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Abstract Background Recombination signal-binding protein for immunoglobulin kappa J region (RBPJ) is a transcriptional regulator that plays an important role in maintaining immune homeostasis. This study aimed to estimate the expression of RBPJ in rheumatoid arthritis (RA) patients and investigate its relationship with RA. Methods A total of 83 newly diagnosed RA patients and 70 healthy controls were included. mRNA was extracted from peripheral blood mononuclear cells (PBMCs), and the expression of RBPJ was detected using quantitative real-time PCR (qRT‒PCR). An RA dataset (GSE89408) was obtained from the Gene Expression Omnibus (GEO) database, and RA synovial tissues were divided into two groups. The differentially expressed genes (DEGs) were selected with the “DESeq2” R package. Results RBPJ expression was lower in RA patients than in health controls and was negatively correlated with the DAS28 score, C-reactive protein (CRP) level and erythrocyte sedimentation rate (ESR). RA synovial tissues from GSE89408 were classified into RBPJ-low (≤ 25%) and RBPJ-high (≥ 75%) groups according to RBPJ expression, and 562 DEGs were identified. Gene Ontology (GO) enrichment analyses revealed that the DEGs significantly affected the regulation of T cell activation and lymphocyte/mononuclear cell differentiation. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the most enriched pathways of DEGs were the T cell receptor signaling pathway, Th1/2 and Th17 cell differentiation, the PI3K − Akt signaling pathway and cytokine‒cytokine receptor interaction. CytoHubba Plugin revealed that most of the top 10 genes were involved in osteoclast differentiation, the T cell receptor signaling pathway and cytokine‒cytokine receptor interaction. Conclusions RBPJ expression was significantly lower in RA patients and negatively correlated with disease activity. GEO dataset analysis demonstrated that RBPJ may be involved in osteoclast differentiation, T cell activation and differentiation, and the T cell receptor signaling pathway. Our research may contribute to understanding the potential mechanisms by which RBPJ regulates T cell differentiation and cytokine‒cytokine receptor interaction in RA patients.

Melatonin (MT) is a multifunctional hormone that enhances crop resilience against various abiotic stresses. However, its regulatory mechanism of osmotic tolerance in forage oats (Avena sativa) plants under water-limited scenarios is still unclear. This study aimed to delineate the impact of MT pretreatment on the morphological, physiological, and biochemical functions of oat seedlings under osmotic stress. Our findings demonstrated that exogenous treatment of MT noticeably elevated leaf area while decreasing the root/shoot ratio of oat seedlings subjected to osmotic stress. Osmotic-induced 38.22% or 48.37% decrease in relative water content could be significantly alleviated by MT pretreatment on day 7 or day 14, respectively. MT treatment also significantly mitigated osmotic-induced decreases in photosynthetic parameters including net photosynthetic rate, stomatic conductance, and intercellular CO2 concentration as well as various chlorophyll fluorescence parameters, which could contribute to enhanced accumulations of free proline and soluble sugars in seedlings after being subjected to a prolonged duration of osmotic stress. Furthermore, MT markedly improved antioxidant enzyme activities including superoxide dismutase, ascorbate peroxidase, catalase, and peroxidase along with the accumulation of ascorbic acid contributing to a significant reduction in reactive oxygen species under osmotic stress. In addition, the MT application induced a 978.12%, 33.54%, or 30.59% increase in endogenous MT, indole acetic acid, or gibberellic acid content under osmotic stress but did not affect the accumulation of abscisic acid. These findings suggest that an optimal concentration of MT (100 μmol·L−1) could relieve osmotic stress via improvement in osmotic adjustment, the enzymatic antioxidant defense system, and endogenous hormonal balance, thereby contributing to enhanced photosynthetic functions and growth of oat seedlings under water-limited conditions.

IntroductionWeak aerobic stability is a notable challenge for whole-plant corn silage, particularly in hot and humid regions. Acetobacter is commonly regarded as an indicator of aerobic deterioration in silage, yet its precise role in fermentation and during aerobic exposure, as well as the factors that promote its growth, remain insufficiently understood.MethodsIn this study, whole-plant corn silage was prepared using a bagged method with controlled dry matter (DM) content at 20%, 25%, and 30%, and initial concentrations of A. pasteurianus at 40%, 50%, and 60%. The silage was stored for 60 days under varying temperatures (20°C, 30°C, and 40°C). Following the anaerobic storage phase, the silage was exposed to air at room temperature (20-25°C) for 7 days, both with and without A. pasteurianus inoculation.ResultsThe results demonstrated that A. pasteurianus did not impact the nutritional value of the silage during anaerobic fermentation, maintaining a low pH (< 3.80). However, during aerobic exposure, the presence of A. pasteurianus significantly reduced the aerobic stability of the silage. The microbial community shifted from primarily Klebsiella species initially to Lactobacillus and Acetobacter species post-ensiling. During the aerobic exposure phase, A. pasteurianus and A. fabarum became the dominant species. Response Surface Methodology (RSM) analysis identified optimal conditions for the proliferation of A. pasteurianus during the aerobic phase, which occurred at 28°C, 25% DM, and 52% initial concentration at 3 ml/kg.DiscussionThese findings confirm that A. pasteurianus plays a critical role in reducing the aerobic stability of whole-plant corn silage. Additionally, the study identifies the optimal conditions that favor the proliferation of A. pasteurianus, offering valuable insights for the development of strategies to prevent and control this bacterium, thereby improving the aerobic stability of silage in hot and humid regions.

Summary: This study investigated host responses to long COVID by following up with 89 of the original 144 cohorts for 1-year (N = 73) and 2-year visits (N = 57). Pulmonary long COVID, characterized by fibrous stripes, was observed in 8.7% and 17.8% of patients at the 1-year and 2-year revisits, respectively, while renal long COVID was present in 15.2% and 23.9% of patients, respectively. Pulmonary and renal long COVID at 1-year revisit was predicted using a machine learning model based on clinical and multi-omics data collected during the first month of the disease with an accuracy of 87.5%. Proteomics revealed that lung fibrous stripes were associated with consistent down-regulation of surfactant-associated protein B in the sera, while renal long COVID could be linked to the inhibition of urinary protein expression. This study provides a longitudinal view of the clinical and molecular landscape of COVID-19 and presents a predictive model for pulmonary and renal long COVID.

