Pathogenicity and landscape of differential gene expression in mice orally infected with clinical coxsackievirus A6 (CA6).

Hand, foot, and mouth disease (HFMD) is caused by more than 20 pathogenic enteroviruses belonging to the Picornaviridae family and Enterovirus genus. Since the introduction of the enterovirus-71 (EV71) vaccine in 2016, the number of HFMD cases caused by EV71 has decreased. However, cases of infections caused by other enteroviruses, such as coxsackievirus A6 (CA6) and coxsackievirus A10, have been increasing accordingly. In this study, we used a clinical isolate of CA6 to establish an intragastric infection mouse model using 7-day-old mice to mimic the natural transmission route, by which we investigated the differential gene expression profiles associated with virus infection and pathogenicity. After intragastric infection, mice exhibited hind limb paralysis symptoms and weight loss, similar to those reported for EV71 infection in mice. The skeletal muscle was identified as the main site of virus replication, with a peak viral load reaching 2.31 × 107 copies/mg at 5 dpi and increased infiltration of inflammatory cells. RNA sequencing analysis identified differentially expressed genes (DEGs) after CA6 infection. DEGs in the blood, muscle, brain, spleen, and thymus were predominantly enriched in immune system responses, including pathways such as Toll-like receptor signaling and PI3K-Akt signaling. Our study has unveiled the genes involved in the host immune response during CA6 infection, thereby enhancing our comprehension of the pathological mechanism of HFMD.IMPORTANCEThis study holds great significance for the field of hand, foot, and mouth disease (HFMD). It not only delves into the disease's etiology, transmission pathways, and severe complications but also establishes a novel mouse model that mimics the natural coxsackievirus A6 infection process, providing a pivotal platform to delve deeper into virus replication and pathogenic mechanisms. Additionally, utilizing RNA-seq technology, it unveils the dynamic gene expression changes during infection, offering valuable leads for identifying novel therapeutic drug targets. This research has the potential to enhance our understanding of HFMD, offering fresh perspectives for disease prevention and treatment and positively impacting children's health worldwide.

Predictive factors for intrathoracic anastomotic leakage and postoperative mortality after esophageal cancer resection.

BACKGROUND: Esophageal cancer is currently one of the high-risk malignant tumors worldwide, posing a serious threat to human health. This study aimed to analyse the causes of postoperative mortality and intrathoracic anastomotic leakage(IAL) after esophagectomy. METHODS: A retrospective analysis was conducted on 172 patients with esophageal cancer resection and focused on the preoperative and postoperative indicators. Cox regression analysis was performed to identify factors affected IAL and evaluated the potential factors on postoperative mortality. The Kaplan-Meier curve was applied to evaluate the effect of leakage on postoperative mortality after propensity score matching. RESULTS: Univariable and multivariable Cox regression analysis showed that infection and high BMI were significant risk factors for IAL, patients with BMI over 24 kg/m2 in IAL group was two times higher than that of the group without IAL (95% CI = 1.01-6.38; P = 0.048). When patients were infected, the hazard ratios(HRs) of anastomotic leakage was twice that of patients without infection (95% CI = 1.22-4.70; P = 0.011). On the other hand, IAL was a significant cause of postoperative mortality, the 40-day postoperative mortality rate in the leakage group was significantly higher than the non leakage group (28.95% in leakage group vs. 7.46% in non leakage group, P<0.01). After propensity score matching, IAL still significantly affected postoperative mortality. The total length of hospital stay of the leakage group was inevitably longer than that of the non leakage group (22.19 ± 10.79 vs. 15.27 ± 8.59). CONCLUSION: IAL was a significant cause of death in patients underwent esophageal cancer resection. Patients with high BMI over 24 kg/m2 and infection may be more prone to developing IAL after esophagectomy. IAL inevitably prolonged the length of hospital stay and increased postoperative mortality.

Narrowband Internet of Things via Low Earth Orbit Satellite Networks: An Efficient Coverage Enhancement Mechanism Based on Stochastic Geometry Approach.

