U.S. Veterans experience a high burden of COVID-19; characterizing immune responses associated with COVID-19 outcomes could help improve treatment. Changes in peripheral blood cytokines over time may predict both acute outcomes and long COVID symptoms.

Cytokine concentrations were quantified from peripheral blood collected 0-7 days (early) and 14-42 days (post-acute) after enrollment from SARS-CoV-2 positive participants in the EPIC³ study, a prospective, longitudinal cohort following U.S. Veterans. Responses were correlated with Veterans Affairs Severity Index for COVID-19 criteria and chronic symptoms with the modified Medical Research Council Dyspnea scale, Patient-Reported Outcomes Measurement Information System (PROMIS) Cognitive function, and PROMIS Fatigue scores 3 months after enrollment (60-135 days). Trends in cytokine concentration with COVID-19 severity were assessed. Odds of COVID-19 severity and long-term symptoms were estimated with logistic regression adjusted for sex, age, and morbidity. Longitudinal changes in cytokine concentration were examined for participants sampled during both time periods, by severity and long-term symptom group.

Early HGF, IL-18, IL-1RA, IP-10, and VEGF-A and post-acute MIP-1α and VEGF-A concentrations trended positively with increasing COVID-19 severity (q-values < 0.05, Jonckheere-Terpstra trend test). Increases in EGF, MIP-1β, and RANTES concentration and decreases in MIP-1α concentration over time were associated with mild rather than moderate or severe disease. Increases in MIP-1β and RANTES concentration and decreases in Eotaxin concentration over time were associated with the absence of long-term symptoms.

Worse COVID-19 severity by 30 days was associated with higher early and post-acute period cytokine concentrations. Participants with long-term symptoms did not see resolution of cytokine responses over time.

Hyperuricemia, a precursor to gout and a risk factor for various cardiometabolic and renal disorders, is influenced by a complex interplay of lifestyle, physiological, and environmental factors. This study aimed to investigate the independent and combined effects of a sedentary lifestyle and obstructive sleep apnea (OSA) on hyperuricemia.

We analyzed data from 14,808 participants aged 40-80 years in the Korea National Health and Nutrition Examination Survey (2019-2022). Sedentary lifestyle was defined based on daily sedentary time, categorized as ≤6 or >6 h/day. OSA risk was assessed using the STOP-Bang questionnaire (Snoring, Tiredness, Observed apnea, blood Pressure, Body mass index, Age, Neck circumference, Gender), classifying participants into high- and low-risk groups. Hyperuricemia was defined as serum uric acid levels ≥7.0 mg/dL in males and ≥6.0 mg/dL in females. Adjusted odds ratios (AORs) and 95% confidence intervals (CIs) were calculated using multiple logistic regression, and interaction effects were evaluated through relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI).

Sedentary time [AOR = 1.16 (95% CI: 1.04-1.29)] was independently associated with increased hyperuricemia risk. High OSA risk was associated with hyperuricemia in the partially adjusted model [AOR = 1.94 (95% CI: 1.71-2.19)], although this association was attenuated and no longer statistically significant after further adjustment for variables incorporated into the STOP-Bang questionnaire [AOR = 1.12 (95% CI: 0.98-1.28)]. A significant synergistic interaction was evident when both coexisted [RERI = 0.14 (95% CI: 0.08-0.19), AP = 0.17 (95% CI: 0.09-0.25), SI = 1.17 (95% CI: 1.01-1.37)].

These findings highlight the need for integrated screening and management strategies targeting sedentary lifestyles and OSA to mitigate hyperuricemia and its associated health burdens in at-risk populations.

