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Abstract Background Since diagnosis of mood disorder heavily depends on signs and symptoms, emerging researches have been studying biomarkers with the attempt to improve diagnostic accuracy, but none of the findings have been broadly accepted. The purpose of the present study was to construct a preliminary diagnostic model to distinguish major depressive disorder (MDD) and bipolar disorder (BD) using potential commonly tested blood biomarkers. Methods Information of 721 inpatients with an ICD-10 diagnosis of MDD or BD were collected from the electronic medical record system. Variables in the nomogram were selected by best subset selection method after a prior univariable screening, and then constructed using logistic regression with inclusion of the psychotropic medication use. The discrimination, calibration and internal validation of the nomogram were evaluated by the receiver operating characteristic curve (ROC), the calibration curve, cross validation and subset validation method. Results The nomogram consisted of five variables, including age, eosinophil count, plasma concentrations of prolactin, total cholesterol, and low-density lipoprotein cholesterol. The model could discriminate between MDD and BD with an area under the ROC curve (AUC) of 0.858, with a sensitivity of 0.716 and a specificity of 0.890. Conclusion The comprehensive nomogram constructed by the present study can be convenient to distinguish MDD and BD since the incorporating variables were common indicators in clinical practice. It could help avoid misdiagnoses and improve prognosis of the patients.

The impact of changing climate on vegetation in dryland is a prominent focus of global research. As a typical arid region in the world, Central Asia is an ideal area for studying the associations between climate and arid-area vegetation. Utilizing data from the European Centre for Medium-Range Weather Forecasts fifth-generation reanalysis (ECMWF ERA-5) and normalized difference vegetation index (NDVI) datasets, this study investigates the spatio-temporal variation characteristics of the NDVI in Central Asia. It quantitatively assesses the contribution rates of climatic factors to vegetation changes and elucidates the impact of an increased vapor pressure deficit (VPD) on vegetation changes in Central Asia. The results indicate that the growing seasons’ NDVI exhibited a substantial increase in Central Asia during 1982–2015. Specifically, there was a pronounced “greening” process (0.012/10 yr, p < 0.05) from 1982 to 1998. However, an insignificant “browning” trend was observed after 1998. Spatially, the vegetation NDVI in the growing seasons exhibited a pattern of “greening in the east and browning in the west” of Central Asia. During spring, the dominant theme was the “greening” of vegetation NDVI, although there was noticeable “browning” observed in southwest region of Central Asia. During summer, the “browning” of vegetation NDVI further expanded eastward and impacted the entire western Central Asia in autumn. According to the estimated results computed via the partial differential equation method, the “browning” trend of vegetation NDVI during the growing seasons was guided by increased VPD and decreased rainfall in western Central Asia. Specifically, the increased VPD contributed 52.3% to the observed vegetation NDVI. Atmospheric drought depicted by the increase in VPD significantly lowers the “greening” trend of vegetation NDVI in arid regions, which further aggravates the “browning” trend of vegetation NDVI.

