Journal of Neuroscience Methods最新文献

{"title":"Methodological determinants of signal quality in electrobulbogram recordings","authors":"Frans Nordén ,&nbsp;Irene Zanettin ,&nbsp;Tora Olsson ,&nbsp;Artin Arshamian ,&nbsp;Mikael Lundqvist ,&nbsp;Fahimeh Darki ,&nbsp;Johan N. Lundström","doi":"10.1016/j.jneumeth.2025.110598","DOIUrl":"10.1016/j.jneumeth.2025.110598","url":null,"abstract":"<div><div>The electrobulbogram (EBG) is a new, non-invasive method for measuring the functional activity of the human olfactory bulb (OB). To date, the EBG has been used to assess how the OB process odor identity, valence, intensity, and it has shown promise as an early biomarker for Parkinson’s disease. However, current implementation of the EBG method depends on several methodological components, including subject specific co-registration of electrode positions through neuronavigation and EEG source reconstruction, which may limit accessibility for many research groups. In this study, we test the quality and reliability of the OB signal under different configurations to potentially remedy this. Specifically, we compare six EBG setups that vary in the use of subject-specific T1 scans versus a template head model, co-registered versus template electrode positions, and individualized versus template-based OB location. Our results indicate that strongest EBG signals are obtained when using subject-specific T1 scans in combination with co-registered electrode positions. However, we obtained significant EBG activity even when using a fully template-based configuration. Our anatomical analysis of OB location of 941 individuals reveals that in 86 % of cases, the OB is centered within the spatial resolution bounds of the EEG source dipole, supporting the feasibility of detecting olfactory bulb signals without precise individual anatomical mapping using template coordinates. These findings suggest that while subject-specific configurations enhance signal quality, the EBG method remains robust enough to yield meaningful results even with less complex setups. This enables a broader adoption of the EBG method in both clinical and research settings.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110598"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Customizable artificial simulator for developing, planning, and training personnel on neurophysiology and surgical procedures in non-human primates","authors":"Lydia I. Smith ,&nbsp;Amy L. Orsborn","doi":"10.1016/j.jneumeth.2025.110587","DOIUrl":"10.1016/j.jneumeth.2025.110587","url":null,"abstract":"<div><h3>Background</h3><div>Neuroscience researchers often surgically implant hardware into model organisms to measure and manipulate neural activity. Designing and optimizing these procedures in non-human primates often requires sedated or euthanized animals. Artificial tissue technologies can reduce animal use in this process, but existing simulators do not include all relevant tissues and do not facilitate iterative design processes.</div></div><div><h3>New method</h3><div>We created a comprehensive, customizable, and modular surgical simulator for neuroscience research. Our simulator incorporates artificial skull, brain, and soft tissues (skin and muscle) into one 3-dimensional model with adaptable components.</div></div><div><h3>Results</h3><div>Incorporating 3-dimensional soft tissues enabled surgical and implant design improvements, which may contribute to improving implant longevity, research outcomes, and animal wellbeing. Our modular design allowed researchers to rapidly prototype designs and exchange parts to reflect implant or anatomical changes across a study. Incorporating all relevant tissues also enabled surgical practice and improved communication with veterinarians. Our approach is low-cost (a few hundred dollars) and uses readily available tools like 3D printing. We also provide models of different non-human primate species to increase access to our approach.</div></div><div><h3>Comparison with existing methods</h3><div>Our method improves upon past surgical simulators for neuroscience research by: adapting existing skin and muscle artificial tissue technologies to more accurately represent cranial 3-dimensional geometry, incorporating models of all tissues relevant for implant design, and introducing modular designs that increase flexibility/customization.</div></div><div><h3>Conclusions</h3><div>We found that this surgery simulator was an inexpensive tool that was useful for planning and practicing surgical procedures, as well as prototyping new neuroscience experiment hardware.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110587"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking non-invasive brain stimulations for Next-Gen Clinical Speciality: Opportunities, challenges and future","authors":"Mohammad Shabaz,&nbsp;Robert E. Hampson,&nbsp;Sara Baber Sial","doi":"10.1016/j.jneumeth.2025.110586","DOIUrl":"10.1016/j.jneumeth.2025.110586","url":null,"abstract":"","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110586"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145137900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstructing time-domain data from discontinuous Percept™ PC and RC output using external data acquisition and linear filtering","authors":"Jinxin Chen ,&nbsp;Mandy M. Koop ,&nbsp;Kenneth B. Baker ,&nbsp;Jay L. Alberts ,&nbsp;James Y. Liao","doi":"10.1016/j.jneumeth.2025.110566","DOIUrl":"10.1016/j.jneumeth.2025.110566","url":null,"abstract":"<div><h3>Background</h3><div>The Medtronic Percept™ PC and RC are deep brain stimulation (DBS) systems with recording capability. However, when the stimulation frequency is changed, the recordings were segmented, introducing interruptions that shift each segment in the time domain.