The existing epilepsy seizure detection algorithms have problems such as overfitting and poor generalization ability due to high reliance on manual labeling of electroencephalogram's data and data imbalance between seizure and interictal periods. An unsupervised learning detection method for epileptic seizure that jointed graph attention network (GAT) and Transformer framework (GAT-T) was proposed. In this method, channel correlations were adaptively learned by GAT encoder. Temporal information was captured by one-dimensional convolution decoder. Combining outputs of the two mentioned above, predicted values for electroencephalogram were generated. The collective anomaly score was calculated and the detection threshold was determined. The results demonstrated that GAT-T achieved the average performance exceeding 90% (or 99%) with a 0.25 s (or 2 s) time segment length, which could effectively detect epileptic seizures. Moreover, the channel association probability matrix was expected to assist clinicians in the initial screening of the epileptogenic zone, and ablation experiments also reflected the significance of each module in GAT-T. This study may assist clinicians in making more accurate diagnostic and therapeutic decisions for epilepsy patients.
Humans ; Electroencephalography/methods* ; Epilepsy/physiopathology* ; Algorithms ; Seizures/physiopathology* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

OBJECTIVES: We propose a multimodal model integrating social media text and image data for automated assessment of psychological stress in college students to support the development of intelligent mental health services in higher education institutions. METHODS: Based on deep learning technology, we designed an evaluation framework comprising a text sentiment modeling module, an image sentiment modeling module, and a multimodal fusion prediction module. Text sentiment features were extracted using Bi-LSTM, and image semantic cues were extracted via U-Net. A feature concatenation strategy was used to enable cross-modal semantic collaboration to achieve automatic identification of 3 psychological stress levels: mild, moderate, and severe. We constructed a multimodal annotated dataset using social platform data from 1577 students across multiple universities in Guangdong Province. After data cleaning, 252 samples were randomly selected for model training and testing. RESULTS: In the 3-classification task, the model demonstrated outstanding performance on the test set, and achieved an accuracy of 92.86% and an F1 score of 0.9276, exhibiting excellent stability and consistency. Confusion matrix analysis further revealed the model's ability to effectively distinguish between different pressure levels. CONCLUSIONS The multimodal psychological stress assessment model developed in this study effectively integrates unstructured social behavior data to enhance the scientific rigor and practical applicability of psychological state recognition, and thus provides support for developing intelligent psychological service systems.
Humans ; Stress, Psychological/diagnosis* ; Students/psychology* ; Universities ; Social Media ; Deep Learning

A novel epileptic seizure prediction prediction model based on multichannel temporal and spatial feature extractions is presented.The model applies Stockwell transform to the original multichannel electroencephalogram(EEG)signals for extracting time-frequency components.To address the issue of insignificant difference between preseizure and interseizure time-frequency features,an adaptive feature module composing of ConvNeXt,SENet and pyramid pooling module is designed to enhance the ability of capturing key time-frequency features in each EEG channel.Meanwhile,a prediction model based on Bi-NLSTM is constructed to improve the spatiotemporal dependence between the time-frequency features of multichannel high-order EEG for further promoting the epilepsy classification performance.On the CHB-MIT dataset,the model has an accuracy,sensitivity,specificity and AUC of 96.0%,97.8%,96.8%and 0.987,respectively,and the false positive rate per hour decreased to 0.038,outperforming the existing mainstream methods.In addition,the effect of each component on the model performance is verified by ablation study.The proposed method improves the overall performance for seizure prediction effectively by optimizing local time-frequency feature extraction and enhancing multichannel spatiotemporal dependence.

