工程技术最新文献

{"title":"3T dilated inception network for enhanced autism spectrum disorder diagnosis using resting-state fMRI data.","authors":"V Kavitha, R Siva","doi":"10.1007/s11571-024-10202-0","DOIUrl":"10.1007/s11571-024-10202-0","url":null,"abstract":"<p><p>Autism spectrum disorder (ASD) is one of the complicated neurodevelopmental disorders that impacts the daily functioning and social interactions of individuals. It includes diverse symptoms and severity levels, making it challenging to diagnose and treat efficiently. Various deep learning (DL) based methods have been developed for diagnosing ASD, which rely heavily on behavioral assessment. However, existing techniques have suffered from poor diagnostic outcomes, higher computational complexity, and overfitting issues. To address these challenges, this research work introduces an innovative framework called 3T Dilated Inception Network (3T-DINet) for effective ASD diagnosis using resting-state functional Magnetic Resonance Imaging (rs-fMRI) images. The proposed 3T-DINet technique designs a 3T dilated inception module that incorporates dilated convolutions along with the inception module, allowing it to extract multi-scale features from brain connectivity patterns. The 3T dilated inception module uses three distinct dilation rates (low, medium, and high) in parallel to determine local, mid-level, and global features from the brain. In addition, the proposed approach implements Residual networks (ResNet) to avoid the vanishing gradient problem and enhance the feature extraction ability. The model is further optimized using a Crossover-based Black Widow Optimization (CBWO) algorithm that fine-tunes the hyperparameters thereby enhancing the overall performance of the model. Further, the performance of the 3T-DINet model is evaluated using the five ASD datasets with distinct evaluation parameters. The proposed 3T-DINet technique achieved superior diagnosis results compared to recent previous works. From this simulation validation, it's clear that the 3T-DINet provides an excellent contribution to early ASD diagnosis and enhances patient treatment outcomes.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"22"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001551","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":"Neuroenhancement by repetitive transcranial magnetic stimulation (rTMS) on DLPFC in healthy adults.","authors":"Elias Ebrahimzadeh, Seyyed Mostafa Sadjadi, Mostafa Asgarinejad, Amin Dehghani, Lila Rajabion, Hamid Soltanian-Zadeh","doi":"10.1007/s11571-024-10195-w","DOIUrl":"10.1007/s11571-024-10195-w","url":null,"abstract":"<p><p>The term \"neuroenhancement\" describes the enhancement of cognitive function associated with deficiencies resulting from a specific condition. Nevertheless, there is currently no agreed-upon definition for the term \"neuroenhancement\", and its meaning can change based on the specific research being discussed. As humans, our continual pursuit of expanding our capabilities, encompassing both cognitive and motor skills, has led us to explore various tools. Among these, repetitive Transcranial Magnetic Stimulation (rTMS) stands out, yet its potential remains underestimated. Historically, rTMS was predominantly employed in studies focused on rehabilitation objectives. A small amount of research has examined its use on healthy subjects with the goal of improving cognitive abilities like risk-seeking, working memory, attention, cognitive control, learning, computing speed, and decision-making. It appears that the insights gained in this domain largely stem from indirect outcomes of rehabilitation research. This review aims to scrutinize these studies, assessing the effectiveness of rTMS in enhancing cognitive skills in healthy subjects. Given that the dorsolateral prefrontal cortex (DLPFC) has become a popular focus for rTMS in treating psychiatric disorders, corresponding anatomically to Brodmann areas 9 and 46, and considering the documented success of rTMS stimulation on the DLPFC for cognitive improvement, our focus in this review article centers on the DLPFC as the focal point and region of interest. Additionally, recognizing the significance of theta burst magnetic stimulation protocols (TBS) in mimicking the natural firing patterns of the brain to modulate excitability in specific cortical areas with precision, we have incorporated Theta Burst Stimulation (TBS) wave patterns. This inclusion, mirroring brain patterns, is intended to enhance the efficacy of the rTMS method. To ascertain if brain magnetic stimulation consistently improves cognition, a thorough meta-analysis of the existing literature has been conducted. The findings indicate that, after excluding outlier studies, rTMS may improve cognition when compared to appropriate control circumstances. However, there is also a considerable degree of variation among the researches. The navigation strategy used to reach the stimulation site and the stimulation location are important factors that contribute to the variation between studies. The results of this study can provide professional athletes, firefighters, bodyguards, and therapists-among others in high-risk professions-with insightful information that can help them perform better on the job.