Pediatric low-grade gliomas (pLGGs) exhibit distinct biological and clinical characteristics compared to adult gliomas, and their treatment strategies differ substantially from those used in adults. Since the release of the 2016 World Health Organization Classification of Tumors of the Central Nervous System and its subsequent updates, significant advances have been made in understanding the diagnosis and management of pLGGs. Therefore, updated guidelines tailored to current clinical practice are needed. In this document, we present the consensus guidelines for the diagnosis and management of pLGGs in China. The recommendations were developed through a comprehensive review of relevant domestic and international guidelines and literature, combined with expert consensus meetings and external peer review to ensure rigorous validation. The guideline integrates the levels of evidence from published studies, expert consensus, and practical clinical considerations. All recommendations were reviewed and approved by a multidisciplinary panel of experts from the Pediatric Neurosurgery Group. This guideline is intended to serve as guidance for healthcare professionals involved in pediatric neuro-oncology, as well as for patients, caregivers, and other healthcare providers participating in the management of pLGGs.

Bacterial infections (BIs) are common and severe complications in patients with liver cirrhosis, but global data are limited. Here, we aimed to evaluate the global prevalence, temporal changes, and associated mortality risk of BIs in liver cirrhosis.

We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library for eligible studies published without language restrictions until 11 August 2025. A random-effects model was used for meta-analyses, meta-regression by study year, and pooling adjusted hazard ratios.

Fifty-nine studies, including 1,191,421 patients with cirrhosis, were analyzed. The pooled prevalence of BIs (33 studies) was 35.1% (95% confidence interval (CI): 29.2–41.4). The prevalence of Escherichia coli and Streptococcus spp. was 3.8% (95% CI: 2.5–5.2) and 1.5% (95% CI: 0.8–2.6), respectively. The pooled prevalence of multidrug-resistant bacteria was 6.8% (95% CI: 4.0–11.3). The most common BI sites were the gastrointestinal tract, ascites fluid, and urinary tract. The highest prevalence of BIs was reported in Europe (38.2%; 95% CI: 24.8–53.6), followed by South America (37.5%; 95% CI: 29.7–46.1) and Asia (22.8%; 95% CI: 16.3–30.9). Patients with acute-on-chronic liver failure showed the highest prevalence of BIs (44.2%; 95% CI: 29.7–59.8). A modest increasing trend in BIs prevalence was observed over time. BIs were associated with an increased risk of mortality in patients with cirrhosis (adjusted hazard ratios 2.22, 95% CI 1.33–3.71).

BIs are prevalent in cirrhosis, especially in acute-on-chronic liver failure, with a modest upward trend and increased mortality risk.

Circular RNAs (circRNAs) are non-coding RNAs characterized by a strictly closed-loop covalent structure. They are abundantly detected in various cells due to their conserved nature. Studies have reported their potential association with chronic liver disease (CLD), including hepatitis, cirrhosis, and hepatocellular carcinoma (HCC), with possible roles as diagnostic and prognostic markers. This study aimed to analyze the potential use of serum-derived hsa_circ_101555 as a diagnostic tool for CLD without HCC, and to compare it with other known non-invasive parameters for liver disease severity and inflammation. Additionally, it aimed to evaluate its expression among non-HCC CLD patients, CLD with HCC cases reported in our published (phase I) study, and healthy controls.

A cross-sectional study (phase II) was conducted involving 30 clinically, laboratory, and radiologically diagnosed Egyptian non-HCC CLD patients and 30 healthy subjects. The serum expression level of hsa_circ_101555 was measured using real-time polymerase chain reaction. The diagnostic accuracy was assessed through receiver operating characteristic curve analysis, calculating the area under the curve to determine sensitivity and specificity. The study also compared hsa_circ_101555 levels with established non-invasive parameters such as the Child-Turcotte-Pugh and model for end-stage liver disease scores, as well as inflammatory markers like the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio.

hsa_circ_101555 demonstrated high diagnostic accuracy (area under the curve of 0.970) at a cutoff point of 2.088 for differentiating non-HCC CLD patients from healthy controls. Elevated circRNA levels were noted in patients with hepatic encephalopathy and ascites, correlating with advanced liver disease scores (Child-Turcotte-Pugh/model for end-stage liver disease scores). Mean circRNA values were highest in HCC cases, followed by non-HCC CLD patients, and lowest in healthy controls.

Serum-derived hsa_circ_101555 demonstrates high diagnostic accuracy in differentiating non-HCC CLD patients from healthy controls. These findings suggest that hsa_circ_101555 has the potential to serve as a reliable non-invasive biomarker for the early diagnosis of CLD, correlating with disease severity and inflammation markers. Further research with larger sample sizes is warranted to validate its clinical utility and enhance the management of CLD.

