Objective:To assess the effect of joint exposure to multiple air pollutants on sleep structure in patients with stable chronic obstructive pulmonary disease (COPD), identify key air pollutants, and analyze potential influencing factors.Methods:In this panel study, 92 stable COPD patients were recruited. From March 2021 to September 2023 in Beijing, all participants completed 254 nights of sleep monitoring. The total sleep duration, light sleep duration, deep sleep duration and rapid eye movement sleep duration and their respective proportions in total sleep duration were recorded. The exposure levels of fine particulate matter (PM 2.5), inhalable particulate matter (PM 10), nitrogen dioxide (NO 2), ozone (O 3), sulfur dioxide (SO 2), and carbon monoxide (CO) were estimated based on the infiltration factor method and time-activity logs of participants. To assess the lag effect of air pollutants, moving average concentrations of air pollutants from 0-1 day to 0-3 months were calculated. The linear mixed-effect model and Bayesian kernel machine regression (BKMR) model were used to assess the single and joint effects of air pollutants on sleep structure parameters in COPD patients, respectively. Results:All six types of air pollutants were associated with changes in sleep structure, manifesting as an increase in total sleep duration and light sleep proportion and a reduction in deep sleep proportion. The effects of O 3 were strongest at lag 0-6 days, while other air pollutants were at lag 0-3 months. Joint exposure to multiple air pollutants exerted significant joint effects on sleep structure, and NO 2 was identified as the dominant pollutant. NO 2 had a posterior inclusion probability (PIP) greater than 0.5 for light sleep proportion (PIP=0.691) and deep sleep proportion (PIP=0.957). With an interquartile range (IQR) increase of 8.6 μg/m 3 in NO 2 at lag 0-3 months, the light sleep proportion increased by 10.5% (95% CI: 2.2%-19.4%), and the deep sleep proportion decreased by 19.5% (95% CI:-30.6%- -6.8%). Conclusion:Joint exposure to air pollutants is associated with changes in sleep structure in stable COPD patients, and NO 2 may be a key pollutant.

Objective:To assess the effect of joint exposure to multiple air pollutants on sleep structure in patients with stable chronic obstructive pulmonary disease (COPD), identify key air pollutants, and analyze potential influencing factors.Methods:In this panel study, 92 stable COPD patients were recruited. From March 2021 to September 2023 in Beijing, all participants completed 254 nights of sleep monitoring. The total sleep duration, light sleep duration, deep sleep duration and rapid eye movement sleep duration and their respective proportions in total sleep duration were recorded. The exposure levels of fine particulate matter (PM 2.5), inhalable particulate matter (PM 10), nitrogen dioxide (NO 2), ozone (O 3), sulfur dioxide (SO 2), and carbon monoxide (CO) were estimated based on the infiltration factor method and time-activity logs of participants. To assess the lag effect of air pollutants, moving average concentrations of air pollutants from 0-1 day to 0-3 months were calculated. The linear mixed-effect model and Bayesian kernel machine regression (BKMR) model were used to assess the single and joint effects of air pollutants on sleep structure parameters in COPD patients, respectively. Results:All six types of air pollutants were associated with changes in sleep structure, manifesting as an increase in total sleep duration and light sleep proportion and a reduction in deep sleep proportion. The effects of O 3 were strongest at lag 0-6 days, while other air pollutants were at lag 0-3 months. Joint exposure to multiple air pollutants exerted significant joint effects on sleep structure, and NO 2 was identified as the dominant pollutant. NO 2 had a posterior inclusion probability (PIP) greater than 0.5 for light sleep proportion (PIP=0.691) and deep sleep proportion (PIP=0.957). With an interquartile range (IQR) increase of 8.6 μg/m 3 in NO 2 at lag 0-3 months, the light sleep proportion increased by 10.5% (95% CI: 2.2%-19.4%), and the deep sleep proportion decreased by 19.5% (95% CI:-30.6%- -6.8%). Conclusion:Joint exposure to air pollutants is associated with changes in sleep structure in stable COPD patients, and NO 2 may be a key pollutant.

Objective:To evaluate the effect of sufentanil on activation of Schwann cells after peripheral nerve injury in mice.Methods:Eighty healthy pathogen-free male Balb/c mice, aged 6-8 weeks, weighing 18-22 g, were divided into 4 groups ( n=20 each) using a random number table method: peripheral nerve injury group (group PNI), high dose sufentanil group (group H), medium dose sufentanil group (group M) and low dose sufentanil group (group L). The model of unilateral sciatic nerve transaction was established in ketamine-anesthetized mice.Immediately after establishment of the model, sufentanil 10, 5 and 2.5 μg/kg was injected intraperitoneally once a day for 3 consecutive days in H, M and L groups, respectively, while the equal volume of normal saline was given instead in group PNI.Sciatic function index (SFI) was calculated at 4, 8 and 12 weeks after establishment of the model.At 2, 4, 8 and 12 weeks, 5 mice in each group were sacrificed, and segments of the injuried ipsilateral sciatic nerve were removed for examination of the ultrastructure of the sciatic nerve (with a transmission electron microscope) and for detection of the expression of glial fibrillary acidic protein (GFAP) of sciatic nerve (by immunohistochemistry). Results:Compared with group PNI, SFI was significantly increased, and the expression of GFAP was up-regluated at each time point after establishment of the model in H and M groups ( P<0.05) and no significant change was found in SFI and GFAP expression after establishment of the model in group L ( P>0.05). Compared with group L, SFI was significantly increased, and GFAP expression was up-regluated in H and M groups ( P<0.05). There was no significant difference in SFI and GFAP expression between group H and group M ( P>0.05). The thickness of myelin lamellae was dense, and the proliferation of Schwann cells was not marked in H and M groups.The thickness of myelin lamellae was thin, and the proliferation of Schwann cells was marked in L and MO groups. Conclusion:The mechanism by which sufentanil improves repair after peripheral nerve injury may be related to promoting activation of Schwann cells in mice.