With the development of IoT technology and 5G massive machine-type communication, the 3GPP standardization body considered as viable the integration of Narrowband Internet of Things (NB-IoT) in low Earth orbit (LEO) satellite-based architectures. However, the presence of the LEO satellite channel comes up with new challenges for the NB-IoT random access procedures and coverage enhancement mechanism. In this paper, an Adaptive Coverage Enhancement (ACE) method is proposed to meet the requirement of random access parameter configurations for diverse applications. Based on stochastic geometry theory, an expression of random access channel (RACH) success probability is derived for LEO satellite-based NB-IoT networks. On the basis of a power consumption model of the NB-IoT terminal, a multi-objective optimization problem is formulated to trade-off RACH success probability and power consumption. To solve this multi-objective optimization problem, we employ the Non-dominated Sorting Genetic Algorithms-II (NSGA-II) method to obtain the Pareto-front solution set. According to different application requirements, we also design a random access parameter configuration method to minimize the power consumption under the constraints of RACH success probability requirements. Simulation results show that the maximum number of repetitions and back-off window size have a great influence on the system performance and their value ranges should be set within [4, 18] and [0, 2048]. The power consumption of coverage enhancement with ACE is about 58% lower than that of the 3GPP proposed model. All this research together provides good reference for the scale deployment of NB-IoT in LEO satellite networks.

Research on Terminal Access Performance of Beam-Hopping Satellite in IoT Scenario.

In recent years, low-orbit satellites have become an important development direction in satellite IoT systems. The number of terminals is large and data collisions occur frequently in the low-orbit satellite IoT scenario. How to design a reliable random access protocol to improve the tolerance of the system for collision is one of the research hotspots in this field. In this paper, the random access protocol, used in the Internet of Things (IoT), for low-orbit satellites is studied, and the access process of the IoT terminals in the scenario is constructed. The access performance of the SSA protocol is analyzed and an improved SSA random access strategy, called Retransmission-SSA (R-SSA), is proposed. The simulation results show that the designed R-SSA can effectively tolerate the signal conflicts between terminals in the beam-hopping LEO IoT scenario and improve the probability of the concurrent access of low-orbit sIoT terminals.

An Asynchronous Collision-Tolerant ACRDA Scheme Based on Satellite-Selection Collaboration-Beamforming for LEO Satellite IoT Networks.

In this paper, an asynchronous collision-tolerant ACRDA scheme based on satellite-selection collaboration-beamforming (SC-ACRDA) is proposed to solve the avalanche effect caused by packet collision under random access (RA) high load in the low earth orbit (LEO) satellite Internet of Things (IoT) networks. A non-convex optimization problem is formulated to realize the satellite selection problem in multi-satellite collaboration-beamforming. To solve this problem, we employ the Charnes-Cooper transformation to transform a convex optimization problem. In addition, an iterative binary search algorithm is also designed to obtain the optimization parameter. Furthermore, we present a signal processing flow combined with ACRDA protocol and serial interference cancellation (SIC) to solve the packet collision problem effectively in the gateway station. Simulation results show that the proposed SC-ACRDA scheme can effectively solve the avalanche effect and improve the performance of the RA protocol in LEO satellite IoT networks compared with benchmark problems.

Nighttime Image Stitching Method Based on Image Decomposition Enhancement.

Image stitching technology realizes alignment and fusion of a series of images with common pixel areas taken from different viewpoints of the same scene to produce a wide field of view panoramic image with natural structure. The night environment is one of the important scenes of human life, and the night image stitching technology has more urgent practical significance in the fields of security monitoring and intelligent driving at night. Due to the influence of artificial light sources at night, the brightness of the image is unevenly distributed and there are a large number of dark light areas, but often these dark light areas have rich structural information. The structural features hidden in the darkness are difficult to extract, resulting in ghosting and misalignment when stitching, which makes it difficult to meet the practical application requirements. Therefore, a nighttime image stitching method based on image decomposition enhancement is proposed to address the problem of insufficient line feature extraction in the stitching process of nighttime images. The proposed algorithm performs luminance enhancement on the structural layer, smoothes the nighttime image noise using a denoising algorithm on the texture layer, and finally complements the texture of the fused image by an edge enhancement algorithm. The experimental results show that the proposed algorithm improves the image quality in terms of information entropy, contrast, and noise suppression compared with other algorithms. Moreover, the proposed algorithm extracts the most line features from the processed nighttime images, which is more helpful for the stitching of nighttime images.

