Guangxi Zhuang Autonomous Region Brain Hospital

High-definition transcranial alternating current stimulation (HD-tACS) is an emerging neuromodulatory intervention for major depressive disorder (MDD). Here, we evaluate the efficacy and safety of a portable, low-intensity (1.6 mA), 10 Hz HD-tACS protocol targeting the bilateral dorsolateral prefrontal cortex (DLPFC) in adults with MDD. This randomized clinical trial was conducted including 120 adult MDD participants. Participants underwent 20 sessions (5 sessions/week for 4 weeks) of either active 10 Hz HD-tACS (1.6 mA) or sham stimulation a ratio of 1:1 and were followed for an additional 4 weeks. The primary outcome was the percentage reduction in 17-item Hamilton Depression Rating Scale scores at week 4. The active group showed significantly greater improvement in depression than the sham group (48% ± 14% vs 24% ± 13%, p < 0.001), sustained through the 4-week follow-up period. Additionally, significant improvements in the active group were also found in anxiety, sleep efficiency, quality of life components of physical, vitality, social functioning, and mental health. Adverse events including two cases of new-onset hypomania occurred, but no serious adverse events were observed. Thus, this trial supported the efficacy and good tolerability of 10 Hz HD-tACS for patients with MDD. Further research requires more focus on the underlying neural mechanisms and the optimized stimulation protocols. Trial Registration: China Clinical Trial Registry Identifier: ChiCTR2500103570. ClinicalTrials.gov Identifier: NCT06891326.

Affective Computing and emotion recognition hold significant importance in healthcare, identity verification, human-computer interaction, and related fields. Accurate identification of emotion is crucial for applications in medicine, education, psychology, and military domains. Electroencephalographic (EEG) signals have gained widespread application in emotion recognition due to their inherent characteristics of being non-concealable and directly reflecting brain activity. In recent years, with the establishment of open datasets and advancements in deep learning, an increasing number of researchers have integrated EEG with deep learning methods for emotion recognition studies. This review summarizes commonly used deep learning models in EEG-based emotion recognition along with their applications in this field, including the design of different network architectures, optimization strategies, and model designs based on EEG signal features. We also discuss limitations from the perspectives of commonality-individuality (C-I) and suggest improvements. The review outlines future research directions and provided a minimal C-I framework to assess models. Through this review, we aim to provide researchers in this field with a comprehensive reference and approach to balance universality and personalization to promote the development of deep learning-based EEG emotion recognition methods.

This study aims to evaluate the impact of the traditional Chinese medicine formula “Pinggan Jiedu Formula” combined with antiretroviral therapy (ART) on the transcriptional and immune status of hepatitis B virus (HBV) in patients with HIV/HBV co-infection. A total of 62 patients with co-infection of HIV/HBV were included in the study and randomly divided into two groups. In the combined treatment group, 31 patients received PGJDP combined with ART treatment for 24 weeks and then continued to receive ART treatment alone. In the control group, 31 cases received ART treatment throughout the course. The study employed real-time quantitative polymerase chain reaction (RT-qPCR) to detect HBV DNA, HIV RNA, HBV RNA and HIV DNA, and to evaluate the viral replication level and transcriptional activity. Flow cytometry was used to detect the count of CD4 + T cells and the CD4/CD8 ratio in peripheral blood, reflecting the immune status of the patients. The level of HBsAg in serum was detected by enzyme-linked immunosorbent assay (ELISA) to monitor the effect of antiviral treatment. Meanwhile, transient elastography was used to detect liver stiffness (LSM) and calculate the FIB-4 index to evaluate the degree of liver fibrosis. The research results show that compared with the control group, the PGJDP combined treatment group significantly reduced the HBV RNA level, significantly decreased the HBsAg level, significantly increased the CD4 + T cell count, and significantly improved the CD4/CD8 ratio. The PGJDP combined treatment group also showed significant improvement in liver fibrosis indicators. In terms of the incidence of abnormal liver function, the PGJDP combined treatment group was significantly lower than the control group. These results suggest that the combination therapy of PGJDP has potential therapeutic benefits in inhibiting HBV transcription and enhancing the immune response. • To evaluate the effects of “Pinggan Jiedu Prescription” (PGJDP) in combination with antiretroviral therapy (ART) on hepatitis B virus (HBV) transcription and immune status in individuals co-infected with human immunodeficiency virus (HIV) and HBV. • PGJDP combination therapy group showed enhanced hepatic protection and a significantly lower incidence of liver function abnormalities. • Providing a novel therapeutic strategy for HIV-HBV co-infected patients through the integration of PGJDP with ART.

