Communications medicine最新文献

{"title":"Author Correction: A comprehensive overview of the burden, prevention, and therapeutic aspects of arboviral diseases in India.","authors":"Himanshu Gupta, Pradip V Barde, Mrigendra Pal Singh, Praveen K Bharti, Nitika Nitika","doi":"10.1038/s43856-025-01010-6","DOIUrl":"10.1038/s43856-025-01010-6","url":null,"abstract":"","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"289"},"PeriodicalIF":5.4,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12254312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning-assisted assessment of extracellular vesicles can monitor cellular rejection after heart transplant.","authors":"Jacopo Burrello, Stefano Panella, Ilaria Barison, Chiara Castellani, Alessio Burrello, Lorenzo Airale, Jessica Goi, Veronica Dusi, Roberto Frigerio, Gino Gerosa, Chiara Tessari, Nicola Pradegan, Giuseppe Toscano, Giovanni Pedrazzini, Mattia Corianò, Francesco Tona, Sara Bolis, Alessandro Gori, Marina Cretich, Marny Fedrigo, Annalisa Angelini, Lucio Barile","doi":"10.1038/s43856-025-00999-0","DOIUrl":"10.1038/s43856-025-00999-0","url":null,"abstract":"<p><strong>Background: </strong>Heart transplant rejection, particularly acute cellular rejection (ACR), remains a critical post-operative concern, despite declining incidence rates. Current diagnostic standards rely on invasive endomyocardial biopsy, which presents limitations in sensitivity and reproducibility. There is an unmet need for noninvasive, accurate biomarkers that can detect and monitor rejection. This study aims to evaluate whether extracellular vesicle (EV) surface antigens, analyzed through flow cytometry and interpreted with artificial intelligence (AI), can serve as reliable biomarkers for ACR detection and monitoring in heart transplant recipients.</p><p><strong>Methods: </strong>We conducted a prospective longitudinal cohort study involving 24 heart transplant recipients over a median follow-up of 303 days. A total of 285 blood samples were analyzed for EV surface antigens exploiting two flow cytometry-based protocols. An adaptive AI model (random forest regressor) was developed to interpret EV antigen profiles, dynamically calibrating thresholds per patient.</p><p><strong>Results: </strong>Here we show that 14 EV surface antigens progressively increase with ACR severity. These changes are evident even before histological diagnosis. The AI model achieves an accuracy of 93.3% at leave-one-out testing (AUC 0.968), and 78.9% at validation in an independent cohort (AUC 0.832), with high specificity and negative predictive value. EV profiling outperforms conventional biochemical markers and provides anticipatory insight into rejection dynamics.</p><p><strong>Conclusions: </strong>EV profiling, enhanced by patient-specific AI modeling, offers a powerful noninvasive method for early detection and monitoring of ACR. This approach holds the potential to reduce reliance on biopsies and tailor immunosuppressive strategies more precisely.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"288"},"PeriodicalIF":5.4,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12246144/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous vital sign monitoring of acute Lassa fever using wearable biosensor devices in West Africa.","authors":"Brady Page, Raphaëlle Klitting, Matthias G Pauthner, Steven Steinhubl, Stephan Wegerich, Margaret Kaiser, Foday Alhasan, Edwin Konuwa, Veronica Koroma, Ibrahim Sumah, Jenneh Brima, Tiangay Kallon, Brima Jusu, Sia Mator-Mabay, Mohamed Kamara, Fatima Kamara, Emilia Jaward, Angella Massally, Zainab Kanneh, Michelle McGraw, John Schieffelin, Donald Grant, Kristian G Andersen","doi":"10.1038/s43856-025-01002-6","DOIUrl":"10.1038/s43856-025-01002-6","url":null,"abstract":"<p><strong>Background: </strong>Lassa fever is a fulminant viral illness associated with high in-hospital mortality. This disease constitutes a serious public health concern in West Africa, in particular Nigeria and the Mano River Union region (Guinea, Liberia, and Sierra Leone). In Sierra Leone, continuous monitoring of critically ill patients is hindered by a lack of equipment and personnel.</p><p><strong>Methods: </strong>We used wearable biosensor devices to remotely monitor hospitalized individuals with acute Lassa fever in order to describe vital sign trends that may be associated with clinical outcome and to evaluate the feasibility of this approach in a resource-limited setting.</p><p><strong>Results: </strong>The case fatality rate among participants (n = 8) was 62.5%, with a median time from hospital presentation to death of 2 days. Our results show that non-survivors (n = 5) spent a greater proportion of their monitoring period in the age-specific tachycardia range (45.8%) compared to survivors (1.7%), and had lower mean heart rate variability (10 ms) compared to those that survived (59 ms). Due to inconsistent sensor adhesion, as well as Bluetooth and cellular connectivity issues, over 80% of collected vital sign data was discarded for poor quality.