Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory lung condition and a leading cause of morbidity and mortality worldwide. Despite well-established links to smoking, emerging evidence highlights the involvement of complex immune and epigenetic mechanisms in its pathogenesis. This study aimed to investigate the expression, secretion, and promoter methylation status of key pro- and anti-inflammatory cytokines in peripheral blood mononuclear cells (PBMCs) of patients with mild and severe COPD, compared with healthy individuals. PBMCs were isolated from 90 participants divided into three groups: severe COPD, mild COPD, and healthy controls. Quantitative polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA), and methylation-specific PCR were employed to evaluate gene expression, protein secretion, and promoter methylation of inflammatory cytokines. Patients with COPD exhibited significant upregulation of pro-inflammatory cytokines (Interleukin1β (IL-1β), IL-6, IL-18, IFN-γ, and TNF-α) at both transcript and protein levels, with more pronounced alterations in the severe group. Conversely, anti-inflammatory mediators (IL-10 and TGF-β) were significantly downregulated. Promoter methylation analysis revealed hypomethylation in pro-inflammatory cytokine genes and hypermethylation in anti-inflammatory ones, correlating with disease severity. The findings demonstrate that COPD progression is associated with a shift toward a hyper-inflammatory, hypo-regulatory immune phenotype sustained by epigenetic modifications. These results support the potential for integrating cytokine-methylation signatures into clinical staging and for targeting epigenetic and immune pathways in future therapeutic strategies.

Exacerbations of chronic obstructive pulmonary disease (COPD) are a leading cause of morbidity, mortality, and healthcare burden. While standard bronchodilator therapy alleviates airway obstruction, its efficacy is often limited. This study evaluated nebulized furosemide, which has bronchodilatory and anti-inflammatory effects, as an adjunct to salbutamol-ipratropium in hospitalized COPD patients. Ninety‑two patients with exacerbated COPD were randomly assigned to two equal groups (46 each). The intervention group received nebulized salbutamol-ipratropium plus furosemide (20 mg), and the control group received salbutamol-ipratropium, both every 8 hours for 10 minutes over 5 consecutive days. Demographic and clinical variables, pulmonary function indices (FEV1, FVC, FEV1/FVC), clinical outcomes (COPD Assessment Test (CAT), Modified Medical Research Council (mMRC)scores, and quality of life by St. George's Respiratory Questionnaire (SGRQ)), arterial blood gases, and inflammatory biomarkers (TNF-α, IL-6, IL-8, CRP, ESR, neutrophil %, WBC) were measured before and after treatment. Demographic characteristics and baseline indices did not differ significantly between the groups. Dyspnea and respiratory symptoms (mMRC and CAT scores) decreased significantly, while quality of life, improved markedly in the intervention group compared to the control group. Pulmonary function also showed significant enhancement, with the FEV₁/FVC ratio increasing. Arterial blood gas analysis showed higher PaO₂ and lower PaCO₂ in the intervention group. IL-6 and IL-8 decreased significantly, and no adverse events were reported. Nebulized furosemide enhances standard therapy in COPD exacerbations, improving lung function, relieving symptoms, and reducing systemic inflammation. Its safety, accessibility, and low cost make it a promising adjunct treatment.

Obstructive sleep apnea (OSA) is increasingly recognized as a risk factor for cognitive impairment and dementia. We investigated stage- and frequency-specific associations between OSA severity and both conventional spectral measures and phase-lag index (PLI)-based functional connectivity.

We retrospectively analyzed polysomnography data from 50 patients (mean age 51.7 ± 14.3 years, 70% male) diagnosed with OSA or primary snoring. Six-channel EEG data were analyzed using conventional spectral power ratios (alpha+beta/theta+delta) and PLI-based functional connectivity across delta, theta, alpha, and beta bands. Pearson correlations assessed associations between apnea-hypopnea index (AHI) and EEG parameters across wakefulness, N2 sleep, and REM sleep.

