Muhammad Noman Almani, John Lazzari, Jeff Walker, Shreya Saxena
{"title":"Embodied sensorimotor control: computational modeling of the neural control of movement.","authors":"Muhammad Noman Almani, John Lazzari, Jeff Walker, Shreya Saxena","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>We review how sensorimotor control is dictated by interacting neural populations, optimal feedback mechanisms, and the biomechanics of bodies. First, we outline the distributed anatomical loops that shuttle sensorimotor signals between cortex, subcortical regions, and spinal cord. We then summarize evidence that neural population activity occupies low-dimensional, dynamically evolving manifolds during planning and execution of movements. Next, we summarize literature explaining motor behavior through the lens of optimal control theory, which clarifies the role of internal models and feedback during motor control. Finally, recent studies on embodied sensorimotor control address gaps within each framework by aiming to elucidate neural population activity through the explicit control of musculoskeletal dynamics. We close by discussing open problems and opportunities: multi-tasking and cognitively rich behavior, multi-regional circuit models, and the level of anatomical detail needed in body and network models. Together, this review and recent advances point towards reaching an integrative account of the neural control of movement.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458597/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Computational modelling of Parkinson's disease: A multiscale approach with deep brain stimulation and stochastic noise.","authors":"A Herrera, H Shaheen","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Multiscale modelling presents a multifaceted perspective into understanding the mechanisms of the brain and how neurodegenerative disorders like Parkinson's disease (PD) manifest and evolve over time. In this study, we propose a novel co-simulation multiscale approach that unifies both micro- and macroscales to more rigorously capture brain dynamics. The presented design considers the electrodiffusive activity across the brain and in the network defined by the cortex, basal ganglia, and thalamus that is implicated in the mechanics of PD, as well as the contribution of presynaptic inputs in the highlighted regions. The application of deep brain stimulation (DBS) and its effects, along with the inclusion of stochastic noise are also examined. We found that the thalamus exhibits large, fluctuating spiking in both the deterministic and stochastic conditions, suggesting that noise contributes primarily to neural variability, rather than driving the overall spiking activity. Ultimately, this work intends to provide greater insights into the dynamics of PD and the brain which can eventually be converted into clinical use. Computational modelling has proved to be an invaluable tool in attempts to discern the intricacies of the brain. The results of research in this field can have many different implications, including explanations to the underlying mechanisms of cognition or the origin and development of neurodegenerative diseases (NDDs). This study focuses on Parkinson's disease (PD), a type of NDD that can degrade the quality of life by inducing movement disorders and other non-motor symptoms. We strive to clarify the dynamics of PD and see how deep brain stimulation - a common treatment given to those with PD and other NDDs - affects the brain when in the Parkinsonian state. This study accomplishes this by incorporating a model that links the large-scale behaviour of diffusion across the brain, as well as a microscale environment that simulates the neuron-level functioning for regions in the basal ganglia and thalamus which are significant constituents in PD development. The brain is also characterized by randomness (i.e. noise), an innate feature in its processes. Hence, our design also involves a noise term. In general, we found that this model reflects the inherent unpredictability of neural firing within the brain.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458589/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Taher Yacoub, Camille Depenveiller, Atsushi Tatsuma, Tin Barisin, Eugen Rusakov, Udo Göbel, Yuxu Peng, Shiqiang Deng, Yuki Kagaya, Joon Hong Park, Daisuke Kihara, Marco Guerra, Giorgio Palmieri, Andrea Ranieri, Ulderico Fugacci, Silvia Biasotti, Ruiwen He, Halim Benhabiles, Adnane Cabani, Karim Hammoudi, Haotian Li, Hao Huang, Chunyan Li, Alireza Tehrani, Fanwang Meng, Farnaz Heidar-Zadeh, Tuan-Anh Yang, Matthieu Montes