Early risk stratification of severe acute liver injury (SLI) that may progress to acute liver failure (ALF), is vital for timely intervention, but no universal prognostic assessment tool covers both conditions. This study aimed to develop a simplified prognostic model for early risk assessment in SLI/ALF patients.

A retrospective cohort study consecutively enrolled SLI patients (including those progressing to ALF) from July 1, 2020 to May 31, 2025. Baseline clinical and laboratory data on admission were collected, with 90-day transplant-free survival as the primary outcome. Independent prognostic factors were screened via Cox regression to build a simplified scoring model, whose performance was compared with the Model for End-Stage Liver Disease (MELD), King’s College Criteria (KCC), and the Acute Liver Failure Study Group Prognostic Index (ALFSG-PI).

Of 302 patients, 190 (62.9%) achieved 90-day transplant-free survival. Multivariate Cox regression identified international normalized ratio (hazard ratio [HR]: 1.118, 95% confidence interval [CI]: 1.050–1.191), platelet count (HR: 0.995, 95% CI: 0.993–0.998), and hepatic encephalopathy grade ≥ 2 (HR: 5.187, 95% CI: 3.403–7.907) as independent predictors, forming the HIP (derived from the above-mentioned three predictors) model. It showed good discrimination (area under the receiver operating characteristic curve [AUC]: 0.82), outperforming MELD (AUC: 0.76, P = 0.019) and KCC (AUC: 0.72, P = 0.002), and performing comparably to ALFSG-PI (AUC: 0.80, P = 0.429). The model also performed robustly in ALF subgroups defined by the American College of Gastroenterology and the 2024 Chinese Medical Association guidelines (AUCs: 0.80 and 0.76, respectively) and achieved an AUC of 0.85 in the validation set.

The HIP model is a simple and effective tool for prognostic risk stratification in SLI/ALF patients, suitable for emergency and primary care to facilitate timely intervention.

Sclerocarya birrea (A. Rich) Hochst (Anacardiaceae) is a plant widely used by traditional healers in several African countries to treat numerous illnesses such as Alzheimer’s disease, schizophrenia, inflammation, infections, arterial hypertension, headaches, and others. This study aimed to determine the therapeutic efficacy of Sclerocarya birrea (S. birrea) against glutamate-induced neurotoxicity.

Thirty naïve white mice (Mus musculus Swiss, Muridae), of both genders and weighing between 18 and 25 g, were used in the experiments. Different doses (102.5, 205, and 410 mg/kg) of the extract and vitamin C (100 mg/kg) were administered to the animals one hour before administration of monosodium glutamate (4 mg/kg) for 15 consecutive days. T-maze and Y-maze tests were conducted over three days to assess the animals’ behavioral performance. After behavioral testing, the animals were sacrificed and their brains removed for analysis of oxidative stress parameters.

S. birrea extract reversed glutamate-induced behavioral alterations by significantly (P < 0.001) reducing the latency to reach the platform in the T-maze and significantly increasing the percentage of spontaneous alternation in the Y-maze. The extract also significantly counteracted (P < 0.001) glutamate-induced oxidative stress parameters. The 102.5 and 205 mg/kg doses of the extract significantly (P < 0.001) reduced catalase and reduced glutathione levels, as well as the increase in malondialdehyde levels induced by glutamate.

S. birrea root bark extract exhibits neuroprotective properties that facilitate memory and ameliorate glutamate-induced cognitive deficits in white mice. The results provide partial justification for the traditional medicinal use of S. birrea extract.

Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by intermittent hypoxia and sleep fragmentation, which may contribute to lung cancer development and progression. This review synthesizes epidemiological evidence on the association between OSA and lung cancer incidence and mortality, highlighting inconsistencies due to study design, population differences, and confounding factors such as smoking and obesity. While some studies report an increased lung cancer risk, particularly with severe nocturnal hypoxemia, others suggest no significant association or a potential protective effect. Pathophysiologically, OSA promotes oncogenesis through hypoxia-inducible factor activation, tumor immune microenvironment remodeling, exosome-mediated signaling, nuclear factor κB pathway activation, and enhanced cancer stem cell properties. Continuous positive airway pressure therapy may mitigate these effects, with evidence suggesting reduced lung cancer incidence and improved prognosis in adherent patients. This review underscores the need for standardized studies using objective diagnostics and robust confounder adjustment to clarify the OSA–lung cancer link and optimize clinical management.

Human immunodeficiency virus (HIV)/hepatitis C virus (HCV) coinfection leads to severe systemic inflammation, increasing non-AIDS morbidity and mortality risk. CD39 ectoenzyme on T-cells, which catalyzes the conversion of pro-inflammatory purines to immunosuppressive adenosine, plays an important role in inflammation control. The role of CD39+ T-cells in systemic inflammation during HIV/HCV coinfection under antiretroviral therapy (ART) remains unexplored. This study aimed to identify specific patterns of CD39 expression on T-cells in ART-treated HIV/HCV coinfected patients and assess their relationship with systemic inflammation.

