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Hepatitis B virus (HBV) infection remains a major public-health challenge in Peru, particularly in historically hyperendemic Amazonian and Andean regions; however, the structure, evolution, and equity of national HBV research have not been systematically evaluated. We conducted a PRISMA-informed bibliometric analysis of all peer-reviewed and theses on HBV in Peru published between 1988 and 2023 using Scopus, Google Scholar, and the Peruvian National Repository (RENATI). Bibliometric indicators, collaboration networks, thematic structure, and temporal thematic evolution were analyzed in R using bibliometrix- and network-based approaches. The final corpus comprised 232 documents, with a marked increase in production after 2005 and a publication peak in 2018. Scientific output was strongly concentrated in Lima-based institutions, while several departments historically associated with HBV endemicity exhibited minimal or absent research production. Nearly half of the corpus corresponded to undergraduate and postgraduate theses. Thematic analyses revealed persistent predominance of epidemiology, seroprevalence, and vaccination-related research, whereas molecular virology, therapeutics, and translational research remained peripheral or poorly represented. International collaboration was markedly limited. Overall, Peruvian HBV research has expanded quantitatively but remains geographically centralized and shows only limited correspondence with the contemporary geographic distribution of HBV incidence, while also remaining only partially aligned with the contemporary global HBV research frontier. These findings provide an evidence-based framework to guide research-priority setting, territorial equity policies, and strategic investment in infectious disease research capacity in Peru. Moreover, the weak association observed between scientific production and departmental HBV incidence suggests that factors beyond contemporary epidemiological burden contribute to the current distribution of research activity in Peru, highlighting a critical but often overlooked dimension of health inequity in low- and middle-income countries (LMIC) research systems. Full article

Global population aging has emerged as a major driver of the growing burden of neurological diseases, highlighting the urgent demand for advances in early diagnosis, prevention, and rehabilitation. These conditions are typically characterized by insidious onset and irreversible progression, yet their clinical management remains critically compromised by substantial diagnostic delays, representing an intractable bottleneck for existing detection technologies. Therefore, the development of precise, early-stage detection technologies is crucial for expanding the therapeutic window and improving long-term clinical outcomes, addressing a critical unmet clinical need. Herein, we review and compare precision detection strategies for neurological diseases, focusing on the types and mechanisms of mainstream biosensing platforms. Based on the classification of detection substrates and signal transduction mechanisms, four major bio-detection branches are analyzed, including liquid, exosomal, imaging, and digital biomarker detection, with representative studies demonstrating detection limits reaching femtomolar concentrations, clinical diagnostic sensitivities exceeding 90%, and classification accuracies comparable to or surpassing conventional imaging modalities. The inherent advantages and limitations of each biosensing technology are also comprehensively discussed. This review underscores that future research on neurological biomarker sensing is trending toward multimodal integration, which enables the construction of more robust early warning and prognostic assessment systems. This work aims to provide valuable theoretical insights for clinical translation of relevant sensing technologies and integrated diagnostic and treatment strategies, thereby facilitating the progress of early intervention and rehabilitation for common neurological diseases. Full article

Background/Objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder traditionally characterized by the extracellular accumulation of amyloid-beta (Abeta) plaques and the formation of intracellular neurofibrillary tau tangles; however, the prevailing scientific paradigm has shifted toward an integrative model of pathogenesis that recognizes neuroinflammation as a critical, self-perpetuating driver of cognitive attrition. This multifaceted interplay is mediated by the brain–body axis, wherein chronic systemic inflammation—stemming from metabolic dysfunction, cardiovascular disease, or environmental stressors such as fine particulate matter PM_2.5—compromises the structural integrity of the blood–brain barrier. Methods: Such environmental insults serve as priming agents for the innate immune system, shifting peripheral immune populations toward a pro-inflammatory phenotype that is further exacerbated by the stabilization of hypoxia-inducible factors (HIFs) through oxidative stress-induced pseudohypoxia, even under normoxic conditions. Results: The subsequent activation of microglia and astrocytes transitions the cerebral microenvironment from a homeostatic, neurosupportive state into a neurotoxic milieu that actively promotes synaptic loss and neuronal death. Conclusions: Consequently, contemporary research has pivoted from broad-spectrum anti-inflammatory interventions toward targeted immune modulation, emphasizing that a comprehensive understanding of how systemic dysfunction perpetuates neuroinflammatory cascades is essential for developing efficacious therapies capable of attenuating AD progression and mitigating its global health burden. Full article