Oat (Avena sativa) is one of the most important cereal crops and cool-season forage grasses in the world. The calmodulin-binding transcription activator (CAMTA) gene family is one of the largest families in plants, and it plays vital roles in multiple biological processes. However, the CAMTA genes in oats, especially those involved in abiotic stress, have not yet been elucidated. Herein, our findings reveal the presence of 20 distinct AsCAMTA genes, which were clustered into three subfamilies based on their gene structure and conserved motifs, indicating functional similarities within each subgroup. Chromosomal mapping indicated an uneven distribution across 10 chromosomes, suggesting a complex evolutionary history marked by potential gene duplication events. The results showed that most AsCAMTA genes contained stress-related cis-elements. The study further investigated the expression patterns of these genes under abiotic stress conditions utilizing RT-qPCR analysis. The results identified three AsCAMTA genes (AsCAMTA5, AsCAMTA7, and AsCAMTA19) that exhibited significant up-regulation under salt stress, with AsCAMTA7 also showing a marked increase in expression under drought stress. These findings suggest a pivotal role of AsCAMTA5, AsCAMTA7, and AsCAMTA19 genes in mediating the responses to various abiotic stresses by integrating multiple stress signals in oats. This investigation provides valuable insights into the potential functions of AsCAMTA genes in the stress response mechanisms of oats, laying a foundation for further functional studies aimed at enhancing abiotic stress tolerance in crops.

IntroductionElymus nutans holds ecological and pastoral significance due to its adaptability and nutritional value, the Qinghai-Tibet Plateau (QTP) is a key hub for its genetic diversity. To conserve and harness its genetic resources in highland ecosystems, a thorough assessment is vital. However, a comprehensive phylogeographic exploration of E. nutans is lacking. The objective of this study was to unravel the genetic diversity, adaptation, and phylogenetics of E. nutans populations.MethodsEncompassing 361 individuals across 35 populations, the species' genetic landscape and dynamic responses to diverse environments were decoded by using four chloroplast DNA (cpDNA) sequences and nine microsatellite markers derived from the transcriptome.Results and discussionThis study unveiled a notable degree of genetic diversity in E. nutans populations at nuclear (I = 0.46, He = 0.32) and plastid DNA levels (Hd = 0.805, π = 0.67). Analysis via AMOVA highlighted genetic variation predominantly within populations. Despite limited isolation by distance (IBD), the Mekong-Salween Divide (MSD) emerged as a significant factor influencing genetic differentiation and conserving diversity. Furthermore, correlations were established between external environmental factors and effective alleles of three EST-SSRs (EN5, EN57 and EN80), potentially linked to glutathione S-transferases T1 or hypothetical proteins, affecting adaptation. This study deepens the understanding of the intricate relationship between genetic diversity, adaptation, and environmental factors within E. nutans populations on the QTP. The findings shed light on the species' evolutionary responses to diverse ecological conditions and contribute to a broader comprehension of plant adaptation mechanisms.

Target tracking faces various challenges in natural scenes, such as changing lighting, scale, occlusion, etc. In response to these issues, research is based on the use of Siamese neural networks for target tracking. And this paper uses channel attention mechanisms and high-quality bounding box models to improve the target tracking algorithm. Firstly, by combining attention mechanism with twin neural networks, useful channel information is enhanced and useless channel information is suppressed. Then, based on this, the classification branch and quality prediction branch are jointly represented, and the bounding box is represented through a general distribution form to further optimize the algorithm. The algorithm optimized based on attention mechanism has a success rate of 71.2% and an accuracy of 91.3%, which has better performance compared to other comparative algorithms. The algorithm optimized based on high-quality bounding box models has a success rate of 73.6% and an accuracy of 92.5%, which further improves its performance compared to attention mechanism optimization. The improvement strategy proposed in the study has improved the robustness and accuracy of target tracking, and the improved algorithm has better robustness and performance advantages in complex tracking scenarios. Meanwhile, the practical applicability of this algorithm has been effectively verified through the simulation experiments of robot control systems.

Yiwei decoction (YWD) is a formula of traditional Chinese medicine (TCM) that is clinically effective for the prevention and treatment of gastric cancer recurrence and metastasis. According to the theory of TCM, YWD tonifies the body and strengthens the body’s resistance to gastric cancer recurrence and metastasis potentially via the immune regulation of the spleen. The aims of the present study were to investigate whether YWD-treated spleen-derived exosomes in rats inhibit the proliferation of tumor cells, to elucidate the anticancer effects of YWD, and to provide evidence supporting the use of YWD as a new clinical treatment for gastric cancer. Spleen-derived exosomes were obtained by ultracentrifugation and identified by transmission electron microscopy, nanoparticle tracking analysis, and western blot analysis. The location of the exosomes in tumor cells was then determined by immunofluorescence staining. After tumor cells were treated with different concentrations of exosomes, the effect of exosomes on cell proliferation was determined by cell counting kit 8 (CCK8) and colony formation assays. Tumor cell apoptosis was detected by flow cytometry. Particle analysis and western blot analysis identified the material extracted from spleen tissue supernatant as exosomes. Immunofluorescence staining showed that spleen-derived exosomes were taken up by HGC-27 cells, and the CCK8 assay confirmed that the relative tumor inhibition rate of YWD-treated spleen-derived exosomes in the 30 μg/mL reached 70.78% compared to control exosomes in the 30 μg/mL (p < 0.05). Compared to control exosomes in the 30 μg/mL, the colony formation assay indicated that YWD-treated spleen-derived exosomes in the 30 μg/mL colonies have decreased by 99.03% (p < 0.01). Moreover, flow cytometry analysis showed that treatment with YWD-treated exosomes in the 30 μg/mL increased the apoptosis rate to 43.27%, which was significantly higher than that of the control group in the 30 μg/mL (25.91%) (p < 0.05). In conclusion, spleen-derived exosomes from YWD-treated animals inhibit the proliferation of HGC-27 cells via inducing apoptosis, suggesting that spleen-derived exosomes are involved in mediating the antitumor effect of YWD. These results demonstrated a novel exosome-mediated anticancer effect of YWD as a TCM formula, thereby supporting the use of YWD-treated exosomes as a new approach for the clinical treatment of gastric cancer.

