其他最新文献

{"title":"Two Pulses per Beat: Parallel Energetics of Myocardium and Coronary Wall.","authors":"Manuel F Muñoz, L Fernando Santana","doi":"10.1152/physiol.00023.2026","DOIUrl":"10.1152/physiol.00023.2026","url":null,"abstract":"<p><p>Each heartbeat is initiated by a sinoatrial node action potential that propagates through the myocardial syncytium, triggering sequential contraction of the four chambers and propelling blood through the coronary, pulmonary, and systemic circulations. This mechanical event is fueled by two coupled energetic pulses: one in the working myocardium, where ATP is consumed by Ca²⁺ cycling, cross-bridge cycling, and ion pumping, and a second in the coronary vascular wall, where smooth muscle cells (SMCs), endothelial cells, and pericytes expend ATP to maintain tone, manage Ca²⁺, and coordinate perfusion against systolic compression that arrests their blood supply. Cardiac myocytes and coronary SMCs share the same actomyosin machinery but are activated differently. In myocytes, beat-to-beat Ca²⁺ transients drive Ca²⁺ binding to troponin C to permit synchronous contraction; in coronary SMCs, Ca²⁺/calmodulin activates myosin light chain kinase (MLCK), which phosphorylates myosin to sustain tone. In both cell types, ATP availability sets the ceiling on excitability: when the energetic budget is met, ion pumps, SERCA, and ATP-sensitive channels operate within range and electrical behavior is stable; when it is not, excitability fails. Biosensor measurements reveal beat-to-beat ATP gains and dips in sinoatrial node and ventricular myocytes across systole and diastole. The vascular wall undergoes its own synchronous cycle: systolic compression arrests perfusion while MLCK, SERCA, and K_ir2.1-mediated retrograde signaling compete for a diastolic replenishment window that narrows with each heart rate increment. We propose that cardiac energetics must treat these pulses as coequal, reframing heart failure as a vascular and computational disease of the coronary wall.</p>","PeriodicalId":520753,"journal":{"name":"Physiology (Bethesda, Md.)","volume":" ","pages":"0"},"PeriodicalIF":10.3,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148582078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification.","authors":"Tonmoy Hossain, Miaomiao Zhang","doi":"10.1007/978-3-032-38098-2_38","DOIUrl":"10.1007/978-3-032-38098-2_38","url":null,"abstract":"<p><p>Deformable shape representations have proven to be robust complements to texture features in cardiac image classification, offering geometric priors that are invariant to imaging artifacts and intensity variations. However, existing deep networks perform simple concatenation to combine these distinct feature representations, which neither fully exploits their complementary nature nor learns cross-modal feature dependencies. Furthermore, this results in uniform attention across all timepoints; hence ignoring the varying diagnostic importance across the cardiac phases. In this paper, we propose a novel cardiac video classification model that, for the first time, <i>learns temporal features in an integrated space of deformable shape and image texture representations</i>. In particular, we design a bi-directional cross-attention in the latent space to fuse latent deformable shape and image features, allowing each modality to adaptively weight the other based on spatio-temporal correspondence. In contrast to current methods that apply uniform weighting across all the cardiac phases, our approach learns to dynamically adjust the contributions of shape and texture representations, derived from images, over time. We demonstrate state-of-the-art classification performance on a cine cardiac magnetic resonance (CMR) video dataset, achieving improved interpretability from attention mechanisms that identify diagnostically critical cardiac phases and modality contributions. Our code is publicly available at https://github.com/tonmoy-hossain/ShapeFuse.</p>","PeriodicalId":94280,"journal":{"name":"Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention","volume":"16886 ","pages":"399-409"},"PeriodicalIF":0.0,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13670926/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149217870","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":"Introducing Adolescents to the Social Dimensions of AI through Story-Driven Game-Based Learning.","authors":"Jessica Vandenberg, Bradford Mott, Carlos Penilla, James Lester, Elizabeth Ozer","doi":"10.1007/978-3-032-29773-0_25","DOIUrl":"10.1007/978-3-032-29773-0_25","url":null,"abstract":"<p><p>AI increasingly shapes high-stakes decisions in domains such as education and healthcare, underscoring the importance of engaging K-12 students in AI literacy experiences that foreground societal dimensions of AI, including fairness, bias, and accountability. This paper presents a story-driven, game-based learning environment designed to support middle school students' reasoning about these societal dimensions. In the game, students take on the role of decision-makers evaluating AI models in simulated clinical scenarios, navigating trade-offs between accuracy, training data representativeness, and model appropriateness for specific populations. We report findings from a classroom-based pilot study with adolescents (ages 11-14) examining how students engaged with issues of fairness, bias, and accountability during the intervention. Data sources included brief pre/post knowledge assessments and attitudinal surveys. Results suggest that participation was associated with improvements in students' understanding of AI-supported decision-making and shifts toward more critical perspectives on AI capabilities and limitations. Given the short duration of the intervention and the modest scope of the assessment measures, these findings should be interpreted as preliminary. Nonetheless, this work provides early evidence that narrative-centered, game-based approaches can support student engagement with the societal dimensions of AI and offers design insights for integrating ethical reasoning into classroom-based AI learning experiences.