工程技术最新文献

{"title":"Effects of dendritic properties on the correlations in ionic channels emerging from firing rate homeostasis: a two-compartment modeling study.","authors":"Guosheng Yi, Jiayi Cui, Ruifeng Bai","doi":"10.1007/s11571-025-10297-z","DOIUrl":"10.1007/s11571-025-10297-z","url":null,"abstract":"<p><p>Homeostatic regulation of firing rate is an important feature of neural excitability, which is achieved through feedback control of diverse ionic channel expression levels. The output firing rate is controlled by the active currents and passive properties of the dendrites. The objective of this study is to determine how dendritic properties affect the homeostatic regulation of somatic firing rate. We used a two-compartment Pinsky-Rinzel model to simulate action potentials in a pyramidal neuron in response to external inputs. We applied a feedback framework to determine the maximum ionic conductances during homeostatic regulation and examined the pairwise correlations among these conductances. We find that the effective regulation of somatic firing rate could be achieved through controlling both somatic and dendritic ionic channels. The correlations among these channels are lower than those emerging from the regulation through the control of somatic or dendritic channels. It is also shown that increasing the number of adjustable channels alters ionic channel correlations when the additional channel has a strong compensatory relationship with other channels. Compared to the coupling conductance between two compartments, varying the proportion of area occupied by the dendrite produces a greater effect on firing rate dynamics and expression correlations between adjustable channels in both dendrite and soma. The results reveal that dendritic ionic channels, morphological feature and dendritic-somatic coupling are all factors that influence the correlations in ionic channel expression. These findings provide a biophysical basis for the relationship between dendritic properties and neuronal information processing.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-025-10297-z.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"107"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209171/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144552511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of transcranial magneto-acoustical stimulation on excitatory and inhibitory neuronal discharge patterns.","authors":"Yiming Li, Haoyu Qiu, Haijun Zhu","doi":"10.1007/s11571-025-10290-6","DOIUrl":"10.1007/s11571-025-10290-6","url":null,"abstract":"<p><p>Transcranial Magneto-Acoustical Stimulation (TMAS) represents an innovative, highly efficacious, and non-invasive modality for brain stimulation. Neurons, as integral components of neural networks, are crucial for the transmission of information. Nevertheless, the impact of TMAS on the discharge patterns of both excitatory and inhibitory neurons is not yet fully understood. To address this gap, the Hodgkin-Huxley neuronal model is analyzed using the improved Euler method. The neuronal discharge patterns are comprehensively examined by systematically adjusting ion channel parameters and stimulation parameters. The results indicate that ultrasound frequency exerted minimal influence on the properties of neuronal action potentials. Conversely, as the static magnetic field strength and ultrasound power are augmented, the excitability of both types of neurons progressively enhances. However, the changes in the electrical properties of action potentials are less pronounced in inhibitory neurons compared to excitatory neurons. Furthermore, alterations in ion channel parameters significantly influence the firing characteristics of both types of neurons. The present study elucidates that TMAS has a significant effect on the firing patterns of excitatory and inhibitory neurons. Excitatory neurons showed stronger regular discharges in response to static magnetic fields and increased ultrasound power, whereas inhibitory neurons did not respond to low-intensity static magnetic fields. In addition, our systematic analysis revealed synergistic effects between ion channel parameters and TMAS stimulation parameters. These findings shed light on how neuron type specificity and ion channel dynamics work together to shape the efficacy of TMAS, thus advancing previous studies.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"108"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144552512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction.","authors":"","doi":"10.1080/21691401.2025.2478352","DOIUrl":"10.1080/21691401.2025.2478352","url":null,"abstract":"","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"138"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143623276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain analysis to approach human muscles synergy using deep learning.","authors":"Elham Samadi, Fereidoun Nowshiravan Rahatabad, Ali Motie Nasrabadi, Nader Jafarnia Dabanlou","doi":"10.1007/s11571-025-10228-y","DOIUrl":"10.1007/s11571-025-10228-y","url":null,"abstract":"<p><p>Brain signals and muscle movements have been analyzed using electroencephalogram (EEG) data in several studies. EEG signals contain a lot of noise, such