Thyroid nodules are increasingly detected in clinical practice, and accurate imaging evaluation is essential for risk stratification, treatment planning, and postoperative surveillance of thyroid cancer. Although ultrasound remains the first-line modality for thyroid nodule assessment, the roles of computed tomography (CT), spectral CT, magnetic resonance imaging (MRI), and positron emission tomography-computed tomography (PET-CT) vary across clinical scenarios, and the optimal integration of these modalities remains insufficiently standardized. In particular, existing studies often focus on individual imaging techniques, while practical guidance on modality selection for initial screening, preoperative anatomical assessment, recurrence monitoring, and high-risk disease evaluation remains limited. This narrative review summarizes the imaging principles, clinical indications, diagnostic value, advantages, and limitations of ultrasound, CT, spectral CT, MRI, and PET-CT in the evaluation of thyroid nodules and thyroid cancer. Future advances should focus on standardized multimodal imaging strategies, quantitative functional imaging, radiomics, and carefully validated artificial intelligence-assisted approaches to improve individualized diagnosis and management of thyroid nodules and thyroid cancer.

Early detection of gastric cancer is critical for reducing incidence and mortality, as well as for improving survival outcomes. Although gastroscopy remains the gold standard for gastric cancer screening and diagnosis, its invasiveness, discomfort during the procedure, and limited acceptability restrict population participation and screening coverage. Recently, rapid advances in liquid biopsy technologies have led to the discovery of numerous multi-omics biomarkers spanning genomics, transcriptomics, proteomics, and metabolomics, with promising diagnostic performance. However, their translational value for population-based gastric cancer screening and control remains insufficiently characterized. This review aims to provide a comprehensive overview of multi-omics biomarkers for gastric cancer screening and to evaluate their potential role in advancing population-level gastric cancer control. First, we synthesize multi-omics biomarkers with diagnostic and screening relevance across the continuum of gastric carcinogenesis, from chronic inflammation and atrophy to intestinal metaplasia, dysplasia, and early gastric cancer. Furthermore, we highlight the integrative value of multi-omics biomarkers, current limitations, translational challenges, and future opportunities for moving biomarkers from discovery to implementation in organized screening programs. In conclusion, multi-omics biomarkers have the potential to complement existing screening strategies by providing scalable, non-invasive, and risk-adapted approaches for early gastric cancer detection. Bridging the gap between biomarker discovery and real-world implementation will be essential for realizing their value in future gastric cancer screening programs.

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). 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.

Given that hemodynamic fluctuations acutely escalate the risk of devastating rebleeding and secondary neurological deficits in unsecured ruptured intracranial aneurysms, this study aimed to synthesize the best available evidence for blood pressure management in this population and to provide an evidence-based foundation for clinical nursing practice.

A systematic search was conducted in domestic and international databases and relevant websites for evidence pertaining to blood pressure management in patients with ruptured intracranial aneurysms, including clinical practices, guidelines, expert consensuses, evidence summaries, and systematic reviews/meta-analyses. The search period covered database inception up to June 2025. Two researchers independently performed literature quality assessments and evidence extraction, with particular attention to nursing-relevant evidence on hemodynamic monitoring, bedside assessment, complication prevention, fluid management, and follow-up coordination.

A total of 17 studies were included, comprising 11 guidelines, 4 expert consensuses, and 2 clinical decision entries. The synthesized evidence yielded 32 recommendations, structured into 6 core clinical domains: personnel and environmental configuration, individualized blood pressure targeting, precision hemodynamic monitoring, complication prevention, fluid therapy strategy, and longitudinal follow-up protocols. These recommendations further clarified key nursing responsibilities in triage coordination, continuous blood pressure surveillance, neurological assessment, delayed cerebral ischemia surveillance, fluid balance monitoring, and long-term follow-up.

Blood pressure management in patients with ruptured intracranial aneurysms should be individualized and multidisciplinary. The synthesized evidence highlights key nursing priorities in hemodynamic monitoring, delayed cerebral ischemia surveillance, fluid management, and follow-up coordination, and may inform standardized clinical nursing protocols.

Sepsis is a life-threatening syndrome associated with high morbidity and mortality, underscoring the urgent need for early diagnostic biomarkers and therapeutic targets. However, current diagnostic strategies remain insufficiently precise because of the complex immune dysregulation and immune microenvironment heterogeneity that characterize sepsis. This study aimed to identify reliable diagnostic biomarkers for sepsis and explore their immune regulatory mechanisms together with potential therapeutic relevance using multidimensional bioinformatic analyses.

Single-cell transcriptomic and bulk RNA sequencing datasets were integrated to screen candidate diagnostic genes for sepsis. Immune infiltration, co-expression network and pathway enrichment analyses were performed to explore immune regulatory mechanisms. Machine-learning approaches were used to validate the diagnostic signature, and molecular docking was conducted to predict candidate targeted compounds.

A total of 346 differentially expressed genes were identified and were mainly enriched in immune, coagulation, and metabolic pathways. CIBERSORT and single-cell analyses revealed increased neutrophils, monocytes, and γδ T cells and reduced CD8+ T cells and resting natural killer cells. Four diagnostic genes (S100A12, CD22, CSTA, and UPP1) were prioritized. The four-gene model showed robust external performance (area under the receiver operating characteristic curve = 0.860; sensitivity = 0.781; specificity = 0.780), and interpretability analysis highlighted UPP1 and S100A12 as dominant predictors. Molecular docking suggested potential interactions between these targets and anti-inflammatory compounds.

This integrative framework identifies four immune-related diagnostic genes for sepsis and links them to immune-cell remodeling and candidate therapeutic interactions, providing a basis for future mechanistic and clinical validation.

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.

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.

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.

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.