Search Results (1,069)

Chronic nasopharyngeal and otic disorders in children represent a significant clinical challenge due to their multifactorial etiology, variable presentation, and frequent resistance to standard therapies. Although often approached from a symptomatic or anatomical perspective, these conditions are deeply rooted in histological and molecular alterations that sustain inflammation, impair mucosal function, and promote recurrence. This narrative review synthesizes the current knowledge on the normal histology of the nasopharynx, Eustachian tube, and middle ear, and explores key pathophysiological mechanisms, including epithelial remodeling, immune cell infiltration, cytokine imbalance, and tissue fibrosis. Special emphasis is placed on the role of immunohistochemistry in defining inflammatory phenotypes, barrier dysfunction, and remodeling pathways. The presence of biofilm, epithelial plasticity, and dysregulated cytokine signaling are also discussed as contributors to disease chronicity. These findings have direct implications for diagnosis, therapeutic stratification, and postoperative monitoring. By integrating histological, immunological, and molecular data, clinicians can better characterize disease subtypes, anticipate treatment outcomes, and move toward a more personalized and biologically informed model of pediatric ENT care. Full article

Background/Objectives: While ART effectively suppresses HIV viremia, many PLWH exhibit persistent immune dysfunction. This study aimed to assess immune recovery and immune exhaustion (PD-1/PD-L1 expression) in newly diagnosed versus long-term ART-treated individuals. Methods: We analyzed 79 PLWH: 52 newly diagnosed individuals (12-month follow-up) and 27 long-term-treated patients (Ukrainian refugees). Flow cytometry was used to evaluate CD4+ and CD8+ counts, the CD4+/CD8+ ratio, and PD-1/PD-L1 expression on CD3+, CD4+, and CD19+ lymphocytes. ART regimen and HIV subtype were included as covariates in linear regression models. Results: At 12 months, CD4+ counts were similar between groups (median 596.5 vs. 621 cells/μL, p = 0.22), but newly diagnosed patients had higher CD8+ counts (872 vs. 620 cells/μL, p = 0.028) and a lower CD4+/CD8+ ratio (0.57 vs. 1.05, p = 0.0027). Immune exhaustion markers were significantly elevated in newly diagnosed individuals: CD4+ PD-1+ T cells (24.4% vs. 3.85%, p = 0.0002) and CD3+ PD-1+ T cells (27.3% vs. 12.35%, p < 0.0001). Linear regression confirmed group membership independently predicted higher CD3+ (β = +21.92, p < 0.001), CD4+ (β = +28.87, p < 0.0001), and CD19+ (β = +8.73, p = 0.002) percentages. Lipid parameters and SCORE2 did not differ significantly. Conclusions: Despite virologic suppression and CD4+ recovery, immune exhaustion markers remain elevated in newly diagnosed PLWH, suggesting incomplete immune normalization. Traditional parameters (CD4+ count and CD4+/CD8+ ratio) may not fully capture immune status, warranting broader immunologic profiling in HIV care. Full article

Allergic contact dermatitis (ACD) is an immunologic reaction to a dermal chemical exposure that, once triggered in an individual, will result in an allergic response following subsequent encounters with the allergen. Air Force epidemiological consultations have indicated that aircraft structural maintenance workers may experience ACD at elevated rates compared to other occupations. We aimed to better understand the utility of non-animal testing methods in characterizing the sensitization potential of chemicals used during Air Force operations by evaluating the skin sensitization hazard of Air Force-relevant chemicals using new approach methodologies (NAMs) in a case study. We also evaluated the use of NAM data to develop preliminary candidate surface guidelines (PCSGs, maximum concentrations of chemicals on workplace surfaces to prevent induction of dermal sensitization) for chemicals identified as sensitizers. NAMs for assessing skin sensitization, including in silico models and experimental assays, were leveraged into an integrated approach to predict sensitization hazard for 19 chemicals. Local lymph node assay effective concentration values were predicted from NAM assay data via previously published quantitative models. The derived values were used to calculate PCSGs, which can be used to compare the presence of these chemicals on work surfaces to better understand the risk of Airmen developing ACD from occupational exposures. Full article