</p>","PeriodicalId":524239,"journal":{"name":"Artificial intelligence in education : 27th international conference, AIED 2026, Seoul, South Korea, June 27-July 3, 2026, proceedings. Part VI. International Conference on Artificial Intelligence in Education (27th : 2026 : Seoul, Kore...","volume":"16586 ","pages":"337-345"},"PeriodicalIF":0.0,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13640418/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149123892","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":"Discovering Heterogeneous Neurodegenerative Disease Patterns From MRI Data for Improved Prediction.","authors":"Yuanwang Zhang, Hongming Li, Yong Fan","doi":"10.1007/978-3-032-38239-9_16","DOIUrl":"10.1007/978-3-032-38239-9_16","url":null,"abstract":"<p><p>Neurodegenerative diseases exhibit substantial heterogeneity, complicating both diagnosis and prognosis. Identifying clinically meaningful subtypes is crucial for understanding disease mechanisms and improving diagnostic precision and prognostic accuracy. Existing subtyping approaches primarily rely on unsupervised learning of patient data for capturing inter-individual variability, but they may fail to uncover subtypes that are directly informative for diagnosis or prognosis. To address this limitation, we propose a novel mixture-of-experts (MoE) framework that integrates predictive modeling with subtype discovery. Unlike traditional subtyping methods, our approach learns a router to assign individuals to specialized expert networks, each corresponding to a distinct subtype, for improving predictive accuracy. By coupling subtype identification with prediction, the proposed MoE framework encourages the discovery of subtypes that are not only statistically distinct but also clinically informative. We evaluate the framework on a real-world dataset of mild cognitive impairment (MCI) subjects and a semi-simulated dataset, demonstrating superior performance in predicting progression from MCI to Alzheimer's disease while revealing distinct, clinically meaningful MCI subtypes. Code is available at https://github.com/Kateridge/MoESubtyping.</p>","PeriodicalId":94280,"journal":{"name":"Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention","volume":"16894 ","pages":"160-170"},"PeriodicalIF":0.0,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13650995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149169297","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":"Gasotransmitters in the regulation of connexins in central and peripheral nervous system injuries.","authors":"Stanislav Rodkin","doi":"10.4103/mgr.MEDGASRES-D-25-00156","DOIUrl":"10.4103/mgr.MEDGASRES-D-25-00156","url":null,"abstract":"<p><p>Gasotransmitters, such as nitric oxide, carbon monoxide, and hydrogen sulfide can freely diffuse across biological membranes, bind to receptors and molecular targets, and modulate multiple intracellular signaling pathways. However, no systematic review exists regarding how gasotransmitters influence central and peripheral nervous system injury by regulating connexins. This review study presents, for the first time, a systematic analysis of the effects of these three gasotransmitters on connexin regulation, with a focus on their potential roles in injuries to the central and peripheral nervous systems. The results of the systematic analysis showed that carbon monoxide can exert both neuroprotective and neurotoxic effects through S-nitrosylation, phosphorylation, and regulation of connexin channels, as well as contribute to neurovascular coupling and ischemic preconditioning. Carbon monoxide primarily modulates connexin activity via the heme oxygenase-1/carbon monoxide/nuclear factor erythroid 2-related factor 2 signaling pathways, demonstrating potential in reducing neuroinflammation and necroptosis. Hydrogen sulfide also affects connexin-related signaling pathways, regulates platelet aggregation and regulatory T cell-mediated immune responses, and supports vascular homeostasis. Importantly, connexins function as molecular hubs integrating gasotransmitter-dependent signals, thereby mediating both secondary injury cascades and neuroregenerative processes. The obtained results indicate that connexins represent promising therapeutic targets, and pharmacological strategies based on gasotransmitters constitute a novel direction in neuroprotection after neural injury. However, the clinical application of these approaches remains limited, and further studies are required to clarify isoform-specific connexin regulation, optimize gasotransmitter delivery systems, and minimize potential systemic toxicity.