Nitric oxide (NO) is a crucial regulator of hepatic and systemic vascular tone. Abnormal distribution of NO in various anatomical locations is a pathogenetic characteristic of portal hypertension. Under normal portal pressure conditions, liver sinusoidal endothelial cells produce NO, which promotes both vasodilation and hepatic stellate cell relaxation. In portal hypertension, endothelial dysfunction, imbalance of asymmetric dimethylarginine levels, and production of superoxide result in impaired intrahepatic NO availability, leading to activation and contraction of hepatic stellate cells and worsening portal hypertension. Excess extrahepatic NO levels in the splanchnic vasculature result in systemic vasodilation, hyperdynamic circulation, and collateral vascular formation, worsening portal pressure. Abnormal clearance and production of NO can lead to extrahepatic complications, including hepatorenal syndrome and hepatopulmonary syndrome. Therapies including statins, phosphodiesterase-5 inhibitors, and midodrine have been developed to restore NO homeostasis but have achieved only partial success in modulating NO production, bioavailability, and distribution. The aim of this review is to update the understanding of the mechanisms and effects of NO dysregulation in cirrhosis as they relate to current and future therapeutic options.

Bladder cancer (BC) remains a major public health concern in China, but comprehensive and up-to-date assessments of its burden and temporal patterns remain limited. This study aimed to systematically evaluate the current burden, temporal trends, and future projections of BC in China using data from the Global Burden of Disease Study 2023.

Data on BC incidence, mortality, disability-adjusted life years, and risk-attributable mortality in China from 1990 to 2023 were extracted from the Global Burden of Disease Study 2023. Temporal trends were assessed using Joinpoint regression, with a maximum of six joinpoints allowed, to estimate annual percentage changes and average annual percentage changes. Age-period-cohort models based on log-linear Poisson regression were used to examine age, period, and cohort effects. Bayesian age-period-cohort models were then applied to project incidence and mortality rates to 2030 while accounting for age-period-cohort effects and demographic changes.

From 1990 to 2023, crude incidence, mortality, and disability-adjusted life year rates increased, whereas age-standardized rates generally declined (average annual percentage changes = −0.32%, −1.31%, and −1.62%, respectively). In 2023, an estimated 38.06% and 10.37% of bladder cancer deaths were attributable to smoking and high fasting plasma glucose, respectively. Recent upward trends were nevertheless observed across all three indicators, particularly for incidence and mortality during 2020–2023 (annual percentage changes = 5.05% and 4.39%, respectively). Local drifts were negative in most age groups but approached or exceeded zero in the oldest groups. The incidence local drift was 0.35% (95% confidence interval [CI]: −0.07%, 0.78%) in the 85–89-year age group and 0.64% (95% CI: −0.31%, 1.61%) in the 90–94-year age group, whereas the corresponding mortality local drifts were −0.70% (95% CI: −0.97%, −0.43%) and −0.18% (95% CI: −0.72%, 0.36%), respectively. Compared with the reference period (2004–2008), the relative risks for incidence and mortality in 2019–2023 were 0.95 (95% CI: 0.91–0.98) and 0.75 (95% CI: 0.71–0.78), respectively. Compared with the reference cohort (1951–1956), earlier birth cohorts had elevated risks; in the 1901–1906 cohort, the relative risks were 1.13 (95% CI: 0.82, 1.57) for incidence and 2.10 (95% CI: 1.75, 2.52) for mortality. During 2024–2030, both crude incidence and crude mortality rates were projected to increase further.

Despite long-term declines in age-standardized rates, BC remains a substantial burden in China, and recent upward trends warrant attention. These findings support targeted primary prevention and risk-stratified early-detection strategies for high-risk populations.

Non-motor symptoms of Parkinson’s disease, including sleep disturbance, cognitive impairment, depression, and anxiety, are common and often undertreated, yet their responsiveness to mind-body exercises remains unclear. This scoping review evaluated the currently available evidence on the effects of Tai Chi and Qigong interventions on non-motor symptoms in patients with Parkinson’s disease.

We searched six databases (PubMed, Google Scholar, EMBASE, CINAHL, Web of Science, and PEDro) through February 28, 2026, for randomized controlled trials (RCTs). We included English-language RCTs that evaluated the effects of Qigong and Tai Chi interventions on non-motor outcomes in Parkinson’s disease and excluded non-RCTs, review articles, and protocol articles. We were predominantly interested in the following non-motor outcome measures: cognition, depression, anxiety, fatigue, and sleep quality.

This review identified 18 RCTs that met the inclusion criteria, including nine Tai Chi studies and nine Qigong studies. Most of the reviewed studies were of high quality according to the PEDro scale, but the small sample sizes limited our analysis to identifying trends in outcomes. A strong trend toward a beneficial effect was found for sleep quality and cognition, a moderate trend toward improvement was found in depression, anxiety and quality of life, and weak or unclear effects were found for other non-motor symptoms such as fatigue. Several studies also had high dropout rates.

Although these studies suggest that Tai Chi and Qigong may improve sleep quality and cognition, the evidence supporting their benefits in alleviating other non-motor symptoms is generally weak, primarily because of small sample sizes. The heterogeneity in methodologies across the reviewed studies and high dropout rates in some studies are significant limitations of previous RCTs.

Cerebrospinal fluid leakage and postoperative tissue adhesion are serious complications following dural injury. Current dural substitutes often lack the functional asymmetry of the native dura mater. This study aimed to develop a hydrophilic/hydrophobic Janus polyvinyl alcohol (PVA) hydrogel membrane with a directional structure and dual functionality for effective dural defect repair.

