Objective:To quantify thoracic and abdominal movements during breathing using inertial measurement units (IMUs) and to build a machine learning model which identifies the abdominal breathing (AB) pattern.Methods:Ten rehabilitation therapists formed the study′s professional group, while 15 patients receiving AB training comprised the validation group. Two synchronized IMUs were applied to capture breathing motions during natural breathing (NB), deep breathing (DB) and AB. Six kinematic features were extracted from each respiratory cycle, and inter-group and inter-pattern differences were analyzed. Correlation analysis was also performed with manually measured changes in thoracic and abdominal circumferences. A support vector classification model for AB pattern detection was then developed using data from the professional and validation groups.Results:A total of 1113 respiratory cycles were extracted and analyzed. The breathing pattern significantly influenced all of the kinematic features studied (0.21≤partial η 2≤0.65, all P≤0.001). The ranges of the angles in medial-lateral axis of the IMUs showed strong correlation with the changes in abdominal and thoracic circumferences (ρ1=0.928, ρ2=0.807, P≤0.001 in both cases). A greater range of abdominal angles was found during AB compared to the other patterns. The best of the models achieved an F1 score of 0.970 (sensitivity: 0.983, specificity: 0.980) in validation. Conclusions:AB generates the greatest abdominal movement. Combining IMUs and machine learning can provide real-time quantification of chest movement and accurate detection of AB during breathing training.

Objective:To quantify thoracic and abdominal movements during breathing using inertial measurement units (IMUs) and to build a machine learning model which identifies the abdominal breathing (AB) pattern.Methods:Ten rehabilitation therapists formed the study′s professional group, while 15 patients receiving AB training comprised the validation group. Two synchronized IMUs were applied to capture breathing motions during natural breathing (NB), deep breathing (DB) and AB. Six kinematic features were extracted from each respiratory cycle, and inter-group and inter-pattern differences were analyzed. Correlation analysis was also performed with manually measured changes in thoracic and abdominal circumferences. A support vector classification model for AB pattern detection was then developed using data from the professional and validation groups.Results:A total of 1113 respiratory cycles were extracted and analyzed. The breathing pattern significantly influenced all of the kinematic features studied (0.21≤partial η 2≤0.65, all P≤0.001). The ranges of the angles in medial-lateral axis of the IMUs showed strong correlation with the changes in abdominal and thoracic circumferences (ρ1=0.928, ρ2=0.807, P≤0.001 in both cases). A greater range of abdominal angles was found during AB compared to the other patterns. The best of the models achieved an F1 score of 0.970 (sensitivity: 0.983, specificity: 0.980) in validation. Conclusions:AB generates the greatest abdominal movement. Combining IMUs and machine learning can provide real-time quantification of chest movement and accurate detection of AB during breathing training.

The interaction of gut microbiota and its metabolites with the host not only plays an important role in maintaining gut homeostasis and host health, but also is a key link in responding to pathogen infections. A thorough understanding of the changes in gut microbiota and its metabolites during infection, as well as their role and mechanism in host defense against infection, is helpful to guide anti-infection treatment. This review focuses on the role of gut microbiota and their metabolites in host defense against bacterial, fungal, and viral infections, and reveals that they can exert anti-infection effects through resistance mechanisms (inducing antimicrobial substances, training immunity, inhibiting pathogen respiration, directly neutralizing pathogens, immune regulation) and tolerance mechanisms (altering energy metabolism patterns of microbiota, cell proliferation and tissue damage repair, maintaining physiological signal transduction in extraintestinal organs, inflammation regulation, maintaining the integrity of the intestinal barrier), and also summarizes measures to regulate gut microbiota against pathogen infections, in order to provide more ideas for novel anti-infection prevention and treatment strategies targeting gut microbiota and its metabolites.

Objective:To explore the microbiological and disease distribution characteristics of multidrug-resistant bacteria in patients hospitalized in a critical care rehabilitation ward, and to analyze the risk factors leading to multidrug-resistant bacterial infections.Methods:Microbiology screening data describing 679 patients admitted to a critical care rehabilitation ward were retrospectively analyzed to divide the subjects into a multidrug-resistant group (positive for multidrug-resistant bacterial infections, n=166) and a non-multidrug-resistant group (negative for multidrug-resistant bacterial infections, n=513). The risk factors were then analyzed using logistic regression. Results:Among 369 strains of multidrug-resistant bacteria observed, 329 were gram-negative bacteria (89.2%), mainly Pseudomonas aeruginosa, Klebsiella pneumoniae and Escherichia coli. They were distributed in sputum (56.9%) and mid-epidemic urine (28.2%) specimens. Patients whose primary disease was hemorrhagic or ischemic cerebrovascular disease accounted for 40.96% and 23.49% of the multidrug-resistant bacterial infections, respectively. Logistic regression analysis showed that albumin level, dependence on mechanical ventilation, central venous cannulation, or an indwelling urinary catheter or cystostomy tube were significant independent predictors of such infections.Conclusion:The multidrug-resistant bacterial infections of patients admitted to the critically ill rehabilitation unit are mainly caused by gram-negative bacteria. Their occurrence is closely related to low albumin levels and mechanical ventilation, as well as to bearing an indwelling central venous catheter, a urinary catheter or a cystostomy catheter.