</p>","PeriodicalId":18559,"journal":{"name":"Medical Gas Research","volume":" ","pages":"139-151"},"PeriodicalIF":4.2,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147988086","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-derived serum carbon dioxide trajectories in predicting prognosis of patients with acute aortic dissection.","authors":"Yong-Bo Zhao, Xin Zhang, Meng-Xin Zhu, Yi-Xuan Wang, Wen-Tao Ding, Xue-Sen Zhao, Dong Ma, Zi-Qiang Tian","doi":"10.4103/mgr.MEDGASRES-D-25-00361","DOIUrl":"10.4103/mgr.MEDGASRES-D-25-00361","url":null,"abstract":"<p><p>Venous partial pressure of carbon dioxide (PvCO 2 ) indicates postoperative adverse outcomes in patients with acute aortic dissection, and its trajectories over time affecting postoperative adverse outcomes remain unclear. This study aimed to investigate the relationship between PvCO 2 trajectories and postoperative adverse outcomes, as well as clinical application through group-based trajectory modeling and machine-learning algorithms. This retrospective cohort study analyzed data from 642 patients with acute aortic dissection treated at the Fourth Hospital of Hebei Medical University from 2019 to 2024, to determine postoperative adverse outcomes, including 6-month mortality and complications. Three PvCO 2 tests within the first 72 hours of admission were used to analyze PvCO 2 trajectories through group-based trajectory modeling. To diagnose high-risk PvCO 2 trajectories in emergency settings, least absolute shrinkage and selection operator regression was conducted to select key features, which were consequently integrated into predictive models using multiple machine-learning methods. Finally, a web-based interpretable website was developed for predicting PvCO 2 trajectories in patients with acute aortic dissection. Overall, 642 patients were classed into four PvCO 2 trajectories (T1, persistent decrease from a medium to a low level; T2, stable low level; T3, persistent decrease from a high to a low level; T4, stable midlevel), showing distinct patterns. After adjustment for other covariates, postoperative adverse outcomes among these groups showed significant differences, with a higher proportion of postoperative adverse outcomes in the T3 group. Subsequently, upon Shapley additive explanations analysis, 17 features with importance sequence were identified (hemoglobin, direct bilirubin, monocyte, adenosine deaminase, drinking, anion gap, chloride, platelet, lymphocyte, albumin/globulin ratio, calcium, alanine aminotransferase, α-L-fucosidase, D-dimer, antihypertensive drugs, and smoking), which were integrated into the model for predicting T3. The optimal machine-learning model was established for predicting postoperative adverse outcomes. Finally, a web-based interpretable model was developed to predict patients with acute aortic dissection and high risk of postoperative adverse outcomes. This study uncovers heterogeneity in PvCO 2 trajectory, highlighting that decreased PvCO 2 is associated with worse prognosis. A web-based tool for the prediction of acute aortic dissection patients at high risk of postoperative adverse outcomes was constructed to facilitate clinical application.</p>","PeriodicalId":18559,"journal":{"name":"Medical Gas Research","volume":" ","pages":"46-54"},"PeriodicalIF":4.2,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148795310","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":"Development and validation of a machine learning-based predictive model for prognosis in cerebral hemorrhage patients after hyperbaric oxygen therapy.","authors":"Congyi Ding, Jun Wu, Guangning Zhang, Xiaoming Feng, Jieyang Zhu","doi":"10.4103/mgr.MEDGASRES-D-25-00168","DOIUrl":"10.4103/mgr.MEDGASRES-D-25-00168","url":null,"abstract":"<p><p>Intracerebral hemorrhage is a common and critical neurological emergency, and the inconsistent results of hyperbaric oxygen therapy make predicting outcomes challenging. Therefore, a reliable predictive model for outcomes is needed to improve treatment plans. This study used interpretable machine learning to determine key risk factors linked to adverse outcomes in cerebral hemorrhage patient post-hyperbaric oxygen therapy. To improve prognostic accuracy and support clinical decision-making, we analyzed the data from 401 patients with intracerebral hemorrhage who received hyperbaric oxygen therapy at the First Affiliated Hospital of Jiaxing, China, using multivariate logistic regression and machine learning to develop predictive models, with model performance assessed via 10-fold cross-validation. SHapley Additive exPlanations values aided in model interpretation and in the development of a logistic regression-based nomogram. Based on the modified Rankin scale, patients were stratified into two prognostic groups: a good prognosis group (modified Rankin scale < 3, n = 265) and a poor prognosis group (modified Rankin scale ≥ 3, n = 136). Significant differences in various factors were observed between the groups. Independent risk factors identified included the Glasgow coma scale score, computed tomography hemorrhage volume, activities of daily living score, treatment modality, intraventricular bleeding, and rebleeding. Among the models tested, the random forest algorithm yielded the highest predictive performance (the area under the receiver operating characteristic curve = 0.99). The study identified key predictors, including activities of daily living score, computed tomography hemorrhage volume, and Glasgow coma scale score, as factors influencing hyperbaric oxygen therapy outcomes in intracerebral hemorrhage patients. Random Forest model demonstrated strong predictive capability, with SHapley Additive exPlanations analysis providing insights into individual risk factors. Overall, these findings are crucial for improving clinical decision-making and personalized treatment.