Diagnostics最新文献

{"title":"Study of MicroRNA-192 as an Early Biomarker for Diagnosis of Diabetic Nephropathy.","authors":"Mohamad Motawea, Mayada S Khalel, Ismail Kandil, Ahmed Mohsen Faheem, Maysaa El Sayed Zaki, Mostafa Abdelsalam, Fady Kyrillos","doi":"10.3390/diagnostics15121504","DOIUrl":"10.3390/diagnostics15121504","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Diabetic nephropathy (DN) is a serious complication of diabetes mellitus. This clinical condition is diagnosed through the detection of microalbuminuria. Molecular biomarkers such as MicroRNA-192 may play a role in the early diagnosis of this condition. This study aims to compare the serum concentrations of MicroRNA-192 in diabetic patients with and without DN and in healthy individuals. <b>Methods:</b> This study was a retrospective case-control study that included three groups. Group I included diabetic patients without DN, Group II included patients with DN, and Group III included healthy control subjects. Blood samples were obtained from each participant and subjected to a full biochemical study including creatinine, albumin, and the detection of MicroRNA-192 by real-time polymerase chain reaction. <b>Results:</b> There were significant differences among the MicroRNA-192 levels in the three groups (<i>p</i>-0.001). There was a significant increase in the MicroRNA-192 level in Group I (1.35 ± 7 0.5) compared with Group II (0.65 ± 7 0.2, <i>p</i>3 = 0.001) and Group III (0.83 ± 7 0.3, <i>p</i>1-0.001). There was a significant reduction in the MicroRNA-192 level in Group II compared with Group III (<i>p</i>2-0.001). <b>Conclusions:</b> This study highlights the potential role of serum miR-192 as a noninvasive biomarker for the early detection of DN in patients with type 2 DM. Our findings demonstrated that serum miR-192 levels were significantly reduced in patients with DN compared with diabetic patients without nephropathy and healthy controls, suggesting the possible protective role of miR-192 in early disease stages.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191681/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Concept of the \"Standard Human\" in the Assessment of Individual Total Heart Size: Lessons from Non-Contrast-Enhanced Cardiac CT Examinations.","authors":"Maciej Sosnowski, Zofia Parma, Marcin Syzdół, Grzegorz Brożek, Jan Harpula, Michał Tendera, Wojciech Wojakowski","doi":"10.3390/diagnostics15121502","DOIUrl":"10.3390/diagnostics15121502","url":null,"abstract":"<p><p><b>Background:</b> This single-center retrospective observational study reviewed data from 2305 persons examined for coronary artery calcium (CAC) with non-contrast-enhanced cardiac CT. Other cardiac structures, including chamber volumes, were evaluated besides the CAC scoring. We proposed a novel body size indexing measure that may outperform common indices for quantifying total heart volume (THV). <b>Methods:</b> This index is the sum of height and the difference between height (unitless) and body surface area (unitless), [h+(h-BSA)], and if the (h-BSA) equals \"zero\", it is a feature of the \"standard human\". <b>Results:</b> We found that, in subjects with a low cardiovascular (CV) risk, the THV normalized for the novel index was simply a function of BW gain, being the highest in obese. If high-CV-risk features (hypertension, diabetes) were present, the measured THV was larger than expected for BW gain, exceeding values observed in low-CV-risk ones. Differences were found to be sex-independent in all BMI categories. <b>Conclusions:</b> Common BSA correction hides these differences and makes the prognostication of CV risk error-introducing. The indexation we proposed might help distinguish the effects of body weight gain from the ones resulting from the presence of certain cardiovascular diseases.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12192549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ViSwNeXtNet Deep Patch-Wise Ensemble of Vision Transformers and ConvNeXt for Robust Binary Histopathology Classification.","authors":"Özgen Arslan Solmaz, Burak Tasci","doi":"10.3390/diagnostics15121507","DOIUrl":"10.3390/diagnostics15121507","url":null,"abstract":"<p><p><b>Background:</b> Intestinal metaplasia (IM) is a precancerous gastric condition that requires accurate histopathological diagnosis to enable early intervention and cancer prevention. Traditional evaluation of H&E-stained tissue slides can be labor-intensive and prone to interobserver variability. Recent advances in deep learning, particularly transformer-based models, offer promising tools for improving diagnostic accuracy. <b>Methods:</b> We propose ViSwNeXtNet, a novel patch-wise ensemble framework that integrates three transformer-based architectures-ConvNeXt-Tiny, Swin-Tiny, and ViT-Base-for deep feature extraction. Features from each model (12,288 per model) were concatenated into a 36,864-dimensional vector and refined using iterative neighborhood component analysis (INCA) to select the most discriminative 565 