WeiTsing, a pericycle-expressed ion channel, safeguards the stele to confer clubroot resistance.

Plant roots encounter numerous pathogenic microbes that often cause devastating diseases. One such pathogen, Plasmodiophora brassicae (Pb), causes clubroot disease and severe yield losses on cruciferous crops worldwide. Here, we report the isolation and characterization of WeiTsing (WTS), a broad-spectrum clubroot resistance gene from Arabidopsis. WTS is transcriptionally activated in the pericycle upon Pb infection to prevent pathogen colonization in the stele. Brassica napus carrying the WTS transgene displayed strong resistance to Pb. WTS encodes a small protein localized in the endoplasmic reticulum (ER), and its expression in plants induces immune responses. The cryoelectron microscopy (cryo-EM) structure of WTS revealed a previously unknown pentameric architecture with a central pore. Electrophysiology analyses demonstrated that WTS is a calcium-permeable cation-selective channel. Structure-guided mutagenesis indicated that channel activity is strictly required for triggering defenses. The findings uncover an ion channel analogous to resistosomes that triggers immune signaling in the pericycle.

Adaptive evolution of the enigmatic Takakia now facing climate change in Tibet.

The most extreme environments are the most vulnerable to transformation under a rapidly changing climate. These ecosystems harbor some of the most specialized species, which will likely suffer the highest extinction rates. We document the steepest temperature increase (2010-2021) on record at altitudes of above 4,000 m, triggering a decline of the relictual and highly adapted moss Takakia lepidozioides. Its de-novo-sequenced genome with 27,467 protein-coding genes includes distinct adaptations to abiotic stresses and comprises the largest number of fast-evolving genes under positive selection. The uplift of the study site in the last 65 million years has resulted in life-threatening UV-B radiation and drastically reduced temperatures, and we detected several of the molecular adaptations of Takakia to these environmental changes. Surprisingly, specific morphological features likely occurred earlier than 165 mya in much warmer environments. Following nearly 400 million years of evolution and resilience, this species is now facing extinction.

Pan-genome analysis of 33 genetically diverse rice accessions reveals hidden genomic variations.

Structural variations (SVs) and gene copy number variations (gCNVs) have contributed to crop evolution, domestication, and improvement. Here, we assembled 31 high-quality genomes of genetically diverse rice accessions. Coupling with two existing assemblies, we developed pan-genome-scale genomic resources including a graph-based genome, providing access to rice genomic variations. Specifically, we discovered 171,072 SVs and 25,549 gCNVs and used an Oryza glaberrima assembly to infer the derived states of SVs in the Oryza sativa population. Our analyses of SV formation mechanisms, impacts on gene expression, and distributions among subpopulations illustrate the utility of these resources for understanding how SVs and gCNVs shaped rice environmental adaptation and domestication. Our graph-based genome enabled genome-wide association study (GWAS)-based identification of phenotype-associated genetic variations undetectable when using only SNPs and a single reference assembly. Our work provides rich population-scale resources paired with easy-to-access tools to facilitate rice breeding as well as plant functional genomics and evolutionary biology research.

Genome-wide association study for stalk lodging resistance related traits in maize (Zea mays L.).

BACKGROUND: The stalk traits stalk diameter, stalk length, rind penetrometer resistance and dry matter content are important indicators for measuring lodging resistance. RESULTS: In this study, 377 inbred lines were used as the basic materials, and four stalk-related traits including stalk diameter, stalk length, rind penetrometer resistance and dry matter content of the third segment of maize, were investigated at the tasseling, grain filling, and maturity stages. 461,053 high-quality SNPs which were obtained by whole genome resequencing were used for genome-wide association study. As a result of mixed linear model analysis (P < 9.77 × 10-6), 29 significant SNPs related to traits were detected, accounting for 7.19% -15.03% of phenotypic variation, among which 4, 1, 4 and 20 SNPs were found related to rind penetrometer resistance, stalk diameter, stalk length, and dry matter content respectively. Most candidate genes are related to plant element structure, signal transduction mechanisms, inorganic ion transport and metabolism, nucleotide transport and metabolism, and transporter enzyme families. Comparing mixed linear model with generalized linear model, a total of 12 candidate genes were detected repeatedly, during which the candidate gene Zm00001d014449 were detected 5 times, with a phenotypic variation interpretation rate of 9.95% -10.84%. This gene is mainly expressed in cells with active cell division and tissue differentiation, and is involved in the formation of stalk vascular bundles and the synthesis of cell walls. Another candidate gene, Zm00001d005300, encodes the transcription factor MYB44, which regulates the dependence of salt stress signal phosphorylation, can effectively inhibit the accumulation of destructive reactive oxygen species, and has a certain resistance to non-biotic stress. In addition, this study also found that 10 unknown functional genes can be further Functional verification. CONCLUSIONS: This study helps to deepen the understanding of the genetic basis of traits related to maize stalk lodging resistance, and provides theoretical guidance for future maize lodging resistance breeding.