Hyperglycemia has increasingly been recognized among individuals recovering from coronavirus disease 2019 (COVID-19); the host factors contributing to heterogeneous metabolic outcomes remain poorly understood. This cohort study investigated the association between innate immune genetic polymorphisms and hyperglycemia in post-COVID-19 patients. A total of 471 adults with previous mild-to-moderate COVID-19 were enrolled through the post-COVID follow-up program at Siriraj Hospital, Thailand, and classified as normoglycemic (HbA1c < 5.7%, n = 252) or hyperglycemic (HbA1c ≥ 5.7%, n = 219). Clinical characteristics, metabolic parameters, inflammatory biomarkers, and immunological measurements were collected during follow-up. Genotyping was performed using the Axiom Human Genotyping SARS-CoV-2 Research Array, focusing on candidate polymorphisms in innate immune-related genes. Associations between genetic variants and hyperglycemia were evaluated using multivariable logistic regression adjusted for age, body mass index, and underlying comorbidities. Participants with hyperglycemia were significantly older and had higher body mass index, greater prevalence of cardiometabolic comorbidities, elevated C-reactive protein levels, and higher LDL cholesterol compared with normoglycemic individuals. Significant associations were identified in NOS2 and CCL2. The NOS2 rs4795067 variant was associated with increased odds of hyperglycemia (adjusted OR = 1.770, 95% CI: 1.137-2.756, p = 0.011), whereas rs35051118 showed a protective effect (adjusted OR = 0.613, 95% CI: 0.386-0.975, p = 0.039). In CCL2, rs28730833 was strongly associated with hyperglycemia (adjusted OR = 2.977, 95% CI: 1.349-6.572, p = 0.007). These findings suggest that innate immune genetic variation may contribute to hyperglycemia in post-COVID-19 patients, although independent validation is required.

Acute respiratory failure (ARF) may develop in some patients with community-acquired pneumonia (CAP), resulting in a significantly increased mortality rate. Early identification of high-risk patients is essential for improving prognosis. This study aimed to investigate the predictive value of inflammatory and immune markers for acute respiratory failure in patients with community-acquired pneumonia.

This single-center retrospective cohort study included 334 patients with community-acquired pneumonia admitted at Zhuji Sixth People's Hospital, between January 2021 and December 2024. Patients were divided into a CAP-only (non-event) group and a CAP-ARF (event) group based on the development of acute respiratory failure. Inflammatory markers (white blood cell count, neutrophil count, tumor necrosis factor-α, etc.) and immune markers (complement components 3 and 4[C3andC4], immunoglobulins A and G [IgAand IgG], etc.) were collected within 24 hours of admission. Univariate and multivariate logistic regression analyses were performed to identify independent predictive factors, and the predictive performance of individual and combined indicators was evaluated using receiver operating characteristic (ROC) curves.

Multivariate analysis showed that elevated white blood cell count, neutrophil count, and tumor necrosis factor-α levels were independent risk factors for acute respiratory failure, while decreased levels of complement C3 and C4, and IgA and IgG, were independent protective factors. The combined predictive model incorporating these indicators demonstrated excellent predictive performance for acute respiratory failure, with an area under the curve (AUC) of 0.853.

In patients with community-acquired pneumonia, inflammatory and immune markers exhibit significant predictive value for the development of acute respiratory failure. A combined assessment of white blood cell count, neutrophil count, tumor necrosis factor-α, complement C3 and C4, and IgA and IgG may facilitate early identification of high-risk patients and inform clinical decision-making.

Patients with ischemic stroke are prone to developing respiratory tract infections, which can seriously affect prognosis. The objective of this study was to assess the association of the serum levels of interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and hypoxia-inducible factor-1 alpha (HIF-1α) with the occurrence of respiratory tract infection, and to determine whether these biomarkers are independently associated with infection risk.

A total of 140 patients with ischemic stroke admitted to The Fifth People's Hospital of Jinan between January 2024 and September 2025 were enrolled. Based on the presence or absence of respiratory tract infection, patients were divided into an infection group (n = 41) and a non-infection group (n = 99). Blood samples were collected within 24 hours after admission. Serum IL-6, TNF-α, and HIF-1α levels were measured using enzyme-linked immunosorbent assay (ELISA). Baseline characteristics were compared between the two groups. Point-biserial correlation and univariate logistic regression were used to assess the relationships between inflammatory markers (IL-6, TNF-α, HIF-1α) and respiratory tract infection, followed by multivariate logistic regression to identify independent influencing factors.

There were no significant differences between the two groups in terms of age, gender, body mass index, smoking and drinking history, hypertension, diabetes, coronary heart disease, hyperlipidemia, infarction site, National Institutes of Health Stroke Scale (NIHSS) score, Glasgow Coma Scale (GCS) score, mean respiratory rate, or mean oxygen saturation (p > 0.05). Serum levels of IL-6, TNF-α, and HIF-1α were significantly higher in the infection group than in the non-infection group (p < 0.001). Point-biserial correlation analysis revealed that IL-6, TNF-α, and HIF-1α were positively correlated with respiratory tract infection (r = 0.695, 0.738, and 0.655, respectively; p < 0.001). Univariate logistic regression indicated that all three biomarkers were influencing factors of respiratory tract infection (p < 0.001), and multivariate logistic regression confirmed them as independent influencing factors (p < 0.05).