A PVA hydrogel with an aligned porous architecture was fabricated via directional freezing combined with salt leaching, and thermal annealing was applied to enhance mechanical strength and structural stability. The hydrogel was asymmetrically modified to obtain a Janus membrane. Morphology, mechanical properties, degradation, swelling, wettability, in vitro biocompatibility, and cell migration were evaluated by the NIH-3T3 mouse fibroblast cell line. In vivo biocompatibility was assessed using a rat subcutaneous implantation model, including blank control, Durepair®, frozen-salted PVA, and Janus-PVA groups, with 5 rats in each group. Dural repair efficacy was evaluated in a rat cranial dural defect model, including untreated defect control, frozen-salted-annealed PVA, and Janus-PVA groups, with 15 rats in each group.

The Janus membrane exhibited high tensile strength (8.93 ± 1.46 MPa), slow degradation (1.42% mass loss at 28 days), and low swelling (58.13% water content at 28 days). It displayed distinct bilateral wettability, and effectively blocked fibroblast migration on both sides, acting as a physical barrier against fibroblast-driven adhesion. In the rat dural defect model, the Janus membrane reduced cerebrospinal fluid leakage and brain–dura adhesion compared with the untreated defect and frozen-salted-annealed PVA control groups.

The engineered hydrophilic/hydrophobic Janus PVA hydrogel membrane mimics the functional asymmetry of the native dura mater and may serve as a promising candidate for further evaluation as a dural repair material.

Brain tumors represent a common class of life-threatening neoplastic conditions. The core objective of neurosurgery is to achieve maximal safe resection of tumors while preserving the patient’s neurological function. Intraoperative ultrasound (IOUS) assists surgeons in achieving complete lesion removal, helping to avoid insufficient resection or excessive excision of normal tissue, thereby reducing surgical morbidity. Contrast-enhanced ultrasound (CEUS), through harmonic imaging, enables more precise localization of lesions and intracranial structures. This review focuses on the synergistic value of IOUS and CEUS in brain tumor surgery. It traces the technological evolution from two-dimensional ultrasound to elastography, color Doppler flow imaging, microvascular flow imaging, artificial intelligence, and beyond, with an emphasis on CEUS for cranial tumors. It also examines the clinical applications of IOUS and CEUS in precise resection, residual tumor identification, vascular protection, boundary differentiation from peritumoral edema, and prognostic assessment. The review concludes by summarizing diagnostic performance, current limitations, and future directions, offering neurosurgeons a theoretical and practical framework for optimizing intraoperative guidance.

Post-stroke dysphagia management research has primarily focused on screening, assessment, and intervention strategies, with limited objective indicators for evaluating nursing care quality. This study aimed to develop a dysphagia nursing quality evaluation index system for neurosurgical inpatients with stroke.

Using the “structure-process-outcome” three-dimensional quality model as the theoretical framework, a preliminary quality evaluation index system was constructed through literature analysis and group discussion. A two-round Delphi expert consultation was conducted among 25 purposively selected clinical experts from tertiary Class A hospitals, with inclusion criteria requiring a bachelor’s degree or higher, an intermediate professional title or above, and at least 10 years of clinical experience in stroke nursing or related fields. The analytic hierarchy process was used to determine indicator weights. Outcome measures included expert authority coefficients (Cr), Kendall’s W concordance coefficient, internal consistency reliability (Cronbach’s α), and the final indicator structure.

The Cr values were 0.87 and 0.88 across the two rounds. Kendall’s W concordance coefficient increased from 0.207 to 0.235 (P < 0.001), indicating statistically significant expert agreement. The final index system comprised 3 first-level indicators, 11 second-level indicators, and 44 third-level indicators, with all indicator definitions and weights determined. The overall Cronbach’s α was 0.86, indicating preliminary internal consistency.

This study developed a dysphagia nursing quality evaluation index system for neurosurgical inpatients with stroke using the three-dimensional quality model and the Delphi method. The system showed acceptable expert authority, statistically significant expert agreement, and preliminary internal consistency, suggesting potential applicability for nursing quality monitoring in neurosurgical wards and Neurosurgery Intensive Care Units. Further clinical validation is needed before routine implementation.

Cervical cancer is a major malignancy that threatens women’s health, and early screening is a core strategy for reducing its incidence and mortality. Multimodal fusion artificial intelligence (AI) pathological diagnosis models integrate multidimensional data—including cytological images, colposcopic images, whole-slide histopathological images, clinical data, and molecular testing results—and may enhance the detection sensitivity, grading accuracy, and screening efficiency for early cervical cancer and precancerous lesions. However, traditional cervical cancer screening methods face limitations such as high subjectivity, reliance on single-source information, relatively low efficiency, and insufficient primary care resources. Furthermore, existing reviews mostly focus on single-modal AI models or specific technical aspects, lacking a comprehensive analysis of the full technical framework and clinical translation pathways of multimodal fusion models. This review aims to comprehensively present the development and application of multimodal fusion AI models in pathological diagnosis for early cervical cancer screening. Specifically, it comprehensively details the technical architecture, data modalities, and fusion strategies—including deep learning, attention mechanisms, and cross-modal alignment techniques—that enable the complementary representation of morphological, clinical, and molecular information. Additionally, the review integrates recent advances in clinical applications and evaluates current translational challenges, providing insights into clinical validation pathways to bridge technological innovation and practical healthcare delivery. In conclusion, with further technological refinement and clinical validation, multimodal fusion AI may become a useful tool for improving the precision and efficiency of cervical cancer screening and prevention, and may inform the standardized application and translational research of AI technology in this field.