Allergic diseases are increasing globally, particularly among children, who are highly vulnerable due to critical windows of immune development. This review examines climate change as a key environmental determinant driving the rising burden of pediatric allergic diseases, including asthma, allergic rhinitis (AR), atopic dermatitis (AD), and food allergy (FA). Climate change influences disease risk through interconnected pathways, such as increased air pollution, altered aeroallergen patterns, and more frequent extreme weather events. Elevated carbon dioxide (CO₂) levels and rising temperatures prolong pollen seasons and enhance allergenicity, while pollutants such as ozone (O₃) and particulate matter (PM) exacerbate airway inflammation and immune dysregulation. Emerging evidence emphasizes the role of early-life exposure, particularly during prenatal and early postnatal periods, when environmental insults can induce long-term effects via epigenetic modifications and immune reprogramming. These mechanisms may increase susceptibility to allergic sensitization and subsequent disease development. Epidemiological studies consistently link exposure to air pollution, including PM_2.5 (PM with aerodynamic diameter < 2.5 μm) and nitrogen dioxide (NO₂), with increased risk of allergic diseases in children. Additionally, climate change-related events such as wildfires, sand and dust storms, and thunderstorms further elevate exposure to allergens and pollutants, contributing to acute exacerbations and disease progression. Climate change may also contribute to allergic diseases through microbiome dysbiosis, as altered environmental microbial exposures, biodiversity loss, air pollution, and antibiotic-associated microbial disruption may impair immune tolerance and promote allergic sensitization in children. Addressing this growing public health challenge requires integrated mitigation strategies to reduce greenhouse gas (GHG) emissions and improve air quality, alongside adaptive interventions to enhance resilience and reduce exposure. Understanding these mechanisms is essential for developing targeted prevention strategies and protecting child health in a changing climate. Full article

Liver disease represents a major global health burden, and early diagnosis is essential for reducing mortality. Machine learning (ML) approaches offer non-invasive alternatives to conventional diagnostics, yet existing studies on liver disease prediction often lack systematic feature selection, apply resampling before data splitting (introducing leakage), and report results from single train-test splits without statistical testing. This study proposes a Hybrid Feature Selection (HFS) framework combining Pearson-correlation-based redundancy elimination with a weighted Information Gain–Gain Ratio scoring function, integrated with SMOTE within a leakage-free pipeline. The framework is evaluated on two benchmarks—the Indian Liver Patient Dataset (ILPD, n = 583) and the BUPA Liver Disorders Dataset (n = 345)—across ten classifiers and ten independent train-test splits, with significance assessed via paired Wilcoxon signed-rank tests. On ILPD, the HFS + SMOTE pipeline produced statistically significant ROC-AUC improvements (p < 0.05) in five of ten classifiers and resolved majority-class collapse, raising mean Specificity from 0.00–0.33 to 0.61–0.92. A 2 × 2 ablation study confirmed that HFS and SMOTE contribute independently, with SMOTE driving the Specificity transformation and HFS reducing feature-space noise. Sensitivity analyses demonstrated robustness to the weighting parameter w and confirmed k = 6 as the optimal feature count. Replication on BUPA—which exhibits near-perfect class balance and no feature redundancy—produced a principled null result, confirming that the pipeline’s effectiveness is mechanistically linked to dataset characteristics. The HFS algorithm consistently identified four clinically meaningful core features (AST, ALT, Total Bilirubin, Age) across all runs, validated by SHAP and Permutation Importance stability analysis. Full article