as electromyographic (EMG) waves. Further studies have been done to improve the quality of the results, though it is thought that the combination of these two signals can lead to a significant improvement in the synergistic analysis of muscle movements and muscle connections. Using graph theory, this study examined the interaction of EMG and EEG signals during hand movement and estimated the synergy between muscle and brain signals. Mapping of the brain diagram was also developed to reconstruct the muscle signals from the muscle connections in the brain diagram. The proposed method included noise removal from EEG and EMG signals, graph feature analysis from EEG, and synergy calculation from EMG. Two methods were used to estimate synergy. In the first method, after calculating the brain connections, the features of the communication graph were extracted and then synergy estimating was made with neural networks. In the second method, a convolutional network created a transition from the matrix of brain connections to the synergistic EMG signal. This study reached the high correlation values of 99.8% and maximum MSE error of 0.0084. Compared to other graph-based methods, this method based on regression analysis had a very significant performance. This research can lead to the improvement of rehabilitation methods and brain-computer interfaces.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"44"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11846801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143491021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Respiratory modulation of beta corticomuscular coherence in isometric hand movements.","authors":"Zhibin Li, Jingyao Sun, Tianyu Jia, Linhong Ji, Chong Li","doi":"10.1007/s11571-025-10245-x","DOIUrl":"10.1007/s11571-025-10245-x","url":null,"abstract":"<p><p>Respiration is a fundamental physiological function in humans, often synchronized with movement to enhance performance and efficiency. Recent studies have underscored the modulatory effects of respiratory rhythms on brain oscillations and various behavioral responses, including sensorimotor processes. In light of this connection, our study aimed to investigate the influence of different respiratory patterns on beta corticomuscular coherence (CMC) during isometric hand flexion and extension. Utilizing electroencephalogram (EEG) and surface electromyography (sEMG), we examined three breathing conditions: normal breathing, deep inspiration, and deep expiration. Two experimental protocols were employed: the first experiment required participants to simultaneously breathe and exert force, while the other involved maintaining a constant force while varying breathing patterns. The results revealed that deep inspiration significantly enhanced beta CMC during respiration-synchronized tasks, whereas normal breathing resulted in higher CMC compared to deep respiration during sustained force exertion. In the second experiment, beta CMC was cyclically modulated by respiratory phase across all breathing conditions. The difference in the outcomes from the two protocols demonstrated a task-specific modulation of respiration on motor control. Overall, these findings indicate the complex dynamics of respiration-related effects on corticomuscular neural communication and provide valuable insights into the mechanisms underpinning the coupling between respiration and motor function.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-025-10245-x.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"54"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11929664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143699812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of cognitive load during computer-aided education using infrared sensors.","authors":"Subashis Karmakar, Tandra Pal, Chiranjib Koley","doi":"10.1007/s11571-025-10242-0","DOIUrl":"10.1007/s11571-025-10242-0","url":null,"abstract":"<p><p>Technology integration in modern education has transformed traditional teaching-learning methods, but maintaining student attentiveness during computer-aided activities remains challenging. Neuroimaging advancements provide valuable insights into cognitive processes. This study measures cognitive load during computer-aided education. We have collected functional near-infrared spectroscopy (fNIRS) brain signals while subjects perform mental tasks and rest. Three datasets have been considered to evaluate the performance of the proposed model. The first two datasets are open-access, and we prepare the third dataset by collecting fNIRS brain signals from 14 healthy subjects. Two feature extraction techniques are proposed: manual and automatic based on wavelet scattering transform (WST). A one dimensional convolutional neural network (1D CNN) is also proposed to automatically extract features through feature engineering and classification. For comparison, four machine learning classifiers, linear discriminant analysis (LDA), Naive Bayes (NB), k-nearest neighbors (KNN) and support vector machine (SVM), are also considered. Classification performance is evaluated using accuracy, precision, recall and F1-score across all datasets. Computational cost, i.e., the CPU time and memory utilization for extracting