</div></div><div><h3>New method</h3><div>Ex-vivo, stimulation frequency was changed while local field potential was being recorded in both leads. One lead captured stimulation artifacts from the DBS system, and another captured stimulation artifacts from the DBS system plus a 0.5 Hz impulse train from an external stimulator. Timing errors were assessed by comparing Percept™-recorded impulses to the gold-standard external stimulator impulses. The Percept™ recordings were then time-shifted to match the external system’s timing, based on the time difference between the two systems when stimulation frequency change was indicated.</div></div><div><h3>Results</h3><div>For both PC and RC, the sawtooth pattern occurred. Timing errors were noted to have linear ramps interrupted by sudden drops, which were used to develop an algorithm to correct, leveraging occasions where the Percept™ happens to record the true moments of stimulated frequency change. Errors ranged from -400 to 400 ms for PC, and from -1 to 1 s for RC. The timing reconstruction algorithm reduced the error to -10.07 ± 45.06 ms (mean ± std) for PC, and -23.52 ± 17.32 ms (mean ± std) for RC.</div></div><div><h3>Comparison with existing methods</h3><div>We measure and characterize the timing errors of each recorded segment, using ex-vivo DBS hardware, and propose a strategy to correct them.</div></div><div><h3>Conclusion</h3><div>This approach can be applied in-vivo using electroencephalogram to correct timing errors that are significant with long recordings, enabling accurate time synchronization.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110566"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity analysis of the balloon model parameters in functional near-infrared spectroscopy simulation","authors":"Murad Althobaiti","doi":"10.1016/j.jneumeth.2025.110599","DOIUrl":"10.1016/j.jneumeth.2025.110599","url":null,"abstract":"<div><h3>Background</h3><div>Accurate modeling of the hemodynamic response is critical for fNIRS data interpretation. While the Balloon model is a cornerstone for this, the quantitative impact of its key parameters on the fNIRS signal, particularly in the presence of realistic artifacts, remains under-characterized.</div></div><div><h3>New method</h3><div>We developed an end-to-end fNIRS simulation pipeline. It incorporates a neural activity model, the Balloon model for hemodynamics, convolution for signal generation, and realistic motion, cardiac, and respiratory artifacts. We performed a sensitivity analysis by systematically varying Grubb's exponent (α) and transit time (τ).</div></div><div><h3>Results</h3><div>Both α and τ significantly influence the simulated fNIRS response. α shows a non-linear relationship with peak amplitude, while τ has a more linear effect on signal timing. Regression models quantifying these effects demonstrated a strong statistical fit (p &lt; 0.05, R² &gt; 0.9 for α).</div></div><div><h3>Comparison with existing methods</h3><div>Unlike prior fMRI-focused studies, this is the first quantitative sensitivity analysis specifically for fNIRS signals that incorporates a realistic noise model. Our framework characterizes the forward model's behavior, providing parameter-specific insights not previously available for fNIRS simulations.</div></div><div><h3>Conclusions</h3><div>The fNIRS hemodynamic response is highly sensitive to the Balloon model's α and τ parameters. These findings highlight the importance of accounting for physiological variability in fNIRS analysis and provide a robust framework for generating synthetic data to test signal processing algorithms.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110599"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the issue of low-frequency EEG generators and methods of their spatial localization","authors":"A.V. Vartanov ,&nbsp;E.L. Masherov","doi":"10.1016/j.jneumeth.2025.110592","DOIUrl":"10.1016/j.jneumeth.2025.110592","url":null,"abstract":"<div><h3>Background</h3><div>The article reviews the theoretical foundations of low-frequency EEG generation and the problems of existing methods and algorithms for localizing low-frequency EEG</div></div><div><h3>New method</h3><div>A new method based on spatial filtering for signal recovery from a specific, pre-set point in space (area of interest) is presented. The algorithm uses the dynamics and correlation of signals in EEG leads with the addition of artificially generated data. The method assumes a volume charge (unipole) as a source and a function of linear potential decay from values inverse to the distance from a given point to scalp electrodes.</div></div><div><h3>Results</h3><div>It is shown that the dipole model based on the summation of postsynaptic potentials cannot adequately describe the low-frequency component of the EEG; arguments are given in favor of the unipolar model based on the summation of trace potentials.