Background/Objectives: Although Clostridioides difficile infection (CDI) is a key cause of global morbidity and mortality, the burden of CDI in mainland China is not well-defined. The objective of this systematic literature review was to summarize the available epidemiologic evidence on the CDI disease burden (cases, hospitalizations, and deaths) in mainland China. Methods: Six databases (three global [PubMed, Embase, Cochrane] and three Chinese [Chinese National Knowledge Infrastructure, Chinese Science Citation, Wanfang]) were searched on 5 August 2025 using CDI-related and epidemiological search terms. No date or language limits were applied. Real-world epidemiologic studies of adults and/or children with laboratory-confirmed CDI in mainland China reporting population-based CDI incidence, hospital-based CDI incidence, and/or CDI admission rates were included. All studies not meeting these criteria were excluded. Risk-of-bias (RoB) assessment was performed using the Newcastle–Ottawa Scale. Results were summarized descriptively. Results: In total, 11 articles formed the evidence base for this review; each was a single-center, hospital-based study conducted in one of six cities in mainland China and published between 2014 and 2023. RoB assessment indicated that the evidence base was appropriate for this study. No study reported population-based CDI incidence. In total, 10 studies reported hospital-based CDI incidence (0 to 82.0/10,000 patient-days), and four reported CDI admission rates (0 to 23.1/1000 admissions). Eight studies reported mortality rates, which varied across studies. Conclusions: Several single-center, hospital-based studies demonstrate that CDI is present in hospitals in mainland China, but there are no published population-based CDI incidence estimates. These results should be interpreted considering this study’s limitations, including potential publication and selection bias, heterogeneity, and limited generalizability. Overall, the burden of CDI is poorly understood in mainland China. Thus, prospective epidemiological studies, including those with sensitive detection methods, are needed to examine CDI burden across multiple cities in mainland China. These efforts would help illuminate the CDI burden and guide prevention efforts. (PROSPERO ID 1140152; registered 17 March 2026; funding by Pfizer Inc.). Full article

Alcohol-related liver disease (ALD) poses a significant global health burden, driven by complex mechanisms including oxidative stress, inflammation, and gut–liver axis disruption. While the individual roles of gut microbiota dysbiosis and ageing in ALD pathogenesis are increasingly recognized, their synergistic interaction remains poorly understood. This review synthesizes current evidence to argue that there is an interaction between ageing and the gut microbiota that collectively amplifies progression of ALD. Specifically, ageing promotes gut dysbiosis through immunosenescence (e.g., reduced IgA diversification and antimicrobial peptide decline), intestinal barrier failure, and altered microbial metabolite profiles (e.g., decreased short-chain fatty acids and dysregulated bile acid metabolism). Conversely, dysbiosis-derived metabolites and endotoxins modulate ageing-related signaling pathways, including SIRT1, FOXO, and Nrf2, thereby accelerating hepatic cellular senescence, inflammation, and fibrogenesis. Furthermore, we also discussed the typical microbial changes in ALD. These include an increase in the Proteobacteria, a decrease in the Bacteroidetes, as well as imbalances in fungi and viruses. In ageing, similar but distinct shifts occur, such as reduced microbial diversity, decreased short-chain fatty acid producers, and increased intestinal permeability. Therapeutic strategies targeting the gut microbiota (probiotics, fecal microbiota transplantation) or ageing-related pathways (SIRT1 activators) hold promise. Future research priorities include validating ageing-associated microbial signatures as predictors of ALD progression and testing microbiota-targeted interventions in aged preclinical models. Collectively, this review identifies the microbiota–ageing axis as a tractable therapeutic target for ALD and provides a framework for future mechanistic and translational studies. Full article

