Critical reviews in clinical laboratory sciences最新文献

{"title":"Machine learning models for acute kidney injury prediction and management: a scoping review of externally validated studies.","authors":"Aqeeb Ur Rehman, Javier A Neyra, Jin Chen, Lama Ghazi","doi":"10.1080/10408363.2025.2497843","DOIUrl":"https://doi.org/10.1080/10408363.2025.2497843","url":null,"abstract":"<p><p>Despite advancements in medical care, acute kidney injury (AKI) remains a major contributor to adverse patient outcomes and presents a significant challenge due to its associated morbidity, mortality, and financial cost. Machine learning (ML) is increasingly being recognized for its potential to transform AKI care by enabling early prediction, detection, and facilitating an individualized approach to patient management. This scoping review aims to provide a comprehensive analysis of externally validated ML models for the prediction, detection, and management of AKI. We systematically searched for relevant literature from inception to 15 February 2024, using four databases-MEDLINE, EMBASE, Web of Science, and Scopus. We focused solely on models that had undergone external validation, employed Kidney Disease Improving Global Outcomes (KDIGO) definitions for AKI, and utilized ML models (excluding logistic regression models). A total of 44 studies encompassing 161 ML models for AKI prediction, severity assessment, and outcomes in both adult and pediatric populations were included in the review. These studies encompassed 4,153,424 patient admissions, with 1,209,659 in the development and internal validation cohorts and 2,943,765 in the external validation cohorts. The ML models demonstrated significant variability in performance owing to differing clinical settings, populations, and predictors used. Most of the included models were developed in specialized patient populations, such as those in intensive care units, post-surgical settings, and specific disease states (e.g. congestive heart failure, traumatic brain injury, etc.). Moreover, only a few models incorporated dynamic predictors of AKI which are crucial for improving clinical utility in rapidly evolving clinical conditions like AKI. The variable performance of these models when applied to external validation cohorts highlights the challenges of reproducibility and generalizability in implementing ML models in AKI care. Despite acceptable performance metrics, none of the models assessed in this review underwent validation or implementation in real-world clinical workflows. These findings underscore the need for standardized performance metrics and validation protocols to enhance the generalizability and clinical applicability of these models. Future efforts should focus on enhancing model adaptability by incorporating dynamic predictors and unstructured data and by ensuring that models are developed in diverse patient populations. Moreover, collaboration between clinicians and data scientists is critical to ensure the development of models that are clinically relevant, fair, and tailored to real-world healthcare environments.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"1-23"},"PeriodicalIF":6.6,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143982756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishing, evaluating and monitoring analytical quality in the traceability era.","authors":"Mauro Panteghini, Magdalena Krintus","doi":"10.1080/10408363.2024.2434562","DOIUrl":"10.1080/10408363.2024.2434562","url":null,"abstract":"<p><p>Poor analytical quality may be the bane of medical use of laboratory tests, and the fight against excessive analytical variability presents a daily struggle. Laboratories should prioritize the perspectives and needs of their customers (the patients and healthcare personnel). Among them, comparability of results from the same patient sample when measured by different laboratories using different <i>in vitro</i> diagnostic (IVD) medical devices is a logical priority to avoid result misinterpretation and potential patient harm. Harmonization (standardization) of laboratory measurements can be achieved by establishing metrological traceability of the results on clinical samples to stated higher-order references and providing an estimate of the uncertainty of measurement (MU). This estimate should be based on an MU budget including all known MU contributions generated by the employed calibration hierarchy, which in turn should be validated against fit-for-purpose maximum allowable MU derived according to internationally recommended models. In this report, we review the available strategies for establishing, evaluating, and monitoring analytical quality, drawing on three decades experience in the field. We discuss the most important aspects that may influence obtaining and maintaining analytical standardization in laboratory medicine, and offer practical solutions aimed at educating all stakeholders for the achievement of harmonized laboratory results. To fully implement the recommended approaches, all involved parties-i.e. reference providers, IVD manufacturers, medical laboratories, and External Quality Assessment organizers-must agree on their importance and enhance their specific knowledge.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"148-181"},"PeriodicalIF":6.