BackgroundBacterium/fungus-associated pneumonia (BAP/FAP) is the prominent cause of high mortality and morbidity with important clinical impacts globally. Effective diagnostic methods and proper specimen types hopefully facilitate early diagnosis of pneumonia and prevent spread of drug-resistant bacteria/fungi among critically ill patients.MethodsIn the present study, 342 bronchoalveolar lavage fluid (BALF) samples were collected from critically ill patients with pulmonary infections between November 2020 and March 2021. The BALF materials were comparatively employed to screen BAP/FAP through microscopy, culture, antigenic marker and PCR-based methods. The limit of detection (LOD) of cultures and PCR for bacteria/fungi was determined by serial dilution assays. Specimen slides were prepared with Gram staining for microscopic examinations. Microbial cultures and identifications underwent routine clinical protocols with the aid of mass spectrometry. (1,3)-β-D-glucan and galactomannan tests with BALF were carried out accordingly. Direct detection of pathogens in BALF was achieved through PCR, followed by sequencing and BLAST in GenBank database for pathogenic identification. The subjects’ demographic and clinical characteristics were well evaluated.ResultsBAP/FAP was identified in approximately 47% of the subjects by the BALF-based PCR. The PCR-based diagnostic methods showed improved detection performance for fungi with good LOD, but performed similarly for bacteria, when compared to the cultures. There was poor agreement among traditional microscopy, culture and PCR assays for bacterial detections (kappa value, 0.184 to 0.277). For overall bacterial/fungal detections, the microscopy showed the lowest detecting rate, followed by the cultures, which displayed a slightly higher sensitivity than the microscopy did. The sensitivity of PCR was much higher than that of the other means of interest. However, the traditional cultures rather than antigenic marker-based approaches were moderately consistent with the PCR-based methods in fungal species identification, particularly for Candida and Aspergillus spp. Our findings further revealed that the age, length of hospital stay, invasive procedures and cerebral diseases were likely considered as main risk factors for BAP/FAP.ConclusionScreening for BALF in critically ill patients with suspected pneumonia pertaining high risk factors using combined PCR-based molecular detection strategies would hopefully contribute to early diagnosis of BAP/FAP and improved prognosis of the patients.

The Taklimakan Desert (TD) is the largest desert in China located in the Tarim Basin (TB) in China’s arid region. This study is a review of the change in precipitation and its extremes since 1961 and the high-impact extreme precipitation events in 2012–2021, particularly in 2021, with a focus on the TD along with the surrounding oases and mountainous regions.The TB has experienced significantly warmer and wetter trends since 1961, and extreme rainfall has increased significantly in the TD and its surrounding areas during the 2000s. In the TB, the year 2021 was identified as the 4th warmest for 1961–2021, and was remembered for unprecedented extreme events. Three high-impact extreme events that occurred in 2021 are highlighted, including extreme heavy rainfall over Hetian in mid-June. The earliest extreme rainfall event occurred over North Bazhou in early spring, and the strongest heavy snowfall over Baicheng in April. In addition, we also discussed the underlying physical mechanisms of extreme events over the TB and proposed novel perspectives and unresolved questions on the sciences of heavy rainfall in arid regions. Our results provide a reference for the physical mechanism, attribution, and high-resolution modeling of extreme events.

This study proposes a two-level optimization model system for vehicle control and signal timing at isolated signal intersections under the mixed traffic flow environment composed of intelligent connected autonomous vehicles (CAVs) and connected human-driven vehicles (CHVs), to minimize the energy consumption and vehicle delay at intersections. The proposed two-layer optimization model is composed of a two-layer vehicle trajectory control model and a fuzzy control signal timing optimization model. The two-layer vehicle trajectory control model includes a signal-oriented vehicle trajectory control model and a car-following oriented vehicle trajectory control model. The former calculates expected acceleration and speed commands at each time step according to the coming signal information, to help vehicle pass the closest signal intersection without stopping during the green light interval; the latter uses the variable headway (VTH) strategy to follow the preceding vehicle by maintaining a safe distance. A microscopic simulator based on SUMO is developed to test the performance of the proposed optimization algorithm. In the simulation experiment, with the driving characteristics of CHV drivers considered, the results show that our model performs well under a CAV penetration rate of 30%–60% and under small or moderate levels of traffic flow. The average waiting time of vehicles is reduced by about 25% compared with the uncontrolled scheme. Under the condition of penetration rate of 60%, the average energy consumption of vehicles in the proposed model is 17.56% lower than that of the uncontrolled scheme. In addition, the proposed model reduces by 21.94% compared with the scheme of only controlling vehicles. When the traffic flow is at a low or medium level, the average energy consumption and waiting time of vehicles are reduced by nearly 35% with the proposed model.

