Rising resistance in Helicobacter pylori to metronidazole, clarithromycin, and fluoroquinolones has significantly reduced eradication efficacy. This narrative review explores evidence-based strategies that minimize the impact of antibiotic resistance. Current practical approaches include empirical therapy (EMT), in which regimens are selected without individual susceptibility testing based on local or regional resistance patterns, previous antibiotic exposure, guideline recommendations, and expected effectiveness, and susceptibility-guided therapy (SGT), which avoids antibiotics to which the infecting strain is resistant. EMT does not simply exclude every antibiotic with a high resistance prevalence because regimen-level efficacy may remain high despite resistance to one component. When susceptibility testing is unavailable, optimized 14-day bismuth quadruple therapy is a guideline-preferred empirical regimen and can remain effective despite metronidazole resistance with adequate dosing and treatment duration. Rifabutin-based triple therapy provides an additional empirical or rescue option for selected patients without penicillin allergy. SGT is not universally superior to well-selected EMT, but may improve eradication rates in selected populations, particularly in settings with high clarithromycin resistance or where rapid molecular testing is available. However, susceptibility testing may be time-consuming, costly, and limited to only a few antibiotics. Emerging approaches include potassium-competitive acid blockers (PCABs), antimicrobial stewardship, probiotics, N-acetylcysteine, nanomaterial-based drug delivery, and vaccination. Among these, vonoprazan-based regimens are the most clinically mature. Vonoprazan-amoxicillin dual therapy can reduce exposure to resistance-prone antibiotics, although its use should reflect regional effectiveness, availability, and cost. Other non-antibiotic approaches remain investigational. In conclusion, management should move from undifferentiated empirical regimen selection toward risk-stratified precision treatment. Locally validated EMT remains appropriate when susceptibility testing is unavailable, whereas SGT should be prioritized after treatment failure or in patients at high risk of resistance. Rifabutin-based and vonoprazan-amoxicillin therapies provide additional options according to treatment history, penicillin allergy, regional evidence, and accessibility.

Despite the 2012 Berlin definition standardizing acute respiratory distress syndrome (ARDS) diagnosis, pharmacological therapies have consistently failed in phase 3 trials, partly reflecting the syndrome’s profound biological heterogeneity. We synthesize evidence on ARDS subphenotyping to evaluate prospects for precision medicine. This narrative review was informed by targeted searches of PubMed/MEDLINE, Embase, and Web of Science from database inception through February 2026, supplemented by an updated PubMed/MEDLINE search through September 2026. Representative clinical trials, multicenter cohorts, mechanistic studies, and methodological reports were selected to support a critical synthesis of ARDS subphenotyping, its therapeutic implications, and barriers to clinical translation. Hyperinflammatory and hypoinflammatory subphenotypes—originally identified using plasma biomarkers (IL-6, IL-8, and soluble tumor necrosis factor receptor 1) in the ARMA and ALVEOLI cohorts—demonstrate reproducible differences in mortality, with worse outcomes in the hyperinflammatory subphenotype, and have shown potential treatment-effect heterogeneity in secondary analyses. Approximately 30%–35% of patients exhibit the hyperinflammatory profile, characterized by greater vasopressor requirements and organ failure. Radiological phenotypes (focal versus non-focal) on computed tomography imaging have been associated with differences in lung recruitability and physiological responses to ventilatory interventions, although the LIVE trial did not demonstrate an overall survival benefit from morphology-guided ventilation. Recent multi-omics studies (transcriptomic, proteomic, and metabolomic) reveal distinct endotypes involving dysregulated innate immunity, endothelial activation, and aberrant coagulation. Machine learning algorithms, particularly unsupervised clustering and deep learning-based computed tomography radiomics, have been investigated for more rapid phenotyping, but reported performance varies by task, cohort, and validation design. However, prospective, phenotype-guided randomized trials remain limited. Subphenotype stratification offers a mechanistically grounded framework for re-evaluating therapies that were ineffective in unselected populations and for investigating phenotype-informed ventilatory strategies. Clinical implementation requires standardized, bedside-compatible biomarker panels and definitive trials demonstrating that phenotype-specific interventions improve patient-centered outcomes.