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142913842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical and clinical considerations of synovial fluid calprotectin in diagnosing periprosthetic joint infections.","authors":"Mohammed F Alkadhem, Paul C Jutte, Marjan Wouthuyzen-Bakker, Anneke C Muller Kobold","doi":"10.1080/10408363.2025.2463634","DOIUrl":"10.1080/10408363.2025.2463634","url":null,"abstract":"<p><p>Calprotectin is a protein predominantly found in the cytosol of myeloid cells, such as neutrophils and monocytes. Calprotectin has several functions in innate immunity, such as attenuating bacteria, recruiting and activating immune cells, and aiding in the production of pro-inflammatory cytokines and reactive oxygen species. Due to its presence in inflammatory sites, it has been investigated as a biomarker for various medical conditions, especially Inflammatory bowel diseases (IBD), rheumatoid arthritis (RA), and has gained interest in the diagnosis of several infectious diseases, in particular for diagnosing periprosthetic joint infections (PJI). Synovial fluid calprotectin has demonstrated to be a sensitive and specific biomarker for both confirming as well as excluding PJI. Synovial fluid calprotectin can be measured using enzyme-linked immunosorbent assay (ELISA), immunoturbidimetry, and lateral flow methods. It is a generally stable biomarker, showing no significant decrease or increase in its levels despite blood or lipid contamination, storage duration, freeze-thaw cycles, and enzymatic pretreatments for viscosity reduction. This review discusses the biology and physiology of calprotectin, pathophysiology of PJI, and the clinical and analytical considerations surrounding its use in diagnosing PJI.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"228-239"},"PeriodicalIF":6.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143448251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The intersection of the laboratory and transgender care.","authors":"Kevin Jessen, Nilika Wijeratne, Ailie Connell","doi":"10.1080/10408363.2025.2488839","DOIUrl":"https://doi.org/10.1080/10408363.2025.2488839","url":null,"abstract":"<p><p>Transgender and gender diverse (TGD) individuals seeking gender affirming treatment are an increasing demographic in today's society; such treatments include hormonal and surgical interventions aimed at alleviating gender dysphoria and increasing quality of life. A number of diagnostic pathology tests are provided to medical professionals with sex specific reference intervals (RIs) for interpretation, due to sex specific physiological differences, organ size and hormone levels for example. These tests may be reported with RIs that are not appropriate, and interpretation for the medical professional can be challenging. From the laboratory perspective, there are limitations in Laboratory Information Management Systems (LIMS) and the ability of these databases to record both sex and gender identifiers, as well as the reporting of appropriate RIs. The use of RIs derived from the transgender population is complex, studies generally have a low sample size and include adults with long established hormonal treatments. The age of an individual undergoing gender affirming therapy has decreased, and the use of Gonadotrophin Releasing Hormone analogues adds complexity. In this review, we will discuss the current challenges and perspectives regarding the reporting of reference intervals in the TGD population, the derivation of personalized or transgender specific RIs and interpretation of specific diagnostic tests.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"1-16"},"PeriodicalIF":6.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144062545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is this test fit-for-purpose? Principles and a checklist for evaluating the clinical performance of a test in the new era of <i>in vitro</i> diagnostic (IVD) regulation.","authors":"S J Lord, A R Horvath, S Sandberg, P J Monaghan, C M Cobbaert, M Reim, A Tolios, R Mueller, P M Bossuyt","doi":"10.1080/10408363.2025.2453148","DOIUrl":"10.1080/10408363.2025.2453148","url":null,"abstract":"<p><p>Recent changes in the regulatory assessment of <i>in vitro</i> medical tests reflect a growing recognition of the need for more stringent clinical evidence requirements to protect patient safety and health. Under current regulations in the United States and Europe, when needed for regulatory approval, clinical performance reports must provide clinical evidence tailored to the intended purpose of the test and allow assessment of whether the test will achieve the intended clinical benefit. The quality of evidence must be proportionate to the risk for the patient and/or public health. These requirements now cover both commercial and laboratory developed tests (LDT) and demand a sound understanding of the fundamentals of clinical performance measures and study design to develop and appraise the study plan and interpret the study results. However, there is a lack of harmonized guidance for the laboratory profession, industry, regulatory agencies and notified bodies on how the clinical performance of tests should be measured. The Working Group on Test Evaluation (WG-TE) of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) is a multidisciplinary group of laboratory professionals, clinical epidemiologists, health technology assessment experts, and representatives of the <i>in vitro</i> diagnostic (IVD) industry. This guidance paper aims to promote a shared understanding of the principles of clinical performance measures and study design. Measures of classification performance, also referred to as discrimination, such as sensitivity and specificity are firmly established as the primary measures for evaluating the clinical performance for screening and diagnostic tests. We explain these measures are just as relevant for other purposes of testing. We outline the importance of defining the most clinically meaningful classification of disease so the clinical benefits of testing can be explicitly inferred for those correctly classified, and harm for those incorrectly classified. We introduce the key principles and a checklist for formulating the research objective and study design to estimate clinical performance: (1) the purpose of a test e.g. diagnosis, screening, risk stratification, prognosis, prediction of treatment benefit, and corresponding research objective for assessing clinical performance; (2) the target condition for clinically meaningful classification; (3) clinical performance measures to assess whether the test is fit-for-purpose; and (4) study design types. Laboratory professionals, industry, and researchers can use this checklist to help identify relevant published studies and primary datasets, and to liaise with clinicians and methodologists when developing a study plan for evaluating clinical performance, where needed, to apply for regulatory approval.