The present study aims to enrich the research on online entrepreneurship education, improve the level and ability of entrepreneurship services in China, and improve the overall success rate of entrepreneurship. Based on the technology acceptance model (TAM) proposed by researcher Davis, the study explores the application of TAM in online entrepreneurship education for new entrepreneurs. First, new entrepreneurs who are users of the online entrepreneurship education platform are selected as research objects, and then the influence of the four factors are studied, including perceived ease of use, perceived usefulness, classroom self-efficacy, and perceived external control. Finally, the hypothesis proposed is tested. Results show that online entrepreneurship education influences the perceived ease of use of the user and perceived credibility: the quality of the online entrepreneurship education has a positive impact on the user's perceived usefulness, interactivity has a positive influence on perceived ease of use and perceived usefulness, and interactivity positively influences the perceived ease of use of the user and perceived credibility. Perceived usefulness, perceived ease of use, and perceived credibility have a positive impact on the behavioral intention of the users. The proposed TAM provides some technical and theoretical support for the application of TAM in online entrepreneurship education for new entrepreneurs.

Desert locusts are notorious for their widespread distribution and strong destructive power. Their influence extends from the vast arid and semiarid regions of western Africa to northwestern India. Large-scale locust outbreaks can have devastating consequences for food security, and their social impact may be long-lasting. Climate change has increased the uncertainty of desert locust outbreaks, and predicting suitable habitats for this species under climate change scenarios will help humans deal with the potential threat of locust outbreaks. By comprehensively considering climate, soil, and terrain variables, the maximum entropy (MaxEnt) model was used to predict the potential habitats of solitary desert locusts in the 2050s and 2070s under the four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. The modeling results show that the average area under the curve (AUC) and true skill statistic (TSS) reached 0.908 ± 0.002 and 0.701, respectively, indicating that the MaxEnt model performed extremely well and provided outstanding prediction results. The prediction results indicate that climate change will have an impact on the distribution of the potential habitat of solitary desert locusts. With the increase in radiative forcing overtime, the suitable areas for desert locusts will continue to contract, especially in the 2070s under the SSP585 scenario, and the moderately and highly suitable areas will decrease by 0.88 × 106 km2 and 1.55 × 106 km2, respectively. Although the potentially suitable area for desert locusts is contracting, the future threat posed by the desert locust to agricultural production and food security cannot be underestimated, given the combination of maintained breeding areas, frequent extreme weather events, pressure from population growth, and volatile sociopolitical environments. In conclusion, methods such as monitoring and early warning, financial support, regional cooperation, and scientific prevention and control of desert locust plagues should be further implemented.

Xinjiang, an arid region of China, has experienced a substantial warming–wetting trend over the past five decades. However, climate change has affected vegetation growth/greening in arid Central Asia in unexpected ways due to complex ecological effects. We found a significant greening trend (consistent increase in the normalized difference vegetation index or NDVI) from 1982 to 1996, during the growing season; however, the NDVI consequently decreased and plateaued from 1997 to 2015, especially in naturally vegetated regions. Atmospheric vapor pressure deficit (VPD) is a critical driver of vegetation growth, is a direct measure of atmospheric aridity, and has increased sharply in recent decades. A partial correlation analysis indicated a significant relationship between growing season NDVI and VPD from 1997 to 2015. This implies that decreased VPD corresponds to increasing NDVI, and increasing VPD corresponds to a decrease and plateauing in the NDVI trend. Using the partial derivative equation method, our results suggest that the trend in growing season NDVI was affected primarily by increasing VPD (contributing 87.57%) from 1997 to 2015, especially in the grassland and desert biomes. Rising temperatures lead to a greater VPD, resulting in exacerbated evaporative water loss. Soil drought and atmospheric aridity limit plant stomatal conductance and could effectively lead to a decrease in the greening trend and increased vegetation mortality in arid Xinjiang. Our results emphasize the importance of VPD as a limiting factor of greening trends in arid regions. The influence of VPD on vegetation growth should be considered when evaluating arid ecosystem functioning under global warming.