Abstract Background This study aimed to investigate the effect of phenyllactic acid as an additive on silage fermentation and bacterial community of reed canary grass (RCG, Phalaris arundinacea L.) on the Qinghai Tibetan Plateau. At the heading stage, RCG was harvested, chopped and ensiled in small bag silos. The silage was treated without (control, 1.0 g/mL sterile water, on a fresh matter basis (FM)) or with phenyllactic acid (PLA, 3 mg/mL, FM), antimicrobial additive (PSB, a mixture of potassium sorbate and sodium benzoate, 2%, FM), lactic acid bacteria inoculant (LABi, L. plantarum + L. curvatus, 1 × 106 cfu/g, FM) and PLA + LABi, and then stored in a dark room at the ambient temperature (5 ~ 15 °C) for 60 days. Results Compared with control, PLA decreased lactic acid, acetic acid and ammonia-N contents, and subsequently increased CP content of RCG silage. PLA enhanced the growth of lactic acid bacteria and reduced the count of yeasts (P

Abstract Background Parkinson’s disease (PD) is associated with enteric nervous system dysfunction and gut microbiota dysbiosis. Short-chain fatty acids (SCFAs), derived from gut microbiota, are supposed to anticipate PD pathogenesis via the pathway of spinal cord and vagal nerve or the circulatory system. However, the serum concentration of SCFAs in PD patients is poorly known. This study aims to investigate the exact level of SCFAs in PD patients and its correlation with Parkinson’s symptoms. Methods 50 PD patients and 50 healthy controls were recruited, and their demographic and clinical characteristics were collected. The serum concentration of SCFAs was detected using a gas chromatography-mass spectrometer. SCFAs were compared between PD and control groups. The correlation between serum SCFAs and Parkinson’s symptoms and the potential effects of medications on the serum SCFAs was analyzed. Results Serum propionic acid, butyric acid and caproic acid were lower, while heptanoic acid was higher in PD patients than in control subjects. However, only the serum level of propionic acid was correlated with Unified Parkinson’s Disease Rating Scale (UPDRs) part III score (R = -0.365, P = 0.009), Mini-mental State Examination (MMSE) score (R = -0.416, P = 0.003), and Hamilton Depression Scale (HAMD) score (R = 0.306, P = 0.03). There was no correlation between other serum SCFAs and motor complications. The use of trihexyphenidyl or tizanidine increased the serum concentration of propionic acid. Conclusions Serum SCFAs are altered in PD patients, and the decrease of serum propionic acid level is correlated with motor symptoms, cognitive ability and non-depressed state. Thus, the gut microbial-derived SCFAs potentially affect Parkinson’s symptoms through the blood circulation. Propionic acid supplementation might ameliorate motor and non-motor symptoms of PD patients, although clinical trials are needed to test this hypothesis.

Mixing grass with legumes before ensiling is beneficial for improving dry matter and crude protein yield, but additional information is needed to balance nutrient content and fermentation quality. In this study, the microbial community, fermentation characteristics, and nutrient content of Napier grass mixed with alfalfa at different proportions were assessed. Tested proportions included: 100:0 (M0), 70:30 (M3), 50:50 (M5), 30:70 (M7), and 0:100 (MF). Treatments included: (CK) sterilized deionized water; (IN) selected lactic acid bacteria: Lactobacillus plantarum CGMCC 23166 and Lacticaseibacillus rhamnosus CGMCC 18233 (1.5 × 105 cfu/g of fresh weight for each inoculant); and (CO) commercial lactic acid bacteria: L. plantarum (1 × 105 cfu/g of fresh weight). All mixtures were ensiled for 60 days. Data analysis was used as a completely randomized design with a 5-by-3 factorial arrangement of treatments. The results showed that with increasing alfalfa mixing ratio, dry matter, and crude protein increased, while neutral detergent fiber and acid detergent fiber decreased both before and after ensiling (p

Elymus breviaristatus, a rare grass species with excellent resistance and ecological importance, is narrowly distributed on the Qinghai-Tibet plateau. Populations of E. breviaristatus are declining due to habitat fragmentation, and thus far, characteristics of genetic differentiation and adaptive responses to climate change remain poorly understood in this species. Here, we explored the genetic structure of 18 natural populations (269 individuals) in the transition zone between Tibet and the Hengduan Mountains using 15 expressed sequence tag (EST)-SSR primer pairs and identified possible barriers to gene flow that might have caused genetic discontinuities. Additional analyses were performed to identify the environmental factors affecting genetic diversity and to test whether the patterns of genetic variation among populations were more consistent with the isolation by distance (IBD) or isolation by environment (IBE) model. Multiple measures of genetic diversity revealed that intra-population genetic variation was low, while inter-population genetic variation was high. Clustering, structure, and principal coordinate analyses identified three genetic groups: (a) Eastern Qamdo, (b) Nagqu and Western Qamdo, and (c) Lhasa and Nyingchi. A clear physical barrier to gene flow was formed by the Yarlung Zangbo Grand Canyon and the Tanggula Mountains. We found that both IBD and IBE contributed to the observed patterns of genetic variation, and the IBE model played a leading role. In addition, precipitation-related variables, soil phosphorus content and soil K:P ratio significantly affected population genetic variation. Overall, our results emphasized the genetic fragility of E. breviaristatus populations and showed that this species requires attention, as future climate changes and human activities may further threaten its survival. In addition, the genetic differences among E. breviaristatus populations should be considered when formulating conservation measures for E. breviaristatus populations in the study area.

