression Omnibus (GEO). Finally, a nomogram was constructed to predict the survival of patients. In addition, analyzing the role of biomarkers in pan-cancer.ResultsA risk scoring model associated with glycolysis and gluconeogenesis was developed and validated. A nomogram was created to predict 2-, 3-, and 5- survival.ConclusionsThe predictive model accurately predicted the prognosis of breast cancer patients.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"41 3-4","pages":"18758592241296278"},"PeriodicalIF":2.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"L1CAM is not prognostic factor in HPV-associated adenocarcinoma and adenosquamous cell carcinoma of the uterine cervix.","authors":"Jaroslav Klát, Martina Romanová, Vladimír Židlík, Ondřej Šimetka, Adela Kondé","doi":"10.3233/CBM-240101","DOIUrl":"10.3233/CBM-240101","url":null,"abstract":"<p><strong>Background: </strong>Cervical cancer (CC) is the fourth most common malignancy. The significant prognostic factors are tumor size and lympho-vascular space invasion. Considering that these are nonspecific factors, research has been aimed at finding a specific molecular marker related to a higher incidence of relapse and mortality in patients with CC.</p><p><strong>Objective: </strong>Our study investigated the prognostic value of L1 cell adhesion molecule (L1CAM) expression in rare histological subtypes of cervical cancer (adenocarcinomas and adenosquamous cell carcinomas).</p><p><strong>Methods: </strong>This is a single-institution retrospective study with 35 patients who underwent radical hysterectomy for early-stage cervical adenocarcinoma or adenosquamous cell carcinoma in 2007 through 2017. Paraffin sections of the tumor were used for L1CAM analysis by immunohistochemistry.</p><p><strong>Results: </strong>L1CAM expression was positive in 15 (42.8%) of the 35 tumors. L1CAM expression did not differ significantly in regard to the stage of disease, tumor size, grading, or lymphovascular space invasion (LVSI) (<i>p</i> = 0.619, <i>p</i> = 0.341, <i>p</i> = 0.445, <i>p</i> = 0.999). Progression-free interval and overall survival did not differ between L1CAM-positive and L1CAM-negative groups (<i>p</i> = 0.704, <i>p</i> = 0.386, respectively).</p><p><strong>Conclusions: </strong>In our study, L1CAM expression is not a negative prognostic factor associated with aggressive tumor behavior, recurrence risk and overall survival.</p>","PeriodicalId":56320,"journal":{"name":"Cancer Biomarkers","volume":"41 3","pages":"CBM240101"},"PeriodicalIF":2.2,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}