A novel epileptic seizure prediction prediction model based on multichannel temporal and spatial feature extractions is presented.The model applies Stockwell transform to the original multichannel electroencephalogram(EEG)signals for extracting time-frequency components.To address the issue of insignificant difference between preseizure and interseizure time-frequency features,an adaptive feature module composing of ConvNeXt,SENet and pyramid pooling module is designed to enhance the ability of capturing key time-frequency features in each EEG channel.Meanwhile,a prediction model based on Bi-NLSTM is constructed to improve the spatiotemporal dependence between the time-frequency features of multichannel high-order EEG for further promoting the epilepsy classification performance.On the CHB-MIT dataset,the model has an accuracy,sensitivity,specificity and AUC of 96.0%,97.8%,96.8%and 0.987,respectively,and the false positive rate per hour decreased to 0.038,outperforming the existing mainstream methods.In addition,the effect of each component on the model performance is verified by ablation study.The proposed method improves the overall performance for seizure prediction effectively by optimizing local time-frequency feature extraction and enhancing multichannel spatiotemporal dependence.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective To study the influence of long term simulated weightlessness on occurrence of laryngopharyngeal reflux(LPR)in healthy volunteers by detection of pepsin in saliva.Methods During a 90-day head-down tilt bed rest(HDTBR)experiment,11 volunteers(4 from the control group and 7 from the countermeasure group)were recruited in the study in the following seven sessions:before bed rest session(Pre),during bed rest sessions for 3 days(BR3),31 days(BR31),61 days(BR61),85 days(BR85)and post bed rest sessions for 7 days(R7)and 25 days(R25).During each testing session,saliva samples were collected for two consecutive days both in the morning and at night before sleeping.Then pepsin in the saliva was measured by enzyme-linked immunosorbent assay.Scale of otorhinolaryngological symptoms for the duration of"Pre-,During-and Post-"were retrospectively performed.Results Among 288 saliva samples of 11 volunteers,17 saliva samples of 8 volunteers were positive for pepsin.The incidence of LPR was 9.1%(1/11)in the Pre session,and it increased to 36.4%in the BR31 session which was higher than the following consequential sessions(0%in BR31,27.3%in BR61 and 27.3%in BR85).Intriguingly,it rose again to 45.5%in R7 session and decreased to 9.1%until in R25 session.There was no significant difference between the control group and the countermeasure group.Total scores for the scale of otorhinolaryngological symptoms showed that a slight elevation tendency emerged during HDTBR session,compared with the pre-HDTBR session.It recovered during the post bed rest sessions.Conclusion The laryngopharyngeal reflux was found in the Pre,During and Post HDTBR experiment.The incidence was significantly increased both in the BR3 and R7 sessions,which indicates that the change of the posture with the stimulation of gastrointestinal dynamic conditions,despite the changes from vertical to horizontal or from horizontal to vertical,might be the major impact factor contributing to the elevation tendency of the incidence of laryngopharyngeal reflux.

Objective To investigate the prevalence of Cryptosporidium infection and the distribution of parasite species and genotypes among HIV-positive individuals in Jiangxi Province. Methods HIV-positive individuals' sociodemographic and clinical data were collected from three AIDS designated hospitals in Jiangxi Province from January 2022 to March 2023. Subjects' stool samples were collected, and genomic DNA was extracted from stool samples. Nested PCR assay was performed based on the small subunit ribosomal RNA (SSU rRNA) gene of Cryptosporidium, and Cryptosporidium gp60 gene was amplified in stool samples positive for the SSU rRNA gene. The second-round PCR amplification product was checked with 1.5% agarose gel electrophoresis, and the products of suspected positive amplifications were sequenced, followed by sequence alignment. The phylogenetic tree was created using the Neighbor-Joining method with the software MEGA 11.0, to characterize the species, genotypes and sub-genotypes of Cryptosporidium. Results A total of 382 HIV-positive individuals were enrolled, with two cases identified with Cryptosporidium infection (0.52% prevalence), and both cases had no abdominal pain or diarrhea. Following sequencing and sequence alignment, the gene sequences of these two Cryptosporidium isolates shared 99.76% and 99.88% similarity with the gene sequence of C. meleagridis isolates. Phylogenetic analysis based on the Cryptosporidium SSU rRNA gene sequence identified the species of these two Cryptosporidium-positive stool samples as C. meleagridis. Following nested PCR amplification of the Cryptosporidium gp60 gene, sequencing and sequence alignment, the two C. meleagridis isolates were characterized as III eA17G2R1 and III bA25G1R1a sub-genotypes, and the sub-genotype III bA25G1R1a was firstly described in humans. Conclusion The prevalence of Cryptosporidium is low among HIV-positive individuals in Jiangxi Province. The likelihood of Cryptosporidium infection cannot be neglected among HIV-positive individuals without diarrhea.