</p>","PeriodicalId":18559,"journal":{"name":"Medical Gas Research","volume":"17 1","pages":"15-21"},"PeriodicalIF":4.2,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148963508","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":"Medical gases and hypertensive disorders of pregnancy: therapeutic mechanisms and research advances.","authors":"Zhiguang Xu, Geng Tian, Di Zhou, Fuju Wu","doi":"10.4103/mgr.MEDGASRES-D-26-00014","DOIUrl":"10.4103/mgr.MEDGASRES-D-26-00014","url":null,"abstract":"<p><p>Hypertensive disorders during pregnancy pose a serious threat to the health of both mothers and infants, yet the range of available clinical treatments is limited. This review summarizes the mechanisms and recent advances in the use of medical gases, such as nitric oxide, hyperbaric oxygen, carbon monoxide and hydrogen sulfide, in the treatment of this condition. These gaseous molecules have unique protective effects, including regulating vascular tone, improving placental blood perfusion and inhibiting oxidative stress and inflammatory responses. However, their clinical application faces major challenges, including precise dose control, optimization of delivery methods and assessment of long-term safety. While this review suggests that medical gas therapy provides new avenues for research and potential applications in the management of hypertensive disorders of pregnancy, it also highlights the need for further basic and clinical studies to clarify their precise mechanisms.</p>","PeriodicalId":18559,"journal":{"name":"Medical Gas Research","volume":"17 1","pages":"242-250"},"PeriodicalIF":4.2,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667357/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148963568","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":"Molecular hydrogen: a potential guardian against environmental radiation damage.","authors":"Yusuke Ichikawa, Bunpei Sato, Yoshiyasu Takefuji, Fumitake Satoh","doi":"10.4103/mgr.MEDGASRES-D-25-00163","DOIUrl":"10.4103/mgr.MEDGASRES-D-25-00163","url":null,"abstract":"<p><p>Molecular hydrogen is known to selectively convert hydroxyl radicals into harmless water and thereby mitigating oxidative stress. Due to hydrogen molecules have masses comparable to protons and neutrons, can also decelerate neutrons and protons present in environmental radiation, thus exerting a physical shielding effect. Through this dual action, chemical radical scavenging and physical radiation shielding, hydrogen may protect cellular integrity and potentially promote biological longevity. In contrast, hydrogen can intervene at the stage of preventing biomolecular damage induced by environmental radiation and provide comprehensive protection at the tissue and cellular levels, uniquely minimizing radiation-induced damage. This review systematically summarizes existing knowledge regarding the antioxidant and radioprotective effects of hydrogen, discusses its role in mitigating oxidative stress and protecting cells from environmental radiation, and proposes a novel hypothesis that hydrogen has universally protected from radiation-induced damage, highlighting its potential for promoting biological longevity.</p>","PeriodicalId":18559,"journal":{"name":"Medical Gas Research","volume":"17 1","pages":"211-216"},"PeriodicalIF":4.2,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667370/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148963590","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":"Rectal ozone insufflation modulates gut microbiota: improving lung function in mice with chronic obstructive pulmonary disease.","authors":"Qinyao Zhao, Xiaofang Zhu, Pengcheng Wang, Shuangjiao Cao, John P Williams, Jianxiong An","doi":"10.4103/mgr.MEDGASRES-D-25-00314","DOIUrl":"10.4103/mgr.MEDGASRES-D-25-00314","url":null,"abstract":"<p><p>Ozone rectal insufflation possesses anti-inflammatory and antioxidant effects and is used for the treatment and prevention of diseases. This study aimed to investigate the effects of ozone rectal insufflation on chronic obstructive pulmonary disease and explore the potential underlying mechanisms from the perspective of gut microbiology. A mouse chronic obstructive pulmonary disease model was established by intratracheal spraying of lipopolysaccharide and elastase. Mice received ozone rectal insufflation intervention following modeling. We found that ozone rectal insufflation improved pulmonary function, alleviated emphysema and pulmonary fibrosis, and reduced inflammatory cytokine levels in the bronchoalveolar lavage fluid of chronic obstructive pulmonary disease mice. Additionally, ozone rectal insufflation modulated the pathogenic-to-beneficial gut bacteria ratio in chronic obstructive pulmonary disease mice. The treatment also led to an upregulation of short-chain fatty acids. The fecal microbiota transplantation results further confirmed that the gut microbiota of ozone rectal insufflation-treated mice was sufficient to attenuate chronic obstructive pulmonary disease symptoms. In summary, our findings indicate that ozone rectal insufflation enhances lung function and reduces inflammation in chronic obstructive pulmonary disease mice by modulating the gut microbiota and its associated metabolites.</p>","PeriodicalId":18559,"journal":{"name":"Medical Gas Research","volume":"17 1","pages":"70-78"},"PeriodicalIF":4.2,"publicationDate":"2027-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667358/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148963622","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}