Temperature and Precipitation Drive Elevational Patterns of Microbial Beta Diversity in Alpine Grasslands.

Understanding the mechanisms underlying biodiversity patterns is a central issue in ecology, while how temperature and precipitation jointly control the elevational patterns of microbes is understudied. Here, we studied the effects of temperature, precipitation and their interactions on the alpha and beta diversity of soil archaea and bacteria in alpine grasslands along an elevational gradient of 4300-5200 m on the Tibetan Plateau. Alpha diversity was examined on the basis of species richness and evenness, and beta diversity was quantified with the recently developed metric of local contributions to beta diversity (LCBD). Typical alpine steppe and meadow ecosystems were distributed below and above 4850 m, respectively, which was consistent with the two main constraints of mean annual temperature (MAT) and mean annual precipitation (MAP). Species richness and evenness showed decreasing elevational patterns in archaea and nonsignificant or U-shaped patterns in bacteria. The LCBD of both groups exhibited significant U-shaped elevational patterns, with the lowest values occurring at 4800 m. For the three diversity metrics, soil pH was the primary explanatory variable in archaea, explaining over 20.1% of the observed variation, whereas vegetation richness, total nitrogen and the K/Al ratio presented the strongest effects on bacteria, with relative importance values of 16.1%, 12.5% and 11.6%, respectively. For the microbial community composition of both archaea and bacteria, the moisture index showed the dominant effect, explaining 17.6% of the observed variation, followed by MAT and MAP. Taken together, temperature and precipitation exerted considerable indirect effects on microbial richness and evenness through local environmental and energy supply-related variables, such as vegetation richness, whereas temperature exerted a larger direct influence on LCBD and the community composition. Our findings highlighted the profound influence of temperature and precipitation interactions on microbial beta diversity in alpine grasslands on the Tibetan Plateau.

Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment.

We investigate a distributed-satellite-clusters (DSC)-system-based spectrum sensing, to enhance the ability for sensing weak signals. However, the spectrum-sensing performance may be significantly decreased by the phase deviations among different satellite clusters, where the deviations may be caused by the movement and the perturbation of satellites. To eliminate such a decrement, we propose a cooperative spectrum-sensing scheme in the presence of phase deviations, where the deviations are alleviated by a special two-stage phase synchronization. Specifically, the phase compensation is first performed relying on broadcasting reference signals and the ephemeris, to address the challenges of the deviations caused by the movement. Then, a two-bit feedback algorithm, having a dynamic disturbance step size, is further adopted for controlling and mitigating the deviations caused by the perturbation. Additionally, we provide the closed-form expression of the correct detection probability of the proposed spectrum-sensing scheme, using the specially derived probability density function of the sum of the shadowed-Rician random variables with independently identical distribution. Simulation results show that the proposed scheme can achieve the best spectrum-sensing performance, comparing with the traditional energy detection, eigenvalue ratio test and the generalized likelihood ratio test.

Nighttime Image Stitching Method Based on Guided Filtering Enhancement.

Image stitching refers to stitching two or more images with overlapping areas through feature points matching to generate a panoramic image, which plays an important role in geological survey, military reconnaissance, and other fields. At present, the existing image stitching technologies mostly adopt images with good lighting conditions, but the lack of feature points in scenes with weak light such as morning or night will affect the image stitching effect, making it difficult to meet the needs of practical applications. When there exist concentrated areas of brightness such as lights and large dark areas in the nighttime image, it will further cause the loss of image details making the feature point matching unavailable. The obtained perspective transformation matrix cannot reflect the mapping relationship of the entire image, resulting in poor splicing effect, and it is difficult to meet the actual application requirements. Therefore, an adaptive image enhancement algorithm is proposed based on guided filtering to preprocess the nighttime image, and use the enhanced image for feature registration. The experimental results show that the image obtained by preprocessing the nighttime image with the proposed enhancement algorithm has better detail performance and color restoration, and greatly improves the image quality. By performing feature registration on the enhanced image, the number of matching logarithms of the image increases, so as to achieve high accuracy for images stitching.

Daylight-White-Emitting and Abnormal Thermal Antiquenching Phosphors Based on a Layered Host SrIn2(P2O7)2.