Satellite-derived vegetation records (GIMMS3g-NDVI) report that climate warming promotes vegetation greening trends; however, the climate impacts on vegetation growth during the global warming hiatus period (1998–2012) remain unclear. In this study, we focused on the vegetation change trend in Xinjiang in spring and autumn before and during the recent warming hiatus period, and their climate-driving mechanisms, which have not been examined in previous studies. Based on satellite records, our results indicated that the summer normalized difference vegetation index (NDVI) in Xinjiang experienced a greening trend, while a browning trend existed in spring and autumn during this period. The autumn NDVI browning trend in Xinjiang was larger than that in spring; however, the spring NDVI displayed a higher correlation with climatic factors than did the autumn NDVI. During the warming hiatus, spring climatic factors were the main controlling factors of spring NDVI, and spring vapor pressure deficit (VPD) had the highest positive correlation with spring NDVI, followed by spring temperature. The larger increase in air temperature in spring than in autumn resulted in increased VPD differences in spring and autumn. In autumn, summer climatic factors (e.g., VPD, WS, RH, and precipitation) were significantly correlated with the autumn NDVI during the warming hiatus. However, the autumn temperature was weakly correlated with the autumn NDVI. Our results have significant implications for understanding the response of vegetation growth to recent and future climatic conditions.

The dynamics of the ecosystem represented by vegetation under the influence of human activities have become an important issue in the study of the regional ecological environment. Xinjiang is one of the most ecologically fragile areas in the world, and vegetation changes have received extensive attention. Xinjiang is one of the most ecologically fragile areas in the world, and vegetation changes have received extensive attention. However, the spatiotemporal patterns and evolutionary trends of anthropogenic impacts on vegetation dynamics in Xinjiang are still unclear. In this study, the anthropogenic impacts on vegetation dynamics were quantitatively assessed by combining the improved normalized difference vegetation index (NDVI) prediction model and the residual analysis method in Xinjiang, China. The human driving factors were analyzed with the support of a stepwise multiple regression model for vegetation changes at the county scale. Based on trend analysis and the Hurst exponent, the spatiotemporal characteristics and evolutionary trends of the impact of human activities on vegetation change were discussed. The results show that (1) the NDVI values in Xinjiang showed a gradually increasing trend at a rate of 0.005/10 years from 1982 to 2018, and the vegetation dynamics mainly showed significant improvements (57.09% of the vegetated areas), especially for crops. (2) The anthropogenic effects of vegetation changes in Xinjiang mainly included positive impact increases (43.22% of the vegetated areas) from 2000 to 2018. Human activities promoted the increase in the NDVI of various vegetation types. Both the positive and negative impacts of human activities increased over the study period, and the growth rate of the positive influence (0.08%/10 years) was higher than that of the negative influence (0.04%/10 years). (3) The cultivated area, GDP of primary industry, and population are the main anthropogenic factors causing the increase in NDVI, which dominate the vegetation greening in 30.34%, 29.22%, and 28.09% of the counties in Xinjiang, respectively. The animal husbandry population, agricultural population, and livestock number are the main anthropogenic factors causing the decrease in NDVI, which dominate the vegetation degradation in 23.60%, 21.35%, and 17.98% of the counties in Xinjiang, respectively. (4) The evolutionary trend of the anthropogenic impact on vegetation dynamics in Xinjiang will be dominated by anti-persistence (53.84% of the vegetated areas), thereby mainly showing that the positive impacts continued to increase (22.56% of the vegetated areas), especially for crops, shrubs, grasslands, and alpine vegetation. Our results are helpful in understanding the characteristics and evolutionary trends of vegetation changes in arid areas caused by human activities and are of significance as a reference for policymakers to appropriately adjust policy guidance in a timely manner to promote the protection and sustainable development of fragile ecosystems.

α-Fe2O3 fusiform nanorods were prepared by a simple hydrothermal method employing the mixture of FeCl3·6H2O and urea as raw materials. The samples were examined by X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy and UV–vis diffuse reflectance spectra (UV–DRS). Its visible-light photocatalytic performances were evaluated by photocatalytic decolorization methylene blue (MB) in visible light irradiation. It was found that pure phase α-Fe2O3 nanorods with a length of about 125 nm and a diameter of 50 nm were successfully synthesized. The photocatalytic decolorization of MB results indicated that α-Fe2O3 nanorods showed higher photocatalytic activity than that of commercial Fe2O3 nanoparticles—these are attributed to its unique three-dimensional structure and lower electron-hole recombination rate.