Using Global Burden of Disease 2021 modeled estimates, we assessed the burden, temporal trends, and inequalities of pediatric all-form tuberculosis (TB) and multidrug-resistant TB (MDR-TB) from 1990 to 2021 across 204 countries and territories. Compared with all-form TB, pediatric MDR-TB showed a distinct and less favorable estimated trajectory. Although GBD-based estimates suggested overall declines in pediatric all-form TB incidence and mortality, the MDR-to-all-form ratio increased worldwide for both incidence and mortality, suggesting a growing proportional contribution of MDR-TB within the estimated pediatric TB burden. In 2021, pediatric MDR-TB remained concentrated in low- and low–middle-SDI settings, where modeled socioeconomic inequalities appeared to become more pronounced over time. Mortality relative to incidence was highest among children aged under 5 years, with particularly elevated and imprecise mortality-to-incidence ratios for MDR-TB. Sex disparities also evolved differently by disease type: they generally narrowed for all-form TB but were more heterogeneous and in some settings widened for MDR-TB. These GBD-based findings suggest that progress in overall pediatric TB control may not have translated evenly to drug-resistant disease and highlight the need for pediatric TB strategies that explicitly address drug resistance, early childhood vulnerability, and inequitable access to diagnosis and treatment. Due to the sparsity of global pediatric data, no independent external validation was performed; findings are based on internal sensitivity analyses of GBD estimates. Full article

Background: Chronic liver disease (CLD) imposes a heavy global burden, particularly among middle-aged and elderly adults. Prospective evidence on whether depressive symptoms independently predict new-onset CLD remains scarce. Methods: This prospective cohort study used CHARLS (2011–2020) data and enrolled 9549 participants without baseline CLD. Depressive symptoms were assessed using the CES-D-10 and categorized into four severity levels. Multivariable Cox regression, Kaplan–Meier analysis, and ROC curves were used. Subgroup analyses were conducted across demographic and behavioral strata to assess consistency. Results: During a mean follow-up of 8.77 years, 746 (7.8%) participants developed new-onset CLD. Higher baseline depression severity was associated with increased CLD risk. In the fully adjusted model, compared with the non-depressed group, the HR for mild depression was 1.34 (95% CI: 1.12–1.59, p = 0.001), for moderate depression 1.65 (95% CI: 1.34–2.04, p < 0.001), and for severe depression 2.16 (95% CI: 1.26–3.72, p = 0.005). Cumulative incidence increased with depression severity, with group differences widening over time (log-rank p < 0.0001). Subgroup analyses showed consistent associations across different demographic and behavioral strata. Conclusions: Across the total population, the analyses consistently demonstrate an independent, graded association between baseline depressive symptom severity and incident CLD that persists after multivariable adjustment. The stratified analyses further reveal that this association is primarily driven by female participants and middle-aged adults (45–60 years), highlighting these subgroups as priority populations for depression-informed CLD prevention and screening strategies. Full article