Median AHI was 25.7 [IQR: 7.2-48.3]. Conventional spectral measures showed no significant AHI correlations in any sleep stage. PLI analysis revealed stage- and frequency-specific associations: during N2 sleep, AHI negatively correlated with delta-band PLI (r = -0.335, 95% CI -0.588 to -0.021, p = 0.037) and theta-band PLI (r = -0.326, 95% CI -0.582 to -0.012, p = 0.043). No significant associations were observed during wakefulness or REM sleep.

Functional connectivity analysis identified stage-specific associations with OSA severity that were not observed with conventional spectral measures, suggesting that PLI-based connectivity may provide complementary information on OSA-related neural network alterations.

Allergen immunotherapy (AIT) represents a cornerstone in managing IgE-mediated allergic diseases, such as allergic rhinitis and asthma. By administering controlled doses of allergens over time, AIT aims to readjust immune tolerance, thereby modifying allergic responses. However, clinical responses to AIT remain heterogeneous, with a subset of patients achieving only partial benefit. This heterogeneity underlines the need for novel adjunctive approaches to potentiate the immunomodulatory effects of AIT. In this context, vitamin D has gained considerable interest, given its well-established role in immune homeostasis and regulation, as well as its emerging relevance in modulating allergic disease. This structured narrative review aims to assess the potential role of vitamin D supplementation during AIT on clinical outcomes as well as the significance of endogenous vitamin D levels on AIT clinical efficacy. A total of 18 studies were reviewed, 13 evaluating the impact of vitamin D supplementation during AIT and 5 assessing the influence of endogenous vitamin D levels on AIT outcomes. Most supplementation studies reported clinical outcomes favoring the addition of vitamin D to AIT, but three found no additional benefit, and two reported a benefit only at an earlier time point, respectively in vitamin D-deficient patients. Of the five studies examining endogenous status, three reported that higher 25-hydroxyvitamin D (25(OH)D) levels were associated with better AIT outcomes. Other findings that were reported as secondary outcomes included favorable immunologic changes, such as IL-10 production, decreased allergen-specific IgE levels, and enhanced regulatory Treg-cell activity, without formal assessment of their contribution to clinical benefit. Nevertheless, findings remain inconsistent across studies due to heterogeneity in study design, supplementation regimens, and outcome measures. While the available evidence suggests that adequate vitamin D status or supplementation may be associated with better clinical responses to AIT, the current findings remain limited by heterogeneity in study design, supplementation regimens, outcome measures, and generally small sample sizes. Therefore, the evidence should be considered suggestive rather than conclusive. Although correction of vitamin D deficiency is appropriate on general clinical grounds, its specific use as an adjunct to improve AIT outcomes cannot yet be routinely recommended. Further adequately powered, standardized, placebo-controlled studies are needed to clarify its role and inform clinical recommendations.

This paper uses a network model to analyze the impact of the COVID-19 pandemic on global trade centers. Using import-export trade data from 12 major economies, we visually assess the shifts in global trade network positions before and after the pandemic. By constructing a balanced trade network for the years 2018, 2019, and 2020, we examine how the pandemic has affected the trade connections of key countries. Our study finds that China maintained positive growth and strengthened its trade ties with the United States, while other major economies experienced declines in their network positions. Subsequently, we apply Liang-Kleeman Information Flow to conduct a causal analysis of the past 30 years of gross domestic product and trade data between China and the United States, demonstrating how economic growth patterns influence changes in the global trade network. This combination of network analysis and causal inference provides robust support for our conclusions on the evolving structure of global trade centers.

Practice variation across physicians is commonly attributed to idiosyncratic tendencies. What factors contribute to physicians' practice variation in the disposition of children with asthma exacerbation? How do metrics demonstrating variation impact physicians and learners?

In this social constructivist qualitative study, we interviewed 11 Pediatric Emergency Medicine attendings, purposively sampling across a spectrum of acute asthma exacerbation admission rates. Participants reflected on their recent care of patients with asthma, how they assess patients, and how they determine disposition. They were shown a de-identified funnel plot demonstrating disposition rates across the physician group and reflected on the 1) quality of the metric and 2) impact on practice. We used reflexive thematic analysis to describe patterns across the data that addressed the study's research questions.