features. A quadratic SVM classifier was trained using these selected features. The model was evaluated on two datasets: (1) a custom-collected dataset consisting of 516 intestinal metaplasia cases and 521 control cases, and (2) the public GasHisSDB dataset, which includes 20,160 normal and 13,124 abnormal H&E-stained image patches of size 160 × 160 pixels. <b>Results:</b> On the collected dataset, the proposed method achieved 94.41% accuracy, 94.63% sensitivity, and 94.40% F1 score. On the GasHisSDB dataset, it reached 99.20% accuracy, 99.39% sensitivity, and 99.16% F1 score, outperforming individual backbone models and demonstrating strong generalizability across datasets. <b>Conclusions:</b> ViSwNeXtNet successfully combines local, regional, and global representations of tissue structure through an ensemble of transformer-based models. The addition of INCA-based feature selection significantly enhances classification performance while reducing dimensionality. These findings suggest the method's potential for integration into clinical pathology workflows. Future work will focus on multiclass classification, multicenter validation, and integration of explainable AI techniques.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12192024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Challenges in Enteropathies: A Histopathological Review.","authors":"Iulia Enache, Ioan-Cristian Nedelcu, Marina Balaban, Daniel Vasile Balaban, Alina Popp, Mariana Jinga","doi":"10.3390/diagnostics15121511","DOIUrl":"10.3390/diagnostics15121511","url":null,"abstract":"<p><p>Various enteropathies, including immune-mediated (IME) and infection-related conditions, can lead to small intestinal mucosal injury and malabsorption. While immune dysregulation plays a central role in diseases like celiac disease and autoimmune enteropathy, other conditions such as small intestinal bacterial overgrowth (SIBO) and tropical sprue (TS) involve infectious or microbial pathogenesis. Common clinical manifestations include weight loss, chronic diarrhea, and nutritional deficiencies. While celiac disease (CD) remains the most prevalent IME in adults, an expanding spectrum of non-celiac enteropathies has been recognized, including autoimmune enteropathy (AIE), common variable immunodeficiency disease (CVID), olmesartan-induced enteropathy, tropical sprue, and small intestinal bacterial overgrowth. These conditions often present with overlapping clinical, serological, and histological features, complicating their differentiation from CD. Accurate diagnosis is critical for the timely initiation of effective treatment to prevent disease progression and associated complications such as severe malabsorption and enteropathy-associated T-cell lymphoma (EATL). The small intestine plays a dual role in nutrient absorption and immune regulation, making it uniquely vulnerable to immune dysregulation. In IMEs, hyperactive immune responses disrupt intestinal homeostasis, leading to mucosal damage and impaired nutrient absorption. Although CD is the prototypical IME, increasing the recognition of non-celiac IMEs, it highlights the need for a more nuanced approach to small bowel biopsy interpretation. This review explores the histopathological and clinical features of common IMEs, with a focus on distinguishing non-celiac disorders that mimic CD. By enhancing the understanding of these conditions, this review aims to improve diagnostic accuracy, facilitate appropriate therapeutic interventions, and mitigate complications associated with delayed or misdiagnosis. A multidisciplinary approach involving gastroenterologists and pathologists is emphasized to optimize outcomes for patients with IMEs. Immune-mediated enteropathies result from an abnormal immune response of the small intestinal mucosa to non-pathogenic molecules, often leading to malabsorption syndrome. The most common symptoms include weight loss, chronic diarrhea, and nutritional deficiencies. While celiac disease (CD) is the most well-known immune-mediated enteropathy (IME) in adults, other related disorders have been identified in recent years. These conditions share many clinical and histopathological features, therefore making differentiations between them challenging. This study aims to review the most common immune-mediated enteropathies, with a focus on non-celiac disorders that should be considered in the differential diagnosis of celiac disease in small bowel biopsies.