Humans ; Asthma/drug therapy* ; Biological Therapy

Pulmonary blast injury has become the main type of trauma in modern warfare, characterized by externally mild injuries but internally severe injuries, rapid disease progression, and a high rate of early death. The injury is complicated in clinical practice, often with multiple and compound injuries. Currently, there is a lack of effective protective materials, accurate injury detection instrument and portable monitoring and transportation equipment, standardized clinical treatment guidelines in various medical centers, and evidence-based guidelines at home and abroad, resulting in a high mortality in clinlcal practice. Therefore, the Trauma Branch of Chinese Medical Association and the Editorial Committee of Chinese Journal of Trauma organized military and civilian experts in related fields such as thoracic surgery and traumatic surgery to jointly develop the Clinical treatment guideline for pulmonary blast injury ( version 2023) by combining evidence for effectiveness and clinical first-line treatment experience. This guideline provided 16 recommended opinions surrounding definition, characteristics, pre-hospital diagnosis and treatment, and in-hospital treatment of pulmonary blast injury, hoping to provide a basis for the clinical treatment in hospitals at different levels.

Objective: To explore the association between Vitamin A, E and mycoplasma pneumoniae pneumonia in children. Methods: 153 children with mycoplasma pneumoniae pneumonia and 653 health children were selected as cases and controls, respectively. Propensity score matching (PSM) analysis were conducted to reducing confounding bias between groups. Blood samples were collected to test serum levels of vitamin A and E using high performance liquid chromatography (HPLC). Logistic regression was implemented to determine odds ratios (OR) and 95% confidence intervals (CI) for evaluating the association of mycoplasma pneumoniae pneumonia with the serum levels of Vitamin A and E. Results: After propensity score matching, the study cohort included 153 cases with mycoplasma pneumoniae pneumonia and 306 health children as controls. Before matching, with age and gender adjusted, logistic regression analysis indicated that higher serum levels of Vitamin A and E led to a lower risk of mycoplasma pneumoniae pneumonia (OR=0.075, 95% CI: 0.007-0.815; OR=0.854, 95% CI: 0.792-0.986). After matching, higher serum level of Vitamin E had a significantly lower risk of mycoplasma pneumoniae pneumonia (OR=0.877, 95% CI: 0.810-0.950). Conclusions The serum levels of Vitamin A didn't have a statistically significant association with mycoplasma pneumoniae pneumonia. However, we observed an obvious association between Vitamin E and mycoplasma pneumoniae pneumonia. Hence Vitamin E clinical monitoring and supplementation are vital for preventing and treating mycoplasma pneumoniae pneumonia.

Objective:To investigate the difference of vitamin A and E levels in children with different respiratory diseases at different ages.Methods:A total of 671 children in Hunan Children's Hospital from July 2017 to October 2019 were selected as the disease group, including 197 cases of pneumonia, 152 cases of recurrent respiratory tract infection, 91 cases of asthma, 88 cases of cough variant asthma and 143 cases of Mycoplasma pneumoniae pneumonia; At the same time, 245 healthy children were selected as the normal group. The serum vitamin A and vitamin E levels of the two groups were detected by high performance liquid chromatography (HPLC).Results:⑴ The vitamin A level [(0.31±0.09)mg/L] of the disease group was lower than the normal group [(0.35±0.25)mg/L], and the vitamin E level [(8.92±2.57)mg/L] was lower than the normal group [(9.62±2.79)mg/L], with statistically significant difference ( P<0.05); ⑵ The level of vitamin A in the disease group at the age of >1-3 years [(0.32±0.09)mg/L] was lower than that in the normal group of the same age group [(0.35±0.08)mg/L]; the level of vitamin A in the disease group at the age of >3-6 years old [(0.30±0.08)mg/L] was lower than that of the same age group [(0.32±0.07)mg/L], with statistically significant difference ( P<0.05); ⑶ The vitamin E level of the disease group at >1-3 years old [(9.23±2.56)mg/L], >3-6 [(8.02±1.86)mg/L] and >6-14 years old [(8.02±1.82)mg/L] were lower than that of the same age normal group [(9.76±2.81)mg/L, (9.67±2.87)mg/L, (9.19±2.58)mg/L], with statistically significant difference ( P<0.05); ⑷ There were significant differences in vitamin A levels among different age in disease group ( P<0.05). Among them, the children with high risk of subclinical deficiency accounted for the largest proportion (45.78%) in the 6-month-1-year-old group, and the proportion of children with normal vitamin A levels in other age groups was the largest; ⑸ There are significant differences in vitamin E levels in different age groups in the disease group ( P<0.05), the levels in the normal range accounts for the largest proportion of all ages; ⑹ The levels of vitamin A and vitamin E in mycoplasma pneumoniae infection group were increased compared with in recurrent respiratory infection group , asthma group, and cough variant asthma group, and the difference was statistically significant ( P<0.05). Compared with the pneumonia group, the level of vitamin E increased in the recurrent respiratory infection group, and the difference was statistically significant ( P<0.05); The vitamin E levels in the cough variant asthma group were reduced compared with the repeated respiratory infection group, asthma group and pneumonia group ( P<0.05). Conclusions:The Vitamin A and E levels of children suffering from respiratory diseases are lower than those of normal children. The Vitamin A and E levels of different respiratory diseases and different age groups are different. Vitamin A and E supplementation may be significantly targeted according to different ages and different respiratory diseases in clinical practice.