The trillions of commensal microorganisms comprising the gut microbiota have received growing attention owing to their impact on host physiology. Recent advances in our understandings of the host–microbiota crosstalk support a pivotal role of microbiota-derived metabolites in various physiological processes, as they serve as messengers in the complex dialogue between commensals and host immune and endocrine cells. In this review, we highlight the importance of tryptophan-derived metabolites in host physiology, and summarize the recent findings on the role of tryptophan catabolites in preserving intestinal homeostasis and fine-tuning immune and metabolic responses. Furthermore, we discuss the latest evidence on the effects of microbial tryptophan catabolites, describe their mechanisms of action, and discuss how perturbations of microbial tryptophan metabolism may affect the course of intestinal and extraintestinal disorders, including inflammatory bowel diseases, metabolic disorders, chronic kidney diseases, and cardiovascular diseases.

Exhausted exercise has been reported to cause the damage of myocardial structure and function in terms of cardiomyocyte apoptosis, oxidative stress, and energy metabolism disturbance. Trimetazidine (TMZ), as an anti-ischemic agent, has been approved to be effective in promoting myocardial energy metabolism, anti-inflammatory, and anti-oxidation. However, few studies examined the effects of TMZ on myocardial injury induced by exhausted exercise. To investigate whether TMZ could ameliorate the exhaustive exercise-induced myocardial injury and explore the underlying mechanisms, here the rat model of exhaustive exercise was induced by prolonged swimming exercise and TMZ was administrated to rats before exhaustive exercise. According to the results, we demonstrated that exhaustive exercise led to cardiomyocyte damage in rats as evidenced by elevations in cTnI and NT-proBNP levels, and decrease in CX43 expression, which was attenuated by TMZ treatment. Moreover, the administration of TMZ was found to restrain exhaustive exercise-induced oxidative stress damage by increasing GSH level, SOD and GSH-Px activities, and decreasing MDA level. Additionally, TMZ ameliorated myocardial injury by inhibiting apoptosis via reducing Bax/Bcl-2 ratio and down-regulating cleaved caspase-3, cleaved PARP, and cytochrome c levels in the myocardium of rats. Furthermore, we found that TMZ suppressed oxidative stress and cardiomyocyte apoptosis via activation of Nrf2/HO-1 and inactivation of NF-κB signaling pathways. Therefore, our study suggested that TMZ provided cardioprotection in rats after exhaustive exercise, indicating TMZ might served as a potential therapeutic drug for exhaustive exercise-induced myocardial injury.

Diabetic nephropathy is a major cause of chronic kidney disease and end-stage kidney disease. However, so little is known about alterations of the glycopatterns in urine with the development of diabetic nephropathy. Presently, we interrogated glycopatterns in urine specimens using a lectin microarray. The results showed that expression levels of Siaα2-6Gal/GalNAc recognized by SNA exhibited significantly increased tendency with the development of diabetic nephropathy; moreover, SNA blotting indicated glycoproteins (90 kDa, 70 kDa, and 40 kDa) in urine may contribute to this alteration. Furthermore, the glycopatterns of (GlcNAc)2–4 recognized by STL exhibited difference between diabetic and nondiabetic nephropathy. The results of urinary protein microarray fabricated by another 48 urine specimens also indicated (GlcNAc)2–4 is a potential indictor to differentiate the patients with diabetic nephropathy from nondiabetic nephropathy. Furtherly, STL blotting showed that the 50 kDa glycoproteins were correlated with this alteration. In conclusion, our data provide pivotal information to monitor the development of diabetic nephropathy and distinguish between diabetic nephropathy and nondiabetic renal disease based on precise alterations of glycopatterns in urinary proteins, but further studies are needed in this regard.