Background: Angiosarcomas (ASs) represent a heterogeneous and highly aggressive subset of tumors that respond poorly to systemic treatments and are associated with short progression-free survival (PFS) and overall survival (OS). The aim of this study was to develop and validate an immune-related prognostic model—termed the AS score—using data from two independent sarcoma cohorts. Methods: A prognostic model was developed using a previously characterized cohort of 25 angiosarcoma samples. Candidate genes were identified via the Maxstat algorithm (Maxstat v0.7-25 for R), combined with log-rank testing. The AS score was then computed by weighing normalized gene expression levels according to Cox regression coefficients. For external validation, transcriptomic data from TCGA Sarcoma cohort (n = 253) were analyzed. The Immunoscore—which reflects the tumor immune microenvironment—was inferred using the ESTIMATE package (v1.0.13) in R. All statistical analyses were performed in RStudio (v 4.0.3). Results: Four genes—IGF1R, MAP2K1, SERPINE1, and TCF12—were ultimately selected to construct the prognostic model. The resulting AS score enabled the classification of angiosarcoma cases into two prognostically distinct groups (p = 0.00012). Cases with high AS score values, which included both cutaneous and non-cutaneous forms, exhibited significantly poorer outcomes, whereas cases with low AS scores were predominantly cutaneous. A significant association was observed between the AS score and the Immunoscore (p = 0.025), with higher Immunoscore values found in high-AS score tumors. Validation using TCGA sarcoma cohort confirmed the prognostic value of both the AS score (p = 0.0066) and the Immunoscore (p = 0.0029), with a strong correlation between their continuous values (p = 2.9 × 10⁻⁸). Further survival analysis, integrating categorized scores into four groups, demonstrated robust prognostic significance (p = 0.00021). Notably, in tumors with a low Immunoscore, AS score stratification was not prognostic. In contrast, among cases with a high Immunoscore, the AS score effectively distinguished outcomes (p < 0.0001), identifying a subgroup with poor prognosis but potential sensitivity to immunotherapy. Conclusions: This combined classification using the AS score and Immunoscore has prognostic relevance in sarcoma, suggesting that angiosarcomas with an immunologically active microenvironment (high Immunoscore) and poor prognosis (high AS score) may be prime candidates for immunotherapy and this approach warrants prospective validation. Full article

Schizophrenia is a challenging multifactorial neuropsychiatric disease that involves interactions between genetic susceptibility and environmental insults. Increasing evidence implicates viral infections as significant environmental contributors, particularly during sensitive neurodevelopmental periods. This review synthesises current findings on the viral hypothesis of schizophrenia, encompassing a wide array of neurotropic viruses, including influenza viruses, herpesviruses (HSV-1 and 2, CMV, VZV, EBV, HHV-6 and 8), hepatitis B and C viruses, HIV, HERVs, HTLV, Zika virus, BoDV, coronaviruses (including SARS-CoV-2), and others. These pathogens can contribute to schizophrenia through mechanisms such as direct microinvasion, persistent central nervous system infection, immune-mediated neuroinflammation, molecular mimicry, and the disturbance of the blood–brain barrier. Prenatal exposure to viral infections can trigger maternal immune activation, resulting in cytokine-mediated alterations in the neurological development of the foetus that persist into adulthood. Genetic studies highlight the role of immune-related loci, including major histocompatibility complex polymorphisms, in modulating susceptibility to infection and neurodevelopmental outcomes. Clinical data also support the “mild encephalitis” hypothesis, suggesting that a subset of schizophrenia cases involve low-grade chronic neuroinflammation. Although antipsychotics have some immunomodulatory effects, adjunctive anti-inflammatory therapies show promise, particularly in treatment-resistant cases. Despite compelling associations, pathogen-specific links remain inconsistent, emphasising the need for longitudinal studies and integrative approaches such as viromics to unravel causal relationships. This review supports a “multi-hit” model in which viral infections interfere with hereditary and immunological susceptibilities, enhancing schizophrenia risk. Elucidating these virus–immune–brain interactions may facilitate the discovery of biomarkers, targeted prevention, and novel therapeutic strategies for schizophrenia. Full article

