Computers in biology and medicine最新文献

{"title":"Towards population scale testis volume segmentation in DIXON MRI","authors":"Jan Ernsting ,&nbsp;Philipp Nikolas Beeken ,&nbsp;Lynn Ogoniak ,&nbsp;Jacqueline Kockwelp ,&nbsp;Wolfgang Roll ,&nbsp;Tim Hahn ,&nbsp;Alexander Siegfried Busch ,&nbsp;Benjamin Risse","doi":"10.1016/j.compbiomed.2025.111139","DOIUrl":"10.1016/j.compbiomed.2025.111139","url":null,"abstract":"<div><div>Testis size is known to be one of the main predictors of male fertility, usually assessed in clinical workup via palpation or imaging. Despite its potential, population-level evaluation of testicular volume using imaging remains underexplored. Previous studies, limited by small and biased datasets, have demonstrated the feasibility of machine learning for testis volume segmentation. This paper presents an evaluation of segmentation methods for testicular volume using Magnetic Resonance Imaging data from the UKBiobank. The best model achieves a median dice score of 0.89, compared to median dice score of 0.85 for human interrater reliability on the same dataset, enabling large-scale annotation on a population scale for the first time. Our overall aim is to provide a trained model, comparative baseline methods, and annotated training data to enhance accessibility and reproducibility in testis MRI segmentation research.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111139"},"PeriodicalIF":6.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145198179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on ''Enhancing clinical decision support with physiological waveforms - A multimodal benchmark in emergency care\" by Lopez Alcaraz et al.","authors":"Kaiyuan Liu","doi":"10.1016/j.compbiomed.2025.111140","DOIUrl":"10.1016/j.compbiomed.2025.111140","url":null,"abstract":"","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111140"},"PeriodicalIF":6.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145198227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, synthesis, and pharmacological evaluation of hydrazide–imine diclofenac derivatives with dual anti-inflammatory and anticancer potential","authors":"Lalnun Hruaitluangi ,&nbsp;Lalduhawma Chhakchhuak ,&nbsp;Caroline Malsawmtluangi ,&nbsp;R. Vanlalruata ,&nbsp;Ajmal Koya Pulikkal ,&nbsp;Lalzikpuii Sailo","doi":"10.1016/j.compbiomed.2025.111123","DOIUrl":"10.1016/j.compbiomed.2025.111123","url":null,"abstract":"<div><div>Diclofenac, a widely used nonsteroidal anti-inflammatory drug (NSAID), is effective in treating pain and inflammation and has also shown potential as an anticancer agent, primarily through cyclooxygenase-2 (COX-2) inhibition. However, its therapeutic application is often limited by adverse effects, necessitating the development of new derivatives with improved pharmacological profiles. In this study, two novel diclofenac hydrazide–imine derivatives, DDCH (cyclohexanone-based) and DDAC (acetylacetone-based), were synthesized, structurally characterized, and evaluated through combined computational and experimental approaches. Density functional theory (DFT) calculations provided transition-state and energy profile analyses, while molecular docking and molecular dynamics (MD) simulations established stable interactions of both derivatives with COX-2 and heat shock protein 90 (HSP90), a key oncogenic chaperone. DDAC exhibited particularly strong binding to HSP90, suggesting enhanced anticancer potential compared with diclofenac. <em>In silico</em> drug-likeness and ADME assessments, including Lipinski's Rule of Five, predicted favorable pharmacokinetic properties. Experimental evaluation confirmed anti-inflammatory efficacy: <em>in vitro</em> protein denaturation assays showed that DDAC display inhibition comparable to diclofenac, while <em>in vivo</em> carrageenan-induced paw edema studies demonstrated significant activity for both derivatives. Collectively, these findings confirm that DDCH and DDAC retain anti-inflammatory properties while offering predicted anticancer potential, with DDAC emerging as the more promising dual-action candidate. This work establishes a rational framework for the further optimization and pharmacological development of diclofenac-based analogues targeting both inflammation and cancer.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111123"},"PeriodicalIF":6.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145198245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barbatic acid inhibits inflammatory responses and endothelial dysfunction in hypertension by regulating HIF1A/FLT1 pathway: A computer-aided biolabel research and experimental validation","authors":"Xu-zhao Li ,&nbsp;Zhen-tao Lv ,&nbsp;Xiang Yu,&nbsp;Yan Zhang,&nbsp;Guo-yong Luo,&nbsp;Yi Long,&nbsp;Wu-de Yang","doi":"10.1016/j.compbiomed.2025.111160","DOIUrl":"10.1016/j.compbiomed.2025.111160","url":null,"abstract":"<div><div>Hypertension is a prevalent cardiovascular and cerebrovascular condition encountered in clinical practice. It has emerged as a significant global public health challenge and is the leading risk factor for mortality. Barbatic acid