Linfu Zhou

Background: Resveratrol has been found to have anti-inflammatory and anti-allergic properties. The effects of resveratrol on thymic stromal lymphopoietin (TSLP)-mediated atopic march remain unclear. Purpose: To explore the potential role of resveratrol in TSLP-mediated atopic march. Methods: The atopic march mouse model was established by topical application of MC903 (a vitamin D3 analog). Following the treatment with resveratrol, airway resistance in mice was discovered by pulmonary function apparatus, and the number of total cells, neutrophils, and eosinophils in bronchoalveolar lavage fluid was counted. The histopathological features of pulmonary and ear skin tissues, inflammation, and cell infiltration were determined by hematoxylin and eosin staining. The messenger RNA (mRNA) levels of TSLP, immunoglobulin E, interleukin (IL)-4, IL-5, and IL-13 were measured by real-time quantitative polymerase chain reaction. The protein expression of nuclear factor kappa B (NF-κB)/nuclear factor erythroid 2-related factor 2 (Nrf2) signaling-associated molecules (p-p65, p65, p-I kappa B kinase alpha (IκBα), IκBα, Nrf2, and TSLP) in lung and ear skin tissues were assessed by Western blot analysis. Results: Resveratrol attenuated airway resistance and infiltration of total cells, eosinophils, and neutrophils in both lung and ear skin tissues. Resveratrol ameliorates serum inflammatory markers in allergic mice. Moreover, the phosphorylation levels of NF-κB pathway-related proteins were significantly reduced by administration of resveratrol in allergic lung and ear skin tissues. Similarly, the protein expression of TSLP in both lung and ear skin tissues was reduced by resveratrol, and Nrf2, a protector molecule, was increased with resveratrol treatment. Conclusion: Resveratrol attenuates TSLP-reduced atopic march through ameliorating inflammation and cell infiltration in pulmonary and ear skin tissues by inhibiting the abnormal activation of NF-κB signaling pathway.

Lung adenocarcinoma (LUAD) is one of the most common causes of cancer-related death. The role of pyroptosis in LUAD remains unclear. Our study aimed to identify a prognostic signature of pyroptosis-related genes (PRGs) and explore the connection of PRGs with the tumour microenvironment in LUAD. Gene expression and clinical information were obtained from The Cancer Genome Atlas database. Consensus clustering was applied to classify LUAD patients. The least absolute shrinkage and selection operator Cox and multivariate Cox regression models were used to generate a PRG-related prognostic signature. The correlations between PRGs and tumour-infiltrating immune cells or the tumour mutational burden were analysed by Spearman’s correlation analysis. In this study, 44 PRGs significantly differed in expression between LUAD and normal tissues. Based on these genes, patients were clustered into three clusters with significantly different distributions of tumour-infiltrating immune cells and immune checkpoint regulators. A total of four PRGs (NLRP1, HMGB1, CYCS, and BAK1) were used to construct a prognostic model. Significant correlations were observed between these prognostic PRGs and immune cell infiltration or the tumour mutational burden. Predictive nomogram results showed that BAK1 could be an independent prognostic biomarker in LUAD. Additionally, the expression level of BAK1 was validated in two independent Gene Expression Omnibus cohorts. Our identified prognostic PRG signature may provide insight for future studies targeting pyroptosis and the tumour microenvironment in LUAD. Future studies are needed to verify our current findings.

Article Animal models: An essential tool to dissect the heterogeneity of chronic obstructive pulmonary disease was published on March 1, 2023 in the journal Journal of Translational Internal Medicine (volume 11, issue 1).

