Comparison of the pathogenicity and neutrophil and monocyte response between SARS-CoV-2 prototype and Omicron BA.1 in a lethal mouse model.

BACKGROUND: SARS-CoV-2, first identified in late 2019, has given rise to numerous variants of concern (VOCs), posing a significant threat to human health. The emergence of Omicron BA.1.1 towards the end of 2021 led to a pandemic in early 2022. At present, the lethal mouse model for the study of SARS-CoV-2 needs supplementation, and the alterations in neutrophils and monocytes caused by different strains remain to be elucidated. METHODS: Human ACE2 transgenic mice were inoculated with the SARS-CoV-2 prototype and Omicron BA.1, respectively. The pathogenicity of the two strains was evaluated by observing clinical symptoms, viral load and pathology. Complete blood count, immunohistochemistry and flow cytometry were performed to detect the alterations of neutrophils and monocytes caused by the two strains. RESULTS: Our findings revealed that Omicron BA.1 exhibited significantly lower virulence compared to the SARS-CoV-2 prototype in the mouse model. Additionally, we observed a significant increase in the proportion of neutrophils late in infection with the SARS-CoV-2 prototype and Omicron BA.1. We found that the proportion of monocytes increased at first and then decreased. The trends in the changes in the proportions of neutrophils and monocytes induced by the two strains were similar. CONCLUSION: Our study provides valuable insights into the utility of mouse models for simulating the severe disease of SARS-CoV-2 prototype infection and the milder manifestation associated with Omicron BA.1. SARS-CoV-2 prototype and Omicron BA.1 resulted in similar trends in the changes in neutrophils and monocytes.

Ba2+-doping introduced piezoelectricity and efficient Ultrasound-Triggered bactericidal activity of brookite TiO2 nanorods.

Exploring highly efficient ultrasound-triggered catalysts is pivotal for various areas. Herein, we presented that Ba2+ doped brookite TiO2 nanorod (TiO2: Ba) with polarization-induced charge separation is a candidate. The replacement of Ba2+ for Ti4+ not only induced significant lattice distortion to induce polarization but also created oxygen vacancy defects for facilitating the charge separation, leading to high-efficiency reactive oxygen species (ROS) evolution in the piezo-catalytic processes. Furthermore, the piezocatalytic ability to degrade dye wastewater demonstrates a rate constant of 0.172 min-1 and achieves a 100 % antibacterial rate at a low dose for eliminating E. coli. This study advances that doping can induce piezoelectricity and reveals that lattice distortion-induced polarization and vacancy defects engineering can improve ROS production, which might impact applications such as water disinfection and sonodynamic therapy.

An Indocyanine Green-Based Nanocluster for Imaging Orthodox Endometriosis Lesions with Negative Contrast.

Indocyanine green (ICG), as the sole near-infrared dye FDA-approved, is limited in biomedical applications because of its poor photostability, lack of targeting, and rapid removal in vivo. Herein, we presented a nanoformulation of poly-l-lysine-indocyanine green-hyaluronic acid (PIH) and demonstrated that it can image orthodox endometriosis (EM) lesions with a negative contrast. The PIH nanocluster, with an average diameter of approximately 200 nm, exhibited improved fluorescence photostability and antioxidant ability compared to free ICG. In the in vivo imaging, EM lesions were visualized, featuring apparent voids and clear boundaries. After colocalizing with the green fluorescent protein, we concluded that the contrast provided by PIH peaked at 4 h postinjection and was observable for at least 8 h. The negative contrast, clear boundaries, and enhanced observable time might be due to the low permeation of PIH to lesions and the enhanced retention on the surfaces of lesions. Thus, our findings suggest an ICG-based nanoprobe with the potential to diagnose abdominal diseases.

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.

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.

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.

Networks of mineral-associated organic matter fractions in forest ecosystems.

