Glycolytic enzyme PGK1 promotes M1 macrophage polarization and induces pyroptosis of acute lung injury via regulation of NLRP3.

Acute lung injury (ALI) is characterized by an unregulated inflammatory reaction, often leading to severe morbidity and ultimately death. Excessive inflammation caused by M1 macrophage polarization and pyroptosis has been revealed to have a critical role in ALI. Recent study suggests that glycolytic reprogramming is important in the regulation of macrophage polarization and pyroptosis. However, the particular processes underlying ALI have yet to be identified. In this study, we established a Lipopolysaccharide(LPS)-induced ALI model and demonstrated that blocking glycolysis by using 2-Deoxy-D-glucose(2-DG) significantly downregulated the expression of M1 macrophage markers and pyroptosis-related genes, which was consistent with the in vitro results. Furthermore, our research has revealed that Phosphoglycerate Kinase 1(PGK1), an essential enzyme in the glycolysis pathway, interacts with NOD-, LRR- and pyrin domain-containing protein 3(NLRP3). We discovered that LPS stimulation improves the combination of PGK1 and NLRP3 both in vivo and in vitro. Interestingly, the absence of PGK1 reduces the phosphorylation level of NLRP3. Based on in vitro studies with mice bone marrow-derived macrophages (BMDMs), we further confirmed that siPGK1 plays a protective role by inhibiting macrophage pyroptosis and M1 macrophage polarization. The PGK1 inhibitor NG52 suppresses the occurrence of excessive inflammation in ALI. In general, it is plausible to consider a therapeutic strategy that focuses on modulating the relationship between PGK1 and NLRP3 as a means to mitigate the activation of inflammatory macrophages in ALI.

PI3K/AKT/FOXO3a Pathway Induces Muscle Atrophy by Ubiquitin-Proteasome System and Autophagy System in COPD Rat Model.

Muscle atrophy is a common extrapulmonary co-morbidity affecting about 20% of patients with COPD. However, the mechanism of muscle atrophy in COPD remains unclear. This study investigated the role of the ubiquitin-proteasome system (UPS) and the autophagy system in COPD muscle atrophy and its mechanism. A COPD rat model was established to evaluate the in vitro effects of the UPS and the autophagy system in muscle atrophy. In addition, the role of the UPS, autophagy systems, and the expressions of the PI3K/AKT/FOXO3a pathway were studied in the CSE-induced L6 myoblast cells. Furthermore, we evaluated the effect of FOXO3a in the CSE-induced L6 myoblast cells using siRNA-FOXO3a. The results showed that the expression of ubiquitin-related proteins and autophagy-related proteins were significantly increased in the COPD rat model and CSE-induced L6 myoblast cells. At the same time, there was a concurrent decrease in the phosphorylation protein expression of PI3K and AKT, but the transcriptional activity of FOXO3a was increased in CSE-induced L6 myoblast cells. And siRNA-FOXO3a significantly decreased the expression level of the UPS and the autophagy system in CSE-induced L6 myoblast cells. These results suggest that PI3K/AKT/FOXO3a participates in COPD muscle atrophy by regulating the UPS and the autophagy systems.

Mesenchymal Stromal Cell Therapy Alleviates Ovalbumin-Induced Chronic Airway Remodeling by Suppressing M2 Macrophage Polarization.

Chronic asthma is characterized by airway hyperresponsiveness, inflammation, and remodeling. Previous studies have shown that mesenchymal stromal/stem cells (MSCs) exert anti-inflammatory effects on asthma via regulation of the immune cells. However, the therapeutic mechanism of MSCs, especially the mechanism of airway remodeling in chronic asthma, remains to be elucidated. Here, we aimed to investigate the therapeutic effect of MSCs on airway remodeling in chronic asthma and explored the mechanisms by analyzing the polarization phenotype of macrophages in the lungs. We established a mouse model of chronic asthma induced by ovalbumin (OVA) and evaluated the effect of MSCs on airway remodeling. The data showed that MSCs treatment before the challenge exerted protective effects on OVA-induced chronic asthma, i.e., decreased the inflammatory cell infiltration, Th2 cytokine levels, subepithelial extracellular matrix deposition, and transforming growth factor ß (TGF-ß)/Smad signaling. Additionally, we found that MSCs treatment markedly suppressed macrophage M2 polarization in lung tissue. At the same time, MSCs treatment inhibited NF-κB p65 nuclear translocation, ER stress, and oxidative stress in the OVA-induced chronic allergic airway remodeling mice model. In conclusion, these results demonstrated that MSCs treatment prevents OVA-induced chronic airway remodeling by suppressing macrophage M2 polarization, which may be associated with the dual inhibition of ER stress and oxidative stress. This discovery may provide a new theoretical basis for the future clinical application of MSCs.

Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.

Backgrounds: During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the disease has placed an enormous burden on the world's healthcare and economy. The early risk assessment system based on a variety of machine learning (ML) algorithms may be able to provide more accurate advice on the classification of COVID-19 patients, offering predictive, preventive, and personalized medicine (PPPM) solutions in the future. Methods: In this retrospective study, we divided a portion of the data into training and validation cohorts in a 7:3 ratio and established a model based on a combination of two ML algorithms first. Then, we used another portion of the data as an independent testing cohort to determine the most accurate and stable model and compared it with other scoring systems. Finally, patients were categorized according to risk scores and then the correlation between their clinical data and risk scores was studied. Results: The elderly accounted for the majority of hospitalized patients with COVID-19. The C-index of the model constructed by combining the stepcox[both] and survivalSVM algorithms was 0.840 in the training cohort and 0.815 in the validation cohort, which was calculated to have the highest C-index in the testing cohort compared to the other 119 ML model combinations. Compared with current scoring systems, including the CURB-65 and several reported prognosis models previously, our model had the highest AUC value of 0.778, representing an even higher predictive performance. In addition, the model's AUC values for specific time intervals, including days 7,14 and 28, demonstrate excellent predictive performance. Most importantly, we stratified patients according to the model's risk score and demonstrated a difference in survival status between the high-risk, median-risk, and low-risk groups, which means a new and stable risk assessment system was built. Finally, we found that COVID-19 patients with a history of cerebral infarction had a significantly higher risk of death. Conclusion: This novel risk assessment system is highly accurate in predicting the prognosis of patients with COVID-19, especially elderly patients with COVID-19, and can be well applied within the PPPM framework. Our ML model facilitates stratified patient management, meanwhile promoting the optimal use of healthcare resources.

The Influencing Factors of Comprehensive Sexuality Education Capacity and Its Correlation with Subjective Social Status among Chinese Junior High School Students.

(1) Objective: Evidence suggests that comprehensive sexuality education (CSE) can protect and empower younger generations to advocate for their reproductive health and wellbeing. This survey aims to investigate the current status and influencing factors of CSE among Chinese junior high school students, and to evaluate its correlation with the learning experience of sex education and subjective social status (SSS) to provide evidence for the implementation of CSE in the future. (2) Methods: A total of 4109 participants aged 11 to 16 years were recruited using data from a cross-sectional survey among junior high school students in China in 2021. CSE knowledge, attitude, and skills were used to generate the CSE comprehensive capacity by a principal component analysis. One-way ANOVA was used to assess the different effects of school sex education and family sex education. Multiple linear regression was used to assess the association between CSE comprehensive capacity and SSS. (3) Results: The average score of CSE comprehensive capacity was 82.44 ± 8.60 (with a total score of 100 points) among participants. After the adjustment, subjective social status was positively related to CSE comprehensive capacity (B = 0.28, 95% CI: 0.20-0.36), and SSS (School) (beta = 0.62) had a higher impact on CSE comprehensive capacity compared to SSS (Family) (beta = -0.10). School sex education was associated with the CSE knowledge level with a larger magnitude compared to family sex education (mean deviation = -0.53, p = 0.031), whereas family sex education was related to the CSE skill level with a greater magnitude (mean deviation =1.14, p = 0.005). (4) Conclusions: These findings suggest that sex education at school and within the family might have a different impact on CSE capacity, which was positively associated with SSS among junior high school students.