Disruption of Physiological Rhythms Persist Following Cessation of Cigarette Smoke Exposure in Mice

Redox Regulatory Changes of Circadian Rhythm by the Environmental Risk Factors Traffic Noise and Air Pollution

Significance: Risk factors in the environment such as air pollution and traffic noise contribute to the development of chronic noncommunicable diseases. Recent Advances: Epidemiological data suggest that air pollution and traffic noise are associated with a higher risk for cardiovascular, metabolic, and mental disease, including hypertension, heart failure, myocardial infarction, diabetes, arrhythmia, stroke, neurodegeneration, depression, and anxiety disorders, mainly by activation of stress hormone signaling, inflammation, and oxidative stress. Critical Issues: We here provide an in-depth review on the impact of the environmental risk factors air pollution and traffic noise exposure (components of the external exposome) on cardiovascular health, with special emphasis on the role of environmentally triggered oxidative stress and dysregulation of the circadian clock. Also, a general introduction on the contribution of circadian rhythms to cardiovascular health and disease as well as a detailed mechanistic discussion of redox regulatory pathways of the circadian clock system is provided. Future Directions: Finally, we discuss the potential of preventive strategies or "chrono" therapy for cardioprotection. Antioxid. Redox Signal. 37, 679-703.

Construction and validation of postoperative hypothermia prediction model for patients undergoing joint replacement surgery

AIM

To construct and validate a postoperative hypothermia prediction model for patients undergoing joint replacement surgery.

BACKGROUND

Postoperative hypothermia is one of the harmful perioperative complications in patients undergoing joint replacement surgery. The previous studies mainly focused on intraoperative hypothermia prediction models. The prediction model for postoperative hypothermia in patients with joint replacement surgery was understudied.

DESIGN

Cohort study.

METHODS

We collected data from 503 participants undergoing joint replacement surgery in a tertiary hospital from January 2019 to December 2021. Of those, 404 cases were assigned to the modelling and 99 to the validation groups. Logistic regression was used to construct the model. The AUC was used to test the predictive effect of the model. Finally, 99 cases were used to verify the application effect of the model. A TRIPOD checklist was used to guide the reporting of this study.

RESULTS

The factors entered into the prediction model were age, intraoperative hypothermia, BMI, heat preservation measures and platelet (PLT). The model was constructed as follows: Logit (P) = .537 + 3.669 × 1 (intraoperative hypothermia) + .030 × age - .289 × BMI + 2.857 × 1 (intraoperative insulation measures) + .003 × PLT. Hosmer-Lemeshow test, p = .608, the area under the receiver operating characteristic curve (AUC) was .861. The Youden index was .530, the sensitivity was .599 and the specificity was .93. The incidence of postoperative hypothermia in the modelling group was 42.93% (173/404), and that in the verification group was 43.43% (43/99), χ2 = .012, p = .912. The correct practical application rate was 87.88%. This model has a good application effect.

CONCLUSION

The current prediction model provided a reference for clinical screening of patients with high-risk hypothermia after joint replacement surgery.

RELEVANCE TO CLINICAL PRACTICE

Clinical nurses can use the developed prediction model to predict the occurrence of postoperative hypothermia and provide a reference for the preventive measure.

Associations of exposure to secondhand smoke with hypertension risk and blood pressure values in adults

Background

The effects of environmental chemical exposure on blood pressure (BP) have been confirmed, but the association between exposure to secondhand smoke (SHS) and hypertension risk and BP in the general population remains unknown.

Methods

Cross-sectional associations between SHS exposure and hypertension risk and BP values were evaluated using data for subjects who participated in the National Health and Nutrition Examination Survey (NHANES), 1999–2016. Logistic regression and linear regression were performed after adjusting for age, sex, race, alcohol consumption, poverty-to-income ratio (PIR), body mass index (BMI), estimated glomerular filtration rate, physical activity, diabetes, cardiovascular disease, and NHANES cycle. Restricted cubic spline models were created to display the potential nonlinear association between SHS and BP levels.

Results

Higher risk of hypertension was found at the highest SHS concentrations (OR = 1.13, 95% CI 1.04, 1.24, P for trend = 0.007). Additionally, SHS exposure had a strong positive association with systolic blood pressure (SBP) but was negatively associated with diastolic blood pressure (DBP). Furthermore, the nonlinear model result showed a significant association between SHS and SBP (P = 0.017); however, the nonlinear model result was not significant for SHS or DBP.

Conclusions

Our results suggest a potential association between high SHS exposure and the risk of hypertension. Further research is needed to elucidate the underlying mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-021-01009-0.

Development and validation of a mouse model of contemporary cannabis smoke exposure

Cannabis is widely used for both recreational and medicinal purposes. Inhalation of combusted cannabis smoke is the most common mode of drug consumption, exposing the lungs to the pharmacologically active ingredients, including tetrahydrocannabinol (THC) and cannabidiol (CBD). While the relationship between cannabis smoke exposure and compromised respiratory health has yet to be sufficiently defined, previous investigations suggest that cannabis smoke may dysregulate pulmonary immunity. Presently, there exist few preclinical animal models that have been extensively validated for contemporary cannabis smoke exposure.

 To address this need, we developed a mouse model with readouts of total particulate matter, serum cannabinoid and carboxyhaemoglobin levels, lung cellular responses, and immune-mediator production.

 Using a commercially available smoke exposure system and a cannabis source material of documented THC/CBD composition, we exposed mice to a mean±sd total particulate matter of 698.89±66.09 µg·L⁻¹ and demonstrate increases in serum cannabinoids and carboxyhaemoglobin. We demonstrate that cannabis smoke modulates immune cell populations and mediators in both male and female BALB/c mice. This modulation is highlighted by increases in airway and lung tissue macrophage populations, including tissue-resident alveolar macrophages, monocyte-derived alveolar macrophages, and interstitial macrophage subpopulations. No changes in airway or lung tissue infiltration of neutrophils were observed. Immune-mediator analysis indicated significant upregulation of macrophage-derived chemokine, thymus and activation-regulated chemokine, and vascular endothelial growth factor within the lung tissue of cannabis smoke-exposed mice.

 This accessible and reproducible smoke-exposure model provides a foundation to explore the impact of chronic cannabis exposures and/or co-exposures with pathogens of clinical relevance, such as influenza.

Validation of the use of contemporary cannabis available on the legal market of known THC/CBD composition in a mouse model of smoke exposure with readouts of lung inflammationhttps://bit.ly/3okHWS4