工程技术最新文献_第4页

Human tendon stem/progenitor cell-derived extracellular vesicle production promoted by dynamic culture.

IF 4.5 3区生物学

Artificial Cells, Nanomedicine, and Biotechnology Pub Date : 2025-12-01 Epub Date: 2025-03-10 DOI: 10.1080/21691401.2025.2475099

Marta Clerici, Maria Camilla Ciardulli, Erwin Pavel Lamparelli, Joseph Lovecchio, Emanuele Giordano, Tina P Dale, Nicholas R Forsyth, Nicola Maffulli, Giovanna Della Porta

{"title":"Human tendon stem/progenitor cell-derived extracellular vesicle production promoted by dynamic culture.","authors":"Marta Clerici, Maria Camilla Ciardulli, Erwin Pavel Lamparelli, Joseph Lovecchio, Emanuele Giordano, Tina P Dale, Nicholas R Forsyth, Nicola Maffulli, Giovanna Della Porta","doi":"10.1080/21691401.2025.2475099","DOIUrl":"https://doi.org/10.1080/21691401.2025.2475099","url":null,"abstract":"Tendon injuries significantly impact quality of life, prompting the exploration of innovative solutions beyond conventional surgery. Extracellular Vesicles (EVs) have emerged as a promising strategy to enhance tendon regeneration. In this study, human Tendon Stem/Progenitor Cells (TSPCs) were isolated from surgical biopsies and cultured in a Growth-Differentiation Factor-5-supplemented medium to promote tenogenic differentiation under static and dynamic conditions using a custom-made perfusion bioreactor. Once at 80% confluence, cells were transitioned to a serum-free medium for conditioned media collection. Ultracentrifugation revealed the presence of vesicles with a 106 particles/mL concentration and sub-200nm diameter size. Dynamic culture yielded a 3-fold increase in EV protein content compared to static culture, as confirmed by Western-blot analysis. Differences in surface marker expression were also shown by flow cytometric analysis. Data suggest that we efficiently developed a protocol for extracting EVs from human TSPCs, particularly under dynamic conditions. This approach enhances EV protein content, offering potential therapeutic benefits for tendon regeneration. However, further research is needed to fully understand the role of EVs in tendon regeneration.","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"1-16"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596200","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}

引用次数: 0

The integration of metabolites from Forsythia suspensa and gut microbiota ameliorates drug-induced liver injury: network pharmacology and molecular docking studies.

IF 4.5 3区生物学

Artificial Cells, Nanomedicine, and Biotechnology Pub Date : 2025-12-01 Epub Date: 2025-03-07 DOI: 10.1080/21691401.2025.2475088

Yanni Wang, Xiangxiang Peng, Bingjie Qian, Libo Wang, Jiabing Wang

{"title":"The integration of metabolites from Forsythia suspensa and gut microbiota ameliorates drug-induced liver injury: network pharmacology and molecular docking studies.","authors":"Yanni Wang, Xiangxiang Peng, Bingjie Qian, Libo Wang, Jiabing Wang","doi":"10.1080/21691401.2025.2475088","DOIUrl":"https://doi.org/10.1080/21691401.2025.2475088","url":null,"abstract":"This study integrates metabolites from Forsythia suspensa (FS) and gut microbiota GM to assess combined therapeutic efficacy against drug-induced liver injury (DILI) using network pharmacology and molecular docking. Metabolites of FS and GM were retrieved from the NPASS and gutMGene databases, respectively. Relevant targets for metabolites and DILI-related targets were identified through public databases. The PPI network and KEGG pathway analysis were employed to identify hub targets and key signalling pathways. Furthermore, we performed a molecular docking assay on the active metabolites and targets to verify the network pharmacological concept. The physicochemical properties and toxicity of identified key metabolites were assessed using in silico platforms. 19 final targets were recognized as key proteins responsible for the alleviation of DILI by FS and GM metabolites, with ESR1 emerging as a central target in the PPI network. The estrogen signalling pathway, particularly involving ESR1, ESR2 and JUN genes, was identified as a key mediator in the therapeutic effects. Four GM metabolites (baicalein, luteolin, lunularin and 2,3-bis(3,4-dihydroxybenzyl)butyrolactone) and two FS metabolites (pinoresinol and isolariciresinol) were identified as non-toxic, promising candidates. In conclusion, metabolites from FS and GM may exert a potent synergistic effect on DILI through modulation of the estrogen signalling pathway.","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"105-121"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584445","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}

引用次数: 0

Attenuated heterogeneity of hippocampal neuron subsets in response to novelty induced by amyloid-β.