Elevated serum levels of IL-6, TNF-α, and HIF-1α are significantly associated with respiratory tract infection in patients with ischemic stroke. However, this association does not imply a causal relationship, and the observed increases in these inflammatory markers may reflect a consequence of infection rather than independent risk factors. Early monitoring of these biomarkers may help identify patients with increased risk of developing infection and facilitate timely clinical assessment and intervention to improve outcomes.

Armed conflicts can deteriorate environmental conditions, including air quality, yet their short-term health implications remain underexplored. This study assessed the impact of the 2024 Beirut conflict on air pollution and associated respiratory and dermatological risks.

Satellite-derived air pollution concentrations for Beirut's Southern Suburbs were compared between the pre-war period (Aug. 1-Sep. 22, 2024) and the war period (Sep. 23-Nov. 29, 2024), using Mann-Whitney U and independent t-tests. Ground-level PM_2.5 was measured across 5 sites from October 25 to November 3, 2024. Relative risk (RR) and attributable risk percentage (AR%) for hospital admissions were estimated using exposure-response functions from the Beirut Air Pollution and Health Effects (BAPHE) study. WHO's AirQ+ tool was applied for the validation of respiratory outcomes.

Median PM_2.5 increased from 15.11 μg/m³ pre-war satellite period to 20.21 μg/m³ during the war. Ground-measured wartime median increased from 19.33 μg/m³ to 22.16 μg/m³ in the direct war zone (DWZ). Wartime respiratory admissions increased modestly (RR = 1.011, AR% = 1.13%) in DWZ, while skin disease admissions were higher in DWZ (RR = 1.032, AR% = 3.10%). AirQ+ estimates were aligned with BAPHE-based findings.

The 2024 Beirut conflict elevated air pollution, with measurable short-term health impacts, underscoring the need for environmental monitoring and preparedness during armed conflicts.

This study aimed to compare the clinical efficacy of high-dose versus conventional-dose methylprednisolone therapy and the prevalence of chronic lung disease (CLD) at the 6-month follow-up in Chinese children with severe Mycoplasma pneumoniae pneumonia (SMPP).

A retrospective cohort study was performed on 82 children with SMPP admitted from January 2018 to January 2024. Patients were categorized into high-dose and conventional-dose groups based on initial glucocorticoid dosage. Clinical data, laboratory tests, chest imaging, and bronchoscopy findings were reviewed to compare pulmonary conditions and therapeutic efficacy. The prevalence of CLD, oxygen saturation levels, and pulmonary function were assessed at the 6-month follow-up.

The main clinical features of SMPP included persistent high fever, cough, excessive inflammation (C-reactive protein, erythrocyte sedimentation rate, procalcitonin, interleukin-6, lactate dehydrogenase, serum ferritin, and D-Dimer), as well as severe pulmonary involvement, including consolidation, pleural effusion, and lung necrosis on computed tomography, and mucus plugging on bronchoscopy. Disease severity was comparable between groups, but the high-dose group exhibited a shorter fever duration (9.8 vs. 16.1 days), faster defervescence after corticosteroid treatment (1.0 vs. 7.0 days), and reduced hospitalization (13.4 vs. 18.4 days) (all p < 0.001). At the 6-month follow-up, the high-dose group had a significantly lower prevalence of CLD (28.2% vs. 85.4%) (p < 0.001), higher oxygen saturation levels (p = 0.033) and better pulmonary function (p < 0.001).

High-dose methylprednisolone therapy was more effective than conventional-dose treatment for SMPP patients. It was also associated with a lower prevalence of CLD, higher oxygen saturation levels, and better pulmonary function outcomes.