Single-phase white-emission phosphors possess a judicious usage potential in phosphor-converted white-light-emitting diodes (WLEDs). Recently, numerous efforts have been made toward the development of new patterns of white-emitting phosphors that achieve excellent quantum yield, superior thermal stability, and applaudable cost effectiveness of WLEDs. Finding suitable single-component white phosphor hosts to provide an ideal local environment for activators remains urgent. Inspired by the original discovery of the promising host MgIn2(P2O7)2 (MIP) and its structural dependence on alkali-metal cations, we synthesized a brand-new phosphor host, SrIn2(P2O7)2 (SIP), via the traditional solid-state reaction. Its crystal structure was determined using an ab initio analysis and the Rietveld method. It belongs to a monoclinic unit cell with the space group C2/c. Besides, SIP exhibits a special layered three-dimensional framework in which the monolayer [SrO10]∞ was surrounded by a bilayer [In2P4O14]∞ made of the InO6 octahedra and P2O7 groups. A series of pure SIP:Tm3+,Dy3+ phosphors with tunable blue-white-yellow emission were prepared by adjusting the dopant concentration and utilizing the Tm3+-Dy3+ energy transfer. The daylight-white-emitting phosphor SIP:0.01Tm3+,0.04Dy3+ (the correlated color temperature is 4448 K) exhibits an abnormal thermal antiquenching property, and the emission intensity of 423 K reaches 103.7% of the initial value at 300 K. On the basis of the temperature-dependent lattice evolution and microenvironment analysis, the reduction of ß and lattice distortion can lead to lower asymmetry of the activators and benefit the compensation of trapped-electron thermal activation. In this work, an integration study was carried out on the crystal structure of the new matrix, the occupation of the luminescent center, the interaction of different activators in the host, and the distortion degree of the local structure for the activators, which is of great practical sense for producing a novel single-matrix white phosphor possessing superior thermal endurance for UV-light-stimulated WLEDs.

Effect of increasing precipitation and warming on microbial community in Tibetan alpine steppe.

Soil microorganisms play an important role in regulating the feedback of Alpine steppe ecosystems to future climate change. However, the interaction effect of warming and increasing precipitation on soil microorganisms remains unclear, in the face of an ongoing warmer and wetter climate on the Tibetan Plateau. In this study, we investigate the multi-factorial effects on soil microbial diversity, community structure, and microbial interactions in a three-year climate change experiment established in an Alpine steppe on the Tibetan Plateau, involving warming (+2 °C), +15% increasing precipitation and +30% increasing precipitation. Compared to warming, warming plus increasing precipitation alleviated the decrease in microbial diversity, and increased the dissimilarities in microbial community structures, largely influenced by water and substrate availability. We further observed differences in moisture increased the differences in microbial diversity and dissimilarities in microbial community structures across different precipitation levels under ambient temperature. Interestingly, warming plus increasing precipitation could create more ecological niches for microbial species to coexist but may lessen the strength of microbial interactions in contrast to increasing precipitation alone. Collectively, our findings indicate that microbial responses to future climate change in Alpine steppe soils will be more complex than those under single-climate-factor conditions.

Comparative genomic analysis reveals metabolic diversity of different Paenibacillus groups.

The genus Paenibacillus was originally recognized based on the 16S rRNA gene phylogeny. Recently, a standardized bacterial taxonomy approach based on a genome phylogeny has substantially revised the classification of Paenibacillus, dividing it into 23 genera. However, the metabolic differences among these groups remain undescribed. Here, genomes of 41 Paenibacillus strains comprising 25 species were sequenced, and a comparative genomic analysis was performed considering these and 187 publicly available Paenibacillus genomes to understand their phylogeny and metabolic differences. Phylogenetic analysis indicated that Paenibacillus clustered into 10 subgroups. Core genome and pan-genome analyses revealed similar functional categories among the different Paenibacillus subgroups; however, each group tended to harbor specific gene families. A large proportion of genes in the subgroups A, E, and G are related to carbohydrate metabolism. Among them, genes related to the glycoside hydrolase family were most abundant. Metabolic reconstruction of the newly sequenced genomes showed that the Embden-Meyerhof-Parnas pathway, pentose phosphate pathway, and citric acid cycle are central pathways of carbohydrate metabolism in Paenibacillus. Further, the genomes of the subgroups A and G lack genes involved in glyoxylate cycle and D-galacturonate degradation, respectively. The current study revealed the metabolic diversity of Paenibacillus subgroups assigned based on a genomic phylogeny and could inform the taxonomy of Paenibacillus. KEY POINTS: • Paenibacillus clustered into 10 subgroups. • Genomic content variation and metabolic diversity in the subgroup A, E, and G were described. • Carbohydrate transport and metabolism is important for Paenibacillus survival.

Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation.

Temperature data over the past five decades show faster warming of the global land surface during the night than during the day. This asymmetric warming is expected to affect carbon assimilation and consumption in plants, because photosynthesis in most plants occurs during daytime and is more sensitive to the maximum daily temperature, Tmax, whereas plant respiration occurs throughout the day and is therefore influenced by both Tmax and the minimum daily temperature, Tmin. Most studies of the response of terrestrial ecosystems to climate warming, however, ignore this asymmetric forcing effect on vegetation growth and carbon dioxide (CO2) fluxes. Here we analyse the interannual covariations of the satellite-derived normalized difference vegetation index (NDVI, an indicator of vegetation greenness) with Tmax and Tmin over the Northern Hemisphere. After removing the correlation between Tmax and Tmin, we find that the partial correlation between Tmax and NDVI is positive in most wet and cool ecosystems over boreal regions, but negative in dry temperate regions. In contrast, the partial correlation between Tmin and NDVI is negative in boreal regions, and exhibits a more complex behaviour in dry temperate regions. We detect similar patterns in terrestrial net CO2 exchange maps obtained from a global atmospheric inversion model. Additional analysis of the long-term atmospheric CO2 concentration record of the station Point Barrow in Alaska suggests that the peak-to-peak amplitude of CO2 increased by 23 ± 11% for a +1 °C anomaly in Tmax from May to September over lands north of 51° N, but decreased by 28 ± 14% for a +1 °C anomaly in Tmin. These lines of evidence suggest that asymmetric diurnal warming, a process that is currently not taken into account in many global carbon cycle models, leads to a divergent response of Northern Hemisphere vegetation growth and carbon sequestration to rising temperatures.

Evaporative cooling over the Tibetan Plateau induced by vegetation growth.

In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.

A Novel Dynamic Spectrum-Sharing Method for Integrated Wireless Multimedia Sensors and Cognitive Satellite Networks.

With the growing demand, Wireless Multimedia Sensor Networks (WMSNs) play an increasingly important role, which enhances the capacity of typical Wireless Sensor Networks (WSNs). Additionally, integrating satellite systems into WMSNs brings about the beneficial synergy, especially in rural and sparsely populated areas. However, the available spectrum resource is scarce, which contradicts the high-speed content required for multimedia. Cognitive radio is a promising solution to address the conflict. In this context, we propose a novel spectrum-sharing method for the integrated wireless multimedia sensor and cognitive satellite network based on the dynamic frequency allocation. Specifically, the Low Earth Orbit (LEO) satellite system plays the role of the auxiliary to connect sensor nodes and the remote control host, and it shares the same frequency with the Geostationary Earth Orbit (GEO) system in the downlink. Because the altitudes of GEO and LEO satellites differ greatly, the beam size of GEO is much larger than that of LEO, which provides the opportunity for LEO beam to reuse the frequency that was allocated to the GEO beam. A keep-out region is defined to guarantee the spectral coexistence based on the interference analysis in the worst case. In addition, a dynamic frequency allocation algorithm is presented to deal with the dynamic configuration caused by the satellite motion. Numerical results demonstrate that the dynamic spectrum-sharing method can improve the throughput.

Sphingomonas montana sp. nov., isolated from a soil sample from the Tanggula Mountain in the Qinghai Tibetan Plateau.