Background: In contrast to the large and increasing number of patients with stroke, clinical rehabilitation resources cannot meet their rehabilitation needs. Especially for those discharged, ways to carry out effective rehabilitation training without the supervision of physicians and receive guidance from physicians remain urgent problems to be solved in clinical rehabilitation and have become a research hot spot at home and abroad. At present, there are many studies on home rehabilitation training based on wearable devices, Kinect, among others, but these have disadvantages (eg, complex systems, high price, and unsatisfactory rehabilitation effects). Objective: This study aims to design a remote intelligent rehabilitation training system based on wearable devices and human-computer interaction training tasks, and to evaluate the effectiveness and safety of the remote rehabilitation training system for nonphysician-supervised motor rehabilitation training of patients with stroke through a clinical trial study. Methods: A total of 120 inpatients with stroke having limb motor dysfunction were enrolled via a randomized, parallel-controlled method in the rehabilitation institutions, and a 3-week clinical trial was conducted in the rehabilitation hall with 60 patients in the experimental group and 60 in the control group. The patients in the experimental group used the remote rehabilitation training system for rehabilitation training and routine clinical physical therapy (PT) training and received routine drug treatment every day. The patients in the control group received routine clinical occupational therapy (OT) training and routine clinical PT training and routine drug treatment every day. At the beginning of the training (baseline) and after 3 weeks, the Fugl-Meyer Motor Function Rating scale was scored by rehabilitation physicians, and the results were compared and analyzed. Results: Statistics were performed using SAS software (version 9.4). The total mean Fugl-Meyer score improved by 11.98 (SD 8.46; 95% CI 9.69-14.27) in the control group and 17.56 (SD 11.65; 95% CI 14.37-20.74) in the experimental group, and the difference between the 2 groups was statistically significant (P=.005). Among them, the mean Fugl-Meyer upper extremity score improved by 7.45 (SD 7.24; 95% CI 5.50-9.41) in the control group and 11.28 (SD 8.59; 95% CI 8.93-13.62) in the experimental group, and the difference between the 2 groups was statistically significant (P=.01). The mean Fugl-Meyer lower extremity score improved by 4.53 (SD 4.42; 95% CI 3.33-5.72) in the control group and 6.28 (SD 5.28; 95% CI 4.84-7.72) in the experimental group, and there was no significant difference between the 2 groups (P=.06). The test results showed that the experimental group was better than the control group, and that the patients’ motor ability was improved. Conclusions: The remote rehabilitation training system designed based on wearable devices and human-computer interaction training tasks can replace routine clinical OT training. In the future, through medical device registration certification, the system will be used without the participation of physicians or therapists, such as in rehabilitation training halls, and in remote environments, such as communities and homes. Trial Registration: Chinese Clinical Trial Registry ChiCTR2200061310; https://tinyurl.com/34ka2725

Background: Baduanjin is a traditional Chinese exercise regimen used to treat various chronic illnesses and is associated with both psychological and physical benefits. However, its benefits for patients suffering from chronic obstructive pulmonary disease (COPD) are unclear. This study aims to assess the efficacy, safety, and underlying mechanisms of Baduanjin exercise in patients with moderate-to-severe COPD (BROCADE) by remote monitoring. Methods: This study protocol describes a multicenter, open-label, prospective randomized computed tomography. A total of 150 individuals who meet the inclusion criteria after the screening and consent processes will take part in the study. All participants will be provided routine medication and lifestyle interventions. They will be randomly assigned to a control group, a classical pulmonary rehabilitation group, or a Baduanjin group, which will undergo remotely monitored Baduanjin exercises for a cumulative duration of 1 hour per day, three times per week for 12 weeks. The participants will be followed for 24 weeks. The primary outcomes will be a 6-minutes walking distance and St. George’s Respiratory Questionnaire index. The secondary outcomes will be lung function, cross-sectional area of the pectoralis major and subcutaneous fat, modified Medical Research Council score, COPD assessment test questionnaire results, extremity muscle strength, and quality of life. Any adverse events that may occur will be monitored and recorded. Results: This study is ongoing and will be submitted to a peer-reviewed journal for publication once completed. Conclusion: A novel neutrophil-related inflammatory mechanism will potentially be identified. In addition, the study results will provide a safe, effective, simple and operational Baduanjin exercise protocol for moderate-to-severe COPD patients aimed at improving prognosis and quality of life.

In order to solve the shortcomings of the current clinical scale assessment for stroke patients, such as excessive time consumption, strong subjectivity, and coarse grading, this study designed an intelligent rehabilitation assessment system based on wearable devices and a machine learning algorithm and explored the effectiveness of the system in assessing patients’ rehabilitation outcomes. The accuracy and effectiveness of the intelligent rehabilitation assessment system were verified by comparing the consistency and time between the designed intelligent rehabilitation assessment system scores and the clinical Fugl–Meyer assessment (FMA) scores. A total of 120 stroke patients from two hospitals participated as volunteers in the trial study, and statistical analyses of the two assessment methods were performed. The results showed that the R² of the total score regression analysis for both methods was 0.9667, 95% CI 0.92–0.98, p < 0.001, and the mean of the deviation was 0.30, 95% CI 0.57–1.17. The percentages of deviations/relative deviations falling within the mean ± 1.96 SD of deviations/relative deviations were 92.50% and 95.83%, respectively. The mean time for system assessment was 35.00% less than that for clinician assessment, p < 0.05. Therefore, wearable intelligent machine learning rehabilitation assessment has a strong and significant correlation with clinician assessment, and the time spent is significantly reduced, which provides an accurate, objective, and effective solution for clinical rehabilitation assessment and remote rehabilitation without the presence of physicians.