Despite advances in understanding systemic immune responses to Mycobacterium tuberculosis (Mtb), the localized immune dynamics within infected lymph nodes, particularly cell-type-specific transcriptional reprogramming and intercellular crosstalk, remain poorly defined, impeding targeted therapy development. By means of single-cell transcriptomics, the objective was to dissect the immune microenvironment and map intercellular crosstalk in Mtb-infected cervical lymph nodes, with the purpose of uncovering the mechanisms of localized immunity and immunopathology. Paired Mtb-positive cervical swollen lymph nodes (SLN) and adjacent Mtb-negative normal-appearing lymph nodes (NLN) from five cervical LNTB patients were analyzed using single-cell RNA sequencing (scRNA-seq). Computational network modeling (CellChat) and flow cytometry validation were employed to map immune cell heterogeneity and cell–cell communication. ScRNA-seq identified ten T cell subsets, ten B cell subsets, and six myeloid subsets, revealing conserved frequencies but substantial transcriptional reprogramming in SLN. The SLN exhibited extensive upregulation of pro-inflammatory pathways across T, B, and myeloid cells, accompanied by minimal alterations in subset frequencies. IL1B + macrophages in SLN showed an enrichment of genes associated with oxidative phosphorylation, antigen presentation, and inflammasome-related genes. The SLN demonstrated an increased cell–cell communication driven by the crosstalk between macrophage and CD8 + T/NKT cells. Validation through flow cytometry confirmed comparable proportions of immune subsets between the SLN and the NLN, which was consistent with the findings of scRNA-seq. This study delineates a spatially coordinated immune strategy in cervical LNTB. In this context, Mtb infection induces transcriptional and metabolic reprogramming rather than subset redistribution. The strengthened interaction between macrophages and T cells emphasizes that cellular immunity serves as the main impetus for bacterial containment. Nevertheless, there are trade-offs between inflammation and tissue integrity. These insights provide a framework for developing therapies that target intercellular networks to achieve a balance between immunity and pathology in LNTB.

Flight behavior in pigeons is governed by intricate neural mechanisms that regulate movement patterns and flight dynamics. Among various kinematic parameters, flight acceleration provides critical information for the brain to modulate movement intensity, speed, and direction. However, the neural representation mechanisms underlying flight acceleration remain insufficiently understood. To address this, we conducted outdoor free-flight experiments in homing pigeons, during which GPS data, flight posture, and eight-channel local field potentials (LFPs) were synchronously recorded. Our analysis revealed that gamma-band activity in the dorsal intermediate arcopallium (AId) region was more prominent during behaviorally demanding phases of flight. In parallel, local functional network analysis showed that the clustering coefficient of gamma-band activity in the AId followed a nonlinear, U-shaped relationship with flight acceleration-exhibiting the strongest and most widespread connectivity during deceleration, moderate connectivity during acceleration, and the weakest network coupling during steady flight. This pattern likely reflects the increased neural demands associated with flight phase transitions, where greater cognitive and sensorimotor integration is required. Furthermore, using LFP signals from five distinct frequency bands as input, machine learning models were developed to decode flight acceleration, further confirming the role of gamma-band dynamics in motor regulation during natural flight. This study provides the first evidence that gamma-band activity in the avian AId region encodes flight acceleration, offering new insights into the neural representation of motor states in natural flight and implications for bio-inspired flight control systems.