</div></div><div><h3>Comparison with existing method</h3><div>Based on deep brain stimulation data, the new method was verified and its effectiveness was compared with some existing algorithms (sLORETA, dSPM, etc., included in the Brainstorm package).</div></div><div><h3>Conclusions</h3><div>As a result, it is shown that the new \"Virtually implanted electrode\" method makes it possible to accurately determine the localization of unipolar current sources. At the same time, it is shown that other methods based on the dipole model gave false solutions. In this regard, it is necessary to revise the results of localization of the low-frequency component of the EEG previously obtained using these tools, especially when evaluating functional relationships based on these data.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110592"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an in vitro fibrotic scar model of spinal cord injury using macromolecular crowding","authors":"Sorour Nemati ,&nbsp;Alanna Stanley ,&nbsp;Michelle Kilcoyne ,&nbsp;Dimitrios Zeugolis ,&nbsp;Siobhan S. McMahon","doi":"10.1016/j.jneumeth.2025.110601","DOIUrl":"10.1016/j.jneumeth.2025.110601","url":null,"abstract":"<div><h3>Background</h3><div>Spinal cord injury (SCI) results in a cascade of cellular and molecular events that lead to permanent tissue damage and functional impairment. A key consequence of this injury is the formation of both glial and fibrotic scars, which pose significant barriers to regeneration. The fibrotic scar that forms following SCI remains a significant therapeutic challenge. One major obstacle in developing anti-fibrotic compounds is the absence of a comprehensive <em>in vitro</em> screening system.</div></div><div><h3>New method</h3><div>In this study, we employed a macromolecular crowding (MMC) technique to accelerate ECM deposition. Leptomeningeal (LPG) cells were cultured in media supplemented with the MMC Ficoll (FC). To mimic the injury environment <em>in vivo</em>, the cells were exposed to either physical or chemical injury.</div></div><div><h3>Results</h3><div>The growth and metabolic activity of the LPG cells remained unchanged under these different injuries and treatments. Groups supplemented with the MMC FC exhibited higher deposition of ECM proteins involved in fibrotic scar formation, including fibronectin, collagen IV, collagen I, and laminin, compared to those without FC.</div></div><div><h3>Comparison with existing methods</h3><div>A key limitation of conventional cell culture in aqueous media is its clear difference from the naturally ‘crowded’ tissue environment, resulting in a slow rate of ECM protein deposition. Using the MMC approach, we successfully accelerated ECM protein deposition within an <em>in vitro</em> model of the fibrotic scar.</div></div><div><h3>Conclusions</h3><div>Supplementing LPG culture media with MMCs can effectively mimic the fibrotic scar environment, providing a valuable refinement in developing SCI <em>in vitro</em> models for drug screening and therapeutic applications.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110601"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145292470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MSAttNet: Multi-scale attention convolutional neural network for motor imagery classification","authors":"Ruiyu Zhao ,&nbsp;Ian Daly ,&nbsp;Yixin Chen ,&nbsp;Weijie Wu ,&nbsp;Lifei Liu ,&nbsp;Xingyu Wang ,&nbsp;Andrzej Cichocki ,&nbsp;Jing Jin","doi":"10.1016/j.jneumeth.2025.110578","DOIUrl":"10.1016/j.jneumeth.2025.110578","url":null,"abstract":"<div><h3>Background:</h3><div>Convolutional neural networks (CNNs) are widely employed in motor imagery (MI) classification. However, due to cumbersome data collection experiments, and limited, noisy, and non-stationary EEG signals, small MI datasets present considerable challenges to the design of these decoding algorithms.</div></div><div><h3>New method:</h3><div>To capture more feature information from inadequately sized data, we propose a new method, a multi-scale attention convolutional neural network (MSAttNet). Our method includes three main components–a multi-band segmentation module, an attention spatial convolution module, and a multi-scale temporal convolution module. First, the multi-band segmentation module adopts a filter bank with overlapping frequency bands to enhance features in the frequency domain. Then, the attention spatial convolution module is used to adaptively adjust different convolutional kernel parameters according to the input through the attention mechanism to capture the features of different datasets. The outputs of the attention spatial convolution module are grouped to perform multi-scale temporal convolution. Finally, the output of the multi-scale temporal convolution module uses the bilinear pooling layer to extract temporal features and perform noise elimination. The extracted features are then classified.</div></div><div><h3>Results:</h3><div>We use four datasets, including <em>BCI Competition IV Dataset IIa</em>, <em>BCI Competition IV Dataset IIb</em>, the <em>OpenBMI</em> dataset and the <em>ECUST-MI</em> dataset, to test our proposed method. MSAttNet achieves accuracies of 78.20%, 84.52%, 75.94% and 78.60% in cross-session experiments, respectively.