Mineral-associated organic matter (MAOM), the largest soil carbon pool, is formed through a series of organo-mineral interaction mechanisms. However, different organo-mineral fractions relevant to specific stabilization mechanisms and their response to environmental variables are poorly understood, which hinders accurate prediction of MAOM preservation under climate change. We applied sequential chemical extraction to separate MAOM into different organo-mineral fractions. To assess of response of different organo-mineral fractions to climate change, alpine forest soils with high environmental sensitivity along a controlled environmental gradient were selected. Residual OM and weakly adsorbed OM were the primary organo-mineral fractions, accounting for approximately 45.1-67.7 % and 16.4-30.6 %, respectively, of the total organic carbon (TOC). Climate exerted considerable indirect effects on the preservation of organo-mineral fractions through weathering and edaphic and biotic variables. Moreover, organo-mineral fractions were closely associated with metal cations (mainly Fe3+/Al3+) and secondary minerals, forming complex networks. Water-soluble OM (WSOM), weakly adsorbed OM and Fe/Al oxyhydroxides-stabilized OM were tightly linked, occupying the central position of the networks, and were closely related to soil pH, moisture and prokaryotic composition, indicating that edaphic and biotic factors might play important roles in maintaining the network structure and topology. In addition, Fe/Al-OM complexes, oxyhydroxides-stabilized OM and residual OM in the network were greatly impacted by climate and weathering factors, including precipitation, temperature and the plagioclase index of alteration (PIA). The complex network among organo-mineral fractions sheds light on MAOM dynamic stabilization for better predicting MAOM preservation under climate change.

pH: A core node of interaction networks among soil organo-mineral fractions.

Mineral-associated organic matter (MAOM) is the largest soil organic carbon (OC) pool with the longest turnover. MAOM is expected to have relatively little sensitivity to climate change due to mineral protection, but its persistence involves several organo-mineral fractions. The uncertainty in the response of specific organo-mineral fractions to climate change hampers the reliability of predictions of MAOM preservation in the future. Here, we applied a sequential chemical fractionation method integrated with network analysis to investigate MAOM stabilization mechanisms across five alpine ecosystems: alpine desert, alpine steppe, alpine meadow, alpine wetland, and alpine forest. Hierarchical cluster analysis revealed grouping of seven extractable OM fractions in MAOM into three OM clusters: a cluster with weak bondings consisting of water-soluble OM (WSOM) and weakly adsorbed fractions (2.1-21.3% of total OC); a cluster with metal-bound complexes comprising Ca-OM complexes and Fe/Al-OM complexes (3.8-12.2% of total OC); and a cluster with strong bonding composed of Al oxyhydroxides, carbonates and Fe oxyhydroxides (12.2-33.5% of total OC). The relative percentages of OM from soils of the five ecosystems in the three clusters exhibited distinct pH dependence patterns. With the increase in pH, the cluster with weak bondings decreased, and that with strong bondings increased, while the one with metal-bound complexes showed a maximum at weakly acidic pH. Organo-mineral fractions and metal cations in MAOM constructed a complex network with pH as the central node. Results suggest that precipitation does not only alter vegetation type and microbial biomass but also regulate soil pH, which is balanced by specific metal cations, thus resulting in particular pH preference of specific OM clusters. These findings demonstrate that soil pH plays a central role in unveiling MAOM dynamics and can serve as a good predictor of soil organo-mineral fractions across alpine ecosystems.

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.

Effects of Different Nanoparticles on Microbes.

Nanoparticles widely exist in nature and may be formed through inorganic or organic pathways, exhibiting unique physical and chemical properties different from those of bulk materials. However, little is known about the potential consequences of nanomaterials on microbes in natural environments. Herein, we investigated the interactions between microbes and nanoparticles by performing experiments on the inhibition effects of gold, ludox and laponite nanoparticles on Escherichia coli in liquid Luria-Bertani (LB) medium at different nanoparticle concentrations. These nanoparticles were shown to be effective bactericides. Scanning electron microscopy (SEM) images revealed the distinct aggregation of cells and nanoparticles. Transmission electron microscopy (TEM) images showed considerable cell membrane disruption due to nanoparticle accumulation on the cell surfaces, resulting in cell death. We hypothesized that this nanoparticle accumulation on the cell surfaces not only disrupted the cell membranes but also physically blocked the microbes from accessing nutrients. An iron-reducing bacterium, Shewanella putrefaciens, was tested for its ability to reduce the Fe (III) in solid ferrihydrite (HFO) or aqueous ferric citrate in the presence of laponite nanoparticles. It was found that the laponite nanoparticles inhibited the reduction of the Fe (III) in solid ferrihydrite. Moreover, direct contact between the cells and solid Fe (III) coated with the laponite nanoparticles was physically blocked, as confirmed by SEM images and particle size measurements. However, the laponite particles had an insignificant effect on the extent of aqueous Fe (III) bioreduction but slightly enhanced the rate of bioreduction of the Fe (III) in aqueous ferric citrate. The slightly increased rate of bioreduction by laponite nanoparticles may be due to the removal of inhibitory Fe (II) from the cell surface by its sorption onto the laponite nanoparticle surface. This result indicates that the scavenging of toxic heavy metals, such as Fe (II), by nanoparticles may be beneficial for microbes in the environment. On the other hand, microbial cells are also capable of detoxifying nanoparticles by coagulating nanoparticles with extracellular polymeric substances or by changing nanoparticle morphologies. Hence, the interactions between microbes and nanoparticles in natural environments should receive more attention.