{"title":"SHREC 2025: Protein Surface Shape Retrieval including Electrostatic potential.","authors":"Taher Yacoub, Camille Depenveiller, Atsushi Tatsuma, Tin Barisin, Eugen Rusakov, Udo Göbel, Yuxu Peng, Shiqiang Deng, Yuki Kagaya, Joon Hong Park, Daisuke Kihara, Marco Guerra, Giorgio Palmieri, Andrea Ranieri, Ulderico Fugacci, Silvia Biasotti, Ruiwen He, Halim Benhabiles, Adnane Cabani, Karim Hammoudi, Haotian Li, Hao Huang, Chunyan Li, Alireza Tehrani, Fanwang Meng, Farnaz Heidar-Zadeh, Tuan-Anh Yang, Matthieu Montes","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This SHREC 2025 track dedicated to protein surface shape retrieval involved 9 participating teams. We evaluated the performance in retrieval of 15 proposed methods on a large dataset of 11,565 protein surfaces with calculated electrostatic potential (a key molecular surface descriptor). The performance in retrieval of the proposed methods was evaluated through different metrics (Accuracy, Balanced accuracy, F1 score, Precision and Recall). The best retrieval performance was achieved by the proposed methods that used the electrostatic potential complementary to molecular surface shape. This observation was also valid for classes with limited data which highlights the importance of taking into account additional molecular surface descriptors.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458584/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Campbell Haasch, Malick Bio Idrissou, Sydney Jupitz, Aubrey Parks, Reinier Hernandez, Brian Pogue, Bryan Bednarz
{"title":"Quantitative In Vivo Cherenkov Luminescence Imaging and Dosimetry of Yttrium-86-NM600.","authors":"Campbell Haasch, Malick Bio Idrissou, Sydney Jupitz, Aubrey Parks, Reinier Hernandez, Brian Pogue, Bryan Bednarz","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Purpose: </strong>The expansion of radiopharmaceutical therapy (RPT) development demands scalable preclinical dosimetry methods. While PET and SPECT remain the gold standards, their low throughput and high cost limit large-cohort studies. Cherenkov luminescence imaging (CLI) offers a high-throughput alternative but suffers from depth-dependent attenuation and photon scatter that compromise quantitative accuracy. This work develops and validates a quantitative CLI methodology incorporating attenuation and scatter corrections for accurate preclinical dosimetry.</p><p><strong>Methods: </strong>Depth-dependent attenuation was characterized using a tissue-mimicking phantom to derive calibration coefficients. Photon scatter was modeled using GEANT4-generated Cherenkov spread functions (CSFs), applied in a depth-weighted iterative Richardson--Lucy deconvolution/reconvolution framework. The method was evaluated in NU/NU mice (n=4) bearing MC38 tumors after injection of $^{86}$Y-NM600, an isotope suitable for both PET and CLI. Liver and tumor activities were quantified at four timepoints using PET and the proposed CLI method. Monte Carlo dosimetry was performed for both modalities.</p><p><strong>Results: </strong>CLI--PET activity quantification yielded mean errors of 15.4% (liver) and 10.3% (tumor) over the first three timepoints. Tumor absorbed doses from CLI-derived synthetic PET images (3.4 $pm$ 0.3 Gy/MBq) were statistically indistinguishable from PET-based estimates (3.2 $pm$ 0.2 Gy/MBq, $p=0.31$). Discrepancies increased at late timepoints due to low activity and background auto-luminescence.</p><p><strong>Conclusions: </strong>With appropriate depth-dependent attenuation calibration and Monte Carlo--derived scatter correction, CLI can provide quantitative biodistribution and dosimetry estimates comparable to PET. This approach enables high-throughput, low-cost in vivo dosimetry, expanding the feasibility of large-scale preclinical RPT studies.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458591/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145151548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Kouřil, Trevor Manz, Tereza Clarence, Nils Gehlenborg
{"title":"Uchimata: a toolkit for visualization of 3D genome structures on the web and in computational notebooks.","authors":"David Kouřil, Trevor Manz, Tereza Clarence, Nils Gehlenborg","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Summary: </strong>Uchimata is a toolkit for visualization of 3D structures of genomes. It consists of two packages: a Javascript library facilitating the rendering of 3D models of genomes, and a Python widget for visualization in Jupyter Notebooks. Main features include an expressive way to specify visual encodings, and filtering of 3D genome structures based on genomic semantics and spatial aspects. Uchimata is designed to be highly integratable with biological tooling available in Python.</p><p><strong>Availability and implementation: </strong>Uchimata is released under the MIT License. The Javascript library is available on NPM, while the widget is available as a Python package hosted on PyPI. The source code for both is available publicly on Github (https://github.com/hms-dbmi/uchimata and https://github.com/hms-dbmi/uchimata-py). The documentation with examples is hosted at https://hms-dbmi.github.io/uchimata/.</p><p><strong>Contact: </strong>david_kouril@hms.harvard.edu or nils@hms.harvard.edu.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458596/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ali Abdollahzadeh, Ricardo Coronado-Leija, Hong-Hsi Lee, Alejandra Sierra, Els Fieremans, Dmitry S Novikov