Artificial intelligence (AI)-based computer-aided detection (CADe) has been associated with improved adenoma detection during colonoscopy. However, prior meta-analyses synthesized earlier trials, and whether the benefit remains consistent in recent contemporary trials is uncertain. This meta-analysis aimed to estimate the effects of current-generation AI-assisted colonoscopy on adenoma detection rate (ADR) as the primary outcome and polyp detection rate (PDR) as the secondary outcome in randomized and quasi-randomized trials published from August 1, 2024, to August 18, 2026, without re-pooling trials included in earlier comprehensive meta-analyses.

MEDLINE/PubMed, Embase, CENTRAL, Scopus, and Google Scholar were searched for peer-reviewed parallel-group randomized and quasi-randomized trials enrolling adults undergoing screening, surveillance, or diagnostic colonoscopy and comparing real-time AI-based CADe-assisted with conventional high-definition white-light colonoscopy. Tandem designs were excluded. The primary and secondary outcomes were ADR and PDR, respectively. Random-effects risk ratios with 95% confidence intervals (CIs) were calculated; heterogeneity and leave-one-out sensitivity were assessed.

Seventeen trials comprising 15,242 patients were included for ADR; 12 trials comprising 8,665 patients reported extractable PDR data. The pooled risk ratio was 1.14 (95% CI 1.09–1.20; I² = 53.8%) for ADR and 1.13 (95% CI 1.07–1.20; I² = 63.4%) for PDR.

This meta-analysis supports an average improvement in adenoma and polyp detection with AI-assisted colonoscopy; however, moderate-to-substantial heterogeneity and variability across settings and platforms warrant cautious interpretation rather than an unqualified recommendation for routine adoption.

Viral hepatitis caused by A to E imposes a substantial global burden of liver disease. Despite US control strategies, long-term national data covering serologic markers of all five hepatitis viruses remain limited. In this study, we analyzed epidemiologic trends from 2011 to 2023 and aimed to identify prevention gaps.

We analyzed National Health and Nutrition Examination Survey (NHANES) data from 2011 to 2023 using weighted logistic regression, with stratification by age, sex, and race/ethnicity.

Current hepatitis B virus (HBV) infection remained stable at 0.3%, while HBV susceptibility was 71.3%. Among individuals born in 1991 or later, HBV vaccination coverage declined from 90.0% to 83.6% during 2011–2020 (P for trend = 0.012); 57.0% of participants reporting vaccination were serologically susceptible. Anti-HDV positivity among participants with current HBV infection was 1.3%. Anti-hepatitis C virus (HCV) seroprevalence remained 1.6%, while active HCV viremia decreased from 0.8% to 0.4%, and viremia among anti-HCV-positive participants fell from 65.5% to 31.3% (P = 0.004). Hepatitis A virus antibody seroprevalence increased from 41.6% to 48.0% (P < 0.001) with stable vaccination coverage. Anti-HEV IgM positivity increased from 1.6% to 1.7% (P = 0.004).

US viral hepatitis trends diverged from 2011 to 2023. The decrease in detectable HCV RNA was consistent with progress in HCV control, whereas persistent HBV susceptibility, declining vaccination coverage in younger birth cohorts, and increasing hepatitis A virus seroprevalence and hepatitis E virus IgM positivity indicate ongoing prevention and surveillance needs.

