Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

This paper has summarized current studies on retinitis pigmentosa （RP） from two perspectives， which were disease mechanism insights from western medicine， and etiology， pathogenesis and therapeutic principles in traditional Chinese medicine （TCM）. From the perspective of western medicine， the understanding of RP has evolved from an early single-factor explanation focusing on pathogenic gene mutations to a more comprehensive， multifactorial model involving genetic abnormalities， photoreceptor cell degeneration， retinal pigment epithelium dysfunction， oxidative stress， inflammatory responses， microenvironmental imbalance， and vascular insufficiency. In TCM， RP is considered to be a disorder manifested in the eyes but rooted in dysfunction of the zang-fu （脏腑） organs. Its pathogenesis is primarily associated with congenital insufficiency， liver-kidney depletion， impaired spleen function of transportation and transformation， and stasis obstructing the meridians. The core pathological mechanism can be summarized as "deficiency complicated by stasis"， emphasizing holistic imbalance， dynamic disease progression， and syndrome differentiation and treatment. The differences and complementarities between the two medical systems in understanding disease progression are further discussed. RP is proposed to be more appropriately regarded as a complex disease characterized by long-term progression， stage-dependent evolution， and persistent decompensation. Western medicine contributes to elucidating the molecular mechanisms underlying RP and provides the foundation for targeted therapeutic interventions， whereas TCM offers a holistic perspective for understanding disease evolution through the assessment of overall functional status， disease-stage stratification， and long-term syndrome-based regulation.

This paper has summarized current studies on retinitis pigmentosa （RP） from two perspectives， which were disease mechanism insights from western medicine， and etiology， pathogenesis and therapeutic principles in traditional Chinese medicine （TCM）. From the perspective of western medicine， the understanding of RP has evolved from an early single-factor explanation focusing on pathogenic gene mutations to a more comprehensive， multifactorial model involving genetic abnormalities， photoreceptor cell degeneration， retinal pigment epithelium dysfunction， oxidative stress， inflammatory responses， microenvironmental imbalance， and vascular insufficiency. In TCM， RP is considered to be a disorder manifested in the eyes but rooted in dysfunction of the zang-fu （脏腑） organs. Its pathogenesis is primarily associated with congenital insufficiency， liver-kidney depletion， impaired spleen function of transportation and transformation， and stasis obstructing the meridians. The core pathological mechanism can be summarized as "deficiency complicated by stasis"， emphasizing holistic imbalance， dynamic disease progression， and syndrome differentiation and treatment. The differences and complementarities between the two medical systems in understanding disease progression are further discussed. RP is proposed to be more appropriately regarded as a complex disease characterized by long-term progression， stage-dependent evolution， and persistent decompensation. Western medicine contributes to elucidating the molecular mechanisms underlying RP and provides the foundation for targeted therapeutic interventions， whereas TCM offers a holistic perspective for understanding disease evolution through the assessment of overall functional status， disease-stage stratification， and long-term syndrome-based regulation.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Objective To explore the nutritional status in elderly patients with type 2 diabetes mellitus (T2DM) and analyze its relationship with the risk of sarcopenia. Methods A retrospective analysis was conducted on 312 elderly patients with T2DM admitted to the 904th Hospital of the Joint Logistics Support Force of the People's Liberation Army between January 2023 and December 2025. Based on the presence or absence of sarcopenia, the patients were classified into a sarcopenia group (121 cases) and a non-sarcopenia group (191 cases). The nutritional status and related factors were compared between the two groups. Binary logistic regression analysis was adopted to analyze the correlation and influencing factors. Results The incidence rate of sarcopenia among elderly patients with T2DM was 38.78%. Compared with the non-sarcopenia group, the sarcopenia group had older age and higher proportions of patients with daily activity dependence, coronary heart disease, and gastrointestinal diseases. Conversely, the proportions of patients exercising ≥4 times per week and those paying attention to nutritional knowledge were lower in the sarcopenia group than those in the non-sarcopenia group (P<0.05). The body mass index (BMI), calf circumference (CC), body weight, albumin (ALB), hemoglobin (Hb), and MNA-SF score in the sarcopenia group were lower compared with those in the non-sarcopenia group (P<0.05). After logistic regression analysis, it was found that low BMI, exercising ≥4 times per week, dependence on daily activity, and low ALB and Hb were independent factors influencing sarcopenia in elderly patients with T2DM (P<0.05). Conclusion The incidence rate of sarcopenia is relatively high in elderly patients with T2DM. Low BMI, low ALB, low Hb, reduced weekly exercise frequency, and daily activity dependence are independent related factors. It is necessary to pay clinical attention to nutritional assessment and intervention.