</p><p><strong>Conclusions: </strong>Real-time monitoring of vital signs using wearable biosensors may have the potential to identify individuals at increased risk for poor outcomes in Lassa fever by detecting age-specific tachycardia and reductions in heart rate variability. Whether this represents an improvement upon traditional bedside vital sign collection in resource-limited settings is not clear, as a substantial proportion of monitoring data was of poor quality. Technical improvements in sensor connectivity and adhesion are needed to enable widespread use of this device, for both clinical and research purposes.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"290"},"PeriodicalIF":5.4,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12254359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144621504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The treatment of primary CoQ deficiency requires the targeting of multiple pathogenic mechanisms.","authors":"Pilar González-García, Laura Jiménez-Sánchez, Julia Corral-Sarasa, Sergio López-Herrador, Sara Torres-Rusillo, María Elena Díaz-Casado, Luis C López","doi":"10.1038/s43856-025-01000-8","DOIUrl":"10.1038/s43856-025-01000-8","url":null,"abstract":"<p><strong>Background: </strong>Primary coenzyme Q (CoQ) deficiency is a severe mitochondrial disorder characterized by diverse clinical manifestations due to multiple pathomechanisms. Although CoQ₁₀ supplementation remains the standard treatment, its therapeutic efficacy is limited by poor bioavailability and restricted tissue distribution, especially to the central nervous system.</p><p><strong>Methods: </strong>In this study, we investigated the therapeutic potential of combining CoQ₁₀ with vanillic acid (VA), a structural analog of 4-hydroxybenzoic acid, in both murine and human models of primary CoQ deficiency, through phenotypic, biochemical, and molecular analyses.</p><p><strong>Results: </strong>In Coq9^R239X mice, we demonstrate that co-administration of CoQ₁₀ and VA significantly extends lifespan and improves motor function beyond the effects observed with either compound alone. Mechanistically, this enhanced therapeutic efficacy results from the complementary actions of both compounds, i.e., CoQ₁₀ increases quinone pools in peripheral tissues and modulates one-carbon metabolism, particularly in the liver, while VA reduces DMQ accumulation in the kidney and liver and exhibits potent anti-neuroinflammatory properties, leading to a reduction in gliosis. The co-treatment shows remarkable tissue-specific responses, with the liver displaying the most pronounced metabolic adaptations. In this tissue, the combined therapy restores the expression of genes involved in sulfide oxidation and one-carbon metabolism pathways. We further validate these findings in human COQ7-deficient fibroblasts, where the co-treatment normalizes key metabolic pathways more effectively than individual treatments.</p><p><strong>Conclusions: </strong>Our findings demonstrate that combining CoQ₁₀ with VA effectively addresses multiple pathogenic mechanisms in CoQ deficiency, resulting in enhanced therapeutic outcomes. This therapeutic strategy could represent a more effective and feasible treatment approach for mitochondrial disorders, particularly those involving CoQ deficiency and neurological manifestations.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"286"},"PeriodicalIF":5.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12246469/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adverse childhood experiences increase the long-term accumulation of morbidity in women.","authors":"Walter A Rocca, Liliana Gazzuola Rocca, Carin Y Smith, Dmitry Esterov, Ekta Kapoor, Jennifer L St Sauver, Elizabeth A Stewart, Kejal Kantarci","doi":"10.1038/s43856-025-00961-0","DOIUrl":"10.1038/s43856-025-00961-0","url":null,"abstract":"<p><strong>Background: </strong>The impact of early-life traumatic experiences on late-life morbidity, or chronic conditions, remains unclear. We tested the hypothesis that traumatic adverse childhood experiences, such as physical, verbal, emotional, or sexual abuse, experienced during childhood or early adulthood are associated with a higher rate of morbidity later in life in women.</p><p><strong>Methods: </strong>We studied 1026 women aged 21-45 years randomly selected from the general population in Olmsted County, Minnesota and used the Rochester Epidemiology Project medical records-linkage system to measure the rate of development of 18 chronic conditions. The women had a median age of 41.0 years at inclusion in the study and were followed historically for a median of 21.0 years.</p><p><strong>Results: </strong>Here we show that women who experienced 2 or more adverse childhood experiences have higher incidence of 10 of the 18 chronic conditions considered separately and an accelerated accumulation of chronic conditions measured as a morbidity score compared to women who did not experience any. In addition, women exposed to abuse in childhood or early adulthood have accelerated accumulation of morbidity. We exclude the possible confounding effect of socioeconomic status and explore a series of possible mediation events or characteristics. We also discuss several possible biological and social or behavioral mechanisms underlying these associations.