{"title":"Scattering approach to diffusion quantifies axonal damage in brain injury.","authors":"Ali Abdollahzadeh, Ricardo Coronado-Leija, Hong-Hsi Lee, Alejandra Sierra, Els Fieremans, Dmitry S Novikov","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Early diagnosis and noninvasive monitoring of neurological disorders require sensitivity to elusive cellular-level alterations that occur much earlier than volumetric changes observable with the millimeter-resolution of medical imaging modalities. Morphological changes in axons, such as axonal varicosities or beadings, are observed in neurological disorders, as well as in development and aging. Here, we reveal the sensitivity of time-dependent diffusion MRI (dMRI) to the structurally disordered axonal morphology at the micrometer scale. Scattering theory uncovers the two parameters that determine the diffusive dynamics of water along axons: the average reciprocal cross-section and the variance of long-range cross-sectional fluctuations. This theoretical development allows us to predict dMRI metrics sensitive to axonal alterations over tens of thousands of axons in seconds rather than months of simulations in a rat model of traumatic brain injury, and is corroborated with ex vivo dMRI. Our approach bridges the gap between micrometers and millimeters in resolution, offering quantitative and objective biomarkers applicable to a broad spectrum of neurological disorders.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11838777/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"COMPLEX-VALUED PHASE SYNCHRONY REVEALS DIRECTIONAL COUPLING IN FMRI AND TRACKS MEDICATION EFFECTS.","authors":"Sir-Lord Wiafe, Najme Soleimani, Masoud Seraji, Bradley Baker, Robyn Miller, Ashkan Faghiri, Vince D Calhoun","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Understanding interactions in complex systems requires capturing the directionality of coupling, not only its strength. Phase synchronization captures this timing, yet most methods either reduce phase to its cosine or collapse it into scalar indices such as the phase-locking value, discarding directionality. We propose a complex-valued phase synchrony (CVPS) framework that estimates phase with an adaptive Gabor wavelet and preserves both cosine and sine components. Simulations confirm that CVPS recovers true phase offsets and tracks non-stationary dynamics more faithfully than Hilbert-based methods. Because antipsychotics are known to modulate the timing of cortical interactions, they provide a rigorous context to evaluate whether CVPS can capture such pharmacological effects. CVPS further reveals cortical neuro-hemodynamic drivers, with occipital-to-parietal and prefrontal-to-striatal lead-lag flows consistent with known receptor targets, confirming its ability to capture pharmacological timing. CVPS, therefore, offers a robust and generalizable framework for detecting directional coupling in complex systems such as the brain.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhonghao Zhang, Ming Lu, Hao Liang, Zhongliang Zu, Yi Gu, Xiao Wang, Yuankai Huo, John C Gore, Xinqiang Yan
{"title":"Fast Electromagnetic and RF Circuit Co-Simulation for Passive Resonator Field Calculation and Optimization in MRI.","authors":"Zhonghao Zhang, Ming Lu, Hao Liang, Zhongliang Zu, Yi Gu, Xiao Wang, Yuankai Huo, John C Gore, Xinqiang Yan","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Purpose: </strong>Passive resonators have been widely used in MRI to manipulate RF field distributions. However, optimizing these structures using full-wave electromagnetic (EM) simulations is computationally prohibitive, particularly for massive-element passive resonator arrays with many degrees of freedom.</p><p><strong>Methods: </strong>While the EM and RF circuit co-simulation method has previously been applied to RF coil design, this work presents, for the first time, a co-simulation framework tailored specifically for the analysis and optimization of passive resonators. The framework performs a single full-wave EM simulation in which the resonator's lumped components are replaced by ports, followed by circuit-level computations to evaluate arbitrary capacitor/inductor configurations. This allows integration with a genetic algorithm to rapidly optimize the resonator parameters to enhance <math> <mrow><msub><mi>B</mi> <mn>1</mn></msub> </mrow> </math> fields in a targeted region of interest (ROI).</p><p><strong>Results: </strong>The proposed method was validated across three scenarios of increasing complexity: (1) a single-loop passive resonator on a spherical phantom, (2) a two-loop array on a cylindrical phantom, and (3) a two-loop array on a human head model. In all cases, the co-simulation results showed excellent agreement with full-wave EM simulations, with relative errors below 1%. The genetic-algorithm-driven optimization, involving tens of thousands of capacitor combinations, completed in under 5 minutes-whereas equivalent full-wave EM sweeps would require an impractically long computation time.