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

Depression, a prevalent mental disorder with significant socioeconomic burdens, underscores the urgent need for safe and effective non-pharmacological interventions. Recent advances in microbiome research have revealed the pivotal role of gut microbiota dysbiosis in the pathogenesis of depression. Concurrently, exercise, as a cost-effective and accessible intervention, has demonstrated remarkable efficacy in alleviating depressive symptoms. This comprehensive review synthesizes current evidence on the interplay among exercise, gut microbiota modulation, and depression, elucidating the mechanistic pathways through which exercise ameliorates depressive symptoms via the microbiota-gut-brain (MGB) axis. Depression is characterized by gut microbiota alterations, including reduced alpha and beta diversity, depletion of beneficial taxa (e.g., Bifidobacterium, Lactobacillus, and Coprococcus), and overgrowth of pro-inflammatory and pathogenic bacteria (e.g., Morganella, Klebsiella, and Enterobacteriaceae). Metagenomic analyses reveal disrupted metabolic functions in depressive patients, such as diminished synthesis of short-chain fatty acids (SCFAs), impaired tryptophan metabolism, and dysregulated bile acid conversion. For instance, Bifidobacterium longum deficiency correlates with reduced synthesis of neuroactive metabolites like homovanillic acid, while decreased Coprococcus abundance limits butyrate production, exacerbating neuroinflammation. Furthermore, elevated levels of indole derivatives from Clostridium species inhibit serotonin (5-HT) synthesis, contributing to depressive phenotypes. These dysbiotic profiles disrupt the MGB axis, triggering systemic inflammation, neurotransmitter imbalances, and hypothalamic-pituitary-adrenal (HPA) axis hyperactivity. Exercise exerts profound effects on gut microbiota composition, diversity, and metabolic activity. Longitudinal studies demonstrate that sustained aerobic exercise increases alpha diversity, enriches SCFA-producing genera (e.g., Faecalibacterium prausnitzii, Roseburia, and Akkermansia), and suppresses pathobionts (e.g., Desulfovibrio and Streptococcus). For example, a meta-analysis of 25 trials involving 1 044 participants confirmed that exercise enhances microbial richness and restores the Firmicutes/Bacteroidetes ratio, a biomarker of metabolic health. Notably, endurance training promotes Veillonella proliferation, which converts lactate into propionate, enhancing energy metabolism and delaying fatigue. Exercise also strengthens intestinal barrier integrity by upregulating tight junction proteins (e.g., ZO-1, occludin), thereby reducing lipopolysaccharide (LPS) translocation and systemic inflammation. However, excessive exercise may paradoxically diminish microbial diversity and exacerbate intestinal permeability, highlighting the importance of moderate intensity and duration. Exercise ameliorates depressive symptoms through multifaceted interactions with the gut microbiota, primarily via 4 interconnected pathways. First, exercise mitigates neuroinflammation by elevating anti-inflammatory SCFAs such as butyrate, which suppresses NF-κB signaling to attenuate microglial activation and oxidative stress in the hippocampus. Animal studies demonstrate that voluntary wheel running reduces hippocampal TNF‑α and IL-17 levels in stress-induced depression models, while fecal microbiota transplantation (FMT) from exercised mice reverses depressive behaviors by modulating the TLR4/NF‑κB pathway. Second, exercise regulates neurotransmitter dynamics by enriching GABA-producing Lactobacillus and Bifidobacterium, thereby counteracting neuronal hyperexcitability. Aerobic exercise also enhances the abundance of Lactobacillus plantarum and Streptococcus thermophilus, which facilitate 5-HT and dopamine synthesis. Clinical trials reveal that 12 weeks of moderate exercise increases fecal Coprococcus and Blautia abundance, correlating with improved 5-HT bioavailability and reduced depression scores. Third, exercise normalizes HPA axis hyperactivity by reducing cortisol levels and restoring glucocorticoid receptor sensitivity. In rodent models, chronic stress-induced corticosterone elevation is reversed by probiotic supplementation (e.g., Lactobacillus), which enhances endocannabinoid signaling and hippocampal neurogenesis. Furthermore, exercise upregulates brain-derived neurotrophic factor (BDNF) via microbial metabolites like butyrate, promoting histone acetylation and synaptic plasticity. FMT experiments confirm that exercise-induced microbiota elevates prefrontal BDNF expression, reversing stress-induced neuronal atrophy. Fourth, exercise reshapes microbial metabolic crosstalk, diverting tryptophan metabolism toward 5-HT synthesis instead of neurotoxic kynurenine derivatives. Butyrate inhibits indoleamine 2,3-dioxygenase (IDO), a key enzyme in the kynurenine pathway linked to depression. Concurrently, exercise-induced Akkermansia enrichment enhances mucin production, fortifies the gut barrier, and reduces LPS-driven neuroinflammation. Collectively, these mechanisms underscore exercise as a potent modulator of the microbiota-gut-brain axis, offering a holistic approach to alleviating depression through microbial and neurophysiological synergy. Current evidence supports exercise as a potent adjunct therapy for depression, with personalized regimens (e.g., aerobic, resistance, or yoga) tailored to individual microbiota profiles. However, challenges remain in optimizing exercise prescriptions (intensity, duration, and type) and integrating them with probiotics, prebiotics, or FMT for synergistic effects. Future research should prioritize large-scale randomized controlled trials to validate causality, multi-omics approaches to decipher MGB axis dynamics, and mechanistic studies exploring microbial metabolites as therapeutic targets. The authors advocate for a paradigm shift toward microbiota-centric interventions, emphasizing the bidirectional relationship between physical activity and gut ecosystem resilience in mental health management. In conclusion, this review underscores exercise as a multifaceted modulator of the gut-brain axis, offering novel insights into non-pharmacological strategies for depression. By bridging microbial ecology, neuroimmunology, and exercise physiology, this work lays a foundation for precision medicine approaches targeting the gut microbiota to alleviate depressive disorders.