The respiratory epithelium is a dynamic immunopharmacological interface that transcends its traditional role as a passive barrier to become a central coordinator of pulmonary immunity. This review introduces and elaborates on the paradigm of the "Epithelial Immunopharmacological Rheostat," a conceptual framework that posits the epithelium as a dynamic, multidimensional signal processor that continuously calibrates the threshold of immune activation. Distinct from static models of barrier dysfunction or isolated alarmin biology, this rheostat operates through four hierarchically interacting axes: barrier integrity, alarmin/type 2, senescence/repair, and tolerogenic programming. We critically dissect how dysregulation of specific axes-alone or in combination-initiates and perpetuates the pathology of chronic respiratory diseases, including asthma, COPD, and idiopathic pulmonary fibrosis. A rigorous, pharmacology-centric analysis deconstructs the molecular circuitry of epithelial-immune crosstalk, evaluating the druggability of targets from tight junction complexes and pattern recognition receptors to the alarmin (TSLP, IL-33, IL-25) signaling cascades and their downstream JAK-STAT, NF-κB, and MAPK effectors. Beyond cataloguing mechanisms, this review provides a comparative and critical appraisal of emerging therapeutic strategies, including alarmin-targeted biologics, barrier-restorative agents (e.g., postbiotics, short-chain fatty acids), kinase inhibitors, senotherapeutics, and frontier cell-based therapies. A dedicated synthesis addresses pivotal pharmacokinetic hurdles, biomarker-driven stratification, and the imperative of precision endotyping. Finally, we forecast how advanced human organoid models are catalyzing the shift toward personalized interventions designed to reset the defective rheostat. This comprehensive synthesis maps the intricate landscape of epithelial immunopharmacology and identifies critical barriers that must be overcome to translate these insights into transformative clinical outcomes.

The acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is characterized by systemic inflammatory response and neuroimmune dysregulation. The dynamic changes of certain key neuroimmune biomarkers during the course of AECOPD and their impact on long-term patient outcomes have not been thoroughly studied.

This study aims to develop a bedside clinical decision tree based on neuroimmune biomarker dynamics to stratify post-AECOPD patient risk and guide personalized discharge planning.

This prospective observational study included 273 patients hospitalized due to AECOPD. Serum levels of brain-derived neurotrophic factor (BDNF), programmed cell death protein 1 (PD-1), matrix metalloproteinase-9 (MMP-9), and inflammatory cytokines (IL-1β, IL-6, IL-10, and TNF-α) were measured within 24 h of admission (T1) and within 48 h after clinical stability at discharge (T2). Unsupervised clustering analysis was performed based on the dynamic changes in biomarkers, and multivariable logistic regression was used to assess their association with 90-day clinical outcomes (acute exacerbation, readmission). Additionally, a biomarker-based decision tree model was developed, and its performance was compared with traditional clinical assessment methods.

Three distinct biomarker response patterns were identified: "Coordinated Improvement " (60.0%), "Inflammatory Rebound" (27.8%), and "Poor Neuro-repair" (12.1%). Among them, the "Poor Neuro-repair" phenotype was the strongest independent predictor of acute exacerbation events at 90 days (adjusted OR 3.42, 95% CI 1.78-6.57, p < 0.001). The dynamic change in BDNF (ΔBDNF) showed predictive value for acute exacerbation events (AUC 0.84). The biomarker-based decision tree model classified patients into four risk levels, with significant differences in the 30-day event incidence (ranging from 3.6% to 68.4%). Its predictive accuracy (AUC 0.87) was markedly superior to that of clinical judgment (AUC 0.74) and the GOLD standard (AUC 0.68).

The biomarker response patterns after acute exacerbation, particularly the "Poor Neuro-repair" phenotype and its dynamic changes in BDNF, are closely associated with short-term clinical outcomes. The decision tree model developed based on this information provides a preliminary approach for risk stratification and discharge planning in AECOPD patients, demonstrating superior efficacy compared to traditional clinical assessment methods.

Stapled bullectomy is a safe procedure for primary spontaneous pneumothorax (PSP). Early infection-driven staple-line failure with metalloptysis after bullectomy for PSP is rare. A 21-year-old man underwent video-assisted thoracoscopic bullectomy for persistent right PSP. The staple lines were reinforced with polyglycolic acid sheets. The early postoperative course was uneventful, but the patient developed fever, cough, and purulent sputum on postoperative day 21. Computed tomography demonstrated fluid-filled cavitary lesions along the staple lines in the right upper and lower lobes, with partial staple-line disruption. Sputum cultures yielded oral commensals, and an acute lung abscess associated with staple-line failure was diagnosed. Antibiotic therapy was initiated, and he expectorated several surgical staples. The abscess resolved with conservative treatment. This case suggests that acute infection along pulmonary staple lines can lead to staple-line failure and metalloptysis even after routine bullectomy. Persistent postoperative fever or purulent sputum should prompt careful evaluation for staple-line-associated infection.