Current Research in Translational Medicine最新文献

{"title":"Efficacy of mesenchymal stem cell transplantation therapy to mitigate psoriasis: A systematic review and meta-analysis","authors":"Rahul Dey ,&nbsp;Amitava Das","doi":"10.1016/j.retram.2025.103504","DOIUrl":"10.1016/j.retram.2025.103504","url":null,"abstract":"<div><div>Psoriasis is a chronic inflammatory skin disease characterized by red lesions and skin patches with silvery scales. Overall, 2 - 3 % of the worldwide population is affected by psoriasis. Recent treatment strategies for psoriasis involve Mesenchymal stromal/stem cell (MSC) transplantation instead of conventional treatment with monoclonal antibodies and small molecule drugs. However, studies systematically determining the efficacy of MSC therapy to treat psoriasis are lacking. Three electronic databases, including Cochrane, PubMed, and Web of Science Library, were searched for related studies from 2013 to 2023 using a widespread list of key terms. Among the collected records, duplicates and non-relevant articles were removed by screening the title, abstract, and full text based on the inclusion and exclusion criteria. Data were extracted from the eligible full-text articles to perform the meta-analysis, determining MSC therapy's efficacy in treating psoriasis. In the screening process, five clinical and sixteen preclinical studies, including 1 study with both preclinical and clinical data, showing the efficacy of MSC transplantation therapy to mitigate psoriasis were eligible for the systematic review. The meta-analysis was based on the data extracted from 10 eligible preclinical studies involving 343 animals. Pooled results demonstrated that the Psoriasis Area and Severity Index (PASI) score and the epidermal thickness of the psoriatic plaques in the animals post-MSC transplantation were significantly reduced. Our meta-analysis showed the efficacy of MSC transplantation therapies in mitigating psoriasis in preclinical animal models. Thus, further clinical research is warranted to translate these findings from bench to bedside.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103504"},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563471","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":"Denutrition status prevails over a standard AML risk assessment in older adults","authors":"Laura Simon ,&nbsp;Alexis Caulier ,&nbsp;Céline Berthon ,&nbsp;Thomas Boyer ,&nbsp;Véronique Harrivel ,&nbsp;Magalie Joris ,&nbsp;Isabelle Leduc ,&nbsp;Nicolas Duployez ,&nbsp;Claude Preudhomme ,&nbsp;Jean-Pierre Marolleau ,&nbsp;Delphine Lebon","doi":"10.1016/j.retram.2025.103500","DOIUrl":"10.1016/j.retram.2025.103500","url":null,"abstract":"<div><div>Older adults with acute myeloid leukemia (AML) have a poor prognosis because frailty and the characteristics of the disease limit the use of intensive chemotherapy (ICT). Treatment with 5-azacitidine (5-AZA) or low-dose cytarabine (Cytarabine) (LDAC) – with or without venetoclax – is currently recommended in this setting. However, we lack real-life data on response rates and treatment outcomes.</div><div>We conducted a retrospective, multicenter registry study of 279 older adults with AML (median [interquartile range (IQR)] age: 76 [70–81]) having undergone first-line treatment with LDAC (<em>n</em> = 87) or 5-AZA (<em>n</em> = 192) between 2009 and 2019 (i.e. mainly before the venetoclax era) in a university medical center in France. The complete remission rate was 27.3 % overall. After a median follow-up period of 6.9 months, the median [IQR] overall survival (OS) time was shorter in the LDAC group (4.8 months [2.13–14.41]) than in the 5-AZA group (8.9 months [3.2–13.5]; <em>p</em> = 0.046). Ultimately, however, the OS rates were similar in the LDAC and 5-AZA groups (hazard ratio [HR]: 95 % confidence interval [CI]: 1.37 [0.92–2.04], <em>p</em> = 0.12).</div><div>None of the conventional markers with prognostic value in younger patients receiving ICT (such as those in the European LeukemiaNet classification) appeared to predict the outcome in our population of older patients. Albumin &lt;30 g/L was the only factor that predicted day-30 mortality and OS (adjusted odds ratio [95 %CI]: 6.25 [2.08 – 20.0]; <em>p</em> &lt; 0.001; adjusted HR [95 %CI]: 0.65 [0.44–0.96]; <em>p</em> = 0.030).