Strategies to Promote the Journey of Nanoparticles Against Biofilm-Associated Infections.

Biofilm-associated infections are one of the most challenging healthcare threats for humans, accounting for 80% of bacterial infections, leading to persistent and chronic infections. The conventional antibiotics still face their dilemma of poor therapeutic effects due to the high tolerance and resistance led by bacterial biofilm barriers. Nanotechnology-based antimicrobials, nanoparticles (NPs), are paid attention extensively and considered as promising alternative. This review focuses on the whole journey of NPs against biofilm-associated infections, and to clarify it clearly, the journey is divided into four processes in sequence as 1) Targeting biofilms, 2) Penetrating biofilm barrier, 3) Attaching to bacterial cells, and 4) Translocating through bacterial cell envelope. Through outlining the compositions and properties of biofilms and bacteria cells, recent advances and present the strategies of each process are comprehensively discussed to combat biofilm-associated infections, as well as the combined strategies against these infections with drug resistance, aiming to guide the rational design and facilitate wide application of NPs in biofilm-associated infections.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images.

BACKGROUND: Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC). METHODS: DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS. RESULTS: Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression. CONCLUSION: DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms.

Association of the triglyceride-glucose index with all-cause and cardiovascular mortality in patients with cardiometabolic syndrome: a national cohort study.

OBJECTIVE: This study aimed to evaluate the association of triglyceride-glucose (TyG) index with all-cause and cardiovascular mortality risk among patients with cardiometabolic syndrome (CMS). METHODS: We performed a cohort study of 5754 individuals with CMS from the 2001-2018 National Health and Nutrition Examination Survey. The TyG index was calculated as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. Multivariate Cox proportional hazards regression models assessed the associations between TyG index and mortality . Non-linear correlations and threshold effects were explored using restricted cubic splines and a two-piecewise Cox proportional hazards model. RESULTS: Over a median follow-up of 107 months, 1201 all-cause deaths occurred, including 398 cardiovascular disease-related deaths. The multivariate Cox proportional hazards regression model showed a positive association between the TyG index and all-cause and cardiovascular mortality. Each one-unit increase in the TyG index was associated with a 16% risk increase in all-cause mortality (HR: 1.16, 95% CI 1.03, 1.31, P = 0.017) and a 39% risk increase in cardiovascular mortality (HR: 1.39, 95% CI 1.14, 1.71, P = 0.001) after adjusting for confounders. The restricted cubic splines revealed a U-shaped association between the TyG index and all-cause (P for nonlinear < 0.001) and cardiovascular mortality (P for nonlinear = 0.044), identifying threshold values (all-cause mortality: 9.104; cardiovascular mortality: 8.758). A TyG index below these thresholds displayed a negative association with all-cause mortality (HR: 0.58, 95% CI 0.38, 0.90, P = 0.015) but not with cardiovascular mortality (HR: 0.39, 95% CI 0.12, 1.27, P = 0.119). Conversely, a TyG index exceeding these thresholds was positively associated with all-cause and cardiovascular mortality (HR: 1.35, 95% CI 1.17, 1.55, P < 0.001; HR: 1.54, 95% CI 1.25, 1.90, P < 0.001, respectively). Notably, a higher TyG index (≥ threshold values) was significantly associated with increased mortality only among individuals aged under 55 compared to those with a lower TyG index (< threshold values). CONCLUSIONS: The TyG index demonstrated a U-shaped correlation with all-cause and cardiovascular mortality in individuals with CMS. The thresholds of 9.104 and 8.758 for all-cause and cardiovascular mortality, respectively, may be used as intervention targets to reduce the risk of premature death and cardiovascular disease.

Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods.

Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one of the key factors for the successful marketing of drug candidates. Therefore, predicting half-life is of great significance in drug design. In this study, we employed eXtreme Gradient Boosting (XGboost), randomForest (RF), gradient boosting machine (GBM), and supporting vector machine (SVM) to build quantitative structure-activity relationship (QSAR) models on 3512 compounds and evaluated model performance by using root-mean-square error (RMSE), R2, and mean absolute error (MAE) metrics and interpreted features by SHapley Additive exPlanation (SHAP). Furthermore, we developed consensus models through integrating four individual models and validated their performance using a Y-randomization test and applicability domain analysis. Finally, matched molecular pair analysis was used to extract the transformation rules. Our results revealed that XGboost outperformed other individual models (RMSE = 0.176, R2 = 0.845, MAE = 0.141). The consensus model integrating all four models continued to enhance prediction performance (RMSE = 0.172, R2 = 0.856, MAE = 0.138). We evaluated the reliability, robustness, and generalization ability via Y-randomization test and applicability domain analysis. Meanwhile, we utilized SHAP to interpret features and employed matched molecular pair analysis to extract chemical transformation rules that provide suggestions for optimizing drug structure. In conclusion, we believe that the consensus model developed in this study serve as a reliable tool to evaluate half-life in drug discovery, and the chemical transformation rules concluded in this study could provide valuable suggestions in drug discovery.

Toward Low-Carbon Rice Production in China: Historical Changes, Driving Factors, and Mitigation Potential.

Under the "Double Carbon" target, the development of low-carbon agriculture requires a holistic comprehension of spatially and temporally explicit greenhouse gas (GHG) emissions associated with agricultural products. However, the lack of systematic evaluation at a fine scale presents considerable challenges in guiding localized strategies for mitigating GHG emissions from crop production. Here, we analyzed the county-level carbon footprint (CF) of China's rice production from 2007 to 2018 by coupling life cycle assessment and the DNDC model. Results revealed a significant annual increase of 74.3 kg CO2-eq ha-1 in the average farm-based CF (FCF), while it remained stable for the product-based CF (PCF). The CF exhibited considerable variations among counties, ranging from 2324 to 20,768 kg CO2-eq ha-1 for FCF and from 0.36 to 3.81 kg CO2-eq kg-1 for PCF in 2018. The spatiotemporal heterogeneities of FCF were predominantly influenced by field CH4 emissions, followed by diesel consumption and soil organic carbon sequestration. Scenario analysis elucidates that the national total GHG emissions from rice production could be significantly reduced through optimized irrigation (48.5%) and straw-based biogas production (18.0%). Moreover, integrating additional strategies (e.g., advanced crop management, optimized fertilization, and biodiesel application) could amplify the overall emission reduction to 76.7% while concurrently boosting the rice yield by 11.8%. Our county-level research provides valuable insights for the formulation of targeted GHG mitigation policies in rice production, thereby advancing the pursuit of carbon-neutral agricultural practices.

Genome sequence of the progenitor of wheat A subgenome Triticum urartu.

Triticum urartu (diploid, AA) is the progenitor of the A subgenome of tetraploid (Triticum turgidum, AABB) and hexaploid (Triticum aestivum, AABBDD) wheat1,2. Genomic studies of T. urartu have been useful for investigating the structure, function and evolution of polyploid wheat genomes. Here we report the generation of a high-quality genome sequence of T. urartu by combining bacterial artificial chromosome (BAC)-by-BAC sequencing, single molecule real-time whole-genome shotgun sequencing 3 , linked reads and optical mapping4,5. We assembled seven chromosome-scale pseudomolecules and identified protein-coding genes, and we suggest a model for the evolution of T. urartu chromosomes. Comparative analyses with genomes of other grasses showed gene loss and amplification in the numbers of transposable elements in the T. urartu genome. Population genomics analysis of 147 T. urartu accessions from across the Fertile Crescent showed clustering of three groups, with differences in altitude and biostress, such as powdery mildew disease. The T. urartu genome assembly provides a valuable resource for studying genetic variation in wheat and related grasses, and promises to facilitate the discovery of genes that could be useful for wheat improvement.

Associations between Life's Essential 8 and abdominal aortic calcification among US Adults: a cross-sectional study.

