Comparison of the different operation room environmental exposures on tear film function before and after operation.

1.2 Previous studies have confirmed that air and light pollution can cause damage to a number of systems throughout the body, including the ocular surface and retina. However, the exact effect of air pollution and light pollution on tear film function is not clear. This study explored the different operation room environmental exposures on tear film function before and after operation. Sixty medical staff in the operating room were selected and divided into 4 groups according to different surgical methods to evaluate the tear film function before and after operation: Da Vinci surgery group (DVSS), Laparoscopic surgery group (LS), Traditional surgery group (TS), and Ophthalmic microsurgery group (OM). The results showed that the levels of light and air pollution were elevated in operating rooms during the operation and the changes of tear film function in the other three groups were statistically significant except for DVSS group. In TS group, particulate matter (pm) 1 (R = 0.61, p < 0.01), pm2.5 (R = 0.63, p < 0.01), and pm10 (R = 0.67, p < 0.01) were positively correlated with eye redness index, and first and average noninvasive tear film break-up times were positively correlated with illuminance (R = 0.54, p < 0.05; R = 0.97, p < 0.01). In OM group, there was a positive correlation between the operation time and the first (R = 0.69, p < 0.01) and average (R = 0.89, p < 0.01) noninvasive tear film break-up times. Our research found that exposure to different operating room environment will lead to damage of tear film function, but also provide a theoretical basis for the improvement of surgical environment.

Scalable Manufacturing of Environmentally Stable All-Solid-State Plant Protein-Based Supercapacitors with Optimal Balance of Capacitive Performance and Mechanically Robust.

The development of advanced biomaterial with mechanically robust and high energy density is critical for flexible electronics, such as batteries and supercapacitors. Plant proteins are ideal candidates for making flexible electronics due to their renewable and eco-friendly natures. However, due to the weak intermolecular interactions and abundant hydrophilic groups of protein chains, the mechanical properties of protein-based materials, especially in bulk materials, are largely constrained, which hinders their performance in practical applications. Here, a green and scalable method is shown for the fabrication of advanced film biomaterials with high mechanical strength (36.3 MPa), toughness (21.25 MJ m-3 ), and extraordinary fatigue-resistance (213 000 times) by incorporating tailor-made core-double-shell structured nanoparticles. Subsequently, the film biomaterials combine to construct an ordered, dense bulk material by stacking-up and hot-pressing techniques. Surprisingly, the solid-state supercapacitor based on compacted bulk material shows an ultrahigh energy density of 25.8 Wh kg-1 , which is much higher than those previously reported advanced materials. Notably, the bulk material also demonstrates long-term cycling stability, which can be maintained under ambient condition or immersed in H2 SO4 electrolyte for more than 120 days. Thus, this research improves the competitiveness of protein-based materials for real-world applications such as flexible electronics and solid-state supercapacitors.

Measuring and evaluating SDG indicators with Big Earth Data.

The United Nations 2030 Agenda for Sustainable Development provides an important framework for economic, social, and environmental action. A comprehensive indicator system to aid in the systematic implementation and monitoring of progress toward the Sustainable Development Goals (SDGs) is unfortunately limited in many countries due to lack of data. The availability of a growing amount of multi-source data and rapid advancements in big data methods and infrastructure provide unique opportunities to mitigate these data shortages and develop innovative methodologies for comparatively monitoring SDGs. Big Earth Data, a special class of big data with spatial attributes, holds tremendous potential to facilitate science, technology, and innovation toward implementing SDGs around the world. Several programs and initiatives in China have invested in Big Earth Data infrastructure and capabilities, and have successfully carried out case studies to demonstrate their utility in sustainability science. This paper presents implementations of Big Earth Data in evaluating SDG indicators, including the development of new algorithms, indicator expansion (for SDG 11.4.1) and indicator extension (for SDG 11.3.1), introduction of a biodiversity risk index as a more effective analysis method for SDG 15.5.1, and several new high-quality data products, such as global net ecosystem productivity, high-resolution global mountain green cover index, and endangered species richness. These innovations are used to present a comprehensive analysis of SDGs 2, 6, 11, 13, 14, and 15 from 2010 to 2020 in China utilizing Big Earth Data, concluding that all six SDGs are on schedule to be achieved by 2030.

Richness and distribution of endangered orchid species under different climate scenarios on the Qinghai-Tibetan Plateau.