</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103500"},"PeriodicalIF":3.2,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-assisted computational screening and docking simulation prioritize marine natural products for small-molecule PCSK9 inhibition","authors":"Neelakandan Annamalai Ramalakshmi ,&nbsp;Muthu Kumar Thirunavukkarasu ,&nbsp;Fayaz Shaik ,&nbsp;Krishna Navami ,&nbsp;Rajanikant Golgodu Krishnamurthy","doi":"10.1016/j.retram.2025.103498","DOIUrl":"10.1016/j.retram.2025.103498","url":null,"abstract":"<div><div>SARS-CoV-2 infection has been associated with long-term cardiovascular complications including myocarditis and heart failure, as well as central nervous system sequelae such as cognitive dysfunction and neuropathy. Proprotein convertase subtilisin/Kexin type 9 (PCSK9), a hepatic protease involved in cholesterol regulation, has shown associations with a spectrum of diseases potentially relevant to these Covid-19 complications, such as atherosclerosis. To identify novel human PCSK9 inhibitors, a custom virtual screening pipeline was developed employing (1) a convolutional neural network-based deep learning model, (2) molecular docking using Schrödinger with Glide scoring function, and (3) molecular dynamics (MD) simulations with Gibbs Free Energy Landscape analysis. The deep learning model was trained on a dataset of known central nervous system, cardiovascular, and anti-inflammatory acting drugs and used to screen the CMNPD database. Docking simulations were performed on shortlisted candidates, followed by MD simulations and free energy landscape analysis to evaluate binding affinities and identify key interaction residues. This multi-step in-silico approach identified promising PCSK9 inhibitor candidates with favorable binding profiles, suggesting that AI-assisted virtual screening can be a powerful tool for discovering novel therapeutic agents.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103498"},"PeriodicalIF":3.2,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387413","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":"Post-transplant cyclophosphamide in matched donor transplantation: are we there yet?","authors":"Lorenzo Lazzari ,&nbsp;Gloria Catalano ,&nbsp;Alessandro Bruno ,&nbsp;Daniele Sannipoli ,&nbsp;Maria Teresa Lupo-Stanghellini ,&nbsp;Jacopo Peccatori ,&nbsp;Fabio Ciceri ,&nbsp;Raffaella Greco","doi":"10.1016/j.retram.2025.103499","DOIUrl":"10.1016/j.retram.2025.103499","url":null,"abstract":"<div><div>Graft-versus-host disease (GvHD) is a frequent cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (alloHCT) and optimal approaches for its prevention have been recently updated. Post-transplant cyclophosphamide (PTCy) has demonstrated impressive results in the setting of haploidentical donor transplantation, allowing for a more widespread application of alloHCT. For this reason, over the years, several groups have implemented the use of PTCy in the context of transplantation from HLA-matched related and unrelated donors, as a replacement for standard GvHD prophylaxis based on calcineurin inhibitors and methotrexate. With increasing results from retrospective studies and new insights from prospective clinical trials, this comprehensive reevaluation of the literature aims to clarify the precise role of PTCy in this context. This review will summarize and critically discuss the overall results of the use of PTCy in alloHCT from HLA-matched donors, unmet needs, and future perspectives.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103499"},"PeriodicalIF":3.2,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143350451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in drug repurposing: Advancing cardiovascular disease management in geriatric populations","authors":"Murali Krishna Moka ,&nbsp;Melvin George ,&nbsp;Deepalaxmi Rathakrishnan ,&nbsp;V Jagadeeshwaran ,&nbsp;Sriram D K","doi":"10.1016/j.retram.2025.103496","DOIUrl":"10.1016/j.retram.2025.103496","url":null,"abstract":"<div><div>Drug repurposing is a promising strategy for managing cardiovascular disease (CVD) in geriatric populations, offering efficient and cost-effective solutions. CVDs are prevalent across all age groups, with a significant increase in prevalence among geriatric populations. The middle-age period (40–65 years) is critical due to factors like obesity, sedentary lifestyle, and psychosocial stress. In individuals aged 65 and older, the incidence of CVDs is highest due to age-related physiological changes and prolonged exposure to risk factors. In this review we find that certain drugs, such as non-cardiovascular drugs like anakinra, probenecid, N-acetyl cysteine, quercetin, resveratrol, rapamycin, colchicine, bisphosphonates, hydroxychloroquine, SGLT-2i drugs, GLP-1Ras drugs and sildenafil are recommended for drug repurposing to achieve cardiovascular benefits in geriatric patients. However, agents such as canakinumab, methotrexate, ivermectin, erythromycin, capecitabine, carglumic acid, chloroquine, and furosemide are constrained in their therapeutic use and warrant meticulous consideration, rendering them less favorable for this specific application. This review emphasizes the importance of exploring alternative therapeutic strategies to improve outcomes in geriatric populations and suggests drug repurposing as a promising avenue to enhance treatment efficacy.