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-03-26 DOI: 10.1007/s11571-025-10237-x

Xiaoxin Ren, Yimeng Wang, Xin Li, Xueling Wang, Zhaodi Liu, Jiajia Yang, Ling Wang, Chenguang Zheng

{"title":"Attenuated heterogeneity of hippocampal neuron subsets in response to novelty induced by amyloid-β.","authors":"Xiaoxin Ren, Yimeng Wang, Xin Li, Xueling Wang, Zhaodi Liu, Jiajia Yang, Ling Wang, Chenguang Zheng","doi":"10.1007/s11571-025-10237-x","DOIUrl":"10.1007/s11571-025-10237-x","url":null,"abstract":"Alzheimer's disease (AD) patients exhibited episodic memory impairments including location-object recognition in a spatial environment, which was also presented in animal models with amyloid-β (Aβ) accumulation. A potential cellular mechanism was the unstable representation of spatial information and lack of discrimination ability of novel stimulus in the hippocampal place cells. However, how the firing characteristics of different hippocampal subsets responding to diverse spatial information were interrupted by Aβ accumulation remains unclear. In this study, we observed impaired novel object-location recognition in Aβ-treated Long-Evans rats, with larger receptive fields of place cells in hippocampal CA1, compared with those in the saline-treated group. We identified two subsets of place cells coding object information (ObjCell) and global environment (EnvCell) during the task, with firing heterogeneity in response to introduced novel information. ObjCells displayed a dynamic representation responding to the introduction of novel information, while EnvCells exhibited a stable representation to support the recognition of the familiar environment. However, the dynamic firing patterns of these two subsets of cells were disrupted to present attenuated heterogeneity under Aβ accumulation. The impaired spatial representation novelty information could be due to the disturbed gamma modulation of neural activities. Taken together, these findings provide new evidence for novelty recognition impairments of AD rats with spatial representation dysfunctions of hippocampal subsets.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"56"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947398/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751144","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}

引用次数: 0

Functional analysis of type II chalcone isomerase (CHI) genes in regulating soybean (Glycine max L.) nodule formation.

IF 4.5 2区农林科学

Gm Crops & Food-Biotechnology in Agriculture and the Food Chain Pub Date : 2025-12-01 Epub Date: 2025-03-31 DOI: 10.1080/21645698.2025.2486280

Xinyue Wang, Jingwen Li, Yuxue Zhou, Jinhao Zhang, Le Wang, Yajing Liu, Xuguang Yang, Hongshuang Han, Qingyu Wang, Ying Wang

{"title":"Functional analysis of type II chalcone isomerase (CHI) genes in regulating soybean (Glycine max L.) nodule formation.","authors":"Xinyue Wang, Jingwen Li, Yuxue Zhou, Jinhao Zhang, Le Wang, Yajing Liu, Xuguang Yang, Hongshuang Han, Qingyu Wang, Ying Wang","doi":"10.1080/21645698.2025.2486280","DOIUrl":"10.1080/21645698.2025.2486280","url":null,"abstract":"Biological nitrogen fixation (BNF) is the most cost-effective and environmentally benign method for nitrogen fertilization. Isoflavones are important signaling factors for BNF in leguminous plants. Whether chalcone isomerase (CHI), the key enzyme gene in the flavonoid synthesis pathway, contributes to soybean (Glycine max) nodulation has not yet been fully clarified. In the present study, we identified the functions of three types of GmCHI for BNF using a hairy root system. The results showed that GmCHI1A and GmCHI1B1 positively increased nodulation while GmCHI1B2 did not, with the GmCHI1A gene having a greater effect than GmCHI1B1. Meanwhile, the daidzein and genistein contents were significantly increased in composite plants overexpressing GmCHI1A and reduced in composite plants, thus interfering with GmCHI1A. However, overexpression of GmCHI1B1 significantly increased the content of glycitein but not daidzein, genistein content implied that homologous genes exhibit functional differentiation. These results provide a reference for subsequent studies on improving nitrogen fixation in soybeans and providing functional genes for the improvement of new varieties.","PeriodicalId":54282,"journal":{"name":"Gm Crops & Food-Biotechnology in Agriculture and the Food Chain","volume":"16 1","pages":"305-317"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11970754/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143755990","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}