ObjectivesAutosomal recessive inherited ataxia with oculomotor apraxia type 2 (AOA2), caused by SETX gene mutations, is characterized by early-onset, progressive cerebellar ataxia, peripheral neuropathy, oculomotor apraxia and elevated serum α-fetoprotein (AFP). This study aimed to expand and summarize the clinical and genetic characteristics of SETX variants related to AOA2.MethodsThe biochemical parameters, electromyogram and radiological findings of the patient were evaluated. Whole-exome sequencing (WES) was performed on the patient using next-generation sequencing (NGS), the variants were confirmed by Sanger sequencing and the pathogenicity of the variants was classified according to the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines. We reviewed 57 studies of AOA2 patients with SETX mutations and collected clinical and genetic information.ResultsThe patient was a 40-year-old Chinese woman who primarily presented with numbness and weakness of the lower limbs in her teenage years. She had elevated AFP, increased serum follicle-stimulating hormone (FSH) and luteinizing hormone (LH) and decreased anti-Müllerian hormone (AMH) levels. We identified a novel homozygous missense mutation of the SETX gene, c.7118 C>T (p. Thr2373Ile), in the patient via Whole-exome and Sanger sequencing. The variant was located in the DNA/RNA helicase domain and is highly conserved. The protein prediction analysis verified the SETX variant as a damaging alteration and ACMG/AMP guidelines classified it as likely pathogenic. Through a literature review, we identified 229 AOA2 cases with SETX variants, and among the variants, 156 SETX variants were exonic. We found that 107 (46.7%) patients were European, 50 (21.8%) were African and 48 (21.0%) were Asian. Among the Asian patients, five from two families were Mainland Chinese. The main clinical features were cerebellar ataxia (100%), peripheral neuropathy (94.6%), cerebellar atrophy (95.3%) and elevated AFP concentration (92.0%). Most reported SETX mutations in AOA2 patients were missense, frameshift and nonsense mutations.ConclusionWe discovered a novel homozygous variant of the SETX gene as a cause of AOA2 in the current patient and expanded the genotypic spectrum of AOA2. Moreover, the clinical features of AOA2 and genetic findings in SETX were assessed in reported cohorts and are summarized in the present study.

Past climatic and topographic variations have created strong biogeographic barriers for alpine species and are key drivers of the distribution of genetic variation and population dynamics of species on the Qinghai-Tibet Plateau (QTP). Therefore, to better conserve and use germplasm resources, it is crucial to understand the distribution and differentiation of genetic variation within species. Elymus breviaristatus, an ecologically important rare grass species with strong resistance, is restricted to a limited area of the QTP. In this study, we investigated the phylogeography of E. breviaristatus using five chloroplast genes and spacer regions in natural populations distributed along the eastern QTP. We identified a total of 25 haplotypes among 216 individuals from 18 E. breviaristatus populations, which were further classified into four haplogroups based on geographical distribution and haplotype network analysis. Notably, we did not observe any signs of population expansion. High genetic diversity was exhibited at both species and population levels, with precipitation being the main limiting factor for population genetic diversity levels. Higher genetic diversity was exhibited by populations located near the Mekong–Salween Divide genetic barrier, suggesting that they may have served as a glacial refuge. The significant pattern of genetic differentiation by environmental isolation highlights the influence of heterogeneous environments on the genetic structure of E. breviaristatus populations. Additionally, the results of ecological niche models indicated that the geographic distribution of E. breviaristatus populations has decreased rapidly since the Last Glacial Maximum but is not threatened by future global warming.

Spectrum sensing in Cognitive radio (CR) is a way to improve spectrum utilization by detecting spectral holes to achieve a dynamic allocation of spectrum resources. As it is often difficult to obtain accurate wireless environment information in real-world scenarios, the detection performance is limited. Signal-to-noise ratio (SNR), noise variance, and channel prior occupancy rate are critical parameters in wireless spectrum sensing. However, obtaining these parameter values in advance is challenging in practical scenarios. A lifting wavelet-assisted Expectation-Maximization (EM) joint estimation and detection method is proposed to estimate multiple parameters and achieve full-blind detection, which uses lifting wavelet in noise variance estimation to improve detection probability and convergence speed. Moreover, a stream learning strategy is used in estimating SNR and channel prior occupancy rate to fit the scenario where the SU has mobility. The simulation results demonstrate that the proposed method can achieve comparable detection performance to the semi-blind EM method.

Channel estimation of an orthogonal frequency division multiplexing (OFDM) system based on compressed sensing can effectively reduce the pilot overhead and improve the utilization rate of spectrum resources. The traditional SAMP algorithm with a fixed step size for sparse channel estimation has the disadvantages of a low estimation efficiency and limited estimation accuracy. An Improved SAMP (ImpSAMP) algorithm is proposed to estimate the channel state information of the OFDM system. In the proposed ImpSAMP algorithm, the received signal is firstly denoised based on the energy-detection method, which can reduce the interferences on channel estimation. Furthermore, the step size is adjusted dynamically according to the l2 norm of difference between two estimated sparse channel coefficients of adjacent phases to estimate the sparse channel coefficients quickly and accurately. In addition, the double threshold judgment is adopted to enhance the estimation efficiency. The simulation results show that the ImpSAMP algorithm outperforms the traditional SAMP algorithm in estimation efficiency and accuracy.

Atmospheric aerosols have important impacts on global radiative forcing, air pollution, and human health. This study investigated the optical and physical properties of aerosol layers over Australia from 2007 to 2019 using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Level 2 aerosol products. Australia was divided into three sub-regions (western highlands, central plains, and eastern ranges). Interannual and seasonal optical property variations in aerosol layers in the three sub-regions were analyzed and compared. Results showed that annual mean values of AODL (lowest aerosol layer AOD) and AODT (total AOD of all aerosol layers) were always higher in the eastern ranges region than the other two regions from 2007 to 2019. The reason could be that Australian population was predominantly located in the eastern ranges region, where more human activities could bring significant aerosol loadings. BL (base height of the lowest aerosol layer), HL (top height of the lowest aerosol layer), and HH (top height of the highest aerosol layer) all showed trends of “western highlands > eastern mountains > central plains”, indicating that the higher the elevation, the higher the BL, HL, and HH. TL (thickness of the lowest aerosol layer) was higher during the day than at night, which might account for increased diurnal atmospheric convection and nocturnal aerosol deposition. DRL (depolarization ratio of the lowest aerosol layer) was higher in the western highlands and central plains than the eastern mountains, probably because these two regions have large deserts with more irregularly shaped dust aerosols. CRL (color ratio of the lowest aerosol layer) had slightly higher values in the eastern ranges than the other two regions, probably due to the wet climate of the eastern ranges, where aerosols were more hygroscopic and had larger particle sizes. This study can provide technical support for the control and management of regional air pollutants.