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103496"},"PeriodicalIF":3.2,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143030324","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":"Identifying potential prognosis markers in relapsed multiple myeloma via integrated bioinformatics analysis and biological experiments","authors":"Yong Xu ,&nbsp;Xinya Cao ,&nbsp;He Zhou ,&nbsp;Han Xu ,&nbsp;Bing Chen ,&nbsp;Hua Bai","doi":"10.1016/j.retram.2025.103495","DOIUrl":"10.1016/j.retram.2025.103495","url":null,"abstract":"<div><h3>Background</h3><div>Almost all multiple myeloma (MM) patients will eventually develop disease that has relapsed with or become refractory to current therapeutic regimes. However, the pervious clinical parameters have been proved inaccurate for defining MM relapse, and molecular targets have become the focuses of interests. Prognostic predictions based on molecular targets have been more effective to this day. Our research was performed to demonstrate hub genes involving relapsed MM by bioinformatics and biological experiments.</div></div><div><h3>Methods and results</h3><div>The integrated bioinformatics analysis in baseline and relapsed MM patients were executed. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were utilized to analyze biologic functions of up-regulated differentially expressed genes (DEGs). Four hub genes (CENPE, ASPM, TOP2A and FANCI) were adopted for construction of relapsed gene score model (RGS), and RGS model was evaluated in two testing sets. The CENPE inhibitor GSK923295 had anti-myeloma effect, including promoting cell death, cell cycle arrest and DNA damage of MM cell lines.</div></div><div><h3>Conclusion</h3><div>Through bioinformatics analysis, we found that the four hub genes (CENPE, ASPM, TOP2A and FANCI) were associated to cell cycle, nuclear division, mitosis and spindle. Our research provided proof-of-concept that RGS model could be utilized to estimate recurrence risk and prognosis for patients, and targeting CENPE contributed to developing novel therapeutic pattern for MM.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103495"},"PeriodicalIF":3.2,"publicationDate":"2025-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016497","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":"Advances in the relationship of immune checkpoint inhibitors and DNA damage repair","authors":"Xiaolin Liu ,&nbsp;Shan Wang ,&nbsp;Hongwei Lv ,&nbsp;Enli Chen ,&nbsp;Li Yan ,&nbsp;Jing Yu","doi":"10.1016/j.retram.2025.103494","DOIUrl":"10.1016/j.retram.2025.103494","url":null,"abstract":"<div><div>Cancer immunotherapy, alongside surgery, radiation therapy, and chemotherapy, has emerged as a key treatment modality. Immune checkpoint inhibitors (ICIs) represent a promising immunotherapy that plays a critical role in the management of various solid tumors. However, the limited efficacy of ICI monotherapy and the development of primary or secondary resistance to combination therapy remain a challenge. Consequently, identifying molecular markers for predicting ICI efficacy has become an area of active clinical research. Notably, the correlation between DNA damage repair (DDR) mechanisms and the effectiveness of ICI treatment has been established. This review outlines the two primary pathways of DDR, namely, the homologous recombination repair pathway and the mismatch repair pathway. The relationship between these key genes and ICIs has been discussed and the potential of these genes as molecular markers for predicting ICI efficacy summarized.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103494"},"PeriodicalIF":3.2,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016489","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":"The impact of artificial intelligence and machine learning in organ retrieval and transplantation: A comprehensive review","authors":"David B. Olawade ,&nbsp;Sheila Marinze ,&nbsp;Nabeel Qureshi ,&nbsp;Kusal Weerasinghe ,&nbsp;Jennifer Teke","doi":"10.1016/j.retram.2025.103493","DOIUrl":"10.1016/j.retram.2025.103493","url":null,"abstract":"<div><div>This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks. Predictive analytics further enable personalized treatment plans by forecasting organ rejection, infection risks, and patient recovery trajectories, thereby supporting early intervention strategies and long-term patient management. AI also optimizes operational efficiency within transplant centers by predicting organ demand, scheduling surgeries efficiently, and managing inventory to minimize wastage, thus streamlining workflows and enhancing resource allocation. Despite these advancements, several challenges hinder the widespread adoption of AI and ML in organ transplantation. These include data privacy concerns, regulatory compliance issues, interoperability across healthcare systems, and the need for rigorous clinical validation of AI models. Addressing these challenges is essential to ensuring the reliable, safe, and ethical use of AI in clinical settings. Future directions for AI and ML in transplantation medicine include integrating genomic data for precision immunosuppression, advancing robotic surgery for minimally invasive procedures, and developing AI-driven remote monitoring systems for continuous post-transplantation care. Collaborative efforts among clinicians, researchers, and policymakers are crucial to harnessing the full potential of AI and ML, ultimately transforming transplantation medicine and improving patient outcomes while enhancing healthcare delivery efficiency.