We conducted a case-control study that enrolled 41 HIV/HCV coinfected patients on stable ART (cases) and 23 healthy controls. CD39 expression on blood CD4+ and CD8+ T-cells, including CD45RA+ and CD45RA– subsets, was quantified using flow cytometry. Cytokines were assessed using multiplex and enzyme-linked immunosorbent assays.

A significant proportion of CD4+ T-cells expressed CD39 in both groups (cases – 24.0%; controls – 16.1%). That was not true for CD8+ T-cells (cases – 3.2%; controls – 2.8%). CD39 expression was higher on CD45RA+ than CD45RA– CD4+ T-cells (cases – 39.4% vs. 19.0%; controls – 24.6% vs. 9.2%). HIV/HCV coinfected patients exhibited a significantly increased proportion of CD39+ CD4+ T-cells compared to uninfected controls (P < 0.01). A negative correlation was observed between the percentage of CD39+ CD4+ CD45RA– T-cells and levels of pro-inflammatory chemokines monocyte chemoattractant protein 1 (R = –0.392; P < 0.01) and eotaxin (R = –0.325; P < 0.05).

The data suggest a compensatory expansion of cells with regulatory properties that is ultimately insufficient to control systemic immune activation.

Helicobacter pylori infection represents a significant modifiable risk factor in the pathogenesis of gastric cancer. Nevertheless, conventional antibiotic treatments have increasingly proven inadequate due to challenges such as antibiotic resistance, microbial dysbiosis, and mucosal damage. In response to these issues, this review introduces an innovative intervention strategy based on the “nanotechnology-based 3R” approach (Remove H. pylori, Remodel the microenvironment, Repair the gastrointestinal tract), which aims to offer a comprehensive solution for managing H. pylori infection. This strategy comprises three principal components. Firstly, the utilization of pH/light/magnetic multi-responsive nanomaterials facilitates the precise eradication of the pathogen and its biofilm. Secondly, to address bacterial immune evasion, these nanomaterials are engineered to target and neutralize virulence factors such as VacA, thereby contributing to the reversal of the local immunosuppressive environment. Thirdly, the utilization of nanomaterials presents a promising approach for the concurrent repair of the mucosal barrier and the maintenance of intestinal microbiome homeostasis. Finally, this paper provides a comprehensive analysis of the specific mechanisms employed by typical nanomaterials, including metal-organic frameworks, charge-reversal nanoparticles, nanozymes, and antimicrobial peptide crystals. These mechanisms involve targeted microbial eradication, activation of autophagy, and the upregulation of tight junction proteins. Furthermore, the study delves into the critical roles played by multimodal external field stimulation and material–host interaction network analysis, which are essential for future clinical translation. Ultimately, this review suggests a potential roadmap for system-precision intervention that transcends the conventional “sterilization first” paradigm. Nonetheless, the current evidence regarding the efficacy and safety of this approach is predominantly derived from cell and mouse models. Therefore, its clinical applicability requires validation through studies involving large animal models and prospective clinical trials.

Digital pathology (DP) is transitioning from an adjunct technology to an enterprise diagnostic platform in the United States. Despite accelerating clinical adoption, many laboratories face persistent barriers, including high capital and operating costs, workflow disruption, interoperability challenges, and a complex regulatory and reimbursement environment. This narrative review proposes a practical lifecycle framework for implementing and sustaining DP programs, with an emphasis on defining and operationalizing institutional artificial intelligence (AI) readiness for safe and sustainable adoption.

We performed a targeted narrative review informed by searches of PubMed/MEDLINE and Google Scholar for English-language publications from January 1, 2014 through December 31, 2025. Core search concepts included DP, whole slide imaging, image management/viewing systems, laboratory information system integration, validation, reimbursement, U.S. Food and Drug Administration clearance, Clinical Laboratory Improvement Amendments oversight, College of American Pathologists accreditation, interoperability standards, cybersecurity, and AI. We supplemented database searches with reference screening and review of primary guidance and public databases from regulatory and professional organizations in the United States. We prioritized peer-reviewed literature and used web-based regulatory sources when they represented the authoritative primary reference. We also incorporated our professional experience and knowledge in DP and AI.

Key implementation domains span foundational infrastructure (scanners, storage/networking, and integrated image management platforms), workflow redesign across pre-analytic, analytic, and post-analytic phases, validation and quality management, regulatory compliance and accreditation, cost capture, interoperability strategy, cybersecurity and access control, education and change management, and long-term governance. We also describe an institution-level AI readiness model that can be assessed across data quality, integration, validation, monitoring, governance, and workforce capabilities to support safe clinical AI deployment.

Successful DP implementation requires a lifecycle approach that couples technical build-out with workflow redesign and institutional governance. Early planning for compliance, interoperability, reimbursement strategy, and AI readiness can reduce implementation risk and position laboratories for sustained clinical and computational innovation.