has a pharmacological basis for preventing and treating hypertension, including mechanisms such as diuresis and anti-inflammatory effects. However, its therapeutic potential and mechanism of action remain incompletely understood. The purpose of this study is to investigate the therapeutic potential and mechanisms of action of barbatic acid in the treatment of hypertension. Based on the biolabel-led research model, bioinformatics was employed to conduct a comprehensive analysis of the therapeutic potential, advantages, and mechanisms of action of barbatic acid in treating hypertension. Ang II was utilized to establish a hypertensive cellular model, while L-NAME was employed to create an animal model of hypertension, thereby validating the findings from the biolabel analysis. Bioinformatics indicates that ten biolabels are implicated in the anti-hypertensive mechanism of barbatic acid. The primary targets are HIF1A and FLT1, which primarily contribute to inflammatory responses and endothelial dysfunction. Cell experiments demonstrate that barbatic acid can effectively enhance the proliferation ability of HUVECs and adjust the levels of ten biolabels and downstream targets. Animal experiments demonstrate that barbatic acid can effectively reduce blood pressure in hypertensive mice, significantly ameliorate associated pathological damage in the heart, kidney, and thoracic aorta tissues, and inhibit HIF1A/FLT1 levels in these mice, thereby improving the inflammatory response and endothelial dysfunction. The verification confirmed the analytical results of the biolabel research model. Barbatic acid has the capacity to inhibit the inflammatory response and endothelial dysfunction in hypertension by mediating the HIF1A/FLT1 pathway.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111160"},"PeriodicalIF":6.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145197840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring learning transferability in deep segmentation of colorectal cancer liver metastases","authors":"Marwan Abbas ,&nbsp;Bogdan Badic ,&nbsp;Gustavo Andrade-Miranda ,&nbsp;Vincent Bourbonne ,&nbsp;Vincent Jaouen ,&nbsp;Dimitris Visvikis ,&nbsp;Pierre-Henri Conze","doi":"10.1016/j.compbiomed.2025.111076","DOIUrl":"10.1016/j.compbiomed.2025.111076","url":null,"abstract":"<div><div>Ensuring the seamless transfer of knowledge and models across various datasets and clinical contexts is of paramount importance in medical image segmentation. This is especially true for liver lesion segmentation which plays a key role in pre-operative planning and treatment follow-up. Despite the progress of deep learning algorithms using Transformers, automatically segmenting small hepatic metastases remains a persistent challenge. This can be attributed to the degradation of small structures due to the intrinsic process of feature down-sampling inherent to many deep architectures, coupled with the imbalance between foreground metastases voxels and background. While similar challenges have been observed for liver tumors originated from hepatocellular carcinoma, their manifestation in the context of liver metastasis delineation remains under-explored and require well-defined guidelines. Through comprehensive experiments, this paper aims to bridge this gap and to demonstrate the impact of various transfer learning schemes from off-the-shelf datasets to a dataset containing liver metastases only. Our scale-specific evaluation reveals that models trained from scratch or with domain-specific pre-training demonstrate greater proficiency.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111076"},"PeriodicalIF":6.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale simulation of respiratory airflow using physiologically consistent geometry and boundary conditions in OpenFOAM","authors":"Quoc Hung Nguyen ,&nbsp;Sungchul Huh ,&nbsp;Kum Ju Chae ,&nbsp;Xinguang Cui ,&nbsp;Ching-Long Lin ,&nbsp;Sanghun Choi","doi":"10.1016/j.compbiomed.2025.111131","DOIUrl":"10.1016/j.compbiomed.2025.111131","url":null,"abstract":"<div><div>In computed tomography (CT)-based computational fluid dynamics (CFD) simulations of the human respiratory system, no or few studies have incorporated both realistic upper and lower airways, along with extensions to CT-unresolved higher-generation airways. In this study, we present a CT-based, physiologically consistent CFD model of the human airway that integrates artificial airway extensions down to the transitional bronchioles within the OpenFOAM framework. The model includes a hybrid turbulence approach combining Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES), and a state-of-the-art airway mesh smooth learning (AMSL) technique for constructing accurate airway geometries. Physiologically consistent boundary conditions are applied using airflow data derived from one-dimensional network simulations. We investigate the impact of the hybrid RANS–LES model on airflow characteristics, pressure distribution, and particle deposition by comparing it with conventional turbulence models, including the wall-adapting local eddy-viscosity (WALE) model for LES and the k–ω SST model for RANS. The AMSL method is also evaluated against the traditional Taubin smoothing technique. Our results show that pressure does not monotonically decrease throughout the upper respiratory tract but exhibits a continual decrease in the lower tract, independent of airway generation. The hybrid RANS–LES model demonstrates flow patterns and particle deposition characteristics comparable to those of the LES model and proves an improved fidelity over traditional RANS models. Furthermore, the AMSL technique significantly influences airflow behavior and particle deposition, highlighting the importance of accurate geometry processing. In conclusion, the proposed physiologically consistent CFD model, implemented in the OpenFOAM framework, demonstrates strong potential for clinical and research applications by offering enhanced accuracy and reliability. The use of an integrated airway model, extending from the upper airways to artificially constructed distal airways, facilitates a better understanding of multiscale airflow dynamics in the lungs.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111131"},"PeriodicalIF":6.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of fast subcellular calcium signals based on label-free second harmonic generation microscopy measurements","authors":"Tihomir Georgiev","doi":"10.1016/j.compbiomed.2025.111138","DOIUrl":"10.1016/j.compbiomed.2025.111138","url":null,"abstract":"<div><div>Calcium (Ca²⁺) sparks were predicted based on the label-free second harmonic generation (SHG) signal of myosin filaments with pix2pix, a conditional adversarial network. Predicted Ca²⁺ sparks and ground truth Ca²⁺ sparks show similar properties. Predicted Ca²⁺ spark frequencies and a predominant location at the periphery of skeletal muscle fibers were in good agreement with ground truth data. High frequencies of predicted Ca²⁺ sparks could be observed at y-shaped structures of myosin filaments. Important image pre-processing was applied in order to enhance the signal of Ca²⁺ sparks used for training. Only open-source software was applied. I provide the image pre-processing algorithm and several algorithms to evaluate the quality of predicted Ca²⁺ sparks. This technique can be extended to other label-free microscopy techniques and other fluorescent indicators developed during the last years. It remains a difficult task to predict the exact location of Ca²⁺ sparks.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111138"},"PeriodicalIF":6.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging few-shot learning and large language models for analyzing blood pressure variations across biological sex from scientific literature","authors":"Yuting Guo ,&nbsp;Seyedeh Somayyeh Mousavi ,&nbsp;Yao Ge ,&nbsp;Madhumita Baskaran ,&nbsp;Reza Sameni ,&nbsp;Abeed Sarker","doi":"10.1016/j.compbiomed.2025.111128","DOIUrl":"10.1016/j.compbiomed.2025.111128","url":null,"abstract":"<div><h3>Background:</h3><div>Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often without adjusting BP readings for individual demographic factors such as sex and age. While these standards provide useful guidelines and help identify at-risk patients, they are not fully reliable for diagnosis due to the lack of demographic considerations. This study aims to assess the feasibility of using large language models (LLMs) for the automated extraction of BP-related information from the scientific literature, with a focus on biological sex-based distinctions in BP distributions.</div></div><div><h3>Method:</h3><div>We employed natural language processing (NLP) methods to extract the means and standard deviations of BP values from the literature, distinguishing by biological sex. We developed a Solr-based search engine to retrieve scientific articles containing BP-related keywords and biological sex indicators from PubMed. From the retrieved articles, we created a manually reviewed subset comprising 213 articles including 90 cases that reported BP values based on biological sex. We experimented with one few-shot learning method and two zero-shot LLM-based methods—LLaMA3 and GPT-3.5—to extract the mean and standard deviations of BP values, and the associated biological sex. Based on the automatically-extracted information, we generated heatmaps and contour plots to study the variations of BP values across biological sex.</div></div><div><h3>Results:</h3><div>The inter-annotator agreement (IAA) between the two annotators measured using Cohen’s kappa (McHugh, 2012) was 0.74. The best performing system was LLaMA3 with an F₁ score of 0.85 (<span><math><mo>±</mo></math></span>0.00). The few-shot learning method (DANN) exhibited low performance with an average F₁ score of 0.30 (<span><math><mo>±</mo></math></span>0.01). GPT-3.5 achieved moderate performance with an average F₁ score of 0.67 (<span><math><mo>±</mo></math></span>0.04). The contour plots show that males tend to exhibit higher BP values than females.