Intensive research has shown that severe COVID-19 outcomes are influenced by antiviral pathways and immune responses, both shaped by genetic predisposition. In this study, we aimed to identify genetic variants associated with disease severity in a cohort of Hungarian patients. We applied a novel stratification method based on age, disease severity, and clinical background to classify patients by susceptibility to severe COVID-19. Whole-exome sequencing (WES) was performed on 168 individuals, and gene mutation loads were assessed. Using a Random Forest machine learning approach, we identified variants of 877 genes that distinguished between severe and non-severe cases. We further categorized these genes as either susceptibility or protective factors. Gene-set enrichment analysis highlighted the most affected biological pathways. Our findings support the development of personalized diagnostic tools to assess the risk of severe COVID-19 and guide targeted treatment strategies. Our findings further extend the results of previous studies, providing novel insights into the genetic determinants of COVID-19 severity.

Post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic disease with unresolved pathophysiology and limited diagnostic options. Extracellular vesicles (EVs) carry disease-specific protein and miRNA signatures and may enable improved disease profiling. We aimed to identify novel protein and miRNA markers as potential biomarkers in plasma EVs from female ME/CFS patients, including post-COVID-19 ME/CFS and post-infectious ME/CFS of other origins, compared with healthy controls. EVs were isolated from plasma by size-exclusion chromatography and characterized for number, size, morphology, and surface marker expression. Flow cytometry showed that small EVs strongly expressed tetraspanins, with only minor differences between ME/CFS patients and healthy donors. Proteomic profiling of EVs from ME/CFS patients identified altered cargo proteins, including hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit compared with healthy controls (n ≤ 10/cohort). Small RNA sequencing followed by qPCR revealed significant downregulation of hsa-let-7b-5p in EVs from post-COVID-19 ME/CFS patients (n = 12) versus healthy controls (n = 15). Reduced hsa-let-7b-5p expression correlated with impaired physical functioning and increased fatigue, pain, and immune activation. These findings indicate that EV cargo differences, particularly hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit, as well as hsa-let-7b-5p, represent promising candidates for ME/CFS diagnosis and patient stratification.

Acute hyperglycaemia is a common COVID-19 complication linked to adverse outcomes. The combined prognostic value of cytokine activation and acute insulin resistance in non-diabetic patients remains unclear. In this prospective cohort study, we enrolled 144 hospitalised adults with RT-PCR-confirmed SARS-CoV-2 infection and no prior diabetes. We aimed to characterise metabolic-inflammatory phenotypes and evaluate their association with disease severity and post-discharge glycaemic outcomes. Patients were classified as normoglycaemic or dysglycaemic based on repeated glucose profiles. Dysglycaemic patients were further phenotyped as stress hyperglycaemia (SHG) or newly diagnosed diabetes (NOD). This classification was based on post-discharge glycaemic assessment at 3 and 6 months, distinguishing transient from persistent hyperglycaemia. Admission hyperglycaemia was associated with a consistently elevated pro-inflammatory cytokine pattern. However, cytokine concentrations were comparable between stress hyperglycaemia and newly diagnosed diabetes, indicating that inflammatory burden alone does not explain metabolic persistence. In contrast, insulin resistance (HOMA-IR) was markedly higher in the newly diagnosed diabetes phenotype. Along with admission oxygenation and key cytokine signals, this contributed to risk stratification for severe disease. In conclusion, early admission assessment of glucose and insulin resistance identifies high-risk metabolic phenotypes. This enables targeted in-hospital risk stratification and post-discharge glycaemic surveillance.