Indoor Positioning on Smartphones Using Built-In Sensors and Visual Images.

With the rapid development of mobile Internet technology, localization using visual image information has become a hot problem in the field of indoor localization research, which is not affected by signal multipath and fading and can achieve high accuracy localization in indoor areas with complex electromagnetic environments. However, in practical applications, position estimation using visual images is easily influenced by the user's photo pose. In this paper, we propose a multiple-sensor-assisted visual localization method in which the method constructs a machine learning classifier using multiple smart sensors for pedestrian pose estimation, which improves the retrieval efficiency and localization accuracy. The method mainly combines the advantages of visual image location estimation and pedestrian pose estimation based on multiple smart sensors and considers the effect of pedestrian photographing poses on location estimation. The built-in sensors of smartphones are used as the source of pedestrian pose estimation data, which constitutes a feasible location estimation method based on visual information. Experimental results show that the method proposed in this paper has good localization accuracy and robustness. In addition, the experimental scene in this paper is a common indoor scene and the experimental device is a common smartphone. Therefore, we believe that the proposed method in this paper has the potential to be widely used in future indoor navigation applications in complex scenarios (e.g., mall navigation).

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.

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.

Stemness-related gene signature for predicting therapeutic response in patients with esophageal cancer.

Background: Extensive research has indicated that tumor stemness promotes tumor progression. However, the underlying role of stemness-related genes (SRGs) in esophageal cancer (ESCA) remains unclear. Methods: This study identified differentially expressed stemness-related (DESR) messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) in ESCA, and correlated them with the clinical features of patients with ESCA to develop a prognostic risk assessment model. Functional analysis, protein-protein interaction (PPI) analysis, competing endogenous RNA (ceRNA) networks, and tumor-infiltrating immune cell analyses were performed to corroborate the results obtained from the model. Results: Correlation analysis of the stemness enrichment scores revealed 1,106 DESR genes (DESRGs), 84 DESRmiRNAs, and 320 DESRlncRNAs were identified from The Cancer Genome Atlas Esophageal Carcinoma (TCGA-ESCA) dataset. Network clustering was performed and the top 20 connection points were identified, including CDC20 that connects to 136 adjacent nodes. A ceRNA network was constructed, including 17 DESRmiRNAs, 44 DESRlncRNAs, and 55 DESRGs. Conclusions: NCAPG [log2fold change (FC) =1.81; q value =2.68×10-11] was significantly upregulated in ESCA and positively correlated with resting natural killer (NK) cells, suggesting that human NK cells rest via the overexpression of NCAPG in ESCA. hsa-miR-1269a is significantly upregulated in ESCA patients with poor prognostic features. CD4+ resting memory T cells (P<0.01) were significantly negatively correlated with hsa-miR-1269a. The insights presented in this study will contribute to the development of innovative therapeutics for the treatment of patients with ESCA.

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.

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.

Sternal lifting increases the operating space in esophagectomy via mediastinoscopy: a prospective cohort study.