Participants cited factors at the patient, caregiver, clinical care team, clinical environment, and personal practice levels that might result in variation. Participants framed the ability to weigh these sometimes competing factors as a reflection of patient-centered care. But when presented with a group-level data display, participants were surprised by the variation, valued seeing how they practiced compared to peers, and sometimes expressed a willingness to alter their practices to be "nearer the mean."

Some variation in care may be driven by physician adaptive expertise, which is not fully captured through metric-driven nomothetic data. Though metrics are fundamental to understanding practice patterns, decontextualized aggregations of data may risk minimizing, or even framing as deviant, the expertise exercised by physicians when they weigh multiple factors in decision-making.

Tacrolimus has emerged as a promising therapeutic agent for connective tissue disease-associated interstitial lung disease (CTD-ILD) patients. However, its clinical application is substantially hindered by high interindividual pharmacokinetic variability and a narrow therapeutic window, which poses critical challenges particularly for the formulation of the initial dosage regimen.

A retrospective real-world study was conducted on 22 CTD-ILD patients receiving tacrolimus therapy. Comprehensive clinical data were systematically collected, encompassing demographic characteristics, routine physiological and biochemical parameters, and detailed concomitant medication records. A population pharmacokinetic (PPK) model for tacrolimus in CTD-ILD patients was developed using the nonlinear mixed-effects modeling approach implemented in NONMEM software. Monte Carlo simulation was subsequently performed to recommend the optimal initial dosage regimen of tacrolimus for CTD-ILD patients.

Based on the results of the model, we proposed initial dosing regimens: for CTD-ILD patients, the recommended initial tacrolimus dosage was 0.10 mg/kg across the body weight range of 50-100 kg, which yielded a target attainment probability of 89.1-93.5%, a probability below 5 ng/mL was 6.3-10.9%, a probability above 10 ng/mL was 0-0.2%.

This was an exploratory single-center PPK analysis recommending the initial dosage of tacrolimus for CTD-ILD patients. We proposed the 0.10 mg/kg regimen as a preliminary model-derived starting dose, which warranted prospective validation and therapeutic drug monitoring (TDM). Given the inherent limitations including the relatively small sample size, lack of external validation, further large-scale prospective studies were warranted to confirm these conclusions.

Stroke-associated pneumonia (SAP) constitutes a major complication following spontaneous intracerebral hemorrhage (sICH), posing a significant clinical challenge for accurate prediction. This study aimed to evaluate whether integrating the pan-immune-inflammation value (PIV) enhances the predictive performance of machine learning (ML) models for SAP and poor functional outcome.

A retrospective cohort of 371 sICH patients was analyzed. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO). Predictive models for SAP and poor outcome [modified Rankin Scale score (mRS) > 2 at 90 days] were developed and compared across nine ML algorithms. Model performance was assessed by discrimination (area under the receiver operating characteristic curve, AUC), calibration, and decision curve analysis (DCA). Interpretability was achieved via SHapley Additive exPlanations (SHAP).

Elevated PIV was independently associated with SAP [odds ratio (OR) 13.55, 95% confidence interval (CI) 4.14-44.39; p < 0.0001] and poor 90-day functional outcome (OR 25.27, 95% CI 7.75-82.34; p < 0.0001). Among the algorithms, extreme Gradient Boosting (XGBoost) and logistic regression (LR) demonstrated the highest predictive performance for poor outcome (AUC 0.912) and SAP (AUC 0.856), respectively. Incorporating PIV significantly improved discriminatory ability (XGBoost: 0.926-0.942; LR: 0.905-0.931; both p < 0.05). The models demonstrated good calibration, provided net clinical benefit on DCA, and were interpretable through SHAP analysis, which consistently identified PIV as a critical predictor.

The integration of PIV into interpretable ML models significantly improves the accuracy of predicting SAP and functional outcome after sICH. This strategy, combining a systemic inflammatory biomarker with explainable ML, holds promise for advancing personalized risk stratification in neurocritical care.

