Objective To explore the effect of calcitonin gene-related peptide (CGRP) on expressions of aquaporin (AQP)1 and AQP 5 in young rats with acute lung injury (ALI) caused by lipopolysaccharide (LPS).Methods Eighty-four young rats were randomly divided into control group,ALI model group and CGRP group.The rats in ALI model group were given intraperitoneal injection of LPS (5 mg/kg)for 2,6,12,24 hours;while the rats in CGRP group were given intraperitoneal CGRP (1 mg/kg) after 1 h injection of LPS.At 2 h,6 h,12 h and 24 h,all rats were sacrificed and lung tissues were obtained.The histopathological changes in lung tissues were evaluated by adopting hematoxylin-eosin staining,and wet/dry(W/D) was measured.The mRNA and protein levels of AQP1 and AQP5 in lung tissues were detected by adopting fluorogenic quantitative PCR (qPCR) and Western blot.Results Pathological stain showed that rats in control group had a normal lung tissue structure,and LPS made lung tissue edema,narrowing the alveolar cavity and inflammatory cell infiltration.CGRP attenuated the effect of LPS on rat's lung.The W/D ratio of lung tissue was significantly higher than that in the control group,and CGRP reduced the W/D ratio of lung tissue.qPCR showed that the mRNA levels of AQP1 and AQP5 from rats in ALI group (0.009 ±0.001 and 0.055 ±0.006)decreased compared with those in the control group (0.035±0.002 and 0.167 ±0.006) and CGRP group (0.024 ± 0.002 and 0.134 ± 0.012) (all P ＜ 0.001).Western blot results showed after 24 h injection of LPS,both AQP1 and AQP5 levels from ALI group (0.397 ± 0.041 and 0.215 ± 0.029) were significantly lower than those in the control group (0.850 ± 0.020 and 0.741 ± 0.032) (all P ＜ 0.001),and their levels in CGRP group (0.593-± 0.065 and 0.461 ± 0.039) were also lower than those in the control group,but higher than those in ALI group (all P ＜ 0.001).Conclusion CGRP can enhance AQP1 and AQP5 levels and reduce pulmonary edema,and it has a protective effect on rats with acute lung injury.

Objective:To investigate the value of bronchoalveolar lavage fluid (BALF) genechip analysis for the identification of pathogens in children with refractory pneumonia.Methods:A retrospective study of 500 children clinically diagnosed with refractory pneumonia in the Department of Respiratory and Critical Care Medicine, Kunming Children′s Hospital, Kunming Medical University between January 2020 to January 2022 was made.During hospitalization, bronchoscopic examination and bronchoalveolar lavage were performed.BALF was collected and analyzed using genechip technology to detect potential pathogens.At the same time, bacterial culture tests of sputum and BALF samples from the patients were performed. χ2 test was used to compare the positive rates of pathogens detected by different detection methods. Results:Of the 500 children patients, 482 cases (96.4%) were positive of BALF genechip analysis for pathogen identification.There were 71 cases (14.7%) infected with a single pathogen, and 411 cases (85.3%) with 2 or more pathogens.The top 3 bacteria were Streptococcus pneumoniae [117 cases (8.3%)], Haemophilus influenzae [63 cases (4.5%)], and Bordetella pertussis [32 cases (2.3%)]. The patients were mostly infected with respiratory syncytial virus [269 cases (19.1%)], followed by parainfluenza virus [217 cases (15.4%)], and adenovirus [132 cases (9.3%)]. Among the 500 patients, 116 cases (23.2%) were positive of BALF genechip analysis for bacteria identification, 47 cases (9.4%) had a positive BALF culture, 43 cases (8.6%) had a positive sputum culture.The bacterial detection rate of BALF genechip analysis was statistically significantly higher than that of BALF culture and sputum culture tests ( χ2=34.90, 39.85; all P<0.001). Conclusions:Most patients with refractory pneumonia have mixed infections.The genechip technology can rapidly and efficiently identify the pathogens, thus providing clinical guidance for anti-infection treatment.