Abnormal liver function tests are frequently reported in patients with COVID-19. This study aimed to identify potential treatment-associated hepatocellular injury in COVID-19 patients by dynamically assessing circulating miR-122, a biomarker with high hepatic specificity and sensitivity. An exploratory approach was additionally used, given the limited evidence regarding factors influencing miR-122 expression in this setting. We performed a prospective cohort study including 96 adult participants enrolled at a tertiary hospital in Bucharest, Romania, between March 2022 and July 2023: 78 COVID-19 patients (57 with baseline and follow-up miR-122 assessment after 5 days of treatment and 21 with a single measurement) and 18 non-COVID-19 participants included for comparison. Plasma miR-122 levels were measured using quantitative polymerase chain reaction, normalized to U6 small nuclear RNA, and expressed as log₁₀(2^-ΔCt). No associations were observed between miR-122 expression and remdesivir administered for standard treatment durations (3-5 days) or other COVID-19-specific therapies. However, a duration-dependent relationship with remdesivir cannot be excluded. Moreover, therapeutic paracetamol use prior to presentation was positively associated with miR-122 expression at follow-up and remained significant after adjustment. Additionally, bivariate analyses revealed inverse correlations between baseline miR-122 and inflammatory biomarkers, with multivariable analysis showing an independent positive association with lymphocyte count.

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide, yet only a fraction of smokers develops the disease, suggesting protective mechanisms in resilient individuals. Identifying airway-localized molecular signatures may improve our understanding of disease pathomechanisms and support hypothesis generation for biomarker research. In this pilot study, induced sputum from smokers with COPD (n = 28) and smokers without COPD (n = 16; Global Initiative for Chronic Obstructive Lung Disease (GOLD)-defined pre-COPD) was analyzed by untargeted proteomics, metabolomics, and lipidomics. After quality control, 1180 proteins, 187 metabolites, and 1234 lipids were retained. Analyses included univariate models with false discovery rate adjustment and multivariate analyses (PCA, PLS-DA), followed by pathway enrichment and protein interaction network analysis. While few features remained significant after FDR correction, consistent cross-omics patterns were observed. COPD was characterized by ↑ glutathione, creatine, and L-arginine; ↓ CCDC88A and ↑ STAT3 and SYDE2; and broad lipid remodeling involving phosphatidylcholines, sphingolipids, and eicosanoids. Network analysis highlighted STAT3 as a highly connected node linking COPD-related genes. These findings suggest that the multi-omic profiling of induced sputum can capture coherent airway-localized molecular signatures such as oxidative stress, cytoskeletal remodeling, and Rho-family GTPase signaling. However, the results should be interpreted as exploratory and require validation in functional studies.

Immunoglobulin G (IgG) is a central component of humoral immunity in coronavirus disease 2019 (COVID-19); however, increasing evidence suggests that infection-induced IgG repertoires exert immunomodulatory effects beyond classical antiviral functions. In this study, we investigated whether IgG from patients with moderate or severe COVID-19 directly modulates human peripheral γδ T cells and whether these effects are associated with disease severity-dependent IgG idiotype profiles. Purified IgG from non-exposed healthy controls, moderate COVID-19 patients, or severe COVID-19 patients was incubat-ed with peripheral blood mononuclear cells from healthy donors. γδ T cell phenotype, subset distribution, homing markers, and cytokine production were assessed by flow cytometry, while direct IgG-cell interactions were evaluated using fluorescent IgG binding assays. In parallel, proteomic profiling using human proteome microarrays was performed to identify γδ T cell-expressed protein targets recognized by COVID-19-induced IgG. IgG from SARS-CoV-2-infected individuals selectively reduced Vγ9⁺Vδ2⁺ γδ T cells, altered memory differentiation, downregulated CCR5, CCR6, and CD161 expression, and reshaped cytokine production in a severity-dependent manner. COVID-19 IgG bound directly to the γδ T cell membrane without inducing apoptosis, indicating a non-cytotoxic mechanism of modulation. Proteomic analysis revealed a marked expansion and diversification of γδ T cell-associated IgG targets in COVID-19, particularly in severe disease, with enrichment of pathways related to immune signaling and inflammation. Collectively, these findings identify γδ T cells as direct functional targets of SARS-CoV-2-induced IgG repertoires and demonstrate that disease severity shapes IgG idiotype networks with distinct immunomodulatory capacities. This work highlights a previously underappreciated antibody-mediated mechanism contributing to immune dysregulation in COVID-19.