Stroke is a life-threatening cerebrovascular disorder categorized into two major subtypes: Ischemic and hemorrhagic. Characterized by high morbidity and mortality rates, its clinical management remains challenging due to limited therapeutic options. Interleukin (IL)-27, a pleiotropic cytokine with demonstrated neuroprotective potential, has emerged as a promising candidate for stroke intervention. IL-27 exerts immunomodulatory effects within the central nervous system, including suppression of proinflammatory T-cell proliferation and induction of regulatory T-cell differentiation. These mechanisms collectively attenuate neuroinflammation, mitigate neuronal apoptosis and prevent neurodegenerative processes. The efficacy of IL-27 in reducing cerebral damage in both ischemic and hemorrhagic stroke models has been validated, although clinical translation remains to be achieved. The present review summarizes: i) The epidemiology of stroke; ii) the immunoregulatory functions of IL-27 and its neuroprotective mechanisms across stroke subtypes; iii) innovative brain-targeted delivery approaches; iv) IL-27 clinical applicability with supporting evidence; and v) possible risks and solutions in clinical applications. By collating the current knowledge, the present study provides a translational framework for advancing IL-27-based therapies in stroke management.

The present study aimed to develop a reliable predictive model for identifying preoperative predictors of poor initial outcomes in patients with primary trigeminal neuralgia (PTN) treated with Gamma Knife radiosurgery (GKRS) and further elucidate the clinical significance of these predictors in initial outcomes and long-term pain recurrence. A total of 217 PTN patients were divided into a training set (n = 167) and a validation set (n = 50). The initial outcomes of GKRS treatment were assessed based on the Barrow Neurological Institute pain intensity scale. A predictive model was developed through multivariate regression and validated with repeated sampling. The differences in predictors of long-term pain recurrence were assessed using Kaplan-Meier analysis. The association between predictors was tested using chi-square tests, and subgroup analyses were performed to compare initial outcomes and long-term pain recurrence between two clinically significant correlates. The training and validation sets showed areas under the curve of 0.85 and 0.88, respectively. Calibration curves and decision curve analysis indicated significant clinical benefits in both sets. Independent risk factors for poor initial outcomes included hyperglycemia, absence of neurovascular contact, carbamazepine insensitivity, and atypical pain (trigeminal neuralgia type 2 [TN2]). Carbamazepine insensitivity was moderately associated with TN2 and predicted long-term pain recurrence. Patients with both phenotypes had significantly worse initial outcomes compared with other subgroups (adjusted p = 0.0125). Patients with both TN2 and carbamazepine insensitivity have the poorest initial treatment outcomes and face an increased risk of recurrence. Furthermore, this predictive model is highly accurate and useful, offering a comprehensive method of identifying PTN patients likely to experience poor initial outcomes based on clinical characteristics and imaging perspectives. The authors believe that the nomogram presented in this model enables clinicians to calculate multiple variables and predict the probability of adverse events.

Schizophrenia may be exacerbated by ambient air pollution. In this study, we aim to explore the association of air pollution with hospital admission for schizophrenia in Liuzhou, China. The daily concentration of air pollutants was gathered from an average of seven fixed monitoring sites in Liuzhou, while the daily admission data for schizophrenia was received from The Guangxi Zhuang Autonomous Region Brain Hospital. A Poisson generalized linear regression model in conjunction with a distributed lag nonlinear model was utilized to quantify the exposure-lag-response connection between ambient air pollution and schizophrenia hospitalization. The stratification analysis was then carried out by age, gender, and season. PM2.5, PM10, and SO2 was significantly associated with elevated number of schizophrenia hospitalization. We observed the largest single-day effects of PM2.5 at lag 17day, PM10 at lag 17day, and SO2 at lag 28day, with the corresponding RRs being 1.01611 (95% CI:1.00652-1.02579), 1.01648 (95% CI:1.00603-1.02704), and 1.02001 (95% CI: 1.00001-1.04041), respectively. Stratification analysis revealed that patients who were < 45 years old and female were more vulnerable to hospitalization due to exposure to PM2.5 and PM10. The effects of PM2.5 and PM10 were more noticeable during the cooler seasons than during the warmer one. This study reveals that being exposed to PM2.5, PM10, and SO2 may increase the chance of schizophrenia hospitalization.