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.

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.

Apatinib has been shown to be efficacious in the treatment of gallbladder cancer. However, the underlying mechanisms remain unclear. This study aimed to explore pathways related to the antitumor effects of apatinib at the cellular level in gallbladder cancer.

NOZ and GBC-SD gallbladder cancer cells were treated with apatinib at concentrations of 0 μM, 10 μM, or 20 μM. The effect of apatinib on the proliferation of these cells was assessed using MTT and colony formation assays, and the effects of apatinib on cell cycle progression and DNA synthesis were evaluated using flow cytometry. Clinical cancer tissue samples, along with paired adjacent normal tissue samples, were obtained from 10 patients with gallbladder cancer. Immunohistochemistry, western blotting, and quantitative real-time polymerase chain reaction analyses were conducted to elucidate molecular changes induced by apatinib treatment.

Treatment with 20 μM apatinib significantly inhibited the expression of phosphorylated (p)-vascular endothelial growth factor receptor 2 (VEGFR2), p-AKT, and histone deacetylase 1 (HDAC1). Additionally, apatinib treatment led to upregulated expression of p-cyclin-dependent kinase 1, p21, and Bax, and downregulated expression of cell division cycle 25B, B-cell lymphoma 2, Snail, and Slug. Apatinib decelerated DNA replication and induced cell cycle arrest at the G2/M phase, consequently suppressing the proliferation of gallbladder cancer cells.

Apatinib inhibits the proliferation of gallbladder cancer cells, and the mechanism involves VEGFR2/AKT, HDAC1, and downstream genes. These findings provide a basis for further investigation into the molecular mechanisms underlying the inhibitory effect of apatinib in gallbladder cancer.

Observational studies have shown that educational attainment is associated with the risk of myopia, but the causality of this relationship is unclear. The aim of the present study was to investigate the causal association between educational attainment and myopia.

Using publicly available data from genome-wide association studies, single nucleotide polymorphisms associated with educational attainment (college/university completion and years of education) were selected as instrumental variables. Causal associations with myopia risk were examined using two-sample Mendelian randomization (MR) analyses. Sensitivity analyses were conducted to assess the robustness of the results in terms of violations of MR assumptions.

The inverse variance–weighted analysis revealed potential causal associations of college/university completion (odds ratio (OR) = 1.102; 95% confidence interval (CI): 1.085–1.119; P < 0.001) and years of education (OR = 1.009; 95% CI: 1.007–1.010; P < 0.001) with myopia risk. MR-Egger and weighted median methods yielded similar results for both educational attainment measures.

MR evidence supports a potential causal association between educational attainment and myopia. This evidence highlights the need for careful management of myopia risk in individuals with higher educational attainment.

While norepinephrine (NE) is the cornerstone of septic shock resuscitation, “macrocirculation–microcirculation decoupling” at high doses remains a critical clinical challenge. This study aimed to explore the quantitative tipping point where the NE dose shifts from a life-saving vasopressor to a microcirculatory toxin in septic intensive care unit patients.

In this prospective observational study (January–September 2025), we used handheld vital microscopy to monitor sublingual microcirculation (microvascular flow index [MFI], total vessel density, perfused vessel density, proportion of perfused vessels [PPV], and heterogeneity index [HI]) in adult septic patients within 24 hours of admission and on Day 3. Beyond standard linear analysis, generalized additive models were employed to identify the dose–response thresholds associated with microcirculatory deterioration, adjusted for Acute Physiology and Chronic Health Evaluation II, interleukin-6, and systemic hemodynamics.

Of 144 screened patients, 66 were analyzed. The NE dose showed strong linear correlations with lactate (r = 0.583, P < 0.001) and HI (r = 0.444, P < 0.001), and negative correlations with MFI (r = −0.492, P < 0.001). Crucially, generalized additive models analysis revealed a significant nonlinear “cliff effect”: when the NE dose exceeds the 0.71–0.80 µg/kg/min threshold (PPV: 0.71 µg/kg/min, HI: 0.72 µg/kg/min, MFI: 0.80 µg/kg/min), microcirculatory perfusion parameters deteriorate abruptly (all P < 0.05). Multivariable Cox regression identified an NE dose of 0.80 µg/kg/min as an independent predictor of increased mortality (hazard ratio = 1.32, 95% confidence interval: 1.28–3.10, P = 0.039).