The physical condition of individuals who contracted COVID-19 had a profound influence on mitigating the physical and psychological impact of the disease and the symptoms of posttraumatic stress disorder (PTSD). Little attention has been focused on the influence of physical condition on PTSD among recovered COVID-19 subjects. This study explored the relationship between physical and psychological status and PTSD and the potential mechanisms. Questionnaires were completed by 73 (50.7%, 73/144) COVID-19 recovered subjects who were diagnosed in Taizhou, Zhejiang, China. We conducted a face-to-face survey from January 17 to March 10, 2020. The mediation analysis approach was applied in this research. Our data show that recovered COVID-19 subjects who were in better physical condition exhibited fewer psychological problems [B (95%CI), (−1.65 −3.04, −0.26)] and lower PTSD [B (95%CI), −6.13 (−9.43, −2.83)]. In addition, the worse the psychological status of recovered COVID-19 subjects was, the stronger the PTSD (B [95%CI], 0.58 [0.02, 1.14]). Moreover, psychological status could significantly mediate the impact of physical condition on PTSD (β1θ2 = −0.87). Together, COVID-19 recovered subjects who have better physical condition could decrease their PTSD, and the worse the physical condition of COVID-19 recovered subjects would increase their psychological problems. Our finding about psychological status could significantly mediate the impact of the physical condition on PTSD might be useful for medical institutions and the government seeking to help with the follow-up rehabilitation training of recovered COVID-19 subjects.

Background: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive and fatal gastrointestinal malignancies with high morbidity and mortality worldwide. Accumulating evidence has revealed the clinical significance of the interaction between the hypoxic microenvironment and cancer stemness in pancreatic cancer progression and therapies. This study aims to identify a hypoxia-stemness index-related gene signature for risk stratification and prognosis prediction in PAAD.Methods: The mRNA expression-based stemness index (mRNAsi) data of PAAD samples from The Cancer Genome Atlas (TCGA) database were calculated based on the one-class logistic regression (OCLR) machine learning algorithm. Univariate Cox regression and LASSO regression analyses were then performed to establish a hypoxia-mRNAsi-related gene signature, and its prognostic performance was verified in both the TCGA-PAAD and GSE62452 corhorts by Kaplan-Meier and receiver operating characteristic (ROC) analyses. Additionally, we further validated the expression levels of signature genes using the TCGA, GTEx and HPA databases as well as qPCR experiments. Moreover, we constructed a prognostic nomogram incorporating the eight-gene signature and traditional clinical factors and analyzed the correlations of the risk score with immune infiltrates and immune checkpoint genes.Results: The mRNAsi values of PAAD samples were significantly higher than those of normal samples (p < 0.001), and PAAD patients with high mRNAsi values exhibited worse overall survival (OS). A novel prognostic risk model was successfully constructed based on the eight-gene signature comprising JMJD6, NDST1, ENO3, LDHA, TES, ANKZF1, CITED, and SIAH2, which could accurately predict the 1-, 3-, and 5-year OS of PAAD patients in both the training and external validation datasets. Additionally, the eight-gene signature could distinguish PAAD samples from normal samples and stratify PAAD patients into low- and high-risk groups with distinct OS. The risk score was closely correlated with immune cell infiltration patterns and immune checkpoint molecules. Moreover, calibration analysis showed the excellent predictive ability of the nomogram incorporating the eight-gene signature and traditional clinical factors.Conclusion: We developed a hypoxia-stemness-related prognostic signature that reliably predicts the OS of PAAD. Our findings may aid in the risk stratification and individual treatment of PAAD patients.

Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The proposed method consists of two steps: firstly, we utilize AP selection to classify all users; secondly, we assign pilots to users with more severe pilot contamination using the graph coloring algorithm and then assign pilots to the remaining users. The numerical simulation results show that the proposed scheme outperforms existing pilot assignment schemes and significantly improves throughout with low complexity.

Intelligent telemedicine technology has been widely applied due to the quick development of the Internet of Things (IoT). The edge-computing scheme can be regarded as a feasible solution to reduce energy consumption and enhance the computing capabilities for the Wireless Body Area Network (WBAN). For an edge-computing-assisted intelligent telemedicine system, a two-layer network architecture composed of WBAN and Edge-Computing Network (ECN) was considered in this paper. Moreover, the age of information (AoI) was adopted to describe the time cost for the TDMA transmission mechanism in WBAN. According to the theoretical analysis, the strategy for resource allocation and data offloading in edge-computing-assisted intelligent telemedicine systems can be expressed as a system utility function optimizing problem. To maximize the system utility, an incentive mechanism based on contract theory (CT) was considered to motivate edge servers (ESs) to participate in system cooperation. To minimize the system cost, a cooperative game was developed to address the slot allocation in WBAN, while a bilateral matching game was utilized to optimize the data offloading problem in ECN. Simulation results have verified the effectiveness of the strategy proposed in terms of the system utility.

To investigate the vertical distribution of aerosol optical characteristics in Nanyang City, a ground-based dual-wavelength (532 nm and 355 nm) lidar system was developed for aerosol observation at the Nanyang Normal University Station (NYNU) from November 2021 to December 2022. Spatio-temporal dynamics information on vertical distributions of aerosol optical properties during polluted and non-polluted days was obtained. Aerosols were characterized by low altitudes (up to 2 km), thinner layers, and high-altitude (up to 4 km) thick layers during non-polluted and polluted days, with extinction coefficient values of ~0.03 km−1 and ~0.2 km−1, respectively. The mean values of the extinction coefficient at different altitudes (0~5 km) were all about ten-times higher on polluted days (0.04~0.19 km−1) than on non-polluted days (0.004~0.02 km−1). These results indicate that aerosol loadings and variations at different altitudes (0~5 km) were much higher and more prominent on polluted days than non-polluted days. The results show ten-times larger aerosol optical depth (AOD) values (0.4~0.6) on polluted days than on non-polluted days (0.05~0.08). At the same time, AOD values on both polluted and non-polluted days slightly decreased from 19:00 to 05:00, possibly due to dry depositions at nighttime. For the first time, this study established a ground-based lidar remote sensing system to investigate the vertical distribution of atmospheric aerosol optical characteristics in Henan Province. The experimental results can provide scientific dataset support for the local government to prevent and control air pollution.

Severity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort, resulting in a data matrix containing 3,065 readings for 124 types of measurements over 52 days. A machine learning model was established to predict the disease progression based on the cohort consisting of training, validation, and internal test sets. A panel of eleven routine clinical factors constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 98% in the discovery set. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 0.70, 0.99, 0.93, and 0.93, respectively. Our model captured predictive dynamics of lactate dehydrogenase (LDH) and creatine kinase (CK) while their levels were in the normal range. This model is accessible at https://www.guomics.com/covidAI/ for research purpose.