Predicting the potential influences of climate change on the richness and distribution is essential for the protection of endangered species. Most orchid species are narrowly distributed in specific habitats and are very vulnerable to habitat disturbance, especially for endangered orchid species on the Qinghai-Tibetan Plateau (QTP). In this study, we simulated the potential influences of climate change on the richness and distribution of 17 endangered orchid species on the QTP using the MaxEnt model based on the shared socioeconomic pathways scenarios (SSPs) in the 2050s and 2070s. The results showed that aspect, annual precipitation, elevation, mean temperature of driest quarter, topsoil pH (H2O), and topsoil sand fraction had a large influence on the potential distribution of endangered orchid species on the QTP. The area of potential distribution for orchid species richness ranging from 6 to 11 under the current climate scenario was 14,462 km2 (accounting for 0.56% of QTP), and it was mostly distributed in the southeastern part of QTP. The area of orchid species richness ranging from 6 to 11 under SSP370 in the 2070s was the smallest (9,370 km2: only accounting for 0.36% of QTP). The largest area of potential distribution for orchid species richness ranging from 6 to 11 was 45,394 km2 (accounting for 1.77% of QTP) under SSP585 in the 2070s. The total potential distribution area of 17 orchid species richness all increased from the 2050s to the 2070s under SSP126, SSP245, SSP370, and SSP585. The orchid species richness basically declined with the increasing elevation under current and future climate scenarios. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 under different climate scenarios was between 3,267 and 3,463 m. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 decreased from SSP126 (3,457 m) to SSP585 (3,267 m) in the 2070s. Based on these findings, future conservation plans should be concentrated on the selection of protected areas in the southeastern part of QTP to protect the endangered orchid species.

Investigation of Influencing Factors on the Prevalence of Retinopathy in Diabetic Patients Based on Medical Big Data.

As one of the most important organs of human beings, the eyes can receive external visual information and play an important role in perception. Therefore, the method of maintaining eye health is a problem that people pay attention to. Omental disease is one of the most serious microvascular complications in diabetic patients, and it is also the main cause of blindness in patients. The purpose of this article is to investigate the main factors that influence the prevalence of retinopathy in diabetic patients based on medical big data. In this article, a method for investigating the causes of the incidence of retinopathy in diabetic patients based on medical big data is proposed, and a questionnaire survey method and other methods are used for experimental investigation. Combining the data in the figure in the experiment in this article, it can be seen that among diabetic patients, the prevalence of diabetes in men is 12.4%, and the prevalence of diabetes in women is 8.4%. From the data in the figure, it can be known that the rate of retinopathy caused by various factors is between 5% and 7%, and the total prevalence of retinopathy is 47.5%. There are many factors affecting the prevalence of retinopathy in diabetic patients, such as the duration of diabetes, urinary albumin index, glycosylated hemoglobin index, and fasting blood glucose level; various factors lead to an increase in the prevalence of retinopathy in diabetic patients. The results show that there are many factors affecting the prevalence of retinopathy in diabetic patients, so patients should pay attention to exercise, control their diet, and prevent retinopathy.

"Green" Flexible Electronics: Biodegradable and Mechanically Strong Soy Protein-Based Nanocomposite Films for Human Motion Monitoring.

Soy protein isolate (SPI) is envisioned as a promising alternative to fabricate "green" flexible electronics, showing great potential in the field of flexible wearable electronics. However, it is challenging to simultaneously achieve conductive film-based human motion-monitoring strain sensors with reliable fatigue resistance, robust mechanical property, environmental degradability, and sensing capability of human motions. Herein, we prepared a series of SPI-based nanocomposite films by embedding a surface-hydroxylated high-dielectric constant inorganic filler, BaTiO3, (HBT) as interspersed nanoparticles into a biodegradable SPI substrate. In particular, the fabricated film comprising 0.5 wt % HBT and glycerin (GL), namely, SPI-HBT0.5-GL0.5, presents multifunctional properties, including a combination of excellent toughness, tensile strength, conductivity, translucence, recyclability, and excellent thermal stability. Meanwhile, this multifunctional film could be simply degraded in phosphate buffered saline solution and does not cause any pollution to the environment. Attractively, wearable sensors prepared with this particular material (SPI-HBT0.5-GL0.5) displayed excellent biocompatibility, prevented the occurrence of an immune response, and could accurately monitor various types of human joint motions and successfully remain operable after 10,000 cycles. These properties make the developed SPI-based film a great candidate in formulating biobased and multifunctional wearable electronics.