</p><p><strong>Conclusions: </strong>We are reporting new evidence that adverse childhood experiences and abuse in childhood or early adulthood have multiple deleterious effects on late-life morbidity. Our findings indicate the importance of protecting children and young adults from abuse and other adverse events.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"287"},"PeriodicalIF":5.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12246220/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drug combination-wide association studies of cancer.","authors":"Panagiotis Nikolaos Lalagkas, Rachel Dania Melamed","doi":"10.1038/s43856-025-00991-8","DOIUrl":"10.1038/s43856-025-00991-8","url":null,"abstract":"<p><strong>Background: </strong>Combinations of common drugs may, when taken together, have unexpected effects on incidence of diseases like cancer. It is not feasible to test for all combination drug effects in clinical trials, but in the real world, drugs are frequently taken in combination. Then, undiscovered effects may protect users of drug combinations from cancer-or increase their risk. By analyzing massive health data containing numerous people exposed to drug combinations, we have an opportunity to discover these associations.</p><p><strong>Method: </strong>We describe, apply, and evaluate an approach for discovering drug combination associations with cancer using health data. Our approach builds on marginal structural model methods to emulate a randomized trial where one arm is assigned to take a drug alone, while the other arm takes that drug in combination with a second drug.</p><p><strong>Results: </strong>Here, we perform drug combination-wide analysis to estimate effects of over 9000 drug combinations on incidence of all common cancer types, using claims data covering more than 100 million people. But, because the discovery of associations from observational data is always prone to confounding, we develop a number of strategies to distinguish confounding from biomedically relevant findings. We describe a robustly supported beneficial drug combination that may synergistically impact lipid levels to reduce the risk of cancer.</p><p><strong>Conclusions: </strong>These findings can suggest new clinical uses for drug combinations to prevent or treat cancer. Our approach can be adapted to mine electronic health records for interactive effects on other late-onset common diseases.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"285"},"PeriodicalIF":5.4,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12241652/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144602423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of the Toronto recurrence inference using machine-learning for post-transplant hepatocellular carcinoma model.","authors":"Zhihao Li, Itsuko Chih-Yi Chen, Leonardo Centonze, Christian T J Magyar, Woo Jin Choi, Tommy Ivanics, Grainne M O'Kane, Arndt Vogel, Lauren Erdman, Luciano De Carlis, Jan Lerut, Quirino Lai, Vatche G Agopian, Neil Mehta, Chao-Long Chen, Gonzalo Sapisochin","doi":"10.1038/s43856-025-00994-5","DOIUrl":"10.1038/s43856-025-00994-5","url":null,"abstract":"<p><strong>Background: </strong>Organ shortages require prioritizing hepatocellular carcinoma (HCC) patients with the highest survival benefit for allografts. While traditional models like AFP, MORAL, and HALT-HCC are commonly used for recurrence risk prediction, the TRIUMPH model, which uses machine learning, has shown superior performance. This study aims to externally validate the model.</p><p><strong>Methods: </strong>The cohort included 2844 HCC patients who underwent liver transplantation at six international centers from 2000-2022. The TRIUMPH model utilized a regularized Cox proportional hazards approach with a penalty term for coefficient adjustment. Discrimination was assessed using the c-index, and clinical utility was evaluated via decision curve analysis.</p><p><strong>Results: </strong>The most common liver diseases are hepatitis C (49%) and hepatitis B (27%). At listing, 84% meets the Milan criteria, and 91% are within criteria at transplant. Median model for end-stage liver disease score is 10 (IQR:8-14), alpha-fetoprotein level 8 ng/mL (IQR:4-25), and tumor size 2 cm (IQR:1.1-3.0). Living donor grafts are used in 24% of cases. Recurrence rate is 9.1% with a median time to recurrence of 17.5 months. Recurrence-free survival rates at 1/3/5 years are 95.7%/89.5%/87.7%, respectively. The TRIUMPH model achieves the highest c-index (0.71), outperforming MORAL (0.61, p = 0.049) and AFP (0.61, p = 0.04), though not significantly better than HALT-HCC (0.67, p = 0.28). TRIUMPH shows superior clinical utility up to a threshold of 0.6.</p><p><strong>Conclusions: </strong>The TRIUMPH model demonstrates good accuracy and clinical utility in predicting post-transplant HCC recurrence. Its integration into organ allocation could improve transplantation outcomes.