Respiratory viral infections (RVIs) have been described traditionally as clinically important infectious complications in pediatric patients with immunosuppression, particularly in those with malignancies (hematological or solid) and recipients of hematopoietic cell or solid organ transplantation. Specifically, advances in the field of cancer therapy and novel immune-based pharmaceuticals have significantly expanded the population of children with prolonged and complex immunosuppression, whereas the widespread use and availability of molecular diagnostics have increased the detection of respiratory viruses. Additionally, these developments have improved the etiologic identification of RVIs, while introducing important challenges in clinical interpretation, mainly in differentiating incidental viral identification from clinically significant diseases. Furthermore, RVIs in immunocompromised children are characterized by heterogeneous and diverse clinical manifestations, with a range from mild upper respiratory tract involvement to severe lower respiratory tract disease, which can lead to substantial morbidity and mortality. Diagnostic strategies in this field are primarily based on nucleic acid amplification tests, requiring careful interpretation because of the possible prolonged viral shedding, co-detection, and overlapping infectious syndromes. Beyond direct clinical consequences, viral detection has an impact on infection control measures, antimicrobial stewardship decisions, and the timing of therapies. In this literature review, we offer an overview of current evidence on the epidemiology, clinical manifestations, diagnostic approaches, and management of RVIs in immunocompromised pediatric populations, underscoring the unmet need for structured, risk-adapted integration of virologic data into pediatric oncology care.

Intra-tracheal thyroid is a rare ectopic thyroid disease. Presenting symptoms can mimic those of airway obstruction such as bronchial asthma. We report the case of a male patient who presented with airway obstruction due to thyroid ectopia and was misdiagnosed initially with bronchial asthma. After a correct diagnosis of intratracheolaryneal thyroid, the case was managed by excision. Surgery is the mainstay of treatment for patients with clinical signs of airway obstruction. We present our experience of his one-month follow-up after resection. Currently, the patient is free of symptoms.

Coronavirus disease 2019 (COVID-19) has highlighted significant neurological complications in severe cases. Cerebrospinal fluid (CSF) proteomics could reveal biomarkers related to clinical outcome among critically ill patients.

We performed high-resolution proteomic analyses of CSF samples from 29 intensive care unit (ICU) patients with severe COVID-19 and 19 controls. Differentially expressed proteins and associated pathways were identified through bioinformatic and statistical analyses.

Proteomic analysis identified 488 significantly altered proteins between COVID-19 patients and controls. Proteins linked to coagulation, inflammation, and blood-brain barrier dysfunction (e.g., SERPINC1, KNG1, PLG) were elevated in patients who survived ICU admission. Conversely, proteins associated with metabolic disruption, cellular stress, and neuroinflammation (e.g., FABP3, PDIA4) were upregulated in non-survivors. Pathway enrichment analyses confirmed involvement of immune activation, inflammatory responses, and coagulation cascades.

CSF proteomics in severe COVID-19 patients reveals potential biomarkers predictive of patient outcomes. These findings support the involvement of systemic inflammation and blood-brain barrier disruption in COVID-19 pathophysiology, suggesting novel targets for personalized intervention strategies.

Chronic rhinosinusitis with nasal polyps (CRSwNP) comprises multiple molecular endotypes that only partly align with the clinical phenotype, which complicates target selection and interpretation of treatment effects. Human omics and biomarker studies define candidate pathways, but causal attribution of specific nodes to lesion formation and remodeling requires perturbable in vivo systems. Here, we present a "module-first" framework that links murine induction paradigms to epithelial-immune-stromal circuits and to a minimal, module-matched endpoint set for reproducible causal inference. We summarize commonly used CRSwNP-like protocols (allergen/protease ± SEB, aeroallergen + SEB, innate trigger-enriched paradigms, and modifier layers), emphasize operational pathology terminology ("polyp-like lesion" versus "true polyp"), and propose a uniform causal template for validated pathway modules (alarmins/IL-33-NF-κB, type 2/ILC2-eosinophil, IL-17A/neutrophil, Wnt/EMT remodeling, and JAK/STAT kinase convergence). Finally, we organize chemical and molecular interventions by leverage point and propose an ARRIVE-aligned Minimum Reporting Set to standardize model anchoring, target engagement, and cross-study comparability. This module-first roadmap is intended to accelerate mechanism-linked discovery and preclinical validation of tractable drug targets in CRSwNP. Importantly, this module-first roadmap is intended as a heuristic organizing principle rather than an exhaustive taxonomy, because pathway modules can overlap and shift dynamically across time and tissue compartments in vivo.