the features and testing the classifiers, is also evaluated. The results suggest that when considering four classifiers across three datasets and comparing among the manual and the WST-based feature extraction methods, the average performance of 1D CNN is superior in terms of classification accuracy (1.16 times higher), precision (1.10 times higher), recall (1.10 times higher) and F1-score (1.09 times higher). However, the CPU time and memory utilization for 1D CNN are significantly higher, 10.09 and 14.70 times, respectively. In comparison to four state-of-the-art deep learning models, the proposed 1D CNN also shows best classification accuracy (92.99%). The analysis of the results shows that identifying cognitive load, SVM with Gaussian kernel function on WST based methods, provides satisfactory classification performance with significantly less CPU time and memory utilization.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"58"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11971117/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143794880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulation of dentate gyrus pattern separation by hilus ectopic granule cells.","authors":"Haibin Yin, Xiaojuan Sun, Kai Yang, Yueheng Lan, Zeying Lu","doi":"10.1007/s11571-024-10204-y","DOIUrl":"10.1007/s11571-024-10204-y","url":null,"abstract":"<p><p>The dentate gyrus (DG) in hippocampus is reported to perform pattern separation, converting similar inputs into different outputs and thus avoiding memory interference. Previous studies have found that human and mice with epilepsy have significant pattern separation defects and a portion of adult-born granule cells (abGCs) migrate abnormally into the hilus, forming hilus ectopic granule cells (HEGCs). For the lack of relevant pathophysiological experiments, how HEGCs affect pattern separation remains unclear. Therefore, in this paper, we will construct the DG neuronal circuit and focus on discussing effects of HEGCs on pattern separation numerically. The obtained results showed that HEGCs impaired pattern separation efficiency since the sparse firing of granule cells (GCs) was destroyed. We provided new insights into the underlining mechanisms of HEGCs impairing pattern separation through analyzing two excitatory circuits: GC-HEGC-GC and GC-Mossy cell (MC)-GC, both of which involve the participation of HEGCs within the DG. It is revealed that the recurrent excitatory circuit GC-HEGC-GC formed by HEGCs mossy fiber sprouting significantly enhanced GCs activity, consequently disrupted pattern separation. However, another excitatory circuit had negligible effects on pattern separation due to the direct and indirect influences of MCs on GCs, which in turn led to the GCs sparse firing. Thus, HEGCs impair DG pattern separation mainly through the GC-HEGC-GC circuit and therefore ablating HEGCs may be one of the effective ways to improve pattern separation in patients with epilepsy.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"10"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11718051/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of SUMO1 Modification of SOX9 in Cartilage Development Stimulated by Zinc Ions in Mice.","authors":"Na Xue, Jing Zhao, Jing Yin, Liang Liu, Zhong Yang, Shuchao Zhai, Xiyun Bian, Xiang Gao","doi":"10.1080/15476278.2025.2460269","DOIUrl":"10.1080/15476278.2025.2460269","url":null,"abstract":"<p><p>Zinc ions play a pivotal role in facilitating the development of cartilage in mice. Nevertheless, the precise underlying mechanism remains elusive. Our investigation was centered on elucidating the impact of zinc deficiency on cartilage maturation by modulating SUMO1 and UBC9 at both the protein and mRNA levels. We administered a regimen inducing zinc deficiency to gravid mice from E0.5 until euthanasia. Subsequently, we subjected the embryos to scrutiny employing HE, Safranin O staining and IHC. Primary chondrocytes were isolated from fetal mouse femoral condyles and utilized for Western blot analysis to discern the expression profiles of SUMO1, SUMO2/3, UBC9, SOX9, MMP13, Collagen II, RUNX2, and aggrecan. Furthermore, ATDC5 murine chondrocytes were subjected to treatment with ZnCl₂, followed by RT-PCR assessment to scrutinize the expression levels of MMP13, Collagen II, RUNX2, and aggrecan. Additionally, we conducted Co-IP assays on ZnCl₂-treated ATDC5 cells to explore the interaction between SOX9 and SUMO1. Our investigation unveiled that zinc deficiency led to a reduction in cartilage development, as evidenced by the HE results in fetal murine femur. Moreover, diminished expression levels of SUMO1 and UBC9 were observed in the IHC and Western blot results. Furthermore, Western blot and Co-IP assays revealed an augmented interaction between SOX9 and SUMO1, which was potentiated by ZnCl₂ treatment. Significantly, mutations at the SUMOylation site of SOX9 resulted in alterations in the expression patterns of crucial chondrogenesis factors. This research underscores how zinc ions promote cartilage development through the modification of SOX9 by SUMO1.</p>","PeriodicalId":19596,"journal":{"name":"Organogenesis","volume":"21 1","pages":"2460269"},"PeriodicalIF":1.