Cognitive NeurodynamicsPub Date : 2025-12-01Epub Date: 2025-01-13DOI: 10.1007/s11571-024-10212-y
Rituparna Bhattacharyya, Brajesh Kumar Jha
{"title":"A fuzzy based computational model to analyze the influence of mitochondria, buffer, and ER fluxes on cytosolic calcium distribution in neuron cells.","authors":"Rituparna Bhattacharyya, Brajesh Kumar Jha","doi":"10.1007/s11571-024-10212-y","DOIUrl":"10.1007/s11571-024-10212-y","url":null,"abstract":"<p><p>A free calcium ion in the cytosol is essential for many physiological and physical functions. Also, it is known as a second messenger as the quantity of free calcium ions is an essential part of brain signaling. In this work, we have attempted to study calcium signaling in the presence of mitochondria, buffer, and endoplasmic reticulum fluxes. Small organelles called mitochondria are found in the nervous system and are involved in several cellular functions, including energy production, response to stress, calcium homeostasis regulation, and pathways leading to cell death. It has been discovered that buffer, endoplasmic reticulum, and mitochondria significantly affect calcium signaling. To investigate how various circumstances impact the quantity of calcium in the cytosol, a mathematical model of a second-order linear partial differential equation with fuzzy boundary conditions has been developed. Systems having ambiguous or imprecise boundary values can be effectively modeled and simulated with the help of fuzzy boundary conditions. Models can provide more dependable and instructive outcomes and become adaptable to real-world circumstances by implementing fuzzy logic into boundary conditions. In this paper, we observed the Fuzzy Laplace Transform to solve variable coefficient fuzzy differential equations using triangular fuzzy numbers. It is noted that maintaining the delicate calcium ion balance, which controls essential cellular functions, depends on the buffer affinity. Also, neurodegenerative illnesses like Alzheimer's, Parkinson's, etc. are linked to disruptions in the control of components such as buffers, mitochondria, and the endoplasmic reticulum.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"25"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729615/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001552","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}
Cognitive NeurodynamicsPub Date : 2025-12-01Epub Date: 2024-12-31DOI: 10.1007/s11571-024-10185-y
Hui Wang, Xiaxia Xu, Zhuo Yang, Tao Zhang
{"title":"Alterations of synaptic plasticity and brain oscillation are associated with autophagy induced synaptic pruning during adolescence.","authors":"Hui Wang, Xiaxia Xu, Zhuo Yang, Tao Zhang","doi":"10.1007/s11571-024-10185-y","DOIUrl":"10.1007/s11571-024-10185-y","url":null,"abstract":"<p><p>Adolescent brain development is characterized by significant anatomical and physiological alterations, but little is known whether and how these alterations impact the neural network. Here we investigated the development of functional networks by measuring synaptic plasticity and neural synchrony of local filed potentials (LFPs), and further explored the underlying mechanisms. LFPs in the hippocampus were recorded in young (21 ~ 25 days), adolescent (1.5 months) and adult (3 months) rats. Long term potentiation (LTP) and neural synchrony were analyzed. The results showed that the LTP was the lowest in adolescent rats. During development, the theta coupling strength was increased progressively but there was no significant change of gamma coupling between young rats and adolescent rats. The density of dendrite spines was decreased progressively during development. The lowest levels of NR2A, NR2B and PSD95 were detected in adolescent rats. Importantly, it was found that the expression levels of autophagy markers were the highest during adolescent compared to that in other developmental stages. Moreover, there were more co-localization of autophagosome and PSD95 in adolescent rats. It suggests that autophagy is possibly involved in synaptic elimination during adolescence, and further impacts synaptic plasticity and neural synchrony.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"2"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11688264/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142920782","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":"Transcriptome and nutritional composition analysis of stacked transgenic maize with insect resistance and herbicide tolerance.","authors":"Xiaoxing Yu, Hongyu Gao, Pengfei Wang","doi":"10.1080/21645698.2025.2472451","DOIUrl":"10.1080/21645698.2025.2472451","url":null,"abstract":"<p><p>The safety assessment of stacked transgenic crops is essential for their commercial cultivation. A crucial element of safety assessment is the nutritional evaluation of transgenic crops. Currently, profiling methods like transcriptome are employed as supplemental analytical tools to find the unintended effects of transgenic crops. In this study, stacked transgenic maize ZDRF8×nCX-1 was produced by crossing of two transgenic maize events ZDRF8 and nCX-1. This stacked transgenic maize expresses five genes: <i>cry1Ab</i>, <i>cry2Ab</i> and <i>g10evo-epsps</i> (from ZDRF8), as well as <i>cp4 epsps</i> and <i>P450-N-Z1</i> (from nCX-1). Molecular analysis showed that the insertion sites of target genes were not changed during stack breeding, and the target genes are effectively expressed at both RNA and protein levels in ZDRF8×nCX-1. Target trait analysis showed that ZDRF8×nCX-1 exhibits tolerant to glyphosate, flazasulfuron and MCPA, and is resistant to damage by corn borers. Transcriptome analysis revealed that gene-stacked maize ZDRF8×nCX-1 did not significantly alter transcriptome profiles compared to the transgenic maize events ZDRF8 and nCX-1. Nutritional composition analysis showed that the grain profile of ZDRF8×nCX-1 was substantially equivalent to that of the non-transgenic counterpart. These results suggest that hybrid stacking does not cause significantly unintended effects beyond providing the intended beneficial traits.</p>","PeriodicalId":54282,"journal":{"name":"Gm Crops & Food-Biotechnology in Agriculture and the Food Chain","volume":"16 1","pages":"216-234"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11875497/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525246","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}