Objective:To compare the epidemiological and clinical characteristics of hospitalized children with respiratory syncytial virus (RSV) infection in Kunming among the pre-and post-COVID-19 era, and to establish a prediction model for severe RSV infection in children during the post-COVID-19 period.Methods:This was a retrospective study. Clinical and laboratory data were collected from 959 children hospitalized with RSV infection in the Department of Pulmonary and Critical Care Medicine at Kunming Children′s Hospital during January to December 2019 and January to December 2023. Patients admitted in 2019 were defined as the pre-COVID-19 group, while those admitted in 2023 were classified as the post-COVID-19 group. Epidemiological and clinical characteristics were compared between the two groups. Subsequently, comparison of the clinical severity among the two groups was performed based on propensity score matching (PSM). Furthermore, the subjects in the post-COVID-19 group were divided into severe and non-severe groups based on clinical severity. Chi-square test and Mann-Whitney U test were used for pairwise comparison between groups, and multivariate Logistic regression was applied for the identification of independent risk factors and construction of the prediction model. The receiver operating characteristic (ROC) curve and calibration curve were employed to evaluate the predictive performance of this model. Results:Among the 959 children hospitalized with RSV infection, there were 555 males and 404 females, with an onset age of 15.4 (7.3, 28.5) months. Of which, there were 331 cases in the pre-COVID-19 group and 628 cases in the post-COVID-19 group. The peak period of RSV hospitalization in the post-COVID-19 group were from May to October 2023, and the monthly number of inpatients for each of these months were as follows: 72 cases (11.5%), 98 cases (15.6%), 128 cases (20.4%), 101 cases (16.1%), 65 cases (10.4%), and 61 cases (9.7%), respectively. After PSM for general data, 267 cases were matched in each group. The proportion of wheezing in the post-COVID-19 group was lower than that in the pre-COVID-19 group (109 cases (40.8%) vs. 161 cases (60.3%), χ2=20.26, P<0.001), while the incidences of fever, tachypnea, seizures, severe case, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein and interleukin-6 levels were all higher than those in the pre-COVID-19 group (146 cases (54.7%) vs. 119 cases (44.6%), 117 cases (43.8%) vs. 89 cases (33.3%), 37 cases (13.9%) vs. 14 cases (5.2%), 69 cases (25.8%) vs. 45 cases (16.9%), 3.6 (1.9, 6.4) vs. 2.3 (1.8, 4.6), 9.9 (7.1, 15.2) vs. 7.8 (4.5, 13.9) mg/L, 20.5 (15.7, 30.4) vs. 17.2 (11.0, 26.9) ng/L, χ2=5.46, 6.36, 11.47, 6.42, Z=4.13, 3.06, 2.96, all P<0.05). There were 252 cases and 107 cases with co-infection in the post-and pre-COVID-19 groups, respectively. The proportion of triple and quadruple infection in the post-COVID-19 group was higher than that in the pre-COVID-19 group (59 cases (23.4%) vs. 13 cases (12.1%), 30 cases (11.9%) vs. 5 cases (4.7%), χ2=5.94, 4.46, both P<0.05). Among the 252 cases with co-infection in post-COVID-19 group, the most prevalent pathogens involving in co-infections, in order, were Mycoplasma pneumoniae 56 cases (22.2%), Influenza A virus 53 cases (21.0%), Rhinovirus 48 cases (19.0%), Parainfluenza virus 35 cases (13.9%), and Adenovirus 28 cases (11.1%).The result of multivariate Logistic regression showed that age ( OR=0.70, 95% CI 0.62-0.78, P<0.001), underlying diseases ( OR=10.03, 95% CI 4.10-24.55, P<0.001), premature birth ( OR=6.78, 95% CI 3.53-13.04, P<0.001), NLR ( OR=1.85, 95% CI 1.09-3.15, P=0.023), and co-infection ( OR=1.28, 95% CI 1.18-1.38, P<0.001) were independently associated with the development of severe RSV infection in the post-COVID-19 group. The ROC curve of the prediction model integrating the above five factors indicated an area under the curve of 0.85 (95% CI 0.80-0.89, P<0.001), with an optimal cutoff of 0.21, a sensitivity of 0.83 and a specificity of 0.80. The calibration curve showed that the predicted probability in this model did not differ significantly from the actual probability ( P=0.319). Conclusions:In the post-COVID-19 era in Kunming, the peak in pediatric hospitalizations for RSV infection was from May to October, with declined incidence of wheezing and increased incidence of fever, tachypnea, seizures, severe cases, and rates of triple and quadruple co-infections. Age, underlying diseases, premature birth, NLR, and co-infection were identified as independent risk factors for severe RSV infection in the post-COVID-19 period. In this study, a risk prediction model for severe pediatric RSV infection was established, which had a good predictive performance.