</div></div><div><h3>Comparison with existing methods</h3><div>: Compared with state-of-the-art algorithms, MSAttNet enhances the decoding performance of MI tasks.</div></div><div><h3>Conclusion:</h3><div>MSAttNet effectively addresses the challenges of MI-EEG datasets, improving decoding performance by robust feature extraction.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110578"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145060868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EC-FST: A novel pipeline for automatically analyzing mouse forced swim test","authors":"Yang Xia ,&nbsp;Xuechun Meng ,&nbsp;Yuxing Ning ,&nbsp;Hongqi Li ,&nbsp;Yue Wu ,&nbsp;Jian Zhang ,&nbsp;Ling Liu ,&nbsp;Zhaohuan Huang ,&nbsp;Ji Liu","doi":"10.1016/j.jneumeth.2025.110585","DOIUrl":"10.1016/j.jneumeth.2025.110585","url":null,"abstract":"<div><h3>Background</h3><div>The mouse forced swim test (FST) is widely used to evaluate the efficacy of potential anti-depressant drugs. Traditional methods for analyzing forced swim test results rely on manually setting the threshold for immobility, which is time-consuming and barely reproducible.</div></div><div><h3>New method</h3><div>In the present study, we introduced a novel pipeline (EC-FST) by extracting the feature of mouse status instead of calculating immobility time. First, we utilized event camera, a powerful AI tool for dynamic object-tracking framework, to capture the mobile events from mouse forced swim test. By quantifying event numbers and their temporal distribution, we were able to determine mouse’s mobile state across time-line.</div></div><div><h3>Results</h3><div>The EC-FST results showed perfect correlation with manual scoring, suggesting that the proposed method is reliable for analyzing forced swim test. We further tested the power of the EC-FST for detecting depressive-like behavior in mouse depression models，including lipopolysaccharide (LPS) injection and chronic restraint stress (CRS). Depressive-model mice exhibited significantly fewer motion events and lower event frequency than controls, aligning with manual scoring.</div></div><div><h3>Comparison with existing methods</h3><div>Unlike traditional threshold-based approaches, EC-FST provides an automated, unbiased, and reproducible analysis of FST behavior, eliminating the subjectivity of manual scoring.</div></div><div><h3>Conclusion</h3><div>Leveraging AI-driven event cameras, we established a robust pipeline for analyzing mouse behavior in the FST, offering greater efficiency and reproducibility for depression research.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110585"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced brain diffusion MRI and image texture measures have the potential to predict multi-domain functional outcomes in multiple sclerosis","authors":"Olayinka Oladosu ,&nbsp;Yunyan Zhang","doi":"10.1016/j.jneumeth.2025.110562","DOIUrl":"10.1016/j.jneumeth.2025.110562","url":null,"abstract":"<div><h3>Background</h3><div>Multiple sclerosis (MS) causes diverse functional impairments that require early accurate characterization, but pertinent methods are scarce. This study aimed to develop new imaging-driven approaches for predicting MS functions.</div></div><div><h3>New method</h3><div>19 women with MS [10 relapsing-remitting (RRMS) and 9 secondary progressive (SPMS) subtypes] and 19 matched controls were examined including 3 T imaging. Advanced measures of nerve tract integrity were derived using diffusion MRI and anatomical MRI texture analysis with phase congruency, respectively. Imaging analysis focused on three tract regions critical in MS: the corpus callosum, corticospinal tracts, and optic radiations. Top-ranked tract measures sensitive to MS severity were employed to predict physical, neurocognitive, and affective functions facilitated by Ridge regression.</div></div><div><h3>Results</h3><div>Top predictors included diffusion apparent fiber density and fractional anisotropy, and phase congruency measures across tracts. The predictions were mostly strong for physical functions including Timed 25-Foot walk, Nine-Hole Peg Test, and neurological disability, strong-to-moderate for neurocognitive functions led by the symbol digit modality test, and relatively weak for affective functions. Further, the normal-appearing white matter (NAWM) models were superior or similar to NAWM+Lesion models based on either imaging type, and the best phase congruency models outperformed the best diffusion-based models.</div></div><div><h3>Comparison with existing methods</h3><div>Few studies attempted to derive novel measures of nerve integrity using clinical MRI, and virtually no study modelled the utility of these measures for predicting multi-domain MS functions.</div></div><div><h3>Conclusion</h3><div>Advanced imaging models could predict MS functions for early intervention, especially phase congruency NAWM models for physical functions.</div></div>","PeriodicalId":16415,"journal":{"name":"Journal of Neuroscience Methods","volume":"424 ","pages":"Article 110562"},"PeriodicalIF":2.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144957593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}