An orange pigmented, Gram-staining negative, aerobic, motile, rod-shaped bacterium isolated from a soil from the Tanggula Mountain, China was studied using a polyphasic approach. Based on 16S rRNA gene sequence similarity, strain W16RDT was found to be closely related to Sphingomonas prati DSM 103336T (99%), Sphingomonas fennica DSM 13665T (97.21%), followed by Sphingomonas laterariae DSM 25432T (96.44%), Sphingomonas haloaromaticamans CGMCC 1.10206 T (96.36%) and Sphingomonas formosensis DSM 24164T (96.06%). The strain was found to be catalase and oxidase positive and was found to grow optimally at temperatures of 20-25 °C, pH 8 and tolerated NaCl concentration up to 1% (w/v). The major fatty acids identified were summed feature eight comprising C18:1 ω 7c and/or C18:1 ω 6c (39.2%), summed feature three comprising of C16:1 ω7c and/or C16:1 ω6c (36.7%) and C16:0 (7.0%). The polar lipids detected were phosphatidylcholine, sphingoglycolipid, phosphatidylglycerol, phosphatidylethanolamine, diphosphatidylglycerol, phosphatidyldimethylethanolamine, phosphatidylmonomethylethanolamine, and three unidentified lipids. The strain possessed ubiquinone-10 (Q-10) as the predominant respiratory quinone. Along with other distinguishing characteristics, we also describe the draft genome of strain W16RDT. The final assembled draft genome sequence is 3,722,743 bp with 3390 coding and 48 RNA (45 tRNA and 3 rRNA) genes. The DNA G+C content of the genomic DNA was determined to be 67%. The DNA-DNA relatedness value between the strain W16RDT and its closest phylogenetic relatives S. prati DSM 103336T, S. fennica DSM 13665T, S. laterariae DSM 25432T, and S. haloaromaticamans CGMCC 1.10206T were 52.17, 47.60, 20.93 and 17.09% respectively. The strain W16RDT could be distinguished genotypically and phenotypically from the recognized species belonging to the genus Sphingomonas and thus represents a novel species, for which the name Sphingomonas montana sp. nov. is proposed. The type strain is W16RDT (=CGMCC 1.15646T = DSM 103337T).

Increased precipitation accelerates soil organic matter turnover associated with microbial community composition in topsoil of alpine grassland on the eastern Tibetan Plateau.

Large quantities of carbon are stored in alpine grassland of the Tibetan Plateau, which is extremely sensitive to climate change. However, it remains unclear whether soil organic matter (SOM) in different layers responds to climate change analogously, and whether microbial communities play vital roles in SOM turnover of topsoil. In this study we measured and collected SOM turnover by the 14C method in alpine grassland to test climatic effects on SOM turnover in soil profiles. Edaphic properties and microbial communities in the northwestern Qinghai Lake were investigated to explore microbial influence on SOM turnover. SOM turnover in surface soil (0-10 cm) was more sensitive to precipitation than that in subsurface layers (10-40 cm). Precipitation also imposed stronger effects on the composition of microbial communities in the surface layer than that in deeper soil. At the 5-10 cm depth, the SOM turnover rate was positively associated with the bacteria/fungi biomass ratio and the relative abundance of Acidobacteria, both of which are related to precipitation. Partial correlation analysis suggested that increased precipitation could accelerate the SOM turnover rate in topsoil by structuring soil microbial communities. Conversely, carbon stored in deep soil would be barely affected by climate change. Our results provide valuable insights into the dynamics and storage of SOM in alpine grasslands under future climate scenarios.

Varying responses of vegetation activity to climate changes on the Tibetan Plateau grassland.

Vegetation activity on the Tibetan Plateau grassland has been substantially enhanced as a result of climate change, as revealed by satellite observations of vegetation greenness (i.e., the normalized difference vegetation index, NDVI). However, little is known about the temporal variations in the relationships between NDVI and temperature and precipitation, and understanding this is essential for predicting how future climate change would affect vegetation activity. Using NDVI data and meteorological records from 1982 to 2011, we found that the inter-annual partial correlation coefficient between growing season (May-September) NDVI and temperature (RNDVI-T) in a 15-year moving window for alpine meadow showed little change, likely caused by the increasing RNDVI-T in spring (May-June) and autumn (September) and decreasing RNDVI-T in summer (July-August). Growing season RNDVI-T for alpine steppe increased slightly, mainly due to increasing RNDVI-T in spring and autumn. The partial correlation coefficient between growing season NDVI and precipitation (RNDVI-P) for alpine meadow increased slightly, mainly in spring and summer, and RNDVI-P for alpine steppe increased, mainly in spring. Moreover, RNDVI-T for the growing season was significantly higher in those 15-year windows with more precipitation for alpine steppe. RNDVI-P for the growing season was significantly higher in those 15-year windows with higher temperature, and this tendency was stronger for alpine meadow than for alpine steppe. These results indicate that the impact of warming on vegetation activity of Tibetan Plateau grassland is more positive (or less negative) during periods with more precipitation and that the impact of increasing precipitation is more positive (or less negative) during periods with higher temperature. Such positive effects of the interactions between temperature and precipitation indicate that the projected warmer and wetter future climate will enhance vegetation activity of Tibetan Plateau grassland.