In patients with septic shock, higher NE doses were associated with impaired microcirculatory perfusion and worse outcomes. These findings support individualized vasopressor titration and suggest that microcirculatory monitoring may help identify patients at risk of vasopressor-associated microvascular dysfunction.

Generative artificial intelligence (AI), particularly large language models (LLMs) and multimodal systems, is emerging as a potentially important innovation in intensive care medicine. The intensive care unit (ICU) is a data-dense, high-acuity setting where rapid and accurate decisions are critical. These models can translate complex multimodal data into interpretable and clinically actionable insights across diagnostic, prognostic, and documentation workflows. This review outlines six key domains in which generative AI is currently being explored for its potential to reshape critical care: clinical decision support; clinical documentation automation (AI scribe, voice-to-note); predictive analytics, including sepsis and acute respiratory distress syndrome prediction, acute kidney injury management, ventilator liberation readiness, delirium monitoring, and continuous renal replacement therapy optimization; ICU data summarization and multimodal monitoring; synthetic data generation; and legal and ethical governance. In clinical decision support, hybrid models that integrate time-series monitoring data with LLMs can contextualize alerts, generate diagnostic suggestions, and offer treatment plans with explainable reasoning. Documentation tools that leverage ambient listening and voice-to-note AI can streamline progress notes and discharge summaries, thereby reducing clinician workload. In predictive analytics, LLMs enhance model performance by augmenting sparse electronic health record data and translating outputs into interpretable narratives. Synthetic data generation enables algorithm development and training, particularly for rare events, while protecting patient privacy. However, the realism and ethical deployment of such data require rigorous validation. Widespread implementation of generative AI will require careful attention to challenges related to trust, validation, bias, liability, and regulatory compliance. The use of these tools must remain under clinician supervision to ensure transparency and accountability. With responsible deployment, generative AI may augment ICU workflows, improve outcomes, and reduce clinician burden, potentially becoming an indispensable component of critical care delivery.

In contemporary practice, elevated 24-hour urinary copper excretion (24-h UCE) often triggers referral for suspected Wilson disease (WD). In this hypercupriuric referral setting, interpretation of 24-h UCE may be distorted by spectrum effects. In this study, we aimed to compare conventional copper biomarkers in hypercupriuric referrals and evaluate whether a Leipzig-aligned ceruloplasmin (Cp) framework could provide a clinically useful triage approach.

We retrospectively studied consecutive, untreated patients evaluated for suspected WD with hypercupriuria between February 2017 and February 2025. The final diagnosis was established using a prespecified Leipzig-based algorithm, with ATP7B testing when indicated. Diagnostic performance of Cp and 24-h UCE was compared. A prespecified Cp three-zone framework was evaluated using <0.10 g/L, 0.10–0.20 g/L, and >0.20 g/L as high-probability, indeterminate, and low-probability zones, respectively.

Among 541 untreated hypercupriuric patients, 65 had WD and 476 had adjudicated non-WD liver disease. Cp outperformed 24-h UCE for diagnosing WD (AUROC, 0.988 vs. 0.762). The optimal Cp cutoff was 0.15 g/L, with 90.8% sensitivity and 97.7% specificity. Cp < 0.10 g/L defined a high-probability zone with 98.0% WD prevalence, whereas Cp > 0.20 g/L defined a low-probability zone with 0.5% WD prevalence. Among non-WD controls, higher urinary copper was independently associated with higher bilirubin, prolonged international normalized ratio, and lower albumin.

In hypercupriuric referrals for suspected WD, Cp retained strong diagnostic performance and outperformed 24-h UCE. A Leipzig-aligned Cp three-zone framework may support probability-based triage in contemporary referral practice.