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.

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.

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.

Cardiorenal syndrome is associated with high morbidity and mortality and is characterized by bidirectional interactions between cardiac and renal dysfunction. The advent of sodium-glucose cotransporter 2 inhibitors (SGLT2i) and the nonsteroidal mineralocorticoid receptor antagonist finerenone has substantially changed the therapeutic landscape. Combination therapy with SGLT2i and finerenone may provide additional benefits through complementary mechanisms, representing a potential paradigm shift in the management of cardiorenal syndrome. In this review, we examine the pathophysiological pathways that characterize cardiorenal syndrome, clinical data from major randomized controlled trials, and the rationale for the concomitant use of these two drug classes. SGLT2 inhibitors significantly reduce hospitalization for heart failure, slow renal function decline, and provide benefits in both heart failure with reduced ejection fraction and heart failure with preserved ejection fraction, irrespective of diabetes status. Finerenone has been shown to reduce the risk of cardiovascular events and chronic kidney disease progression in patients with type 2 diabetes and chronic kidney disease, with a more favorable safety profile than steroidal mineralocorticoid receptor antagonists. Emerging evidence suggests that combination therapy may reduce hospitalizations for heart failure and slow renal disease progression beyond the effects of either monotherapy. However, implementation of these therapeutic options requires careful patient selection, ongoing monitoring of renal function and electrolytes, and close collaboration between cardiologists and nephrologists.

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.

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.

Randomized controlled trials (RCTs) have been conducted to evaluate treatment efficacy for metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis. This study aimed to compare the effectiveness and safety of 11 promising targets among adults with MASLD.

PubMed, Web of Science, the Cochrane Central Register of Controlled Trials, Scopus, and Embase were searched from inception to November 20, 2024. The primary outcomes were fibrosis improvement ≥1 stage without worsening of steatohepatitis and steatohepatitis resolution without worsening of fibrosis. Additional outcomes included reductions in liver fat content, liver enzymes, metabolic profiles, and selected safety outcomes. The surface under the cumulative ranking curve (SUCRA) was used to rank efficacy.

Of 11,584 articles screened, 44 eligible RCTs (11,410 participants, 33 medications) were included. For fibrosis improvement, d-(R)-pioglitazone (SUCRA: 79.3) and fibroblast growth factor (FGF) 21 analogs (SUCRA: 71.9) ranked higher. For steatohepatitis resolution, glucagon-like peptide-1 (GLP-1)/glucose-dependent insulinotropic polypeptide (GIP) dual receptor agonists (RAs) (SUCRA: 91.7) ranked higher. Co-agonists of GLP-1/GIP/GCG and GLP-1/GCG receptors ranked higher for relative and absolute changes in liver fat content, respectively. For liver enzymes and glucose improvement, the combination of a GLP-1 RA and an acetyl-coenzyme A carboxylase inhibitor ranked higher. GLP-1 RAs, peroxisome proliferator-activated RAs, and FGF21 analogs showed favorable effects on lipid profile improvement.

Incretin-based co-agonists and FGF21 analogs showed favorable profiles across key endpoints, while d-(R)-pioglitazone and GLP-1/GIP dual RAs ranked higher for fibrosis improvement and steatohepatitis resolution, respectively. SUCRA rankings should be interpreted in conjunction with effect sizes, uncertainty, and available safety data.