</p><p><strong>Conclusion: </strong>This work extends co-simulation methodology to passive resonator design for the first time, enabling fast, accurate, and scalable optimization. The approach significantly reduces computational burden while preserving full-wave accuracy, making it a powerful tool for passive RF structure development in MRI.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lucas Amoudruz, Gregory Buti, Luciano Rivetti, Ali Ajdari, Gregory Sharp, Petros Koumoutsakos, Simon Spohn, Anca L Grosu, Thomas Bortfeld
{"title":"Ising energy model for the stochastic prediction of tumor islets.","authors":"Lucas Amoudruz, Gregory Buti, Luciano Rivetti, Ali Ajdari, Gregory Sharp, Petros Koumoutsakos, Simon Spohn, Anca L Grosu, Thomas Bortfeld","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>A major challenge in diagnosing and treating cancer is the infiltrative growth of tumors into surrounding tissues. This microscopic spread of the disease is invisible on most diagnostic imaging modalities and can often only be detected histologically in biopsies. The purpose of this paper is to develop a physically based model of tumor spread that captures the histologically observed behavior in terms of seeding small tumor islets in prostate cancer. The model is based on three elementary events: a tumor cell can move, duplicate, or die. The propensity of each event is given by an Ising-like Hamiltonian that captures correlations between neighboring cells. The model parameters were fitted to clinical data obtained from surgical specimens taken from 23 prostate cancer patients. The results demonstrate that this straightforward physical model effectively describes the distribution of the size and the number of tumor islets in prostate cancer. The simulated tumor islets exhibit a regular, approximately spherical shape, correctly mimicking the shapes observed in histology. This is due to the Ising interaction term between neighboring cells acting as a surface tension that gives rise to regularly shaped islets. The model addresses the important clinical need of calculating the probability of tumor involvement in specific sub-volumes of the prostate, which is required for radiation treatment planning and other applications.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458594/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Junchi Feng, Fernanda Garcia-Piña, Mahya Beheshti, Todd E Hudson, William Seiple, John-Ross Rizzo
{"title":"Residual Gaze Behavior During Navigation in Blindness and Low Vision.","authors":"Junchi Feng, Fernanda Garcia-Piña, Mahya Beheshti, Todd E Hudson, William Seiple, John-Ross Rizzo","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Background: </strong>Outdoor navigation poses significant challenges for people with blindness or low vision, yet the role of gaze behavior in supporting mobility remains underexplored. Fully sighted individuals typically adopt consistent scanning strategies, whereas those with visual impairments rely on heterogeneous adaptations shaped by residual vision and experience.</p><p><strong>Methods: </strong>We conducted a comparative eye-tracking study of fully sighted, low vision, blind, and fully blind participants navigating outdoor routes. Using a wearable eye tracker, we quantified fixation counts, fixation rate, fixation area, direction, peak fixation location, and walking speed.</p><p><strong>Results: </strong>Walking speed declined systematically with worsening vision. Fixation count increased with greater impairment, reflecting slower travel times and more frequent sampling. Fixation rate rose with worsening vision, though between-group differences were generally not significant between most groups. Fixation spatial coverage decreased along the continuum of vision loss. Fixation patterns were most consistent in the fully sighted group. Peak fixation locations were centered in fully sighted participants but shifted outward and became more variable with impairment.</p><p><strong>Conclusion: </strong>Gaze strategies during navigation form a graded continuum across vision groups, with fully sighted and fully blind participants at opposite poles and low vision and blind groups spanning the middle. Visual acuity alone does not predict functional gaze use, as rehabilitation experience and adaptive strategies strongly shape behavior. These findings highlight the need for personalized rehabilitation and assistive technologies, with residual gaze patterns offering insight into mobility capacity and training opportunities for safer navigation.</p>","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12458586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}