Nacre-Inspired Strong and Multifunctional Soy Protein-Based Nanocomposite Materials for Easy Heat-Dissipative Mobile Phone Shell.

Inspired by the hierarchically ordered "brick and mortar" (BM) architecture of natural nacre, in this study a rational assembly of boron nitride (BN) nanosheets was introduced into a mixture of trimethylolpropane triglycidyl ether (TTE) and soy protein isolate (SPI), and a strong and multifunctional SPI-based nanocomposite film with multinetwork structure was synthesized. At a low BN loading (<0.5%), the resulting multifunctional film was flexible, antiultraviolet, and nearly transparent and also displayed good thermal diffusion ability and exhibited an excellent combination of high tensile strength (36.4 MPa) and thermal conductivity (TC, 2.40 W·m-1·K-1), surpassing the performances of various types of petroleum-based plastics (displayed a tensile strength ranging from 1.9 to 21 MPa and TC ranging from 0.55-2.13 W·m-1·K-1), including nine different types of materials currently utilized for mobile phone shells, suggesting its vast potential in practical applications.

Hydrothermal combination and geometry control the spatial and temporal rhythm of glacier flow.

The dynamic response of glacier to atmospheric change has varied both spatially and temporally. While some of this variability is likely related to regional climate signals, the geometry of this particular glacier also appears to be important. In this study, we investigated the hydrothermal conditions and geometric controls on the temporal and spatial evolution of Baishui River Glacier No.1's velocity from 2012 to 2019. To do this, we combined field investigations and remote sensing observations to measure the velocity of the glacier, and factors controlling this velocity. Annual changes showed that, from 2012 to 2019, the Baishui River Glacier No. 1 experienced continuous shrinkage, accompanied by decreasing ice velocities. Seasonal changes showed that the glacier velocity during the monsoon period was significantly higher than during the non-monsoon period. Spatially, the glacier's dynamic variability decreased toward its terminus, but increased toward the upper reaches of the glacier, along a longitudinal axis. We would suggest that the interannual velocity variation of Baishui River Glacier No.1 corresponded to thinning of the glacier, which in turn affected its gravitational force. Given that surface melt-induced basal lubrication, basal friction controlled by freezing rate, and dynamic thickening can alter seasonal patterns of movement, these variations may be important for understanding the seasonal evolution of this, and other glaciers. Our results further indicated that glacier width, slope, surface meltwater and crevasses were important constraints on any spatial movement patterns.

Assessing the Impact of Climate Change on Potential Distribution of Meconopsis punicea and Its Influence on Ecosystem Services Supply in the Southeastern Margin of Qinghai-Tibet Plateau.

Meconopsis punicea is an iconic ornamental and medicinal plant whose natural habitat has degraded under global climate change, posing a serious threat to the future survival of the species. Therefore, it is critical to analyze the influence of climate change on possible distribution of M. punicea for conservation and sustainable utilization of this species. In this study, we used MaxEnt ecological niche modeling to predict the potential distribution of M. punicea under current and future climate scenarios in the southeastern margin region of Qinghai-Tibet Plateau. Model projections under current climate show that 16.8% of the study area is suitable habitat for Meconopsis. However, future projections indicate a sharp decline in potential habitat for 2050 and 2070 climate change scenarios. Soil type was the most important environmental variable in determining the habitat suitability of M. punicea, with 27.75% contribution to model output. Temperature seasonality (16.41%), precipitation of warmest quarter (14.01%), and precipitation of wettest month (13.02%), precipitation seasonality (9.41%) and annual temperature range (9.24%) also made significant contributions to model output. The mean elevation of suitable habitat for distribution of M. punicea is also likely to shift upward in most future climate change scenarios. This study provides vital information for the protection and sustainable use of medicinal species like M. punicea in the context of global environmental change. Our findings can aid in developing rational, broad-scale adaptation strategies for conservation and management for ecosystem services, in light of future climate changes.

Chinese caterpillar fungus (Ophiocordyceps sinensis) in China: Current distribution, trading, and futures under climate change and overexploitation.