引用次数: 0

An effective encryption approach using a combination of a non-chain ring and a four-dimensional chaotic map. 一种利用非链环和四维混沌映射相结合的有效加密方法。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-15 DOI: 10.1007/s11571-025-10217-1

Muhammad Umair Safdar, Tariq Shah, Asif Ali

{"title":"An effective encryption approach using a combination of a non-chain ring and a four-dimensional chaotic map.","authors":"Muhammad Umair Safdar, Tariq Shah, Asif Ali","doi":"10.1007/s11571-025-10217-1","DOIUrl":"10.1007/s11571-025-10217-1","url":null,"abstract":"Algebraic structures are highly effective in designing symmetric key cryptosystems; however, if the key space is not sufficiently large, such systems become vulnerable to brute-force attacks. To address this challenge, our research focuses on enlarging the key space in symmetric key schemes by integrating the non-chain ring with a four-dimensional chaotic system. While chaotic maps offer significant potential for data processing, relying solely on them does not fully leverage their operational advantages. Therefore, it is essential to incorporate algebraic structures that enhance the complexity of the scheme. In the proposed technique, four-dimensional chaotic sequences are employed for image pixel permutation, diffusion, and exclusive-or operations. The scheme is further strengthened against chosen and known plaintext attacks by incorporating pixel values during the exclusive-or operation, where images are XORed with hashed images and keys generated from chaotic sequences. The effectiveness of the technique, its resilience to various forms of attack, and its feasibility for practical implementation are demonstrated through extensive testing and a comprehensive security analysis.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"27"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000913","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}

引用次数: 0

Multi-view domain adaption based multi-scale convolutional conditional invertible discriminator for cross-subject electroencephalogram emotion recognition. 基于多视域自适应的多尺度卷积条件可逆判别器在跨主体脑电图情绪识别中的应用。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-13 DOI: 10.1007/s11571-024-10193-y

Sivasaravana Babu S, Prabhu Venkatesan, Parthasarathy Velusamy, Saravana Kumar Ganesan

{"title":"Multi-view domain adaption based multi-scale convolutional conditional invertible discriminator for cross-subject electroencephalogram emotion recognition.","authors":"Sivasaravana Babu S, Prabhu Venkatesan, Parthasarathy Velusamy, Saravana Kumar Ganesan","doi":"10.1007/s11571-024-10193-y","DOIUrl":"10.1007/s11571-024-10193-y","url":null,"abstract":"Cross subject Electroencephalogram (EEG) emotion recognition refers to the process of utilizing electroencephalogram signals to recognize and classify emotions across different individuals. It tracks neural electrical patterns, and by analyzing these signals, it's possible to infer a person's emotional state. The objective of cross-subject recognition is to create models or algorithms that can reliably detect emotions in both the same person and several other people. Accurately predicting emotions poses challenges due to dynamic traits. Models struggle with feature extraction, convergence, and negative transfer issues, hindering cross subject emotion recognition. The proposed model employs thorough signal preprocessing, Short-Time Geodesic Flow Kernel Fourier Transform (STGFKFT) for feature extraction, enhancing classifiers' accuracy. Multi-view sheaf attention improves feature discrimination, while the Multi-Scale Convolutional Conditional Invertible Puma Discriminator Neural Network (MSCCIPDNN) framework ensures generalization. Efficient computational techniques and the puma optimization algorithm enhance model robustness and convergence. The suggested framework demonstrates extraordinary success with high accuracy, of 99.5%, 99% and 99.50% for SEED, SEED-IV, and DEAP dataset sequentially. By incorporating these techniques, the proposed method aims to precisely recognition emotions, and accurately captures the features, thereby overcoming the limitations of existing methodologies.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"23"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001038","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}

引用次数: 0

3T dilated inception network for enhanced autism spectrum disorder diagnosis using resting-state fMRI data. 利用静息状态fMRI数据增强自闭症谱系障碍诊断的3T扩展初始网络。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-13 DOI: 10.1007/s11571-024-10202-0

V Kavitha, R Siva

{"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":"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.","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}

引用次数: 0

Implementation of memristive emotion associative learning circuit. 记忆性情感联想学习电路的实现。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-09 DOI: 10.1007/s11571-024-10211-z

Zhangzhi Zhou, Mi Lin, Xuanxuan Zhou, Chong Zhang

引用次数: 0

Optimal time-frequency localized wavelet filters for identification of Alzheimer's disease from EEG signals. 基于时频局部化小波滤波的脑电信号阿尔茨海默病识别。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-09 DOI: 10.1007/s11571-024-10198-7