Background: Dyslipidemia and schistosomiasis are major public health challenges, particularly in endemic regions where their coexistence may influence host metabolism and immune responses. This study aimed to evaluate visceral adipose tissue (AT) remodeling in a murine model of acute Schistosoma mansoni infection combined with diet-induced dyslipidemia. Methodology: Female Swiss Webster mice were fed either a standard or high-fat diet (HFD) for 29 weeks and infected with S. mansoni at week 20. Nine weeks after infection, biochemical, morphometric, histopathological, and immunological analyses were performed. Results: The HFD promoted weight gain and dyslipidemia, while S. mansoni infection alone did not alter lipid profiles but partially mitigated the metabolic effects of the HFD. Morphometric analysis revealed adipocyte hypertrophy and reduced cell number in HFD-fed animals. In HFD-fed infected mice, infection partially reversed hypertrophy, suggesting a modulatory effect on AT remodeling. Histopathological examinations showed that while a HFD induced mild inflammation, infection led to intense leukocyte infiltration, hyperemia, and plasma cell degeneration. Peritoneal lavage confirmed a proinflammatory immune profile. Conclusions: These findings indicate that the interaction between a HFD and S. mansoni infection exacerbates adipose tissue inflammation and metabolic alterations, highlighting the complex interplay between parasitic infection, diet, and immune-metabolic regulation. Full article

Artificial Intelligence (AI) and machine learning (ML) are increasingly being applied across the transplantation care pathway, supporting tasks such as donor–recipient matching, immunological risk stratification, early detection of graft dysfunction, and optimisation of immunosuppressive therapy. This review provides a structured synthesis of current AI applications in transplantation, with a focus on underrepresented areas including real-time graft viability assessment, adaptive immunosuppression, and cross-organ immune modelling. The review also examines the translational infrastructure needed for clinical implementation, such as federated learning, explainable AI (XAI), and data governance. Evidence suggests that AI-based models can improve predictive accuracy and clinical decision support when compared to conventional approaches. However, limitations related to data quality, algorithmic bias, model transparency, and integration into clinical workflows remain. Addressing these challenges through rigorous validation, ethical oversight, and interdisciplinary collaboration will be necessary to support the safe and effective use of AI in transplant medicine. Full article

Background: Despite distinct etiologies, type 1 diabetes (T1D) and type 2 diabetes (T2D) share chronic inflammation as a core feature. Interleukins, key immune mediators, play important yet still not fully understood roles in the development and complications of both conditions. Objective: This narrative review aims to provide a comprehensive and critical synthesis of current evidence on the role of key interleukins in T1D and T2D, highlighting their immunological functions, genetic associations, clinical correlations, and translational potential. Methods: A targeted literature search was conducted in PubMed, Google Scholar, and ScienceDirect up to January 2025, focusing on English-language clinical and experimental studies involving interleukins and their relevance to T1D and T2D. Reference lists were manually screened for additional sources. Interleukins (ILs) were reviewed individually to assess their immunobiology, disease specificity, and biomarker or therapeutic value. Findings: Pro-inflammatory cytokines such as IL-1β, IL-6, and IL-17 contribute to islet inflammation, insulin resistance, and microvascular damage in both T1D and T2D. Anti-inflammatory mediators including IL-4, IL-10, and IL-13 exhibit protective effects but vary in expression across disease stages. Less-characterized interleukins such as IL-3, IL-5, IL-9, and IL-27 demonstrate dual or context-dependent roles, particularly in shaping immune tolerance and tissue-specific complications such as nephropathy and neuropathy. Polymorphisms in IL-10 and IL-6 genes further suggest genetic contributions to interleukin dysregulation and metabolic dysfunction. Despite promising insights, translational gaps persist due to overreliance on preclinical models and limited longitudinal clinical data. Conclusions: Interleukins represent a mechanistic bridge linking immune dysregulation to metabolic derangements in both T1D and T2D. While their diagnostic and therapeutic potential is increasingly recognized, future research must address current limitations through isoform-specific targeting, context-aware interventions, and validation in large-scale, human cohorts. A unified interleukin-based framework may ultimately advance personalized strategies for diabetes prevention and treatment. Full article