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103493"},"PeriodicalIF":3.2,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142958844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of a stromal-related prognostic model in acute myeloid leukemia by comprehensive bioinformatics analysis","authors":"Laya Khodayi Hajipirloo ,&nbsp;Maryam Nabigol ,&nbsp;Reza Khayami ,&nbsp;Najibe Karami ,&nbsp;Mehdi Allahbakhshian Farsani ,&nbsp;Amir Abbas Navidinia","doi":"10.1016/j.retram.2025.103492","DOIUrl":"10.1016/j.retram.2025.103492","url":null,"abstract":"<div><h3>Background</h3><div>Stromal cells play a pivotal role in the tumor microenvironment (TME), significantly impacting the progression of acute myeloid leukemia (AML). This study sought to develop a stromal-related prognostic model for AML, aiming to uncover novel prognostic markers and therapeutic targets.</div></div><div><h3>Methods</h3><div>RNA expression data and clinical profiles of AML patients were retrieved from the Cancer Genome Atlas (TCGA). The extent of stromal cell infiltration within the TME was quantified using the ESTIMATE algorithm. Associations between stromal scores and the French-American-British (FAB) classification, overall survival (OS), and the Cancer and Leukemia Group B (CALGB) cytogenetic risk categories were analyzed. Differentially expressed genes (DEGs) were identified, and gene ontology (GO) and protein-protein interaction (PPI) networks were constructed. Prognostic DEGs were selected through LASSO-cox regression analysis. A risk score model was then developed based on these DEGs. A stromal-related prognostic model (SPM) was constructed from the patients' risk scores (RS), and its efficacy was evaluated using Receiver Operating Characteristic (ROC) curves and a nomogram. The association between FAB, CALGB, age, and common mutations and SPM was also assessed. Ultimately, the SPM was validated using an external dataset from 246 patients in the TARGET-AML study.</div></div><div><h3>Results</h3><div>Kaplan-Meier analysis revealed a significant association between stromal scores and patient survival (<em>p</em> = 0.04). LASSO<img>Cox regression identified four genes (MAP7D2, CDRT1, HOXB9, and IRX5) as highly predictive of survival. The prognostic model showed a strong correlation with overall survival, with higher scores indicating poorer outcomes (<em>p</em> = 1.48e-07). Older patients (over 60 years) faced significantly worse prognoses (<em>p</em> = 0.0055). Although no significant association was found between the SPM and the FAB classification (<em>p</em> = 0.063), both poor and intermediate/normal cytogenetic groups had significantly higher SPM risk scores than the favorable group (<em>p</em> = 0.0057 and 0.0026). External validation of the SPM in the TARGET-AML dataset confirmed a significant association with survival (<em>p</em> = 0.00035), with the area under the curve (AUC) for 10-year survival at 75.81 %.</div></div><div><h3>Conclusion</h3><div>Our research successfully established a stromal-related prognostic model in AML, offering new perspectives for prognostic evaluation and identifying potential targets for therapeutic intervention.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 2","pages":"Article 103492"},"PeriodicalIF":3.2,"publicationDate":"2025-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143016494","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":"Caspases in PANoptosis","authors":"Kaiyuan Song ,&nbsp;Yongbin Wu ,&nbsp;Sipin Tan","doi":"10.1016/j.retram.2025.103502","DOIUrl":"10.1016/j.retram.2025.103502","url":null,"abstract":"<div><div>Recent studies prove that the three well-established cell death pathways—pyroptosis, apoptosis, and necroptosis—are not isolated but rather engage in extensive crosstalk. PANoptosis, a newly identified pathway of inflammatory regulated cell death (RCD), integrates characteristics of apoptosis, pyroptosis, and necroptosis. Caspases are a family of conserved cysteine proteases that play critical roles in pyroptosis, apoptosis, and necroptosis. Similarly, caspases also play a role in PANoptosis. In this paper, we review the molecular mechanisms of these three RCDs and the crosstalk between them. We also delineate the discovery of PANoptosis and its association with disease. Furthermore, we discuss the caspase function in PANoptosis, mainly focusing on caspase-6 and caspase-8 molecules. This review describes the key molecules, especially caspases, in the context of PANoptosis research, aiming to provide a foundation for targeted interventions in PANoptosis-associated diseases.</div></div>","PeriodicalId":54260,"journal":{"name":"Current Research in Translational Medicine","volume":"73 1","pages":"Article 103502"},"PeriodicalIF":3.2,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471431","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}