Background: Osteoporotic vertebral compression fractures (OVCFs) are the most prevalent manifestation of osteoporotic skeletal disease, associated with severe pain, functional decline, and elevated risk of subsequent fractures. Conservative management remains the first-line approach for stable fractures, yet pain control is often suboptimal, and vertebral collapse progresses in up to 37% of patients. Bio-activated orthosilicic acid combined with vitamins D3 and K2 (BioSi-DK) may support fracture healing through complementary mechanisms acting on osteoblast differentiation, collagen synthesis, osteocalcin carboxylation, and mineralization, but its clinical efficacy in OVCFs has not previously been investigated. Methods: A retrospective, multi-center comparative cohort study was conducted in patients aged >50 years with DXA-confirmed osteoporosis and acute thoracolumbar OVCFs (AO Spine OF1-OF2) managed conservatively. Patients receiving BioSi-DK supplementation (two capsules daily for two months, then one capsule daily for four months) in addition to standard conservative treatment were compared with controls receiving conservative treatment alone. Propensity score matching (1:1, sex-exact constraint, caliper 0.3 SD) was applied across twelve pre-specified baseline covariates. The primary outcome was pain intensity at six months, assessed by numerical rating scale (NRS). Secondary outcomes included NRS change, analgesic use, Patient Global Impression of Change (PGIC), requirement for vertebral augmentation (kyphoplasty), MRI marrow edema score (MES), and Genant grade change. Results: After propensity score matching, 38 patients (19 per group) with balanced baseline characteristics were analyzed (mean age 71.2 ± 6.5 years; 89.5% female; mean T-score −2.61 ± 0.32; mean baseline NRS 8.26 ± 0.95). The BioSi-DK group achieved a significantly lower post-treatment NRS score compared with controls (2.05 ± 2.17 vs. 3.84 ± 2.83; p = 0.015; Cohen’s d = −0.71) and a significantly greater mean NRS reduction (−6.21 ± 1.90 vs. −4.42 ± 2.12 points; p = 0.005; d = −0.89). Analgesic discontinuation was more frequent in the BioSi-DK group (68.4% vs. 36.8%; p = 0.068). Kyphoplasty was required in 5.3% of BioSi-DK patients versus 21.1% of controls (p = 0.340; OR = 0.21), and vertebral compression grade remained stable in 100% of supplemented patients versus 84% of controls. At two months, MES improvement by at least one category was more frequently observed in the BioSi-DK group than in controls, suggesting an earlier edema resolution effect; at six months, MES distribution was comparable between groups (p = 0.620). Conclusions: BioSi-DK supplementation as an adjunct to conservative management was associated with a statistically significant and clinically large reduction in pain at six months, with favorable trends in analgesic burden, kyphoplasty requirement, and edema resolution. The safety profile was excellent. These findings support the conduct of prospective, randomized, placebo-controlled trials to confirm BioSi-DK as an effective adjunct therapy for OVCFs. Full article

Chronic respiratory diseases, including chronic obstructive pulmonary disease (COPD), asthma, and interstitial lung diseases (ILDs), represent a major global health burden. Their significant clinical and biological heterogeneity complicates diagnosis and limits the efficacy of traditional, one-size-fits-all management approaches. The advent of high-throughput genomic and multi-omic technologies has initiated a paradigm shift from syndromic classification to molecular-based endotyping. A narrative review of the literature was performed, synthesising foundational and recent research in the genomics, epigenomics, and multi-omics of chronic respiratory diseases. Key studies were selected based on their relevance to genetic architecture, biomarker development, and translational applications in precision medicine. We discuss the complex genetic architecture of pulmonary conditions, highlighting the contribution of both rare, high-penetrance variants, such as SERPINA1, CFTR, and BMPR2, and polygenic risk from many common variants, such as HHIP, FAM13A, and IL33. We provide detailed analyses of polygenic risk scores (PRSs) for COPD and asthma, including their construction, validation across ancestries, and predictive performance. We detail how integrative multi-omic approaches, including transcriptomics, proteomics, and metabolomics, are successfully defining molecular endotypes, such as Type 2-high asthma, which, in turn, inform the use of targeted biologic therapies. Finally, we review the development of molecular diagnostics, including metagenomic sequencing of infections and liquid biopsies for lung cancer and the development of prognostic biomarkers. The genomic revolution is transforming pulmonary medicine through the discovery of novel disease pathways, precise molecular classification, and the recognition of new therapeutic targets. Despite major challenges in functional interpretation, data integration, and clinical–translational equity, these technologies hold the key to a new era of personalised respiratory health and precision medicine. Full article

