BackgroundDue to the complex interplay among different urban-related exposures, a comprehensive approach is advisable to estimate the health effects. We simultaneously assessed the effect of “green”, “grey” and air pollution exposure on respiratory/allergic conditions and general symptoms in schoolchildren.MethodsThis study involved 219 schoolchildren (8–10 years) of the Municipality of Palermo, Italy. Data were collected through questionnaires self-administered by parents and children. Exposures to greenness and greyness at the home addresses were measured using the normalized difference vegetation index (NDVI), residential surrounding greyness (RSG) and the CORINE land-cover classes (CLC). RSG was defined as the percentage of buffer covered by either industrial, commercial and transport units, or dump and construction sites, or urban fabric related features. Two specific categories of CLC, namely “discontinuous urban fabric - DUF” - and “continuous urban fabric - CUF” - areas were found. Exposure to traffic-related nitrogen dioxide (NO2) was assessed using a Land-Use Regression model. A symptom score ranging from 0 to 22 was built by summing affirmative answers to twenty-two questions on symptoms. To avoid multicollinearity, multiple Logistic and Poisson ridge regression models were applied to assess the relationships between environmental factors and self-reported symptoms.ResultsA very low exposure to NDVI ≤0.15 (1st quartile) had a higher odds of nasal symptoms (OR = 1.47, 95% CI [1.07–2.03]). Children living in CUF areas had higher odds of ocular symptoms (OR = 1.49, 95% CI [1.10–2.03]) and general symptoms (OR = 1.18, 95% CI [1.00–1.48]) than children living in DUF areas. Children living in proximity (≤200 m) to High Traffic Roads (HTRs) had increased odds of ocular (OR = 1.68, 95% CI [1.31–2.17]) and nasal symptoms (OR = 1.49, 95% CI [1.12–1.98]). A very high exposure to NO2 ≥ 60 μg/m3 (4th quartile) was associated with a higher odds of general symptoms (OR = 1.28, 95% CI [1.10–1.48]). No associations were found with RGS. A Poisson ridge regression model on the symptom score showed that children living in proximity to HTRs (≤200 m) had a higher symptoms score (RR = 1.09, 95% CI [1.02–1.17]) than children living > 200 m from HTRs. Children living in CUF areas had a higher symptoms score (RR = 1.11, 95% CI [1.03–1.19]) than children living in DUF areas.ConclusionsMultiple exposures related to greenness, greyness (measured by CORINE) and air pollution within the urban environment are associated with respiratory/allergic and general symptoms in schoolchildren. No associations were found when considering the individual exposure to greyness measured using the RSG indicator.Electronic supplementary materialThe online version of this article (10.1186/s12940-018-0430-x) contains supplementary material, which is available to authorized users.

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Background: Saline nasal irrigation is labelled as an add-on treatment in patients with allergic rhinitis (AR). The primary aim of this study was to compare the efficacy of 21-day use of buffered hypertonic saline (BHS) versus normal saline solution (NSS) on reducing nasal symptoms in children with seasonal AR (SAR). Comparing their efficacy on nasal cytology counts (NCC), quality of life, and sleep quality was the secondary aim. Methods: In this 21-day,open-label, randomized controlled study, 36 SAR children (aged 6-13 years) with a Total 5 Symptom Score (T5SS) ≥5 received twice-daily BHS or NSS delivered through a nasal douche. Efficacy measures were least square mean changes (LSmc) in T5SS, NCC, Paediatric Rhinoconjunctivitis Quality of Life Questionnaire (PRQLQ), and Pittsburgh Sleep Quality Index (PSQI) scores. Results: BHS improved the T5SS total score to a greater extent than NSS (LSmc -6.45 vs. -5.45, p < 0.001). Concerning NCC, BHS significantly reduced the scores of neutrophils (LSmc -0.76, p = 0.004) and eosinophils (LSmc -0.46, p = 0.018), while NSS did not. Similarly, only BHS yielded a significant improvement in the PRQLQ score (LSmc -0.57, p = 0.009), whereas the improvement in PSQI score was comparable between the BHS (LSmc -0.77, p = 0.025) and NSS (LSmc -1.39, p < 0.001) groups. Overall, BHS was well tolerated. Conclusions: In children with SAR, BHS is effective in improving nasal symptoms and NCC, with an associated beneficial effect on quality of life.

Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decision support, care delivery, and chronic care management have been identified within the healthcare areas that could benefit from introducing AI. In pediatric allergy research, the recent developments in AI approach provided new perspectives for characterizing the heterogeneity of allergic diseases among patients. Moreover, the increasing use of electronic health records and personal healthcare records highlighted the relevance of AI in improving data quality and processing and setting-up advanced algorithms to interpret the data. This review aimed to summarize current knowledge about AI and discuss its impact on the diagnostic framework of pediatric allergic diseases such as eczema, food allergy, and respiratory allergy, along with the future opportunities that AI research can offer in this medical area.

Exposure of the airways epithelium to environmental insults, including cigarette smoke, results in increased oxidative stress due to unbalance between oxidants and antioxidants in favor of oxidants. Oxidative stress is a feature of inflammation and promotes the progression of chronic lung diseases, including Chronic Obstructive Pulmonary Disease (COPD). Increased oxidative stress leads to exhaustion of antioxidant defenses, alterations in autophagy/mitophagy and cell survival regulatory mechanisms, thus promoting cell senescence. All these events are amplified by the increase of inflammation driven by oxidative stress. Several models of bronchial epithelial cells are used to study the molecular mechanisms and the cellular functions altered by cigarette smoke extract (CSE) exposure, and to test the efficacy of molecules with antioxidant properties. This review offers a comprehensive synthesis of human in-vitro and ex-vivo studies published from 2011 to 2021 describing the molecular and cellular mechanisms evoked by CSE exposure in bronchial epithelial cells, the most used experimental models and the mechanisms of action of cellular antioxidants systems as well as natural and synthetic antioxidant compounds.

Mothers’ knowledge about childhood asthma influences management practices and disease control, but validating knowledge/practice questionnaires is difficult due to the lack of a gold standard. We hypothesized that Latent Class Analysis (LCA) could help identify underlying mother profiles with similar knowledge/practices. A total of 438 mothers of asthmatic children answered a knowledge/practice questionnaire. Using answers to the knowledge/practice questionnaire as manifest variables, LCA identified two classes: Class 1, “poor knowledge” (33%); Class 2, “good knowledge” (67%). Classification accuracy was 0.96. Mothers in Class 2 were more likely to be aware of asthma-worsening factors and indicators of attacks. Mothers in Class 1 were more likely to prevent exposure to tobacco smoke (91.1% vs. 78.8%, p = 0.005). For attacks, mothers in Class 2 were more likely to go to the emergency department and follow the asthma action plan. Mothers in Class 2 more frequently had a high education level (79.5% vs. 65.2%, p = 0.004). Children in Class 2 more frequently had fully controlled asthma (36.7% vs. 25.9%, p = 0.015) and hospitalizations for attacks in the previous 12 months (24.2% vs. 10.7%, p = 0.003). LCA can help discover underlying mother profiles and plan targeted educational interventions.

GLI 2012 references underestimate FEV/FVC predicted values in a sample of normal South Italian children. Physicians interpreting spirometry should be aware to test reference values prior to their use in a local area.

E-noses provide potential non-invasive metabolic biomarkers for diagnosing and monitoring pulmonary diseases. The primary aim of the present study was to assess the within-day and between-day repeatability of a modern breath sampling system (Pneumopipe® plus an array of e-nose sensors) in asthmatic and healthy children. The secondary aim was to compare the repeatability of the breath sampling system, spirometry and exhaled nitric oxide (eNO). Fifteen children (age 6–11 years) with asthma and thirty healthy children matched by age and gender (1:2 allocation) were recruited; of them, three healthy children did not complete the study. All measurements were collected twice during the baseline visit, 30 min apart, and once during the final visit, after 7 d. Repeatability was assessed through the intra-cluster correlation coefficient (ICC), and a significance test was performed to detect an at least ‘fair’ repeatability (ICC > 0.2). In asthmatic children, the within-day (0–30 min) ICCs for e-nose sensors (8 sensors × 4 desorption temperatures) ranged from 0.24 to 0.84 (median 0.57, IQR 0.47-0.71), while the between-day (0–7 d) ICCs ranged from 0.25 to 0.83 (median 0.66, IQR 0.55-0.72). In healthy children, the within-day ICCs for e-nose sensors ranged from 0.29 to 0.85 (median 0.58, IQR 0.49-0.63), while the between-day ICCs ranged from 0.33 to 0.82 (median 0.55, IQR 0.49-0.63). In both groups, most of the within-day and between-day ICCs for e-nose sensors were statistically significant. Moreover, the within-day and between-day ICCs for all spirometry parameters and eNO were significant and similar to those of the most reliable sensors. The modern breath sampling system showed more than acceptable within-day and between-day repeatability, in both asthmatic and healthy children. The present study was registered on the central registration system ClinicalTrials.gov (ID: NCT03025061).