{"title":"The potential associations between acupuncture sensation and brain functional network: a EEG study.","authors":"Dongyang Shen, Banghua Yang, Jing Li, Jiayang Zhang, Yongcong Li, Guofu Zhang, Yanyan Zheng","doi":"10.1007/s11571-025-10233-1","DOIUrl":"10.1007/s11571-025-10233-1","url":null,"abstract":"<p><p>Acupuncture has been widely used as an effective treatment for post-stroke rehabilitation. However, the potential association between acupuncture sensation, an important factor influencing treatment efficacy, and brain functional network is unclear. This research sought to reveal and quantify the changes in brain functional network associated with acupuncture sensation. So multi-channel EEG signals were collected from 30 healthy participants and the Massachusetts General Hospital Acupuncture Sensation Scale (MASS) was utilized to assess their needling sensations. Phase Lag Index (PLI) was used to construct the brain functional network, which was analyzed with graph theoretic methods. It showed that in the needle insertion (NI) state the MASS Index was significantly higher than in the needle retention (NR) state (<i>P</i> < 0.001), and the mean values of PLI were also higher than in the Pre-Rest state and NR state significantly (<i>P</i> < 0.01). In the NI state global efficiency, local efficiency, nodal efficiency, and degree centrality were significantly higher than in the Pre-Rest state and the NR state (<i>P</i> < 0.05), while the opposite is true for the shortest path length (<i>P</i> < 0.01). Then Pearson correlation analysis showed a correlation between MASS Index and graph theory metrics (<i>P</i> < 0.05). Finally, Support Vector Regression (SVR) was used to predict the MASS Index with a minimum mean absolute error of 0.65. These findings suggest that the NI state of acupuncture treatment changes the structure of the brain functional network and affects the graph theory metrics of the brain functional network, which may be an objective biomarker for quantitative evaluation of acupuncture sensation.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-025-10233-1.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"49"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910458/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647571","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}
Svante Resjö, Iqra, Nam P Kieu, Muhammad Awais Zahid, Marit Lenman, Björn Andersson, Erik Andreasson
{"title":"Late blight field resistance in potatoes carrying <i>Solanum americanum</i> resistance genes (Rpi-amr3 and Rpi-amr1).","authors":"Svante Resjö, Iqra, Nam P Kieu, Muhammad Awais Zahid, Marit Lenman, Björn Andersson, Erik Andreasson","doi":"10.1080/21645698.2025.2479913","DOIUrl":"10.1080/21645698.2025.2479913","url":null,"abstract":"<p><p>Potato (<i>Solanum tuberosum</i> L.) is an important global crop, but its production is severely impacted by late blight, caused by the pathogen <i>Phytophthora infestans</i>. The economic burden of this disease is significant, and current control strategies rely mainly on fungicides, which face increasing regulatory and environmental constraints. To address this challenge, potatoes with resistance genes from wild potato relatives offer a promising solution. This study evaluated field resistance to late blight in potato lines (Maris Piper) containing the <i>Solanum americanum</i> resistance genes <i>Rpi-amr3</i> and <i>Rpi-amr1</i> across three years (2018-2020) in Sweden. Field trials were conducted under natural infection conditions to assess disease resistance. Results showed that the transgenic lines conferred strong resistance to late blight compared to the susceptible control. However, slight late blight symptoms were observed in the transgenic lines. These results highlight the effectiveness of <i>S. americanum</i> resistance genes in providing strong resistance, and emphasize the potential of stacking multiple R genes, including these genes to maintain efficacy. This research supports the development of resistant potato varieties as a sustainable alternative to chemical control, promoting food security and environmentally friendly agriculture.</p>","PeriodicalId":54282,"journal":{"name":"Gm Crops & Food-Biotechnology in Agriculture and the Food Chain","volume":"16 1","pages":"263-271"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11934159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694331","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}