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11801356/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143190193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">Deep neural networks and stochastic methods for cognitive modeling of rat behavioral dynamics in <ns0:math><ns0:mi>T</ns0:mi></ns0:math> -mazes.","authors":"Ali Turab, Josué-Antonio Nescolarde-Selva, Farhan Ullah, Andrés Montoyo, Cicik Alfiniyah, Wutiphol Sintunavarat, Doaa Rizk, Shujaat Ali Zaidi","doi":"10.1007/s11571-025-10247-9","DOIUrl":"https://doi.org/10.1007/s11571-025-10247-9","url":null,"abstract":"<p><p>Modeling animal decision-making requires mathematical rigor and computational analysis to capture underlying cognitive mechanisms. This study presents a cognitive model for rat decision-making behavior in <math><mi>T</mi></math> -mazes by combining stochastic methods with deep neural architectures. The model adapts Wyckoff's stochastic framework, originally grounded in Bush's discrimination learning theory, to describe probabilistic transitions between directional choices under reinforcement contingencies. The existence and uniqueness of solutions are demonstrated via fixed-point theorems, ensuring the formulation is well-posed. The asymptotic properties of the system are examined under boundary conditions to understand the convergence behavior of decision probabilities across trials. Empirical validation is performed using Monte Carlo simulations to compare expected trajectories with the model's predictive output. The dataset comprises spatial trajectory recordings of rats navigating toward food rewards under controlled experimental protocols. Trajectories are preprocessed through statistical filtering, augmented to address data imbalance, and embedded using t-SNE to visualize separability across behavioral states. A hybrid convolutional-recurrent neural network (CNN-LSTM) is trained on these representations and achieves a classification accuracy of 82.24%, outperforming conventional machine learning models, including support vector machines and random forests. In addition to discrete choice prediction, the network reconstructs continuous paths, enabling full behavioral sequence modeling from partial observations. The integration of stochastic dynamics and deep learning develops a computational basis for analyzing spatial decision-making in animal behavior. The proposed approach contributes to computational models of cognition by linking observable behavior to internal processes in navigational tasks.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"66"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12031716/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143971746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Maize 4-coumarate coenzyme A ligase <i>Zm4CL-like9</i> gene positively regulates drought stress response in <i>Arabidopsis thaliana</i>.","authors":"Jiayi Fan, Zhipeng Luo, Yuankai Wang, Peng Jiao, Qingxu Wang, Yuntao Dai, Shuyan Guan, Yiyong Ma, Huiwei Yu, Siyan Liu","doi":"10.1080/21645698.2025.2469942","DOIUrl":"10.1080/21645698.2025.2469942","url":null,"abstract":"<p><p>Maize is a major food crop in China, and drought is one of the major abiotic stresses that threaten the growth and development of the crop, seriously affecting the crop yield. 4-coumaric acid coenzyme A ligase (<i>4CL</i>) is a key enzyme in the phenylpropane metabolic pathway, which can regulate the lignin content of the plant and play an important role in the plant's resistance to drought stress, plays an important role in plant resistance to drought stress. In the present study, we screened the differentially expressed up-regulated gene <i>Zm4CL-like9</i> under drought stress by pre-transcriptome sequencing data (PRJNA793522) in the laboratory, and analyzed the significant up-regulation of <i>Zm4CL-like9</i> gene in roots under drought stress by qRT-PCR(Real-Time Quantitative Reverse Transcription PCR). The results of prokaryotic expression experiments showed that the protein encoded by the <i>Zm4CL-like9</i> gene was able to be expressed in prokaryotic cells and could effectively improve the drought tolerance of E. coli. Phenotypic analysis of transgenic <i>Arabidopsis</i> plants under drought stress revealed that seed germination rate, root length, and plant survival after drought rehydration were significantly higher in transgenic <i>Zm4CL-like9 Arabidopsis</i> compared with wild-type <i>Arabidopsis</i>; physiological and biochemical indexes revealed that peroxidase activity, proline (Pro) content, and chlorophyll content were significantly higher in transgenic <i>Arabidopsis</i> compared with wild-type <i>Arabidopsis</i>. Under drought stress, the expression of drought-related genes was significantly up-regulated in transgenic <i>Arabidopsis</i> compared with wild-type <i>Arabidopsis</i>. Taken together, the <i>Zm4CL-like9</i> gene enhances plant resistance to drought stress by reducing reactive oxygen species accumulation in plants.</p>","PeriodicalId":54282,"journal":{"name":"Gm Crops & Food-Biotechnology in Agriculture and the Food Chain","volume":"16 1","pages":"199-215"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11853610/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143484741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}