Background: This study presents an innovative approach to cardiovascular disease (CVD) risk prediction based on a comprehensive analysis of clinical, immunological and biochemical markers using mathematical modelling and machine learning methods. Baseline data include indices of humoral and cellular immunity (CD59, CD16, IL-10, CD14, CD19, CD8, CD4, etc.), cytokines and markers of cardiovascular disease, inflammatory markers (TNF, GM-CSF, CRP), growth and angiogenesis factors (VEGF, PGF), proteins involved in apoptosis and cytotoxicity (perforin, CD95), as well as indices of liver function, kidney function, oxidative stress and heart failure (albumin, cystatin C, N-terminal pro B-type natriuretic peptide (NT-proBNP), superoxide dismutase (SOD), C-reactive protein (CRP), cholinesterase (ChE), cholesterol, and glomerular filtration rate (GFR)). Clinical and behavioural risk factors were also considered: arterial hypertension (AH), previous myocardial infarction (PICS), aortocoronary bypass surgery (CABG) and/or stenting, coronary heart disease (CHD), atrial fibrillation (AF), atrioventricular block (AB block), and diabetes mellitus (DM), as well as lifestyle (smoking, alcohol consumption, physical activity level), education, and body mass index (BMI). Methods: The study included 52 patients aged 65 years and older. Based on the clinical, biochemical and immunological data obtained, a model for predicting the risk of premature cardiovascular aging was developed using mathematical modelling and machine learning methods. The aim of the study was to develop a predictive model allowing for the early detection of predisposition to the development of CVDs and their complications. Numerical methods of mathematical modelling, including Runge–Kutta, Adams–Bashforth and backward-directed Euler methods, were used to solve the prediction problem, which made it possible to describe the dynamics of changes in biomarkers and patients’ condition over time with high accuracy. Results: HLA-DR (50%), CD14 (41%) and CD16 (38%) showed the highest association with aging processes. BMI was correlated with placental growth factor (37%). The glomerular filtration rate was positively associated with physical activity (47%), whereas SOD activity was negatively correlated with it (48%), reflecting a decline in antioxidant defence. Conclusions: The obtained results allow for improving the accuracy of cardiovascular risk prediction, and form personalised recommendations for the prevention and correction of its development. Full article

Background: While timely blood transfusion is critical for restoring oxygen-carrying capacity after coronary artery bypass grafting (CABG), allogeneic blood product transfusions are independently associated with increased long-term mortality, necessitating a risk-stratified approach to balance oxygen delivery against immunological complications and infection risks. Methods: We retrospectively analyzed 3376 patients undergoing isolated CABG between 2005 and 2023 at a single tertiary center. Patients who died during their perioperative hospital stay within 30 days were excluded. Transfusion burden was assessed both as the absolute number of blood product units (packed red blood cells, platelet transfusion, fresh frozen plasma) and as a percentage of calculated patient blood volume. The primary outcome was all-cause mortality at 5 years. Flexible Cox regression with penalized smoothing splines, adjusted for EuroSCORE II, was used to model dose–response relationships. Results: From our cohort of 3376 patients, a total of 137 patients (4.05%) received >10 units of packed red blood cells (PRBC) perioperatively. These patients were older (median 71 vs. 68 years, p < 0.001), more often female (29% vs. 15%, p < 0.001), and had higher preoperative risk (EuroSCORE II: 2.53 vs. 1.41, p < 0.001). After 5 years, mortality was 42% in the massive transfusion group versus 10% in controls. Spline regression revealed an exponential increase in mortality with transfused units: 14 units yielded a 1.5-fold higher hazard of death (HR 1.46, 95% CI 1.31–1.64), rising to HR 2.71 (95% CI 2.12–3.47) at 30 units. When transfusion was indexed to blood volume, this relationship became linear and more tightly correlated with mortality, with lower maximum hazard ratios and narrower confidence intervals. Conclusions: Indexing transfusion burden to the percentage of patient blood volume replaced provides a more accurate and clinically actionable predictor of 5-year mortality after CABG than absolute unit counts. Our findings support a shift toward individualized, volume-based transfusion strategies to optimize patient outcomes and resource stewardship in a time of limited availability of blood products. Full article