</div></div><div><h3>Conclusions:</h3><div>Our results demonstrate that LLMs can be reliable in extracting population-level BP and biological sex information from clinical literature. They also outperform traditional low-shot information extraction systems in this context, showcasing their ability to extract BP-related information more accurately and efficiently. By employing LLMs, we provide a scalable framework for analyzing demographic differences in BP and emphasize the broader utility of LLMs in addressing similar challenges in biomedical research.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111128"},"PeriodicalIF":6.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eudesma-4(15), 7-dien-1-β-ol, A promising natural drug candidate for Alzheimer's disease targeting the NMDA pathway: GC-MS identification, molecular docking, pharmacokinetic and molecular dynamic analysis","authors":"Hanane Ferrassi ,&nbsp;Abderrahim Ait Ouchaoui ,&nbsp;Mohammed Hakmi ,&nbsp;Hamza Ghammaz ,&nbsp;Salah Eddine EL Hadad ,&nbsp;Youssra EL-Ghandouri ,&nbsp;Souad Kartti ,&nbsp;Elmostafa El Fahime ,&nbsp;Ilhame Bourais ,&nbsp;Youssef Elouafy","doi":"10.1016/j.compbiomed.2025.111151","DOIUrl":"10.1016/j.compbiomed.2025.111151","url":null,"abstract":"<div><h3>Background</h3><div>Alzheimer's disease (AD) remains a significant global health challenge, with no definitive cure available.</div></div><div><h3>Purpose</h3><div>This study investigates Juglans regia essential oil as a source of therapeutic molecules for AD, targeting the NMDA receptor pathway.</div></div><div><h3>Study design</h3><div><em>&amp; Methods</em>: The essential oil was extracted by hydrodistillation, and the GC-MS analyzed the chemical composition. Antioxidant activity was evaluated using DPPH assay. Molecular docking compared compound affinities to the NMDA receptor against Memantine, with pharmacokinetic analysis evaluating drug-likeness. Interaction and molecular dynamic analysis were also performed.</div></div><div><h3>Results</h3><div>GC-MS identified 34 compounds, predominantly caryophyllene oxide (20.6 %) and β-Eudesmol (10.7 %). The DPPH assay resulted in an IC₅₀ value of 855.34 μg/mL. Eleven compounds showed superior/equivalent affinities (−7.4 kcal/mol) to Memantine. Eudesma-4(15),7-dien-1-β-ol demonstrated exceptional NMDA receptor interaction, outperforming Memantine in binding affinity, interaction quality, and stability in molecular dynamics while meeting drug-likeness criteria.</div></div><div><h3>Conclusion</h3><div>These findings suggest that Eudesma-4(15),7-dien-1-β-ol from <em>J. regia</em> shows promise as an AD therapeutic candidate via NMDA receptor modulation, warranting clinical investigation to assess its therapeutic efficacy and safety.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111151"},"PeriodicalIF":6.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of binding kinetics and mass transport in SPR-based biosensor using the Generalized Integral Transform Technique and the Markov Chain Monte Carlo Method","authors":"Carlos Henrique Rodrigues de Moura ,&nbsp;Carlos Adriano Moreira da Silva ,&nbsp;Josiel Lobato Ferreira ,&nbsp;Emanuel Negrão Macêdo ,&nbsp;João Nazareno Nonato Quaresma ,&nbsp;Renato Machado Cotta","doi":"10.1016/j.compbiomed.2025.111129","DOIUrl":"10.1016/j.compbiomed.2025.111129","url":null,"abstract":"<div><div>The present work addresses biomolecular interactions in Surface Plasmon Resonance (SPR)-based biosensors, explicitly focusing on mass transport and binding kinetics. The Generalized Integral Transform Technique (GITT) is employed to solve the nonlinear system of partial differential equations describing mass transport, while the Markov Chain Monte Carlo (MCMC) method is adopted for accurately estimating the kinetic constants of the model. The outcomes were corroborated with simulated measurements and validated against experimental data related to the binding of the receptor-binding domain (RBD) of the spike protein of SARS-CoV-2 bound to the cell receptor angiotensin-converting enzyme 2 (ACE2) in the Biacore system. Our findings demonstrate the efficacy of the GITT in describing the dynamics of average concentrations of the free analyte and of the bound analyte-receptor complex, aligning with results obtained in prior studies. Furthermore, our results demonstrate that the MCMC method is a robust tool for estimating model kinetic constants, with estimates closely approximating the exact values and falling within a 99 % confidence interval. The estimated average concentrations concurred with simulated measurements, even when accounting for Gaussian noise. The experimental validation results strengthen our conclusions, aligning the model parameter estimates with reference values from the literature. Therefore, this study suggests that the adopted mathematical model and numerical methodology hold significant potential for analyzing and comprehending biomolecule binding data, representing a valuable tool for studying complex biomolecular interactions.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"198 ","pages":"Article 111129"},"PeriodicalIF":6.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145157573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}