In this research, a magnetic core-shell composite, consisting of a Fe3O4 core and a silica shell (called Fe3O4@SiO2), was developed and then functionalized via MnO2 grafting at different MnO2 deposition levels (termed Fe3O4@SiO2-MnO2). The resulting materials were characterized by X-ray fluorescence, X-ray diffraction, a vibration sample magnetometer, transmission electron microscopy, N2 adsorption-desorption, zeta-potential studies and X-ray photoelectron spectroscopy. Visualizations showed that Fe3O4@SiO2-MnO2 had a magnetite core with size of 100 nm, overlaid by a rough silica shell and a relatively loose MnO2 deposition. The Pb(II) adsorption onto the composites was also assessed. It was found that MnO2 deposition on the Fe3O4@SiO2 surface enhanced Pb(II) adsorption, and the Pb(II) adsorption amount was highly correlated to the MnO2 deposition level. The adsorption kinetics of Pb(II) followed pseudo-second-order kinetics, and the adsorption rate could be decreased by increasing the initial concentration of Pb(II). A higher pH resulted in enhanced Pb(II) adsorption, which slightly increased with the coexistence of Na+ and Ca2+, along with the presence of dissolved humic acid. The adsorbent could easily be separated and recovered under the action of the external magnetic component and it displayed stable adsorption behaviour over four adsorption-desorption periods. The results emphasize the high potential of Fe3O4@SiO2-MnO2 materials for the adsorptive removal of Pb(II) in water.

Concomitant coagulation disorder can occur in severe patients withCOVID-19, but in-depth studies are limited. This study aimed to describe the parameters of coagulation function of patients with COVID-19 and reveal the risk factors of developing severe disease. This study retrospectively analyzed 113patients with SARS-CoV-2 infection in Taizhou Public Health Center. Clinical characteristics and indexes of coagulation function were collected. A multivariate Cox analysis was performed to identify potential biomarkers for predicting disease progression. Based on the results of multivariate Cox analysis, a Nomogram was built and the predictive accuracy was evaluated through the calibration curve, decision curve, clinical impact curve, and Kaplan–Meier analysis. Sensitivity, specificity, predictive values were calculated to assess the clinical value. The data showed that Fibrinogen, FAR, and D-dimer were higher in the severe patients, while PLTcount, Alb were much lower. Multivariate Cox analysis revealed that FAR and PLT count were independent risk factors for disease progression. The optimal cutoff values for FAR and PLT count were 0.0883 and 135*109/L, respectively. The C-index [0.712 (95% CI = 0.610–0.814)], decision curve, clinical impact curve showed that Nomogram could be used to predict the disease progression. In addition, the Kaplan–Meier analysis revealed that potential risk decreased in patients with FAR135*109/L.The model showed a good negative predictive value [(0.9474 (95%CI = 0.845–0.986)].This study revealed that FAR and PLT count were independent risk factors for severe illness and the severity of COVID-19 might be excluded when FAR135*109/L.

Guidelines and recommendations from public health authorities related to face masks have been essential for containing the COVID-19 pandemic. A cross-sectional survey was conducted in Ningbo City, China, from April 8 to 12, 2022. We assessed the behavioral differences and correlates of mask usage, primarily mask-removal. We examined public mask-wearing behavior during on-site COVID-19 nucleic acid detection. The survey instrument was developed based on the guidelines issued by the World Health Organization and consisted of demographics, mask-wearing knowledge, and behavior. We analyzed data from 1180 participants; 73.2% demonstrated good mask-wearing knowledge. However, regarding mask-wearing behavior, only 53.7% knew the correct way to remove a mask; 70.3% maintained hand hygiene after touching the outside. Binary logistic regression analyses revealed that health prevention knowledge and free mask distribution were positively associated with two types of mask-wearing behaviors. Most participants used masks during the COVID-19 pandemic; however, mask-removal and hand hygiene were neglected when touching the outside of the mask. More attention must be paid to mask-removal and hand hygiene details. Local health authorities should consider introducing the free distribution of masks.

Primary coenzyme Q10 deficiency-6 (COQ10D6), as a rare autosomal recessive disease caused by COQ6 mutations, is characterized by progressive infantile-onset nephrotic syndrome resulting in end-stage renal failure and sensorineural hearing loss. Here, we report two Chinese siblings with COQ10D6 who primarily presented with severe metabolic acidosis, proteinuria, hypoalbuminemia, growth retardation, and muscle hypotonia and died in early infancy. Using whole-exome sequencing and Sanger sequencing, we identified two rare recessive nonsense mutations in the COQ6 gene segregating with disease in affected family members: c.249C > G (p.Tyr83Ter) and c.1381C > T (p.Gln461Ter), resulting in two truncated protein products. Both mutations are located in a highly conserved area and are predicted to be pathogenic. Indeed, the death of our patients in early infancy indicates the pathogenicity of the p.Tyr83Ter and p.Gln461Ter variants and highlights the significance of the two variants for COQ6 enzyme function, which is necessary for the biosynthesis of coenzyme Q10. In conclusion, we discovered a novel compound heterozygous pathogenic variant of the COQ6 gene as a cause of severe COQ10D6 in the two siblings. Based on the clinical history and genetic characteristics of the patients, our cases expand the genotypic spectrum of COQ10D6 and highlight the heterogeneity and severity of clinical features associated with COQ6 mutations. For patients with clinical manifestations suggestive of COQ10D6, early testing for COQ6 mutations is beneficial for disease diagnosis and therapeutic interventions as well as disease prevention in future generations.