Chinese caterpillar fungus (Ophiocordyceps sinensis) is a precious traditional medicine which is mostly distributed on the Qinghai-Tibetan Plateau (QTP). Due to its medicinal values, it has become one of the most valuable biological commodities and widely traded in recent years worldwide. However, its habitat has changed profoundly in recent years under global warming as well as anthropogenic pressures, resulting in a sharp decline in its wild population in recent years. Based on the occurrence samples, this paper estimates the potential distribution of caterpillar fungus using MaxEnt model. The model simulates potential geographical distribution of the species under current climate conditions, and examine future distributions under different climatic change scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 have been modelled in 2050s and 2070s, respectively). For examining the impacts of climate change in future, the integrated effects of climatic impact, trading, and overexploitation had been analyzed in detailed routes. The results show that: 1) The distribution patterns of caterpillar fungus under scenario RCP 2.6 have been predicted without obvious changes. However, range shift has been observed with significant shrinks across all classes of suitable areas in Tianshan, Kunlun Mountains, and the southwestern QTP in 2050s and 2070s under RCP 4.5, RCP 6.0 and RCP 8.5 scenarios, respectively. 2) The exports were decreasing drastically in recent years. Guangzhou and Hongkong are two international super import and consumption centres of caterpillar fungus in the world. 3) Both ecological and economic sustainable utilization of the caterpillar fungus has been threatened by the combined pressures of climate change and overexploitation. A strict but effective regulation and protection system, even a systematic management plan not just on the collectors but the whole explore process are urgently needed and has to be issued in the QTP.

Energy balance model of mass balance and its sensitivity to meteorological variability on Urumqi River Glacier No.1 in the Chinese Tien Shan.

Energy exchanges between atmosphere and glacier surface control the net energy available for snow and ice melt. Based on the meteorological records in Urumqi River Glacier No.1 (URGN1) in the Chinese Tien Shan during the period of 2012-2015, an energy-mass balance model was run to assess the sensitivity of glacier mass balance to air temperature (T), precipitation (P), incoming shortwave radiation (Sin), relative humidity (RH), and wind speed (u) in the URGN1, respectively. The results showed that the glacier melting was mainly controlled by the net shortwave radiation. The glacier mass balance was very sensitivity to albedo for snow and the time scale determining how long the snow albedo approaches the albedo for firn after a snowfall. The net annual mass balance of URGN1 was decreased by 0.44 m w.e. when increased by 1 K in air temperature, while it was increased 0.30 m w.e. when decreased by 1 K. The net total mass balance increased by 0.55 m w.e. when increased precipitation by 10%, while it was decreased by 0.61 m w.e. when decreased precipitation by 10%. We also found that the change in glacier mass balance was non-linear when increased or decreased input condition of climate change. The sensitivity of mass balance to increase in Sin, u, and RH were at -0.015 m w.e.%-1, -0.020 m w.e.%-1, and -0.018 m w.e.%-1, respectively, while they were at 0.012 m w.e.%-1, 0.027 m w.e.%-1, and 0.017 m w.e.%-1 when decreasing in those conditions, respectively. In addition, the simulations of coupled perturbation for temperature and precipitation indicated that the precipitation needed to increase by 23% could justly compensate to the additional mass loss due to increase by 1 K in air temperature. We also found that the sensitivities of glacier mass balance in response to climate change were different in different mountain ranges, which were mainly resulted from the discrepancies in the ratio of snowfall to precipitation during the ablation season, the amount of melt energy during the ablation season, and precipitation seasonality in the different local regions.

Emodin attenuates Alzheimer's disease by activating the protein kinase C signaling pathway.

To investigate the effects of emodin on learning and memory and protein kinase C (PKC) signaling pathway in Alzheimer's disease (AD) model mice. 60 APP/PS1 double transgenic AD mice were selected as model mice at the age of 7-8 months, 36 healthy male C57BL/6 mice served as the control group. Morris water maze method and passive avoidance experiment were used to evaluate the memory ability of mice. The thiazole blue (MTT) method and the lactate dehydrogenase (LDH) cytotoxicity test kit were used to evaluate the effect of emodin on the cell viability of hippocampal neurons in HT22 mice treated with ß-amyloid peptide 1-42 (Aß1-42). The effect of emodin on PKC levels was explored using the modified Takai method and Western blotting. Behavioral test results showed that the escape latency of the mice in the model group was longer than that in the control group (P<0.05), and the escape latency was significantly shortened given a emodin prognosis. The MTT and LDH test results showed that emodin to Aß- overexpression induced the protective effect of hippocampus cells in HT22 mice. Western blot analysis showed that the phosphorylation level of PKC in mice increased significantly after emodin administration. Emodin can attenuate oxidative stress and inflammatory response in Alzheimer's model mice by activating PKC pathway, thereby improving cognitive function.