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"182-197"},"PeriodicalIF":6.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143254902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From population-based to personalized laboratory medicine: continuous monitoring of individual laboratory data with wearable biosensors.","authors":"Abdurrahman Coskun, Irem Nur Savas, Ozge Can, Giuseppe Lippi","doi":"10.1080/10408363.2025.2453152","DOIUrl":"10.1080/10408363.2025.2453152","url":null,"abstract":"<p><p>Monitoring individuals' laboratory data is essential for assessing their health status, evaluating the effectiveness of treatments, predicting disease prognosis and detecting subclinical conditions. Currently, monitoring is performed intermittently, measuring serum, plasma, whole blood, urine and occasionally other body fluids at predefined time intervals. The ideal monitoring approach entails continuous measurement of concentration and activity of biomolecules in all body fluids, including solid tissues. This can be achieved through the use of biosensors strategically placed at various locations on the human body where measurements are required for monitoring. High-tech wearable biosensors provide an ideal, noninvasive, and esthetically pleasing solution for monitoring individuals' laboratory data. However, despite significant advances in wearable biosensor technology, the measurement capacities and the number of different analytes that are continuously monitored in patients are not yet at the desired level. In this review, we conducted a literature search and examined: (i) an overview of the background of monitoring for personalized laboratory medicine, (ii) the body fluids and analytes used for monitoring individuals, (iii) the different types of biosensors and methods used for measuring the concentration and activity of biomolecules, and (iv) the statistical algorithms used for personalized data analysis and interpretation in monitoring and evaluation.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"198-227"},"PeriodicalIF":6.6,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laboratory test utilization and effect on clinical outcomes in a pediatric setting.","authors":"Ridwan B Ibrahim, Anil K Chokkalla, Adetoun A Ejilemele, Sridevi Devaraj","doi":"10.1080/10408363.2025.2494614","DOIUrl":"https://doi.org/10.1080/10408363.2025.2494614","url":null,"abstract":"<p><p>Given recent economic concerns, there has been pressure on the health-care system to improve efficiency, quality and reduce cost. The clinical laboratory is now under close scrutiny to adopt \"practicing to value\" which involves shifting its focus from performing many tests to performing only necessary tests. To achieve this, clinical laboratories have been implementing strategies for effective laboratory test utilization and participating in health outcome studies to provide evidenced-based insights on test utilization, clinical decision-making and policy improvements. It is essential to highlight the full spectrum of this additional role of the clinical laboratory to administrators, policy makers and other health-care stakeholders, as clinical laboratories are an easy target for economic restrictions. This review highlights how strategic stewardship implementation by a clinical laboratory improves clinical outcomes in a pediatric setting.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"1-8"},"PeriodicalIF":6.6,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143976606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The current state in liquid chromatography-mass spectrometry methods for quantifying kynurenine pathway metabolites in biological samples: a systematic review.","authors":"Md Munnaf Hossen, Bobbi Fleiss, Rosita Zakaria","doi":"10.1080/10408363.2025.2495160","DOIUrl":"https://doi.org/10.1080/10408363.2025.2495160","url":null,"abstract":"<p><p>Kynurenine pathway (KP) metabolites are implicated in various disorders, including Alzheimer's disease, schizophrenia, and adverse pregnancy outcomes. Simultaneous measurement of multiple KP metabolites offers valuable insight into the pathway's role in health and disease, would improve this relatively undeveloped field. This systematic review aim was to summarize the state of the art for measuring the eight key KP metabolites, using liquid chromatography-mass spectrometry (LC-MS), explicitly focusing on whether methods were validated using established guidelines with superior sensitivity and selectivity. We undertook a comprehensive review of the literature using the PRISMA guidelines. Our search uncovered 66 publications, and 39 qualified the defined key criteria. We summarized each publication's method development parameters, analytical design, and method performance specifications. We found notable variability in sample preparation techniques and analytical design across biological matrices, underscoring a lack of universally established and validated methods for KP metabolite quantification. We also identified significant gaps in the basic method evaluation. Our findings highlight that no single method has been evaluated for quantifying the eight key KP metabolites across three or more biological sample types, revealing a critical gap in the field. Our review emphasizes the need for robust analytical methods to quantify KP metabolites across multiple biological matrices, facilitating a better understanding of their roles in health and disease. Given the diversity of disorders involving the KP in the clinical testing lab, developing such methods will reduce diagnostic errors and advance KP metabolite research, supporting more precise, and personalized medical care.