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"34"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11759757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045801","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 dynamic impact of adult neurogenesis on pattern separation within the dentate gyrus neural network.","authors":"Kai Yang, Xiaojuan Sun, Zengbin Wang","doi":"10.1007/s11571-025-10244-y","DOIUrl":"10.1007/s11571-025-10244-y","url":null,"abstract":"<p><p>Pattern separation in the dentate gyrus (DG) is crucial for distinguishing similar memories. The DG continues to undergo neurogenesis throughout the lifespan, and adult hippocampus neurogenesis leads to the incorporation of thousands of adult-born granule cells (adult-born GCs) into the existing DG circuitry. These newborn GCs exhibit high excitability and are easier to respond to novel stimuli, which seems to be contrary to the requirement of pattern separation for high input specificity. Meanwhile, the changes brought about by the growth of adult-born GCs can not be ignored. Here, we build a biologically relevant model of the DG containing adult-born GCs and test it using the Modified National Institute of Standards and Technology (MNIST) database. By analyzing this model, the results show that the net effect of adult-born GCs to GCs is inhibition, thereby improving the sparsity of GCs and pattern separation. This provides computational evidence for \"indirect encoding\" of adult-born GCs. In addition, as adult-born GCs transition toward maturity, they have the following growth characteristics: decreased activity, increased coupling strength with feedback inhibition, and enhanced synaptic plasticity. We find that the decreased activity reduces pattern separation efficiency while the other characteristics increase pattern separation efficiency. Finally, given that the firing rate of entorhinal cortex (EC) neurons is influenced by numerous factors (such as the complexity of memory tasks), the input frequency to the DG should be within a range rather than being fixed. To address this, we gradually increase the input frequency and notice that the presence of adult-born GCs increases the adaptability of the DG neural network and thus improves the robustness of pattern separation.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"57"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11971114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143794881","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":"Analysis of brain network effective connectivity in juvenile myoclonic epilepsy.","authors":"Ming Ke, Xin Kang, Di Xu, Guangyao Liu","doi":"10.1007/s11571-025-10256-8","DOIUrl":"10.1007/s11571-025-10256-8","url":null,"abstract":"<p><p>Juvenile Myoclonic Epilepsy (JME) is a prevalent idiopathic generalized epilepsy whose neurophysiological mechanisms remain elusive. This study aims to elucidate the aberrant brain network patterns in JME through a multi-modal fMRI approach combining local consistency, functional connectivity, and causal interaction analysis. Resting-state fMRI data were acquired from 37 JME patients and 35 healthy controls. Regional homogeneity (ReHo) and amplitude of low-frequency fluctuations (ALFF) analyses identified eight brain regions with significant between-group differences (FDR-corrected p < 0.05), including the right middle frontal gyrus, right insula, right medial/paracingulate gyrus, bilateral superior frontal gyri, left postcentral gyrus, and left superior occipital gyrus. These regions served as regions of interest (ROIs) for subsequent functional and effective connectivity analyses. Functional connectivity analysis revealed increased connectivity strength between the right middle frontal gyrus and right medial or paracingulate gyrus, as well as between the right insula and right medial/paracingulate gyrus (two-sample <i>t</i> test, p < 0.01), despite decreased local synchrony in these regions. Dynamic causal modeling (DCM) demonstrated bidirectional enhancement of effective connectivity between the right insula and right medial or paracingulate gyrus in patients (Bayesian posterior probability > 0.95). These findings suggest that the observed decoupling of local neuronal synchronization and long-range connectivity may reflect compensatory neuroadaptive processes, particularly involving the salience network (insula) and cognitive control circuitry (cingulate regions).The integration of ReHo/ALFF mapping with DCM provides a novel framework for understanding the neurodevelopmental trajectory of JME, highlighting the critical role of cortico-subcortical dysregulation in its pathogenesis.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"69"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12052659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143984172","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":"Dynamic analysis of multi-spiral chaotic inertia model with a cyclic configuration involving four homogeneous HNN cells: stability analysis, analog and digital verifications.","authors":"Jean Baptiste Koinfo, Donghua Jiang, Jean Chamberlain Chedjou, Jacques Kengne, Khabibullo Nosirov","doi":"10.1007/s11571-025-10240-2","DOIUrl":"10.1007/s11571-025-10240-2","url":null,"abstract":"<p><p>This paper investigates the behavior of a Hopfield neural network consisting of four interconnected inertial neurons arranged in a loop configuration. The mathematical equation that governs the