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"284"},"PeriodicalIF":5.4,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144593076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeted in vivo gene integration of a secretion-enabled GLP-1 receptor agonist reverses diet-induced non-genetic obesity and pre-diabetes.","authors":"Jun Hirose, Emi Aizawa, Shogo Yamamoto, Shigenori Iwai, Keiichiro Suzuki","doi":"10.1038/s43856-025-00959-8","DOIUrl":"10.1038/s43856-025-00959-8","url":null,"abstract":"<p><strong>Background: </strong>In vivo genome editing offers a long-term therapeutic approach for monogenic diseases by directly modifying genetic sequences. However, its application to non-monogenic, noncommunicable diseases, which are the leading causes of global mortality, remains limited due to the lack of well-defined genetic targets.</p><p><strong>Methods: </strong>We developed an in vivo genome-editing approach to introduce a gene encoding the glucagon-like peptide-1 (GLP-1) receptor agonist Exendin-4, modified with a secretion signal peptide. Mice with obesity and pre-diabetic conditions received a single administration of genome editing. Blood Exendin-4 levels, food intake, body weight, and metabolic parameters were monitored over several months.</p><p><strong>Results: </strong>Here we show that in vivo genome editing enables sustained Exendin-4 secretion from liver cells, leading to prolonged elevation of Exendin-4 levels in the bloodstream. Treated mice exhibited reduced food intake, attenuated weight gain, and improved glucose metabolism and insulin sensitivity without detectable adverse effects.</p><p><strong>Conclusions: </strong>This study demonstrates that a single administration of genome editing can achieve sustained therapeutic peptide secretion, providing a potential strategy for treating complex diseases without defined genetic causes.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"269"},"PeriodicalIF":5.4,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12241343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144602425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased testing is needed for Mpox in DR Congo to urgently curb disease spread.","authors":"Prince Imani-Musimwa, Placide Mbala-Kingebeni, Stéphane Hans-Bateyi-Mustafa, Alfred Ombeni-Musimwa, Mija Ververs","doi":"10.1038/s43856-025-00813-x","DOIUrl":"10.1038/s43856-025-00813-x","url":null,"abstract":"","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"280"},"PeriodicalIF":5.4,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12241371/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144602424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning approaches to dissect hybrid and vaccine-induced immunity.","authors":"Giorgio Montesi, Simone Costagli, Simone Lucchesi, Jacopo Polvere, Fabio Fiorino, Gabiria Pastore, Margherita Sambo, Mario Tumbarello, Massimiliano Fabbiani, Francesca Montagnani, Donata Medaglini, Elena Pettini, Annalisa Ciabattini","doi":"10.1038/s43856-025-00987-4","DOIUrl":"10.1038/s43856-025-00987-4","url":null,"abstract":"<p><strong>Background: </strong>The spread of SARS-CoV-2 Omicron variant and its subvariants, highly transmissible but responsible of milder disease, has increased unreported infection cases. Identifying unaware infected individuals is crucial for estimating the true prevalence of infection and evaluating the breadth of hybrid immunity. In this study, this challenge was addressed by applying several Machine Learning approaches.</p><p><strong>Methods: </strong>A group of 116 participants, vaccinated against SARS-CoV-2, was enrolled in the IMMUNO_COV study at Siena University Hospital, Italy. Blood samples were collected before and six months after third vaccine dose. Machine Learning analysis, involving dimensionality reduction techniques, unsupervised clustering methods and classification models, were applied to serological data including antibody responses specific for wild type SARS-CoV-2 strain as well as Delta, Omicron BA.1 and Omicron BA.2 variants. Spike- and nucleocapsid-specific B cells were also assessed in each participant.</p><p><strong>Results: </strong>Using dimensionality reduction and unsupervised clustering, participants are grouped into high- and low-responders, with infected participants mainly distributed within the high-responders. Implementation of a consensus-based approach, including k-NN, RF, and SVM models, identifies 14 participants unaware of previous infection. Their immunological profile, characterized by strong spike- and nucleocapsid-specific humoral and B cell responses, significantly differs from that of non-infected participants.</p><p><strong>Conclusions: </strong>Machine Learning approaches are applied to identify participants unaware of prior infection and to dissect their hybrid immunity profiles. Based on serological data, this cost-effective method can be a valuable tool for estimating the true prevalence of infection, improving comprehension of immune responses elicited by vaccination alone or combined with infection, and tailoring public health interventions.</p>","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":"5 1","pages":"282"},"PeriodicalIF":5.4,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144593074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}