The relationship among the gut microbiome, global fecal metabolites and rheumatoid arthritis (RA) has not been systematically evaluated. In this study, we performed 16S rDNA sequencing and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based nontargeted metabolomic profiling on feces of 26 untreated RA patients and 26 healthy controls. Twenty-six genera and forty-one MS2-identified metabolites were significantly altered in the RA patients. Klebsiella, Escherichia, Eisenbergiella and Flavobacterium were more abundant in the RA patients, while Fusicatenibacter, Megamonas and Enterococcus were more abundant in the healthy controls. Function prediction analysis demonstrated that the biosynthesis pathways of amino acids, such as L-arginine and aromatic amino acids, were depleted in the RA group. In the metabolome results, fecal metabolites including glycerophospholipids (PC(18:3(9Z,12Z,15Z)/16:1(9Z)), lysoPE 19:1, lysoPE 18:0, lysoPC(18:0/0:0)), sphingolipids (Cer(d18:0/16:0), Cer(d18:0/12:0), Cer(d18:0/14:0)), kynurenic acid, xanthurenic acid and 3-hydroxyanthranilic acid were remarkably altered between the RA patients and healthy controls. Dysregulation of pathways, such as tryptophan metabolism, alpha-linolenic acid metabolism and glycerophospholipid metabolism, may contribute to the development of RA. Additionally, we revealed that the gut microbiome and metabolites were interrelated in the RA patients, while Escherichia was the core genus. By depicting the overall landscape of the intestinal microbiome and metabolome in RA patients, our study could provide possible novel research directions regarding RA pathogenesis and targeted therapy.

The alpine forage grass species Elymus nutans Griseb. is widely distributed in the Qinghai–Tibet Plateau and the Himalayas due to its high adaptability. However, it has become threatened by climate warming and excessive grazing. Thus, understanding its genetic and phenotypic information is crucial to aid resource management and conservation efforts. In this study, microsatellite markers were developed based on RNA-seq transcriptome data from E. nutans Griseb. varieties ‘Aba’ and ‘Kangbei’, resulting in the identification of 48,457 SSRs from 304,554 de novo assembled unigenes. Seventeen polymorphic markers, 13 inflorescence phenotypic traits, and seed shattering values were determined for 31 E. nutans accessions collected from eastern Tibet. The molecular markers generated 134 well-amplified bands with a mean Nei’s genetic diversity of 0.31 and a Shannon information index of 0.46. Pairwise genetic similarity ranged from 0.554 to 0.895, with an average of 0.729. Based on the molecular marker data, all accessions were divided into two classes via the unweighted pair-group method with arithmetic mean (UPGMA), the Markov chain Monte Carlo method, and the principal coordinate analysis (PCA) method. We used Tassel analysis to determine 11 loci with a significant relationship to phenotypic traits, and Pearson’s correlation analysis showed that some inflorescence traits were significantly influenced by the environment. Furthermore, we detected strong patterns of isolation by both environment (IBE) and distance (IBD) via Mantel analysis. This study provides valuable insights into the genetic and phenotypic differentiation of E. nutans, informing germplasm resource evaluation and future breeding.

Mobile crowdsensing (MCS) has been an emerging sensing paradigm in recent years, which uses a sensing platform for real-time processing to support various services for the Internet of Things (IoT) and promote the development of IoT. As an important component of MCS, how to design task assignment algorithms to cope with the coexistence of multiple concurrent heterogeneous tasks in group-oriented social relationships while satisfying the impact of users’ preferences on heterogeneous multitask assignment and solving the preference matching problem under heterogeneous tasks, is one of the most pressing issues. In this paper, a new algorithm, group-oriented adjustable bidding task assignment (GO-ABTA), is considered to solve the group-oriented bilateral preference-matching problem. First, the initial leaders and their collaborative groups in the social network are selected by group-oriented collaboration, and then the preference assignment of task requesters and users is modeled as a stable preference-matching problem. Then, a tunable bidding task assignment process is completed based on preference matching under budget constraints. Finally, the individual reasonableness, stability, and convergence of the proposed algorithm are demonstrated. The effectiveness of the proposed algorithm and its superiority to other algorithms are verified by simulation results.

The purpose of this study is to investigate the air quality levels of Nanyang city according to Chinese air quality standards. Therefore, in this study, fine particulate matter (PM2.5), coarse particulate matter (PM10), and total suspended particulate (TSP) were analyzed from 19 November 2021 to 19 March 2022 in Nanyang city. The results show that the average concentrations of PM2.5, PM10, and TSP were 106.47 µg/m3, 137.32 µg/m3, and 283.40 µg/m3, respectively. The numbers of days that meet the national secondary air quality standard of 24-h average concentrations were 29.75% for PM2.5, 63.64% for PM10, and 63.64% for TSP, indicating that most of the time, the air quality of Nanyang city remains polluted in winter, especially with more contributions of PM2.5 compared to PM10 and TSP. The higher concentrations were observed between 07:00 and 08:00, suggesting that vehicular emissions can be a major cause of air pollution in Nanyang city. The results also show a significant positive correlation between particulate matter and relative humidity, and a weak correlation with temperature and wind speed, which suggests that higher relative humidity increases the formation of particulate matter. This study can provide theoretical support for the local government to formulate air pollution prevention and control policies for Nanyang city.

Energy harvesting (EH) and cooperative communication techniques have been widely used in cognitive radio networks. However, most studies on throughput in energy-harvesting cooperative cognitive radio networks (EH-CCRNs) are end-to-end, which ignores the overall working state of the network. For the above problems, under the premise of prioritizing the communication quality of short-range users, this paper focuses on the optimization of the EH-CCRN average throughput, with energy and transmission power as constraints. The formulated problem was an unsolved non-deterministic polynomial-time hardness (NP-hard) problem. To make it tractable to solve, a multi-user time-power resource allocation algorithm (M-TPRA) is proposed, which is based on sub-gradient descent and unary linear optimization methods. Simulation results show that the M-TPRA algorithm can improve the average throughput of the network. In addition, the energy consumed by executing the M-TPRA algorithm is analyzed.

With increasing nitrogen application in soil, the problem of nitrate accumulation in soil and vegetable bodies has become increasingly serious. In this study, Bacillus subtilis (B. subtilis) Strain11 was isolated and studied for its effects in combination with Molybdenum (Mo) on the growth of Chinese cabbage and soil nitrate content. The results showed that the strain effectively increased the growth, height, and moisture content of Chinese cabbage by 27% and 2.5%, respectively, compared to the control. Mo application alone reduced soil nitrate accumulation and increased root length, height, chlorophyll content, and moisture content of Chinese cabbage, with an optimal rate of 0.8–1.2 mg/kg soil. The application of Mo fertilizer in combination with the Bacillus strain was the most effective in increasing plant height and root length of Chinese cabbage, which were 1.49 times and 1.68 times that of the control, respectively. The proportion of dry matter, the average fresh weight, and the dry weight under this treatment were 9.01%, 5.83 g/plant, and 0.53 g/plant, respectively, higher than the rest. At harvest, the highest ammonium-nitrogen content in this treatment group was 8.56 mg/kg, and the soil nitrate reduction reached 40.68%. In conclusion, Mo fertilizer at a rate of 0.8 mg Mo/kg soil, in combination with B. subtilis Strain11, was recommended for the remediation of nitrate-contaminated soils.