The effect of statins on microalbuminuria, proteinuria, progression of kidney function, and all-cause mortality in patients with non-end stage chronic kidney disease: A meta-analysis.

Conclusive evidence regarding the effect of statins on non-end stage chronic kidney disease (CKD) has not been reported previously. This meta-analysis evaluated the association between statins and microalbuminuria, proteinuria, progression, and all-cause mortality in patients with non-end stage CKD. Databases (e.g., PubMed, Embase and the Cochrane Library) were searched for randomized controlled trials (RCTs) with data on statins, microalbuminuria, proteinuria, renal health endpoints, and all-cause mortality patients with non-end stage CKD to perform this meta-analysis. The mean difference (MD) of the urine albumin excretion ratios (UAER), 24-h urine protein excretion, and risk ratios (RR) of all-cause mortality and renal health endpoints were calculated, and the results are presented with 95% confidence intervals (CI). A total of 23 RCTs with 39,419 participants were selected. The analysis demonstrated that statins statistically reduced UAER to 26.73 µg/min [95%CI (-51.04, -2.43), Z=2.16, P<0.05], 24-h urine protein excretion to 682.68 mg [95%CI (-886.72, -478.63), Z=6.56, P<0.01] and decreased all-cause mortality [RR=0.78, 95%CI (0.72, 0.84), Z=6.08, P<0.01]. However, the analysis results did not indicate that statins reduced the events of renal health endpoints [RR=0.96, 95%CI (0.91,1.01), Z=1.40, P>0.05]. In summary, our study indicates that statins statistically reduced microalbuminuria, proteinuria, and clinical deaths, but statins did not effectively slow the clinical progression of non-end stage CKD.

Pedobacterpsychrotolerans sp. nov., isolated from soil.

A Gram-stain-negative, non-motile, light-pink-pigmented, aerobic, rod-shaped bacterium, designated V5RDT, was isolated from soil of Damxung county in the Qinghai-Tibetan Plateau. Strain V5RDT grew luxuriously at 10 °C, at pH 9.0 and in the presence of 1 % NaCl (w/v). Phylogenetic analysis of 16S rRNA gene sequences placed strain V5RDT in the genus Pedobacter and found that it was most closely related to Pedobacter alluvionis DSM 19624T (97.3 %), Pedobacter ginsenosidimutans JCM 16721T (96.84 %), Pedobacter agri DSM 19486T (96.28 %), Pedobacter roseus JCM 13399T (96.22 %), Pedobacter sandarakinus KCTC 12559T (95.92 %) and Pedobacter borealis DSM 19626T (95.85 %). The G+C content of the genomic DNA of the type strain V5RDT was 37.40 mol%. DNA-DNA relatedness for the type strain V5RDT with respect to its closest phylogenetic relative, P. alluvionis DSM 19624T, was 62.5±1.7 %. The polar lipid profile of the strain consisted of phosphatidylethanolamine, one unidentified aminolipid, one unidentified glycolipid and two unidentified polar lipids. Menaquinone MK-7 was the predominant respiratory quinone, and summed feature 3 (comprising C16 : 1ω7c and/or C16 : 1ω6c), iso-C15 : 0 and iso-C17 : 0 3-OH were the major fatty acids. With respect to phenotypic characteristics, biochemical properties and phylogenetic inference, strain V5RDT represents a novel species of the genus Pedobacter, for which the name Pedobacter psychrotolerans sp. nov is proposed. The type strain is V5RDT (=CGMCC 1.15644T=DSM 103236T).