Chronic inflammatory response syndrome (CIRS) and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) are debilitating multisystem illnesses that share overlapping symptoms and molecular patterns, including immune dysregulation, mitochondrial impairment, and vascular dysfunction. This review provides a chronological synthesis of biomarker development in CIRS, tracing its evolution from early functional tests such as visual contrast sensitivity (VCS) to advanced transcriptomic profiling. Drawing on peer-reviewed studies spanning two decades, we examine the layered integration of neuroendocrine, immunologic, metabolic, and genomic markers that collectively support a multisystem model of innate immune activation specific to environmentally acquired illness. Particular focus is given to the Gene Expression: Inflammation Explained (GENIE) platform’s use of transcriptomics to classify disease stages and distinguish CIRS from other fatiguing conditions. While ME/CFS research continues to explore overlapping pathophysiologic features, it has yet to establish a unified diagnostic model with validated biomarkers or exposure-linked mechanisms. As a result, many patients labeled with ME/CFS may, in fact, represent unrecognized CIRS cases. This review underscores the importance of structured biomarker timelines in improving differential diagnosis and guiding treatment in complex chronic illness and highlights the reproducibility of the CIRS framework in contrast to the diagnostic ambiguity surrounding ME/CFS. Full article

Background/Objectives: Melanoma is an aggressive skin cancer influenced by genetic and immunological factors. The PDCD1 gene encodes PD-1, a receptor involved in immune evasion and therapeutic response. This study aimed to evaluate the association of PDCD1 variants (rs2227982, rs36084323, rs7421861) and its relative gene expression with melanoma in a Mexican population. Methods: An analytical cross-sectional study was conducted with 262 samples: 131 from melanoma patients (newly diagnosed and treatment-naïve) and 131 from cancer-free controls. Genotyping was performed using real-time PCR. PDCD1 expression was assessed by qPCR, normalized with GAPDH, using the 2^−ΔΔCt method and the Pfaffl model. Statistical comparisons included allele/genotype frequencies, expression levels, and clinicopathological associations. Results: No significant association was found between the studied PDCD1 variants and melanoma susceptibility. However, PDCD1 was significantly overexpressed in melanoma samples (2.42-fold increase; p < 0.01), consistent across both quantification methods. Significant associations were also observed between histopathological subtype and Breslow thickness, and between subtype and anatomical site (p < 0.01). Conclusions: Although PDCD1 variants showed no association with melanoma risk, the gene’s overexpression highlights its potential relevance in melanoma immunobiology. These findings contribute to the molecular characterization of melanoma in the Mexican population and support future research on PDCD1 as an immunological biomarker. Full article