Digambar V Puri, Jayanand P Gawande, Pramod H Kachare, Ibrahim Al-Shourbaji

{"title":"Optimal time-frequency localized wavelet filters for identification of Alzheimer's disease from EEG signals.","authors":"Digambar V Puri, Jayanand P Gawande, Pramod H Kachare, Ibrahim Al-Shourbaji","doi":"10.1007/s11571-024-10198-7","DOIUrl":"10.1007/s11571-024-10198-7","url":null,"abstract":"Alzheimer's disease (AD) is a chronic disability that occurs due to the loss of neurons. The traditional methods to detect AD involve questionnaires and expensive neuro-imaging tests, which are time-consuming, subjective, and inconvenient to the target population. To overcome these limitations, Electroencephalogram (EEG) based methods have been developed to classify AD patients from normal controlled (NC) and mild cognitive impairment (MCI) subjects. Most of the EEG-based methods involved entropy-based feature extraction and discrete wavelet transform. However, the existing AD classification methods failed to provide promising classification accuracy. Here, we proposed a wavelet-machine learning (ML) framework to detect AD using a newly designed biorthogonal filter bank by optimization of frequency and time localization of triplet halfband filter banks (OTFL-THFB). The OTFL-THFB decomposes EEG signals into various EEG sub- bands. Hjorth Parameters (HP) and Higuchi's Fractal Dimension (HFD) have been investigated to extract features from each EEG subband. Subsequently, ML models are trained and tested using different features such as OTFL-THFB with HFD, OTFL-THFB with HP, and OTFL-THFB with HFD and HP used for detecting AD with 10-fold cross-validation. This method was applied to two publicly available datasets. Our model achieved an accuracy of <math><mrow><mn>98.91</mn> <mo>%</mo></mrow> </math> for AD versus NC and <math><mrow><mn>98.65</mn> <mo>%</mo></mrow> </math> for AD versus MCI versus NC using the least square support vector machine. Results indicate that this framework surpassed existing state-of-the-art techniques for classifying AD from NC.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"12"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717779/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969957","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}

引用次数: 0

The phonation test can distinguish the patient with Parkinson's disease via Bayes inference. 语音测试可以通过贝叶斯推理来区分帕金森病患者。

IF 3.1 3区工程技术

Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-09 DOI: 10.1007/s11571-024-10194-x

Yifeng Liu, Hongjie Gong, Meimei Mouse, Fan Xu, Xianwei Zou, Jingsheng Yang, Qingping Xue, Min Huang

{"title":"The phonation test can distinguish the patient with Parkinson's disease via Bayes inference.","authors":"Yifeng Liu, Hongjie Gong, Meimei Mouse, Fan Xu, Xianwei Zou, Jingsheng Yang, Qingping Xue, Min Huang","doi":"10.1007/s11571-024-10194-x","DOIUrl":"10.1007/s11571-024-10194-x","url":null,"abstract":"Parkinson's disease (PD) is a neurodegenerative disease with various clinical manifestations caused by multiple risk factors. However, the effect of different factors and relationships between different features related to PD and the extent of those factors leading to the incidence of PD remains unclear. we employed Bayesian network to construct a prediction model. The prediction system was trained on the data of 35 patients and 26 controls. The structure learning and parameter learning of Bayesian Network was completed through the tree-augmented network (TAN) and Netica software, respectively. We employed four Bayesian Networks in terms of the syllable, including monosyllables, disyllables, multisyllables and unsegmented syllables. The area under the curve (AUC) of monosyllabic, disyllabic, multisyllabic, and unsegmented-syllable models were 0.95, 0.83, 0.80 and 0.84, respectively. In the monosyllabic tests, the best predictor of PD was duration, the posterior probability of which was 92.70%. Meanwhile, minimum f0 (61.60%) predicted best in the disyllabic tests and the variables that predicted best in multisyllables and unsegmented syllables were end f0 (59.40%) and maximum f0 (58.40%). In the cross-sectional comparison, the prediction effect of each variable in the monosyllabic tests was generally higher than that of other test groups. The monosyllabic models had the highest predicted performance of PD. Among acoustic parameters, duration was the strongest feature in predicting the prevalence of PD in monosyllabic tests. We believe that this network methodology will be a useful tool for the clinical prediction of Parkinson's disease.Supplementary information: The online version contains supplementary material available at 10.1007/s11571-024-10194-x.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"18"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969961","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}

引用次数: 0