{"title":"Statement of Retraction: Myricetin nanoliposomes induced SIRT3-mediated glycolytic metabolism leading to glioblastoma cell death.","authors":"","doi":"10.1080/21691401.2025.2465942","DOIUrl":"https://doi.org/10.1080/21691401.2025.2465942","url":null,"abstract":"","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"56"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717889","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":"Cross-patient seizure prediction via continuous domain adaptation and similar sample replay.","authors":"Ziye Zhang, Aiping Liu, Yikai Gao, Ruobing Qian, Xun Chen","doi":"10.1007/s11571-024-10216-8","DOIUrl":"10.1007/s11571-024-10216-8","url":null,"abstract":"<p><p>Seizure prediction based on electroencephalogram (EEG) for people with epilepsy, a common brain disorder worldwide, has great potential for life quality improvement. To alleviate the high degree of heterogeneity among patients, several works have attempted to learn common seizure feature distributions based on the idea of domain adaptation to enhance the generalization ability of the model. However, existing methods ignore the inherent inter-patient discrepancy within the source patients, resulting in disjointed distributions that impede effective domain alignment. To eliminate this effect, we introduce the concept of multi-source domain adaptation (MSDA), considering each source patient as a separate domain. To avoid additional model complexity from MSDA, we propose a continuous domain adaptation approach for seizure prediction based on the convolutional neural network (CNN), which performs sequential training on multiple source domains. To relieve the model catastrophic forgetting during sequential training, we replay similar samples from each source domain, while learning common feature representations based on subdomain alignment. Evaluated on a publicly available epilepsy dataset, our proposed method attains a sensitivity of 85.0% and a false alarm rate (FPR) of 0.224/h. Compared to the prevailing domain adaptation paradigm and existing domain adaptation works in the field, the proposed method can efficiently capture the knowledge of different patients, extract better common seizure representations, and achieve state-of-the-art performance.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"26"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735696/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001017","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}
Cognitive NeurodynamicsPub Date : 2025-12-01Epub Date: 2025-02-05DOI: 10.1007/s11571-025-10221-5
Gaoxuan Li, Bo Chen, Weigang Sun, Zhenbing Liu
{"title":"A stacking classifier for distinguishing stages of Alzheimer's disease from a subnetwork perspective.","authors":"Gaoxuan Li, Bo Chen, Weigang Sun, Zhenbing Liu","doi":"10.1007/s11571-025-10221-5","DOIUrl":"10.1007/s11571-025-10221-5","url":null,"abstract":"<p><p>Accurately distinguishing stages of Alzheimer's disease (AD) is crucial for diagnosis and treatment. In this paper, we introduce a stacking classifier method that combines six single classifiers into a stacking classifier. Using brain network models and network metrics, we employ <i>t</i>-tests to identify abnormal brain regions, from which we construct a subnetwork and extract its features to form the training dataset. Our method is then applied to the ADNI (Alzheimer's Disease Neuroimaging Initiative) datasets, categorizing the stages into four categories: Alzheimer's disease, mild cognitive impairment (MCI), mixed Alzheimer's mild cognitive impairment (ADMCI), and healthy controls (HCs). We investigate four classification groups: AD-HCs, AD-MCI, HCs-ADMCI, and HCs-MCI. Finally, we compare the classification accuracy between a single classifier and our stacking classifier, demonstrating superior accuracy with our stacking classifier from a subnetwork-based viewpoint.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"38"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11799466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143381814","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}
Cognitive NeurodynamicsPub Date : 2025-12-01Epub Date: 2025-02-20DOI: 10.1007/s11571-025-10222-4
Weixiong Jiang, Lin Li, Yulong Xia, Sajid Farooq, Gang Li, Shuaiqi Li, Jinhua Xu, Sailing He, Xiangyu Wu, Shoujun Huang, Jing Yuan, Dexing Kong
{"title":"Neural dynamics of deception: insights from fMRI studies of brain states.","authors":"Weixiong Jiang, Lin Li, Yulong Xia, Sajid Farooq, Gang Li, Shuaiqi Li, Jinhua Xu, Sailing He, Xiangyu Wu, Shoujun Huang, Jing Yuan, Dexing Kong","doi":"10.1007/s11571-025-10222-4","DOIUrl":"10.1007/s11571-025-10222-4","url":null,"abstract":"<p><p>Deception is a complex behavior that requires greater cognitive effort than truth-telling, with brain states dynamically adapting to external stimuli and cognitive demands. Investigating these brain states provides valuable insights into the brain's temporal and spatial dynamics. In this study, we designed an experiment paradigm to efficiently simulate lying and constructed a temporal network of brain states. We applied the Louvain community clustering algorithm to identify characteristic brain states associated with lie-telling, inverse-telling, and truth-telling. Our analysis revealed six representative brain states with unique spatial characteristics. Notably, two distinct states-termed <i>truth-preferred</i> and <i>lie-preferred</i>-exhibited significant differences in fractional occupancy and average dwelling time. The truth-preferred state showed higher occupancy and dwelling time during truth-telling, while the lie-preferred state demonstrated these characteristics during lie-telling. Using the average z-score BOLD signals of these two states, we applied generalized linear models with elastic net regularization, achieving a classification accuracy of 88.46%, with a sensitivity of 92.31% and a specificity of 84.62% in distinguishing deception from truth-telling. These findings revealed representative brain states for lie-telling, inverse-telling, and truth-telling, highlighting two states specifically associated with truthful and deceptive behaviors. The spatial characteristics and dynamic attributes of these brain states indicate their potential as biomarkers of cognitive engagement in deception.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-025-10222-4.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"42"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11842687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482401","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}