The COVID-19 pandemic substantially affected people who use drugs (PWUD) with comorbid psychiatric disorders. Lockdowns, shifts in drug markets, and fear of infection may have altered drug-use patterns. This prospective study examined changes in drug-use behaviors among PWUD with comorbid psychiatric disorders and identified factors associated with these changes across three distinct phases of the COVID-19 pandemic.

A cohort of adult PWUD with ICD-10-defined comorbid psychiatric disorders was followed longitudinally from March 2021 to January 2024. Drug-use behaviors were assessed at three time points: during the active COVID-19 pandemic period, after receipt of at least two doses of a World Health Organization (WHO)-endorsed COVID-19 vaccine, and after the WHO declared the end of the global pandemic. Structured interviews and standardized rating scales were used to assess demographic characteristics, ICD-10 comorbid psychiatric disorders, drug-use behaviors, DSM-5 substance use disorder severity, and psychological dependence. COVID-19 infection history and vaccination status were verified through centralized electronic health records. Within-person changes in drug-use behaviors across time points and factors associated with these changes were examined using mixed-effects models.

One hundred and thirty participants (mean age 40.03 years) completed the study. The majority (62.3%) had a comorbid substance-induced psychotic disorder. Overall, 27.7% had laboratory-confirmed COVID-19 infection during the study period. Across the three phases, participants demonstrated significant reductions in substance use disorder severity and drug-use frequency. Sharing of drug-use equipment also declined and remained lower after the pandemic. Greater worry about contracting COVID-19 was associated with increased avoidance of drug use with others and reduced sharing of drug-use equipment. Prior COVID-19 infection was associated with lower drug-use frequency. Among individual drugs, cough syrup was uniquely linked to more frequent use, less solitary use, and sustained reductions in equipment sharing.

Adult PWUD with comorbid psychiatric disorders demonstrated sustained improvements in drug-use behaviors throughout the COVID-19 pandemic and after its official conclusion. Both prior COVID-19 infection and greater worry about contracting COVID-19 were associated with these positive behavioral changes.

The evidence regarding montelukast‑associated neuropsychiatric adverse events in children with asthma is controversial and inconclusive. We sought to further examine the association between use of montelukast and the risk of neuropsychiatric events in children with asthma.

We conducted a pooled analysis of two birth cohorts: the AMerican PREGNANcy-Mother-Child CohorT (AM-PREGNANT) from the US, and the Quebec Pregnancy Cohort (QPC) from Canada. We included children aged 1 to < 18 years with the first incident diagnosis of asthma after birth and whose initial asthma controller therapy was either montelukast monotherapy or inhaled corticosteroids (ICS) monotherapy. The primary outcomes were sleep disorders and attention-deficit/hyperactivity disorder (ADHD), while secondary outcomes included mood disorders, anxiety disorders, and oppositional defiant and conduct disorders. We used Cox proportional hazards regressions, adjusting for potential confounders, to quantify the associations in each birth cohort independently. A random effects Meta-analysis was used to pool outcome-specific results if heterogeneity was acceptable.

In AM-PREGNANT, 85,322 asthmatic children were included, with 21,534 in the montelukast monotherapy group and 63,788 in the ICS monotherapy group. In QPC, 11,854 asthmatic children were included, with 373 in the montelukast monotherapy group and 11,481 in the ICS monotherapy group. Use of montelukast was significantly associated with increased risks of ADHD (pooled adjusted hazard ration [HR], 1.40; 95% confidence interval [CI], 1.19-1.66) and oppositional defiant and conduct disorders (adjusted HR, 1.43; 95% CI, 1.13-1.82) compared to ICS; however, AM-PREGNANT and QPC yielded inconsistent findings regarding sleep disorders. In the subgroup analyses, use of montelukast was significantly associated with an increased risk of sleep disorders in the controlled and partly controlled asthma subgroup and in children who had not used oral corticosteroids during follow-up time when compared to ICS. There were no significant between-group differences with regards to mood disorders or anxiety disorders.

Among children newly diagnosed with asthma, use of montelukast is associated with increased risks of ADHD and oppositional defiant and conduct disorders compared to ICS; among those with newly diagnosed controlled, partly controlled, or non-severe asthma, use of montelukast is associated with an increased risk of sleep disorders compared to ICS.