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"1-17"},"PeriodicalIF":6.6,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143977776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of laboratory practices for CSF oligoclonal banding and associated tests.","authors":"Victoria Higgins, Yu Chen, Mark S Freedman, Karina Rodriguez-Capote, Daniel R Beriault","doi":"10.1080/10408363.2025.2490166","DOIUrl":"https://doi.org/10.1080/10408363.2025.2490166","url":null,"abstract":"<p><p>Multiple sclerosis (MS) is a chronic autoimmune disorder affecting the central nervous system, often emerging in early adulthood and representing a leading cause of neurological disability in young adults. Diagnosing MS involves a combination of clinical assessment, imaging and laboratory tests, with cerebrospinal fluid (CSF)-specific immunoglobulin G (IgG) oligoclonal bands (OCB) being an important marker for fulfilling the dissemination in time criteria. A recent survey of Canadian clinical laboratories highlighted considerable variation in OCB reporting practices nationwide, spanning quality control (QC) practices, acceptable time limits between paired CSF and serum sample collections, protocols for reporting band counts, interpretation and reporting of mirrored patterns, testing panels, and interpretive thresholds. These inconsistencies impact patient care and the comparability of laboratory results across different laboratories. The Harmonized CSF Analysis for MS Investigation (hCAMI) subcommittee of the Canadian Society of Clinical Chemists Reference Interval Harmonization Working Group was established to generate recommendations for laboratory processes and reporting of CSF OCB and associated tests supporting MS diagnosis. This review serves as a foundation for these efforts, summarizing the available evidence in areas where practice variations have been noted. This review begins by examining current practices and guidelines for standardized quality assurance, including optimal QC materials, frequency, documentation, and participation in external quality assurance programs. The disparity between paired CSF and serum sample acceptability time limits was further examined by reviewing current practices and recommendations as well as compiling evidence on IgG synthesis, turnover rate, biological variation, and stability in CSF and serum samples. Additionally, this review addresses the lack of consensus on reporting the number of CSF-specific and CSF-serum matched bands, focusing on interpreter variability and clinical utility. Contributing factors and clinical implications of mirror patterns, including discussion on monoclonal gammopathies and cases of matched bands of differing staining intensity, is provided. Testing panel components including adjunctive CSF tests, such as the IgG index, to support MS investigations despite their absence from clinical guidelines is also discussed. This review also provides a comprehensive analysis of current practices, guidelines, and the evidence surrounding different cutoffs for IgG index and CSF-specific bands.</p><p><p>Finally, the review considers emerging biomarkers, such as the kappa free light chain index and serum neurofilament light chain, which show promise for MS diagnosis and management. This comprehensive review of current practices, guidelines, and evolving evidence will guide the hCAMI subcommittee's efforts to harmonize CSF OCB analysis and improve MS diagnosis.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"1-23"},"PeriodicalIF":6.6,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143978477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rigorous validation of machine learning in laboratory medicine: guidance toward quality improvement.","authors":"Hunter A Miller, Roland Valdes","doi":"10.1080/10408363.2025.2488842","DOIUrl":"https://doi.org/10.1080/10408363.2025.2488842","url":null,"abstract":"<p><p>The application of artificial intelligence (AI) in laboratory medicine will revolutionize predictive modeling using clinical laboratory information. Machine learning (ML), a sub-discipline of AI, involves fitting algorithms to datasets and is broadly used for data-driven predictive modeling in various disciplines. The majority of ML studies reported in systematic reviews lack key aspects of quality assurance. In clinical laboratory medicine, it is important to consider how differences in analytical methodologies, assay calibration, harmonization, pre-analytical errors, interferences, and physiological factors affecting measured analyte concentrations may also affect the downstream robustness and reliability of ML models. In this article, we address the need for quality improvement and proper validation of ML classification models, with the goal of bringing attention to key concepts pertinent to researchers, manuscript reviewers, and journal editors within the field of pathology and laboratory medicine. Several existing predictive modeling guidelines and recommendations can be readily adapted to the development of ML models in laboratory medicine. We summarize a basic overview of ML and key points from current guidelines including advantages and pitfalls of applied ML. In addition, we draw a parallel between validation of clinical assays and ML models in the context of current regulatory frameworks. The importance of classification performance metrics, model explainability, and data quality along with recommendations for strengthening journal submission requirements are also discussed. Although the focus of this article is on the application of ML in laboratory medicine, many of these concepts extend into other areas of medicine and biomedical science as well.</p>","PeriodicalId":10760,"journal":{"name":"Critical reviews in clinical laboratory sciences","volume":" ","pages":"1-20"},"PeriodicalIF":6.6,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143955362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}