Objective: To determine the clinical significance of nontuberculous mycobacteria (NTM) isolated from respiratory specimens. Methods: Clinical data of patients with NTM strains isolated from the respiratory tract between January 2014 and February 2017 were retrospectively analyzed. Clinical significance of NTM isolated strains was evaluated based on diagnostic criteria of NTM pulmonary diseases from American Thoracic Society (ATS). Quantitative data of two groups were analyzed by independent t test. Categorical data were analyzed by Pearson χ² test or Fisher exact test. Results: Totally 352 NTM strains from 257 patients had been isolated between January 2014 and February 2017. Among 15 identified NTM species, M. intracellular (51.7%, 182/352), M. abscessus (25.6%, 90/352), and M. avium (10.8%, 38/352) were predominant. Of the 157 patients with full clinical data involved in the analysis, 58 (36.9%) patients were determined to have definite disease, and 34 patients (21.7%) were designated as probable disease candidates, and 16 (10.2%) patients were regarded as uncertain disease, and 49(31.2%) patients were diagnosed as unlikely disease. The age of 58 patients with definite disease was (63.9±12.7) years, and 48.3% (28/58) were female. M. intracellulare (55.2%, 32/58) was the main cause of pulmonary NTM disease, followed by M. abscessus (25.9%, 15/58) and M. avium (12.1%, 7/58), while other NTM species only accounted for 6.8% (4/58). Definite cases with M. intracellulare, M. abscessus, M. avium, M. kansasii, M. marseillense, and M. columbia accounted for 35.2% (32/91), 57.7% (15/26), 7/15, 2/3, 1/3 and 1/2, respectively, among patients with corresponding isolations, while patients with other species of isolation did not meet the diagnostic criteria. Patients with clinical significant isolation of NTM were older than those without clinical significance (χ²=3.603, P=0.000), and proportion of anti-acid staining positivity of patients with clinical significance was higher than that of patients without clinical significance (χ²=18.815, P=0.000). The proportion of M. abscessus in patients with clinical significance was higher than that in patients without clinical significance (χ²=6.313, P=0.012). However, there was no significant difference between the two groups in the isolation of M. Gordon (Fisher exact test, P=0.028). The proportion of M. abscessus lung disease in women was 11/15, which was higher than that of M. intracellulare lung disease (41.5%, 17/41), and the difference between the two groups was statistically significant (χ²=4.462, P=0.035). There was no significant difference of clinical symptoms and underlying diseases in NTM lung disease among different groups (all P>0.05). In these patients with definite disease, 39.7% (23/58) of them manifested the upper lobe cavitary form, 53.4% (31/58) exhibited nodular bronchiectatic form, and only 6.9% (4/58) exhibited unclassified form. The upper lobe cavitary form (43.8%, 14/32) and the nodular bronchiectatic form (53.1%, 17/32) dominated in patients with M. intracellulare lung disease. M. abscessus lung disease was dominated by the nodular bronchiectatic form (11/15) while the upper lobe cavitary form only accounts for 3/15. There was no significant difference of image characteristics between NTM lung disease and other different groups (all P>0.05). Conclusions 36.9% of the patients with NTM isolates met the ATS diagnostic criteria for NTM lung disease. Different species have different clinical significance. M. intracellulare and M. abscessus are the most predominant NTM isolated species that cause NTM lung disease. Majority of patients manifest as the upper lobe cavitary form, followed by the nodular bronchiectatic form.