overall dynamic of the model is consists of a set of eight first-order ordinary differential equations (ODEs) with odd symmetry. The system has 81 equilibrium points, some of which undergo multiple Hopf bifurcations as a control parameter is varied. The maximum number of coexisting states is related to the maximum number of active equilibrium points. Through numerical investigations, intriguing nonlinear properties are discovered, including both homogeneous and heterogeneous multistability and the coexistence of up to sixteen bifurcation branches, the presence of multi-spiral chaos, crisis phenomenon, period splitting and the oscillation death phenomenon. In order to obtain a comprehensive understanding of the dynamics, various tools are used, such as phase portraits, bifurcation diagrams, Poincare maps, frequency spectra, Lyapunov exponent spectra, and attraction basins. A Significant achievement of this study is the demonstration that coupling inertial neurons can be an effective method to generate multi-spiral chaotic signals. The overall dynamics is non-hidden and meticulous adjustment of the gradient connected to the fourth neuron allows to complete annihilate oscillations (no motion) in the neural network in a particular interval. Finally, an electronic circuit inspired by the coupled inertial neuron system is designed using Orcad-PSpice software and implemented using an Arduino-based microcontroller. The simulation results from PSpice and microcontroller confirm the findings from the theoretical analysis.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"63"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006643/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143981892","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":"ECn-MultiBSTM: multiclass epileptic seizure classification using electro cetacean optimized bidirectional long short-term memory model.","authors":"Pankaj Kunekar, Pankaj Dadheech, Mukesh Kumar Gupta","doi":"10.1007/s11571-025-10268-4","DOIUrl":"10.1007/s11571-025-10268-4","url":null,"abstract":"<p><p>Multiclass epileptic seizureclassification aims to identify and categorize different epileptic seizure types like a non-epileptic seizure, epileptic interictal seizure, and epileptic ictal seizurein individuals based on Electroencephalography (EEG) signal characteristics. Multi-class seizure classification requires recognizing various seizure forms and patterns, which can be challenging due to noise and high variability patterns in EEG signals. Existing models face limitations such as difficulty in handling the complex and dynamic nature of seizure patterns, poor generalization to unseen data, and sensitivity to noise and artifacts, all of which impact classification accuracy and reliability. To address these issues, the Electro Cetacean Optimization based Multi Bidirectional Long Short-Term Memory (ECn-MultiBSTM) model is proposed. The BiLSTM modelis utilized for feature extraction, which captures sequential data by processing data in both forward and backward directions. This bidirectional approach enables the model to identify subtle patterns that distinguish various seizure types with higher accuracy. The ECn-MultiBSTM model also incorporates advanced Electro Cetacean optimizationtechniques that enhance its ability to search efficiently for optimal solutions.Through dynamic social coordination and rapid search strategies, the model fine-tunes its hyperparameters, ensuring improved performance and adaptability.The proposed ECn-MultiBSTM model significantly enhances multiclassseizure classification performance, achieving impressive metrics of 95.84% accuracy, 95.30% precision, 95.54% F1-score,0.94% MCC, 95.79% sensitivity, and 95.88% specificity when evaluated on the CHB-MIT SCALP EEG dataset.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"83"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12116414/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144180545","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":"Investigating the anticancer and synergistic effects of the combination of green synthesized silver nanoparticles and papaverine on breast cancer cell lines: focusing on the apoptosis pathway and microRNA regulation.","authors":"Maryam Fekri Soufiabadi, Reza Haji Hosseini, Zolfaghar Lotfi","doi":"10.1080/21691401.2025.2507372","DOIUrl":"https://doi.org/10.1080/21691401.2025.2507372","url":null,"abstract":"<p><p>The study investigates the anticancer effects of green silver nanoparticles (Ag-NPs) synthesized from <i>Viola cornuta</i> extract combined with papaverine on breast cancer cells. Ag-NPs were characterized using various analytical techniques, confirming their presence with UV-vis spectroscopy showing a peak at 413 nm and an average size of 42 nm via field emission scanning electron microscopy (FE-SEM) analysis. The particles demonstrated a face-centred cubic structure, with energy-dispersive X-ray spectroscopy (EDX) confirming elemental composition. Additionally, the zeta potential measurement of -6.75 mV indicated favourable electrostatic repulsion between nanoparticles, thereby confirming their stability. Antioxidant activity was significant, with an EC₅₀ value of 38.78 μg/mL. The combination treatment of Ag-NPs and papaverine exhibited synergistic effects, lowering IC₅₀ values to 2.8 + 112.7 μg/mL for MCF-7 cells and 6.2 + 112 μg/mL for MDA-MB-231 cells, without toxicity to normal cells. Flow cytometry revealed G0/G1 phase inhibition and increased sub-G1 populations, indicating cell cycle arrest, alongside increased reactive oxygen species generation and apoptosis. Notably, the experimental group showed altered expression of oncogenic and tumour suppressor microRNAs and apoptotic genes (<i>p</i> < .0001), underscoring the potential of this nanoparticle-papaverine combination as an effective anticancer strategy against breast cancer treatment resistance.