Humans ; Aged ; Lung Diseases ; Pneumonia/drug therapy* ; Adrenal Cortex Hormones/therapeutic use* ; Pulmonary Disease, Chronic Obstructive/drug therapy* ; Administration, Inhalation ; Community-Acquired Infections/drug therapy*

Objective:To explore the pathogenesis of flunarizine-induced parkinsonism from gut-brain axis perspective.Methods:Thirty male C57BL/6 mice were randomly divided into control group and flunarizine group ( n=15). Mice in the control group were given 0.1 mL 50% polyethylene glycol 400+50% saline by gavage once/d for 2 weeks, while mice in the flunarizine group were given 6 mg/mL flunarizine+50% polyethylene glycol 400+50% saline by gavage at a daily dose of 30 mg/kg for 2 weeks. Body mass was recorded 1, 3, 5, 7, 10 and 14 d after drug administration, and motor function was assessed by rotarod test 14 d after drug administration; 16s RNA sequencing was performed in the feces to observe the intestinal flora; intestinal transit function was detected by Evans blue by gavage; and then, the mice were sacrificed and homogenate or frozen sections (brain and intestinal tissues) were prepared; dopamine-ergic neuron expression was detected by Western blotting; RT-qPCR was applied to detect the expressions of inflammatory factors in the substantia nigra, and immunofluorescent staining was used to detect the expressions of ZO-1 and Claudin-5 in the intestinal epithelial tissues. Results:Compared with the control group, the flunarizine group had lower body mass ratio 1, 3, 5, 7, 10 and 14 d after drug administration (ratio to body mass before drug administration). Compared with the control group, the flunarizine group had significantly shortened residence time in rod rotating and lower rotational speed when falling ( P<0.05). Compared with the control group, the flunarizine group had decreased tyrosine hydroxylase protein in the substantia nigra without significant difference ( P>0.05). Compared with the control group, the flunarizine group had significantly increased interleukin-6 and tumor necrosis factor-α in the substantia nigra (1.00±0.00 vs. 2.79±0.83; 1.00±0.00 vs. 3.39±1.37), significantly lower intestinal Evans blue propulsion rate (80.67%±4.51% vs. 50.67%±6.03%), and statistically decreased ZO-1 and Claudin-5 expressions in the colonic epithelial tissues (27.01±1.41 vs. 16.32±2.83; 37.00±2.80 vs. 24.52±2.12, P<0.05). Totally, 576 microorganisms were noted in both control group and flunarizine group, 744 in the control group alone, and 634 in the flunarizine group alone. The intestinal flora β diversity indices in the 2 groups were significantly different based on weighted Unifrac-principle coordinates analysis (PCoA, PCoA1: 39.88%; PCoA2: 30.69%). Compared with the control group, the microbial colony structure of mice in flunarizine group was dominated by phylum thick-walled bacteria and phylum warty microbacteria, and by families Muribaculaceae, Lachnospiraceae and Akkermansiaceae. Compared with the control group, the flunarizine group had significantly decreased relative abundance of Ackermannia spp. and Lactobacillus spp. in the intestinal flora ( P<0.05). Conclusion:Flunarizine may contribute to the pathogenesis of DIP by causing structural disturbances in the intestinal flora and inducing neuroinflammation based on the gut-brain axis.