Dental caries is the world’s most common non-communicable disease with a complex etiology including social, behavioral, medical, biological and economical elements. The distribution among populations and age groups is skewed, which calls for validated clinical tools to identify those with increased caries risk. The aim of this article was therefore to review risk factors for caries development in children, based on global prospective birth cohorts, genetic proceedings and data from validated risk assessment tools. The genetic elements involve four main categories comprising enamel quality, salivary composition, dental biofilm function and taste preferences. Recent studies suggest that genes may account for 35–55% of the variation in caries scores in the young permanent dentition. Prospective birth cohorts have pointed out poverty, socioeconomic level, early introduction and excessive sugar intake as significant factors for a child’s dental caries trajectory up into adulthood. Moreover, prolonged breastfeeding, child obesity and maternal oral conditions are linked to the caries burden later in life. In the clinic, the strongest predictors are past caries history and selected behavioral and social factors. The performance of the validated caries risk assessment models is far from perfect, but still acceptable in terms of reliability during childhood. These tools are the best clinical practice since they add objectivity, consistency and documentation to the clinical routines. In addition, the dental staff has the advantage of using the outcome of the assessment for a structured risk communication with the caregivers. The protocol should also form the basis for a personalized intervention program addressing the entire family, with particular focus on maternal oral health and sugar reduction. Full article

Osteoarthritis (OA) is a disabling joint disease characterised by cartilage degradation, synovial inflammation, and subchondral bone remodelling. Furthermore, catabolic inflammatory processes as well as dysregulated cellular signalling and oxidative stress are central to OA pathogenesis. Despite its growing global burden, currently available therapies primarily provide symptomatic relief and fail to target underlying molecular mechanisms and halt disease progression. Cold atmospheric plasma (CAP), a partially ionised, non-thermal gas that generates controlled reactive oxygen and nitrogen species (RONS), has emerged as a promising therapeutic modality capable of modulating redox-sensitive signalling pathways. CAP has demonstrated the capacity to suppress pro-inflammatory cytokine expression, enhance antioxidant defence mechanisms, influence macrophage polarisation, and stimulate tissue repair processes in rheumatoid arthritis, diabetic and dermal wound healing models. However, its potential as a disease-modifying therapy for the treatment of OA is not yet fully understood and warrants further experimental investigation. This review explores current pre-clinical evidence from different disease models, which may have implications for the potential application of CAP as a therapeutic intervention for OA, either as a disease-modifying therapy or as an adjuvant therapy for intra-articular drug delivery. Furthermore, key translational challenges including plasma parameter standardisation, interactions with synovial fluid and optimisation of joint-specific delivery strategies are discussed, identifying gaps that require further experimental investigation. Collectively, the findings of this review highlight CAP as a promising multimodal therapy with translational potential for the treatment of OA warranting further experimental validation and may open innovative avenues for future research. Full article

Objective: This study aims to examine the association between the frailty index (FI) and stroke risk among Chinese adults, describe the burden of stroke in China, and explore the causal role of FI in ischemic stroke through Mendelian randomization. Methods: Data from the China Health and Retirement Longitudinal Study (CHARLS) included 13,473 participants aged 45 years and older without a history of stroke. Cox models, restricted cubic splines, and sensitivity analyses were employed to assess the association between the modified frailty index (mFI) and incident stroke. Additionally, data from the Global Burden of Disease (GBD) 2021 data report were utilized to describe stroke trends in China from 1990 to 2021. Two-sample Mendelian randomization was conducted to evaluate the causal effects of FI on ischemic stroke subtypes. Results: During a median follow-up period of approximately 7 years, 811 incident strokes were recorded. Each 0.1-point increase in mFI was associated with a 16% increase in stroke risk (HR = 1.16, 95% CI: 1.06–1.27), demonstrating a linear dose–response relationship. From 1990 to 2021, the proportion of ischemic stroke rose from 46.9% to 63.2%. Mendelian randomization analysis provided genetic evidence supporting a causal association between FI and ischemic stroke (OR = 1.191, 95% CI: 1.046–1.357), particularly driven by large-artery atherosclerotic (OR = 1.852) and small-vessel stroke (OR = 1.415), but not by cardioembolic stroke. Conclusions: A higher FI is associated with an increased risk of stroke among Chinese adults, with genetic evidence supporting a causal role in ischemic stroke. Therefore, FI may serve as a valuable addition to existing risk assessment tools. Full article