</p>","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"1-19"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198213","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":"Correction.","authors":"","doi":"10.1080/21691401.2025.2532221","DOIUrl":"https://doi.org/10.1080/21691401.2025.2532221","url":null,"abstract":"","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"286"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641643","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":"Neurofusionnet: a comprehensive framework for accurate epileptic seizure prediction from EEG data with hybrid meta-heuristic optimization algorithm.","authors":"Tejashwini P S, Sahana L, Thriveni J, Venugopal K R","doi":"10.1007/s11571-025-10293-3","DOIUrl":"https://doi.org/10.1007/s11571-025-10293-3","url":null,"abstract":"<p><p>This work uses cutting edge Electroencephalogram (EEG) data processing techniques to present a complete paradigm for epileptic seizure prediction. The methodology is a multi-step procedure that includes pre-processing, feature extraction, feature selection, and a new detection model based on deep learning for enhanced durability and accuracy. Bandpass filtering is used to reduce noise during the pre-processing phase, which improves the signal-to-noise ratio. EEG data quality is further improved using Independent Component Analysis, which finds and removes artifacts. Splitting continuous EEG data into fixed-duration segments, known as epoching, facilitates the investigation of discrete temporal patterns. Standard amplitude values are guaranteed by Z-score normalization, and seizure-related patterns are more sensitively detected when channels are selected using Common Spatial Patterns. Step one of the feature extraction processes involves statistical features and time-domain features. For spectrum information it is essential to recognizing seizures, frequency-domain features such as Power spectrum Density are extracted using a technique Fourier Transform. A full representation is obtained by extracting Time-Frequency Domain Features with the Wavelet Transform. Predictive power is increased by the efficient selection of discriminative characteristics through the use of a hybrid optimization model called Hybrid Chimp Enhanced Fox Optimization algorithm that combines optimization methods inspired by FOX and Chimp. The suggested NeuroFusionNet-based detection model combines Improved ShuffleNet V2, SqueezeNet, EfficientNet V2, and Multi Head Attention (MHA) based GhostNet V2, which captures complex patterns linked to epileptic episodes.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"113"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12255646/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144636384","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":"Microvesicles and exosomes isolated from murine bone marrow-derived mesenchymal stromal cells primed with p38MAPK inhibitor differentially regulate hematopoietic stem cell function.","authors":"Pallavi Budgude, Vaijayanti Kale, Anuradha Vaidya","doi":"10.1080/21691401.2025.2475095","DOIUrl":"10.1080/21691401.2025.2475095","url":null,"abstract":"<p><p>The signaling mechanisms active within mesenchymal stromal cells (MSCs) influence the composition of microvesicles (MVs) and exosomes (Exos) secreted by them. Previously, we showed that priming MSCs with a p38 pharmacological inhibitor (pMSCs) rejuvenates them and improves their ability to promote <i>ex vivo</i> hematopoietic stem cell (HSC) expansion. This study examined whether pMSCs exerted HSC-supportive ability via MVs (pMVs) and Exos (pExos). Our findings demonstrate distinct regulation of HSC fate by pMVs and pExos. pMVs promoted the expansion of long-term HSCs (LT-HSCs), distinguished by their robust self-renewal capacity and superior engraftment ability. In contrast, pExos facilitated expansion of short-term HSCs (ST-HSCs) with high proliferative and differentiation potential. Infusing a combination of pMVs- and pExos-expanded HSCs as a composite graft resulted in significantly higher HSC engraftment, emphasizing the synergistic interaction between LT- and ST-HSC populations. Gene expression studies, functional and phenotypic experiments showed that pMVs regulate HSC quiescence via the <i>Egr1/Cdkn1a</i> axis, while pExos control HSC proliferation via the <i>Nfya/Cdkn1a</i> axis. These findings provide insights into the molecular mechanisms underlying the differential regulation of HSC function by pMVs and pExos. It also proposes a composite graft strategy of using pMVs and pExos as \"MSC-derived biologics\" for improving the HSC transplantation success.</p>","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"122-137"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584443","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}