Kengyilia is a group of allohexaploid species that arose from two hybridization events followed by genome doubling of three ancestral diploid species with different genomes St, Y, and P in the Triticeae. Estimating the phylogenetic relationship in resolution of the maternal lineages has been difficult, owing to the extremely low rate of sequence divergence. Here, phylogenetic reconstructions based on the plastome sequences were used to explore the role of maternal progenitors in the establishment of Kengyilia polyploid species. The plastome sequences of 11 Kengyilia species were analyzed together with 12 tetraploid species (PP, StP, and StY) and 33 diploid taxa representing 20 basic genomes in the Triticeae. Phylogenomic analysis and genetic divergence patterns suggested that (1) Kengyilia is closely related to Roegneria, Pseudoroegneria, Agropyron, Lophopyrum, Thinopyrum, and Dasypyrum; (2) both the StY genome Roegneria tetraploids and the PP genome Agropyron tetraploids served as the maternal donors during the speciation of Kengyilia species; (3) the different Kengyilia species derived their StY genome from different Roegneria species. Multiple origins of species via independent polyploidization events have occurred in the genus Kengyilia, resulting in a maternal haplotype polymorphism. This helps explain the rich diversity and wide adaptation of polyploid species in the genus Kengyilia.

Mechanical equipment is a key component of mechanical equipment, and its working condition is directly related to the overall performance of mechanical equipment. Accurate evaluation and prediction of the performance degradation trend of mechanical equipment is of great significance to ensure the reliability and safety of the mechanical equipment system. Based on the data of typical faulty equipment, this paper analyzes the energy characteristic parameters of mechanical equipment under different types and degrees of failure in the time domain. Using amplitude spectrum analysis, Hilbert envelope demodulation and wavelet packet decomposition method, and other vibration signal processing methods, preliminary extraction of multiple statistical feature parameters are given. Secondly, in view of the irrelevant and redundant components of multiple statistical parameters, a new method for extracting fault features of mechanical equipment based on variance value and principal component analysis is proposed. This method can effectively classify the fault status of mechanical equipment. The effectiveness of the method is verified by actual equipment signals. After that, the value extracted from the vibration signal of the double-row roller equipment is used as the degradation feature. In order to reduce the influence of irregular characteristics in the vibration signal and simplify the complexity of the vibration signal, the wavelet transform and the support vector machine model are combined, according to the degradation after decomposition. The 95% confidence interval of the predicted value is also given. The SVM model is established based on data characteristics, and single-step and multistep prediction of equipment degradation trends are carried out. The prediction result shows that, according to the mapping position formula, the distribution of equipment degradation prediction points is obtained, and a 95% confidence interval based on the distribution of the prediction points is given. Finally, on the basis of completing feature extraction, this paper applies an unsupervised feature selection method. The sensitive characteristics of life prediction and the prediction results of a single SVM model and a neural network model are compared and analyzed at the same time.

Dactylis glomerata L. (orchardgrass) is an important perennial forage species in temperate areas of the world. It is usually used for silage, grazing and hay because of its high nutritional value and reproducibility. Central Asia, Xinjiang and Tibetan Plateau in China possess various special micro-environments that harbor many valuable resources, while different degrees of degradation of the grassland ecosystem occurred due to climatic changing and human activities. Investigating the genetic diversity of wild D. glomerat could provide basis for collection, protection, and utilization of some excellent germplasm resources. Totally 210 individuals from 14 populations-five from Xinjiang, two from Kangding (Tibetan Plateau), and seven from Central Asia were identified using AFLP technology. The average values of Nei's genetic diversity (Hj) and Shannon information index (Ho) were 0.383 and 0.394 respectively. UPGMA tree, STRUCTURE analysis and principal coordinate analysis (PCoA) showed populations from same region clustered together. AMOVA revealed 35.10% of the genetic differentiation (Fst) occurred among populations. Gene flow (Nm) was limited among all populations. Genetic diversity of D. glomerata was high but limited under isolation-by-distance pattern, resulting in high genetic differentiation and low gene flow among populations. Adjacent regions also exhibited similar results because of the barriers of high mountains. The environmental factors, such as precipitation, elevation, latitude and longitude also had some impacts on genetic diversity and structure pattern of populations.

A novel dual‐band bandpass filter (BPF) based on a single triple‐mode ring resonator is proposed. The proposed BPF could provide three transmission poles for each passband to improve operating bandwidth. Meanwhile, seven transmission zeros are achieved at the stopband to improve the selectivity. The proposed dual‐band BPF was designed, fabricated and tested. The measured results are in good agreement with the simulated values.

E. sibiricus L., the type species of the genus Elymus, is a perennial, self-pollinating and allotetraploid grass indigenous to Northern Asia, which in some countries can be cultivated as an important forage grass. In the present study, eighty-six Elymus sibiricus accessions, mostly from different parts of Asia, were assayed by gliadin markers based on Acid Polyacrylamide Gel Electrophoresis to differentiate and explore their genetic relationships. The genetic similarity matrix was calculated by 47 polymorphic bands, which ranged from 0.108 to 0.952 with an average of 0.373. The total Shannon diversity index (Ho) and the Simpson index (He) was 0.460 and 0.302, respectively. Cluster analysis showed a clear demarcation between accessions from Qinghai-Tibetan Plateau, China and the others as separate groups. The clustering pattern was probably dependent on geographic origin and ecological adaptability of the accessions. The population structure analysis based on Shannon indices showed that the proportion of variance within and among the five geographic regions of the Northern Hemisphere was 55.9 and 44.1%, respectively, or 63.4 and 36.6% within and among six Chinese provinces. This distinct geographical divergence was perhaps depended on ecogeographical conditions such as climate difference and mountain distribution. The results of gladin analysis in this study are useful for the collection and preservation of E. sibiricus germplasm resources.