BACKGROUND: Esophagectomy with combined single-port inflatable mediastinoscopy and laparoscopy reduces the risk of postoperative respiratory complications as it obviates the need to pass through the pleural space. However, it has strict indications owing to the narrow space for operation. Therefore, we adopted a sternal lifting method using a retractor that enables the expansion of the operating space, a technique which has not been previously reported. We describe our experience and report the results of an evaluation of this new approach. METHODS: Thirty-nine patients with esophageal squamous cell carcinomas underwent esophagectomy using combined single-port inflatable mediastinoscopy and laparoscopy from March 2019 to August 2021. Among them, 20 cases received sternal suspension [sternal suspension group (SS group)], and 19 cases did not receive sternal suspension [non-sternal suspension group (NSS group)]. The short-term efficacy of the two groups was observed. RESULTS: Patients in the SS group had a shorter intramediastinal operation time (82.50 vs. 110.00 minutes; P<0.001), more dissected chest lymph nodes (14 vs. 12; P=0.036), and a lower incidence of postoperative hoarseness (2 vs. 6; P=0.235) than did those in the NSS group. There were no significant differences between the SS group and NSS group in terms of intraoperative blood loss, postoperative hospital stay, post-surgical pathologic TNM classification (pTNM), post-surgical pathologic tumor classification (pT), post-surgical pathologic extent of lymph node involvement (pN), and total number of dissected lymph nodes. There were no statistical differences in the incidence of anastomotic fistula, respiratory complications, arrhythmia, or chylothorax between the two groups. There was no mortality during hospitalization in the two groups. CONCLUSIONS: Sternal lifting increases the working space in esophagectomy via mediastinoscopy. It can make video-assisted radical esophagectomy by a transmediastinal approach with total pneumomediastinum assistance (VARETT) easier to perform, and sternal suspension in VARETT is safe and effective.

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.

Carbon turnover times shape topsoil carbon difference between Tibetan Plateau and Arctic tundra.

The Tibetan Plateau (TP) and Arctic permafrost constitute two large reservoirs of organic carbon, but processes which control carbon accumulation within the surface soil layer of these areas would differ due to the interplay of climate, soil and vegetation type. Here, we synthesized currently available soil carbon data to show that mean organic carbon density in the topsoil (0-10 cm) in TP grassland (3.12 ± 0.52 kg C m-2) is less than half of that in Arctic tundra (6.70 ± 1.94 kg C m-2). Such difference is primarily attributed to their difference in radiocarbon-inferred soil carbon turnover times (547 years for TP grassland versus 1609 years for Arctic tundra) rather than to their marginal difference in topsoil carbon inputs. Our findings highlight the importance of improving regional-specific soil carbon turnover and its controlling mechanisms across permafrost affected zones in ecosystem models to fully represent carbon-climate feedback.

Excessive nitrogen addition accelerates N assimilation and P utilization by enhancing organic carbon decomposition in a Tibetan alpine steppe.

High amounts of deposited nitrogen (N) dramatically influence the stability and functions of alpine ecosystems by changing soil microbial community functions, but the mechanism is still unclear. To investigate the impacts of increased N deposition on microbial community functions, a 2-year multilevel N addition (0, 10, 20, 40, 80 and 160 kg N ha-1 year-1) field experiment was set up in an alpine steppe on the Tibetan Plateau. Soil microbial functional genes (GeoChip 4.6), together with soil enzyme activity, soil organic compounds and environmental variables, were used to explore the response of microbial community functions to N additions. The results showed that the N addition rate of 40 kg N ha-1 year-1 was the critical value for soil microbial functional genes in this alpine steppe. A small amount of added N (≤40 kg N ha-1 year-1) had no significant effects on the abundance of microbial functional genes, while high amounts of added N (>40 kg N ha-1 year-1) significantly increased the abundance of soil organic carbon degradation genes. Additionally, the abundance of microbial functional genes associated with NH4+, including ammonification, N fixation and assimilatory nitrate reduction pathways, was significantly increased under high N additions. Further, high N additions also increased soil organic phosphorus utilization, which was indicated by the increase in the abundance of phytase genes and alkaline phosphatase activity. Plant richness, soil NO2-/NH4+ and WSOC/WSON were significantly correlated with the abundance of microbial functional genes, which drove the changes in microbial community functions under N additions. These findings help us to predict that increased N deposition in the future may alter soil microbial functional structure, which will lead to changes in microbially-mediated biogeochemical dynamics in alpine steppes on the Tibetan Plateau and will have extraordinary impacts on microbial C, N and P cycles.