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards an Integrated Multi-Omic Approach to Improve the Diagnostic Accuracy of Fine-Needle Aspiration in Thyroid Nodules with Indeterminate Cytology.","authors":"Monia Bordoni, Nairus Aboud, Francesca Silvetti, Augusto Taccaliti, Giancarlo Balercia, Gianmaria Salvio","doi":"10.3390/diagnostics15121506","DOIUrl":"10.3390/diagnostics15121506","url":null,"abstract":"<p><p>Thyroid nodules are accidentally found in up to 68% of people undergoing neck ultrasound (US) examination, and fine needle aspiration (FNA) is the current gold standard to discriminate between malignancy and benign lesions. Unfortunately, one-third of FNAs are classified as indeterminate, requiring surgery for definitive diagnosis. This leads to high costs and health risks of unnecessary procedures, since malignancies are observed in less than half of operative specimens. This narrative review aims to describe the most innovative multi-omics approach techniques, including genomics, proteomics, and metabolomics, aimed at making the preoperative evaluation of indeterminate thyroid nodules more accurate. The advantages and disadvantages of the techniques are described in detail, and a SWOT (strengths, weaknesses, opportunities, and threats) analysis of the multi-omic approach is provided.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12192114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Heart Disease Diagnosis Using ECG Signal Reconstruction and Deep Transfer Learning Classification with Optional SVM Integration.","authors":"Mostafa Ahmad, Ali Ahmed, Hasan Hashim, Mohammed Farsi, Nader Mahmoud","doi":"10.3390/diagnostics15121501","DOIUrl":"10.3390/diagnostics15121501","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Accurate and efficient diagnosis of heart disease through electrocardiogram (ECG) analysis remains a critical challenge in clinical practice due to noise interference, morphological variability, and the complexity of overlapping cardiac signals. <b>Methods</b>: This study presents a comprehensive deep learning (DL) framework that integrates advanced ECG signal segmentation with transfer learning-based classification, aimed at improving diagnostic performance. The proposed ECG segmentation algorithm introduces a distinct and original approach compared to prior research by integrating adaptive preprocessing, histogram-based lead separation, and robust point-tracking techniques into a unified framework. While most earlier studies have addressed ECG image processing using basic filtering, fixed-region cropping, or template matching, our method uniquely focuses on automated and precise reconstruction of individual ECG leads from noisy and overlapping multi-lead images-a challenge often overlooked in previous work. This innovative segmentation strategy significantly enhances signal clarity and enables the extraction of richer and more localized features, boosting the performance of DL classifiers. The dataset utilized in this work of 12 lead-based standard ECG images consists of four primary classes. <b>Results</b>: Experiments conducted using various DL models-such as VGG16, VGG19, ResNet50, InceptionNetV2, and GoogleNet-reveal that segmentation notably enhances model performance in terms of recall, precision, and F1 score. The hybrid VGG19 + SVM model achieved 98.01% and 100% accuracy in multi-class classification, along with average accuracies of 99% and 97.95% in binary classification tasks using the original and reconstructed datasets, respectively. <b>Conclusions</b>: The results highlight the superiority of deep, feature-rich models in handling reconstructed ECG signals and confirm the value of segmentation as a critical preprocessing step. These findings underscore the importance of effective ECG segmentation in DL applications for automated heart disease diagnosis, offering a more reliable and accurate solution.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191851/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From Target Product Profiles (TPPs) to Target Specimen Profiles (TSPs): A New Concept in Infectious Disease Biobanking for Diagnostic Applications.","authors":"Fay Betsou, Warren Fransman, Patrick Lammie","doi":"10.3390/diagnostics15121503","DOIUrl":"10.3390/diagnostics15121503","url":null,"abstract":"<p><p>A target specimen profile (TSP) corresponds to the required characteristics of the specimen panels needed to demonstrate that a diagnostic kit meets the target product profile (TPP). TSPs can guide biobanks in the prospective collection of sample panels to support the development and validation of diagnostics.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191804/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Hôtel-Dieu MRI Classification of Uterosacral Ligament Involvement in Endometriosis: A Pictorial Guide to Clinical Use.","authors":"Siegfried Hélage, Claudia Laponche, Margaux Homps, Jonathan Dong, Lucas Rivière, Frédéric Préaux, Pierre-Alexandre Just, Nizar Aflak, Jean-Noël Buy, Élisabeth Dion","doi":"10.3390/diagnostics15121508","DOIUrl":"10.3390/diagnostics15121508","url":null,"abstract":"<p><p><b>Objectives:</b> Endometriosis is a common gynecologic condition characterized by the presence of endometrial-like tissue outside the uterus, often leading to pelvic pain and infertility. Diagnosis is frequently delayed, with prolonged diagnostic wandering that could be improved through enhanced first-line radiologic assessment. The uterosacral ligament (USL) is the most frequent site of deep infiltrating endometriosis (DIE). The Hôtel-Dieu (HTD) MRI