Kidney transplant recipients face a substantial burden of premature mortality and morbidity, primarily due to persistent inflammation, cardiovascular risk, and nutritional deficiencies. Traditional nutritional interventions in this population have either focused on supplementing individual nutrients—often with limited efficacy—or required comprehensive dietary overhauls that compromise patient adherence. In this narrative review, we explore the rationale for dietary nut enrichment as a feasible, multi-nutrient strategy tailored to the needs of kidney transplant recipients. Nuts, including peanuts and tree nuts with no added salt, sugar, or oil, are rich in beneficial fats, proteins, vitamins, minerals, and bioactive compounds. We summarize the multiple post-transplant challenges—including obesity, sarcopenia, dyslipidemia, hypertension, immunological dysfunction, and chronic inflammation—and discuss how nut consumption may mitigate these issues through mechanisms involving improved micro-nutrient intake (e.g., magnesium, potassium, selenium), lipid profile modulation, endothelial function, immune support, and gut microbiota health. Additionally, we highlight the scarcity of randomized controlled trials in high-risk populations such as kidney transplant recipients and make the case for studying this group as a model for investigating the clinical efficacy of nuts as a nutritional intervention. We also consider practical aspects for future clinical trials, including the choice of study population, intervention design, duration, nut type, dosage, and primary outcome measures such as systemic inflammation. Finally, potential risks such as nut allergies and oxalate or mycotoxin exposure are addressed. Altogether, this review proposes dietary nut enrichment as a promising, simple, and sustainable multi-nutrient approach to support cardiometabolic and immune health in kidney transplant recipients, warranting formal investigation in clinical trials. Full article

The Gliomas account for 81% of all malignant central nervous system tumors and are classified by WHO into four grades of malignancy. Glioblastoma multiforme (GBM), the most common grade IV glioma, exhibits an extremely aggressive phenotype and a dismal five-year survival rate of only 6%, underscoring the urgent need for novel therapeutic approaches. Immunotherapy has emerged as a promising strategy, and photodynamic therapy (PDT) in particular has attracted attention for its dual cytotoxic and immunostimulatory effects. In GBM models, PDT induces immunogenic cell death characterized by the release of damage-associated molecular patterns (DAMPs), which promote antigen presentation and activate T cell responses. Additionally, PDT transiently increases blood–brain barrier permeability, facilitating immune cell infiltration into the tumor microenvironment, and enhances clearance of waste products via stimulation of meningeal lymphatic vessels. Importantly, PDT can reprogram or inactivate immunosuppressive tumor-associated macrophages, thereby counteracting the pro-tumoral microenvironment. Despite these encouraging findings, further preclinical and clinical studies are required to elucidate PDT’s underlying immunological mechanisms fully and to optimize treatment regimens that maximize its efficacy as part of integrated immunotherapeutic strategies against GBM. Full article

Background: Glioblastoma (GBM) is one of the most challenging malignancies in all of neoplasms. These malignancies are associated with unfavorable clinical outcomes and significantly compromised patient wellbeing. The immunological landscape within the tumor microenvironment (TME) plays a critical role in determining GBM prognosis. By mining data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and correlating them with immune responses in the TME, genes associated with the immune microenvironment with potential prognostic value were obtained. Method: We selected GSE16011 as the training set. Gene expression profiles were substrates scored by both ESTIMATE and xCell, and immune cell subpopulations in GBM were analyzed by CIBERSORT. Gene expression profiles associated with low immune scores were performed by lasso regression, Cox analysis and random forest (RF) to identify a prognostic model for the multiple genes associated with immune infiltration in GBM. Then we constructed a nomogram to optimize the prognostic model using GSE7696 and TCGA-GBM as validation sets and evaluated these data for gene mutation and gene enrichment analysis. Result: The prognostic correlation between the six genes (MEOX2, PHYHIP, RBBP8, ST18, TCF12, and THRB) and GBM was finally found by lasso regression, Cox regression, and RF, and the online database obtained that all six genes were differentially expressed in GBM. Therefore, a prognostic correlation model was constructed based on the six genes. Kaplan–Meier (KM) survival analysis showed that this prognostic model had excellent prognostic ability. Conclusions: Prognostic models based on tumor microenvironment and immune score stratification and the construction of related genes have potential applications for prognostic analysis of GBM patients. Full article