Objective: Based on spinopelvic parameters and biomechanical principles, the pedicle-facet joint (PFJ) morphological characteristics of isthmic and degenerative spondylolisthesis were analyzed, and the mechanism of their onset and progression was discussed. Methods: This retrospective cross-sectional study included 194 patients with L5 spondylolysis or L5–S1 low-grade isthmic spondylolisthesis (IS group), 172 patients with L4–5 degenerative spondylolisthesis (DS group), and 366 patients with nonlumbar spondylolysis (NL group). The spinopelvic parameters and PFJ morphological parameters of the patients were measured, the differences in these parameters among and within the 3 groups were compared, and the correlations were analyzed. Results: Sacral slope (SS) and lumbar lordosis (LL) were the highest in the IS group, the second highest in the DS group, and the lowest in the NL group. Among the 3 groups, the L4 facet joint angle (FJA) was the largest in the IS group, the second largest in the NL group, and the smallest in the DS group. The L4 pedicle-facet joint angle (PFA) was the largest in the DS group, the second largest in the IS group, and the smallest in the NL group. Pearson correlation analysis showed that within each group, SS and LL were negatively correlated with FJA and positively correlated with PFA. Conclusion This study found a correlation between the PFJ morphological characteristics of patients with lumbar spondylolisthesis and spinopelvic parameters, suggesting that the morphological characteristics of PFJs may be caused by varying stresses under different spinopelvic morphologies.

Objective To understand the surveillance situation of poliovirus in Guangzhou from 2011 to 2024, and to further strengthen polio surveillance and ensure the continued maintenance of a polio-free status. Methods An analysis was conducted on the discovery and investigation results of six cases of vaccine-derived poliovirus (VDPV) detected in Guangzhou. Results A total of 6 VDPV incidents were reported in Guangzhou from 2011 to June 2024, among which 5 incidents were from sewage sample testing in the Liede Sewage Treatment Plant in Guangzhou, all of which were confirmed as VDPV, with 1 for type I, 1 for type II, and 3 for type III. In addition, one confirmed HFMD case was identified as a type VDPV II carrier. No presence of any wild poliovirus (WPV), VDPV cases, or circulating VDPV (cVDPV) was reported. Conclusion Guangzhou City has maintained a high level of vigilance and effectiveness in the monitoring and prevention of polio. Continuously strengthening the construction of the polio monitoring network, optimizing vaccination strategies, and comprehensively improving public health awareness are still the focus of the prevention and control work in the future.

Objective: Based on spinopelvic parameters and biomechanical principles, the pedicle-facet joint (PFJ) morphological characteristics of isthmic and degenerative spondylolisthesis were analyzed, and the mechanism of their onset and progression was discussed. Methods: This retrospective cross-sectional study included 194 patients with L5 spondylolysis or L5–S1 low-grade isthmic spondylolisthesis (IS group), 172 patients with L4–5 degenerative spondylolisthesis (DS group), and 366 patients with nonlumbar spondylolysis (NL group). The spinopelvic parameters and PFJ morphological parameters of the patients were measured, the differences in these parameters among and within the 3 groups were compared, and the correlations were analyzed. Results: Sacral slope (SS) and lumbar lordosis (LL) were the highest in the IS group, the second highest in the DS group, and the lowest in the NL group. Among the 3 groups, the L4 facet joint angle (FJA) was the largest in the IS group, the second largest in the NL group, and the smallest in the DS group. The L4 pedicle-facet joint angle (PFA) was the largest in the DS group, the second largest in the IS group, and the smallest in the NL group. Pearson correlation analysis showed that within each group, SS and LL were negatively correlated with FJA and positively correlated with PFA. Conclusion This study found a correlation between the PFJ morphological characteristics of patients with lumbar spondylolisthesis and spinopelvic parameters, suggesting that the morphological characteristics of PFJs may be caused by varying stresses under different spinopelvic morphologies.