classification, published in 2024, offers a structured framework for evaluating USL involvement by correlating MRI findings with the diagnostic certainty of endometriosis. <b>Key Findings:</b> This pictorial essay provides a practical guide for applying the HTD MRI classification, presenting key imaging criteria with illustrative examples for each USL type. The classification distinguishes between \"linear\" and \"nodular\" USL lesions, with implications for diagnostic confidence. \"Nodular\" types demonstrate a 100% positive predictive value (PPV), while \"linear\" types may yield higher false positive rates (FPR). The HTD MRI classification may also be complemented by innovative biomarker testing, such as microRNA signatures, especially in cases with \"linear\" USL involvement. <b>Conclusions:</b> By standardizing the assessment of USL lesions, the HTD MRI classification enhances diagnostic accuracy, improves MRI reproducibility, and supports earlier identification of endometriosis in first-line settings. Its integration into radiologic workflows can contribute to reduced diagnostic delays. <b>Implications for practice:</b> The HTD MRI classification is a valuable screening tool for first-line radiologists and clinicians. Incorporating it into routine pelvic MRI interpretations may streamline diagnostic pathways, promote consistency across readers, and guide additional testing strategies, such as microRNA assays, for cases where MRI alone is less definitive.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12192483/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-Frequency Domain Analysis of Quantitative Electroencephalography as a Biomarker for Dementia.","authors":"Chanda Simfukwe, Seong Soo A An, Young Chul Youn","doi":"10.3390/diagnostics15121509","DOIUrl":"10.3390/diagnostics15121509","url":null,"abstract":"<p><p>Biomarkers currently used to diagnose dementia, including Alzheimer's disease (AD), primarily detect molecular and structural brain changes associated with the condition's pathology. Although these markers are pivotal in detecting disease-specific neuropathological hallmarks, their association with the clinical manifestations of dementia frequently remains poorly defined and exhibits considerable variability. These biomarkers may show abnormalities in cognitively healthy individuals and frequently fail to accurately represent the severity of cognitive and functional impairments in individuals with dementia. Research indicates that synaptic degeneration and functional impairment occur early in the progression of AD and exhibit the strongest correlation with clinical symptoms. This identifies brain functional impairment measurements as promising early indicators for AD detection. Electroencephalography (EEG), a non-invasive and cost-effective method with high temporal resolution, is used as a biomarker for the early detection and diagnosis of AD through frequency-domain analysis of quantitative EEG (qEEG). Many researchers demonstrate that qEEG measures effectively identify disruptions in neuronal activity, including alterations in activity patterns, topographical distribution, and synchronization. Specific findings along the stages of AD include impaired neuronal synchronization, generalized EEG slowing, and an increase in lower-frequency bands accompanied by a decrease in higher-frequency bands of resting state EEG. Moreover, qEEG helps clinicians effectively correlate indicators of AD neuropathology and distinguish between various forms of dementia, positioning it as a promising, low-cost, non-invasive biomarker for dementia. However, additional clinical investigation is required to clarify the diagnostic and prognostic significance of qEEG measurements as early functional markers for AD. This narrative review examines time-frequency domain qEEG analysis as a potential biomarker across various types of dementia. Through a structured search of PubMed and Scopus, we identified studies assessing spectral and connectivity-based qEEG features. Consistent findings include EEG slowing, reduced functional connectivity, and network desynchronization. The review outlines key methodological challenges, such as lack of standardization and limited longitudinal validation, and recommends integrative, multimodal approaches to enhance diagnostic precision and clinical applicability.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12192203/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Misconceptions Yield Misleading Results. Comment on Wong et al. Comparative Study of Eclipse and RayStation Multi-Criteria Optimization-Based Prostate Radiotherapy Treatment Planning Quality. <i>Diagnostics</i> 2024, <i>14</i>, 465.","authors":"Björn Hårdemark","doi":"10.3390/diagnostics15121493","DOIUrl":"10.3390/diagnostics15121493","url":null,"abstract":"<p><p>The study by Wong et al [...].</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 12","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191525/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}