Identifying the Relationship between PM2.5 and Hyperlipidemia Using Mendelian Randomization, RNA-seq Data and Model Mice Subjected to Air Pollution.

Air pollution is an important public health problem that endangers human health. However, the casual association and pathogenesis between particles < 2.5 µm (PM2.5) and hyperlipidemia remains incompletely unknown. Mendelian randomization (MR) and transcriptomic data analysis were performed, and an air pollution model using mice was constructed to investigate the association between PM2.5 and hyperlipidemia. MR analysis demonstrated that PM2.5 is associated with hyperlipidemia and the triglyceride (TG) level in the European population (IVW method of hyperlipidemia: OR: 1.0063, 95%CI: 1.0010-1.0118, p = 0.0210; IVW method of TG level: OR: 1.1004, 95%CI: 1.0067-1.2028, p = 0.0350). Mest, Adipoq, Ccl2, and Pcsk9 emerged in the differentially expressed genes of the liver and plasma of PM2.5 model mice, which might mediate atherosclerosis accelerated by PM2.5. The studied animal model shows that the Paigen Diet (PD)-fed male LDLR-/- mice had higher total cholesterol (TC), TG, and CM/VLDL cholesterol levels than the control group did after 10 times 5 mg/kg PM2.5 intranasal instillation once every three days. Our study revealed that PM2.5 had causality with hyperlipidemia, and PM2.5 might affect liver secretion, which could further regulate atherosclerosis. The lipid profile of PD-fed Familial Hypercholesterolemia (FH) model mice is more likely to be jeopardized by PM2.5 exposure.

The influence path of community green exposure index on activity behavior under multi-dimensional spatial perception.

The purpose of this research is to reveal the internal relationship among community green space, space perception, and activity behavior response to supplement the lack of research results on the binary relationship between green space and behavior. Nine residential community green spaces and 398 residents were selected as the research objects. Thematic clustering and factor identification were used to determine the spatial dimensions of community green space that residents were concerned about. The analysis of the green exposure index, spatial perception evaluation, and activity behavior survey were combined to determine the influence of the green exposure index on spatial perception and activity behavior and its internal correlation path. According to research data, the community green view index (GVI) and normalized difference vegetation index (NDVI) negatively affected the perception factor, while the perception factor positively affected the activity frequency. The SEM model shows that the green exposure index stimulated activity behavior through the intermediate effect of the internal perception path of perceived landscape quality, perceived workability, and perceived accessibility. Spatial perception as the basis of the instantaneous emotional reaction process may affect people's choices for activities but be unable to extend the duration of the activities. The internal association among community green space, spatial perception, and physical activity behavior develops on the basis of spatial patterns at certain scales. This study provides a theoretical basis for understanding the spatial experience and residents' behavioral needs, evaluating the quality of urban green space scientifically, and promoting the optimization of community green space structure.

A Holocene lacustrine record of variations in chemical weathering intensity in the Mu Us Desert, China.

The Mu Us Desert is an ideal location to study environmental changes during the Late Quaternary, because of its unique characteristics. The Abaoyan (ABY) profile, a typical aeolian-lacustrine profile located at the eastern edge of the desert, was investigated in this study. A basic chronological framework was established based on a combination of radiocarbon dating by accelerator mass spectrometry and in situ sedimentary phase identification. Furthermore, changes in regional chemical weathering intensity since the Holocene were evaluated through comprehensive analysis of the collected samples in terms of grain size, loss on ignition (LOI), chromaticity, geochemical element contents, and soil micromorphology. The results showed that the ABY profile was under the influence of primary and moderate chemical weathering. Regional paleoclimatic environmental changes could be divided into four stages. During Stage I (before 12.6 ka BP; pre-Holocene), the ABY profile was dominated by aeolian sand, showing a coarse average grain size, low LOI, and high chromaticity values, which may have indicated a dry and cold period. During Stage II (12.6-10.3 ka BP; early Holocene), the ABY profile was dominated by lacustrine sediments, indicating a shallow lake water environment with strong chemical weathering and a warm and humid climate. During Stage III (10.3-4.2 ka BP), the profile was dominated by sandy peat deposits with a relatively large proportion of clay particles suggesting that the intensity of chemical weathering was relatively strong in the region during this period and the climate was mainly warm and humid. During Stage IV (after 4.2 ka BP), the sediment was dominated by aeolian sand and secondary loess, the chromaticity increased, the LOI reduced, and the regional chemical weathering intensity was weaker. The change in chemical weathering intensity in this region was inferred to be a positive response to the Holocene East Asian monsoon circulation.

The long-term and short-term effects of ambient air pollutants on sleep characteristics in the Chinese population: big data analysis from real world by sleep records of consumer wearable devices.

Several studies on long-term air pollution exposure and sleep have reported inconsistent results. Large-scale studies on short-term air pollution exposures and sleep have not been conducted. We investigated the associations of long- and short-term exposure to ambient air pollutants with sleep in a Chinese population based on over 1 million nights of sleep data from consumer wearable devices. Air pollution data including particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were collected from the Ministry of Ecology and Environment. Short-term exposure was defined as a moving average of the exposure level for different lag days from Lag0 to Lag0-6. A 365-day moving average of air pollution was regarded as long-term exposure. Sleep data were recorded using wearable devices from 2017 to 2019. The mixed-effects model was used to evaluate the associations. We observed that sleep parameters were associated with long-term exposure to all air pollutants. Higher levels of air pollutant concentrations were associated with longer total sleep and light sleep duration, shorter deep sleep duration, and decreases in wake after sleep onset (WASO), with stronger associations of exposures to NO2 and CO [a 1-interquartile range (IQR) increased NO2 (10.3 µg/m3) was associated with 8.7 min (95% CI: 8.08 to 9.32) longer sleep duration, a 1-IQR increased CO (0.3 mg/m3) was associated with 5.0 min (95% CI: - 5.13 to - 4.89) shorter deep sleep duration, 7.7 min (95% CI: 7.46 to 7.85) longer light sleep duration, and 0.5% (95% CI: - 0.5 to - 0.4%) lower proportion of WASO duration to total sleep]. The cumulative effect of short-term exposure on Lag0-6 is similar to long-term exposure but relatively less. Subgroup analyses indicated generally greater effects on individuals who were female, younger (< 45 years), slept longer (≥ 7 h), and during cold seasons, but the pattern of effects was mixed. We supplemented two additional types of stratified analyses to reduce repeated measures of outcomes and exposures while accounting for individual variation. The results were consistent with the overall results, proving the robustness of the overall results. In summary, both short- and long-term exposure to air pollution affect sleep, and the effects are comparable. Although people tend to have prolonged total sleep duration with increasing air pollutant concentrations, their sleep quality might remain poor because of the reduction in deep sleep.

[TLC-FT-SERS study on ingredients of Isrhynchophylline].

A new method for analysing the ingredients of Isrhynchophylline in Uncaria Rhynchophylla Jacks by thin layer chromatography (TLC) and the surface-enhanced Raman spectroscopy (SERS) is reported in this paper. The results show that the characteristic spectra bands of Isrhynchophylline situated at the thin layer with the amount of sample about 2.5 micrograms were obtained. The difference between SERS and solid spectra was found. Great enhancement of the 1,615 cm-1 spectral band was abstained. Molecule was absorbed in surface silver sol by pi electrons in phenyl and by pair of electrons in N together. An absorption model of Isrhynchophylline and silver sol was proposed. This method can be used to analyse the chemical ingredients with high sensitivity.