Hepatitis B virus (HBV) reactivation is a well-recognized complication in patients with lymphoma receiving immunosuppressive therapy, particularly rituximab-containing regimens. We describe a 58-year-old man with diffuse large B-cell lymphoma and an atypical baseline HBV serological profile: hepatitis B surface antibody (anti-HBs) positivity (102.00 U/L), antibody to hepatitis B core antigen negativity, a low-level hepatitis B surface antigen (HBsAg) result (0.35 COI, reported as negative by the local laboratory), and undetectable HBV DNA. Thirteen days after initiation of the fourth cycle of modified R-CHOP (rituximab, cyclophosphamide, pirarubicin, vinorelbine and dexamethasone) chemoimmunotherapy, the anti-HBs titer had decreased to 1.31 S/CO, the HBsAg level to 0.02 S/CO, and HBV DNA was not reassessed until reactivation. Approximately 16 weeks after treatment completion, the patient developed fatigue, anorexia, and jaundice. HBsAg increased from 28.66 S/CO to 8048.30 IU/mL, hepatitis B e antigen became positive, and HBV DNA increased to 1.94 × 109 IU/mL. Despite treatment with tenofovir alafenamide fumarate and plasma exchange, the patient died of refractory liver failure and hepatic encephalopathy. These findings suggest that atypical serological profiles may not reliably indicate a low risk of severe HBV reactivation during intensive immunosuppressive therapy. Comprehensive pretreatment risk assessment and long-term monitoring of anti-HBs titers, HBsAg, and HBV DNA during and after therapy may facilitate earlier detection and intervention.

Interactions among tumors, nerves, and immune cells influence cancer progression, but the mechanisms coordinating these compartments remain incompletely understood. Bioelectric signaling has been proposed as an additional coordinating layer, yet direct in vivo evidence for a tumor–nerve–immune electrical axis remains limited. In non-tumor models, RUSH3D-HR enables mesoscale in vivo imaging of dynamic cellular behaviors, including neutrophil swarming and migrasome dynamics, and has revealed reduced splenic neutrophil swarming following electroacupuncture at Zusanli (ST36). These observations provide dynamic cellular readouts and demonstrate an intervention-associated response; however, the platform does not directly measure membrane voltage, ionic currents, or electric fields, and these findings establish neither electrical coupling nor a specific neural circuit. In this mini review, we examine the proposed axis as a focused, falsifiable complement to broader cancer neuroscience. We distinguish direct observations from mechanistic hypotheses, consider established biochemical explanations involving neurotransmitters and inflammatory mediators, and discuss how context-dependent neural effects, supporting glial cells, opioids, and cancer-induced nerve injury may modify tumor–nerve–immune interactions. We then outline a staged experimental roadmap in tumor models, integrating RUSH3D-HR with voltage and ion reporters, extracellular electrophysiological recordings, and compartment-specific perturbations. This framework prioritizes temporal relationships, identification of candidate signal sources and responding compartments, and causal tests that discriminate electrical contributions from biochemical and systemic effects. Establishing reproducible links between electrical measurements, cellular behavior, and tumor outcomes will be essential for evaluating the axis. Until such evidence is obtained, the tumor–nerve–immune electrical axis should be regarded as a hypothesis-generating experimental program rather than a validated physiological circuit.

Standardized pathologic sampling and reporting are essential for pancreatic cancer staging, prognosis assessment, and comparable clinical data. This guideline aimed to develop evidence-based recommendations for standardized pathologic sampling and diagnostic reporting of pancreatic cancer in China. Literature searches were conducted in English and Chinese databases, guideline websites, Google, and reference lists for records published before December 31, 2023. Two investigators screened and extracted the evidence; methodological quality and certainty were assessed using AMSTAR/AGREE II and GRADE, respectively; and recommendations were formulated through two rounds of modified Delphi consultations, with an agreement threshold of ≥ 75% for consensus. The final guideline includes 11 recommendations, including six strong and five weak recommendations, addressing margin and surface assessment, sampling methods, histologic classification and grading, lymphovascular and perineural invasion, TNM staging, tumor regression grading after neoadjuvant therapy, background lesions, and structured reporting. These recommendations provide a standardized framework for pathologic assessment and reporting of pancreatic cancer resection specimens and may support more consistent prognostic evaluation and clinical decision-making.