ATDC contributes to sustaining the growth and invasion of glioma cells through regulating Wnt/ß-catenin signaling.

Accumulating evidence has documented that ataxia-telangiectasia group D complementing gene (ATDC) is aberrantly expressed in various cancers and is associated with cancer development and progression. However, little is known about the role of ATDC in glioma tumorigenesis. In this study, we aimed to explore the biological function and regulatory mechanism of ATDC in glioma. We found that ATDC expression was highly upregulated in glioma cell lines. Knockdown of ATDC significantly inhibited the growth and invasion of glioma cells. In contrast, overexpression of ATDC markedly promoted the growth and invasion of glioma cells. Moreover, our results showed that inhibition of ATDC reduced the expression levels of Dishevelled 2 (Dvl2) and ß-catenin and impeded the activation of Wnt/ß-catenin signaling, whereas overexpression of ATDC showed the opposite effect. Knockdown of Dvl2 significantly blocked the promotion effect of ATDC overexpression on activation of Wnt/ß-catenin signaling. In addition, silencing of ß-catenin partially reversed the oncogenic effect of ATDC overexpression in glioma cells. Taken together, out study reveals an oncogenic role of ATDC that drives the growth and invasion of glioma by modulating the Wnt/Dvl2/ß-catenin signaling pathway, suggesting a potential therapeutic target for treatment of glioma.

The Haze Nightmare Following the Economic Boom in China: Dilemma and Tradeoffs.

This study aims to expand on a deeper understanding of the relationship between rapid economic development and ensuing air pollution in China. The database includes the gross domestic product (GDP), the value added of a secondary industry, the per capita GDP (PGDP), greenhouse gases emissions, and PM2.5 concentrations. The results indicate that China's PGDP has continued to rise over the past decade, and the rate of PGDP slowed down from 1980 to 2004 (slope = 5672.81, R² = 0.99, p < 0.001) but was significantly lower than that from the year 2004 to 2013 (slope = 46,911.08, R² > 0.99, p < 0.001). Unfortunately, we found that total coal consumption, annual steel production, and SO2 emission had been continually growing as the overall economy expands at temporal scale, with the coefficient of determinations greater than 0.98 (p < 0.001). Considering the spatial pattern aspect, we also found a significant relationship between GDP and greenhouse gases. Meanwhile, severe air pollution has negatively impacted the environment and human health, particularly in some highlighted regions. The variation explained by both total SO2 emission and total smoke and dust emission were 33% (p < 0.001) and 24% (p < 0.01) for the rate of total pertussis at temporal scale, respectively. Furthermore, at the spatial scale, pulmonary tuberculosis rates and pertussis mainly occurred in area with serious air pollution (economically developed region). It can be summarized that the extensive mode of economic growth has brought a number of serious environment and human health problems. Thus, a new policy framework has been proposed to meet the goals of maintaining a healthy economy without harming natural environment, which may prove integral, especially when coupled with long-term national strategic development plans.

Spatio-temporal characteristics of global warming in the Tibetan Plateau during the last 50 years based on a generalised temperature zone-elevation model.

Temperature is one of the primary factors influencing the climate and ecosystem, and examining its change and fluctuation could elucidate the formation of novel climate patterns and trends. In this study, we constructed a generalised temperature zone elevation model (GTEM) to assess the trends of climate change and temporal-spatial differences in the Tibetan Plateau (TP) using the annual and monthly mean temperatures from 1961-2010 at 144 meteorological stations in and near the TP. The results showed the following: (1) The TP has undergone robust warming over the study period, and the warming rate was 0.318°C/decade. The warming has accelerated during recent decades, especially in the last 20 years, and the warming has been most significant in the winter months, followed by the spring, autumn and summer seasons. (2) Spatially, the zones that became significantly smaller were the temperature zones of -6°C and -4°C, and these have decreased 499.44 and 454.26 thousand sq km from 1961 to 2010 at average rates of 25.1% and 11.7%, respectively, over every 5-year interval. These quickly shrinking zones were located in the northwestern and central TP. (3) The elevation dependency of climate warming existed in the TP during 1961-2010, but this tendency has gradually been weakening due to more rapid warming at lower elevations than in the middle and upper elevations of the TP during 1991-2010. The higher regions and some low altitude valleys of the TP were the most significantly warming regions under the same categorizing criteria. Experimental evidence shows that the GTEM is an effective method to analyse climate changes in high altitude mountainous regions.