BACKGROUND: Cardiovascular health (CVH) and abdominal aortic calcification (AAC) are closely linked to cardiovascular disease (CVD) and related mortality. However, the relationship between CVH metrics via Life's Essential 8 (LE8) and AAC remains unexplored. METHODS: The study analyzed data from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) cohort, which included adults aged 40 or above. The research used the LE8 algorithm to evaluate CVH. Semi-quantitative AAC-24 scoring techniques were employed to assess AAC, categorized into no calcification, mild to moderate calcification, and severe calcification. RESULTS: The primary analysis involved 2,478 participants. Following adjustments for multiple factors, the LE8 score exhibited a significant association with ACC risk (Mild-moderate ACC: 0.87, 95% CI: 0.81,0.93; Severe ACC: 0.77, 95% CI: 0.69,0.87, all P < 0.001), indicating an almost linear dose-response relationship. Compared to the low CVH group, the moderate CVH group showed lower odds ratios (OR) for mild-moderate and severe calcification (OR = 0.78, 95% CI: 0.61-0.99, P = 0.041; OR = 0.68, 95% CI: 0.46-0.99, P = 0.047, respectively). Moreover, the high CVH group demonstrated even lower ORs for mild-moderate and severe calcification (OR = 0.46, 95% CI: 0.31, 0.69, P < 0.001; OR = 0.29, 95% CI: 0.14, 0.59, P = 0.001, respectively). Interactions were found between chronic kidney disease (CKD) condition, history of CVD, marital status and CVH metrics to ACC. Participants without CKD exhibited a more pronounced negative association between the CVH metric and both mild-moderate and severe ACC. Those lacking a history of CVD, and never married/widowed/divorced/separated showed a stronger negative association between the CVH metric and severe ACC. CONCLUSIONS: The novel CVH metrics demonstrated an inverse correlation with the risk of AAC. These findings suggest that embracing improved CVH levels may assist in alleviating the burden of ACC.

SNHG1, interacting with SND1, contributes to sorafenib resistance of liver cancer cells by increasing m6A-mediated SLC7A11 expression and promoting aerobic glycolysis.

Aerobic glycolysis plays an important role in multidrug resistance of cancer cells. Here, we screened different expressed lncRNAs associated with sorafenib resistance of liver cancer cells, by intersecting the bioinformatics analyses of TCGA and GEO (the GSE62813 dataset) databases. Our results revealed that the 18 upregulated lncRNAs in the intersection are associated with and enriched in metabolism of small molecule organic acids, suggesting their potential in glycolysis. The lncRNA small nucleolar RNA host gene 1 (Snhg1) was chosen as a potential regulator of aerobic glycolysis in liver cancer cells, for its significant promotion on lactate production. Gain- and loss-of-function experiments mediated by Crispr-Cas9 technique in HepG2 cells indicated that Snhg1 promoted cell proliferation, invasion, sorafenib resistance, and aerobic glycolysis. In the mechanism exploration, we found that Snhg1 can interact with SND1 protein, a famous RNA binding protein and recently identified "Reader" of N6-methyladenosine (m6A). SND1 was demonstrated to be positively regulated by Snhg1 and had similar promoting effects on proliferation, invasion, sorafenib resistance, and aerobic glycolysis of HepG2 cells. SND1 bound with and promoted the expression of SLC7A11, an aerobic glycolysis regulator. Furthermore, either silencing SLC7A11 or blocking aerobic glycolysis with 2-deoxy-d-glucose (2-DG) was able to reverse the promotion of Snhg1 overexpression on malignancy, sorafenib resistance, and aerobic glycolysis of HepG2 cells. Finally, in a liver cancer xenograft mouse model, we found that formed tumors with Snhg1-knocked-down HepG2 cells were more sensitive to sorafenib administration. Altogether, SNHG1 contributes to sorafenib resistance of liver cancer cells by promoting SND1-m6A-SLC7A11-mediated aerobic glycolysis.

Environmental fate of microplastics in high-altitude basins: the insights into the Yarlung Tsangpo River Basin.

Microplastics (MPs) have been found in remote high-altitude areas, but the main source and migration process remained unclear. This work explored the characteristics and potential sources of MPs in the Yarlung Tsangpo River Basin. The average abundances of MPs in water, sediment, and soil samples were 728.26 ± 100.53 items/m3, 43.16 ± 5.82 items/kg, and 61.92 ± 4.29 items/kg, respectively, with polypropylene and polyethylene as the main polymers. The conditional fragmentation model revealed that the major source of MPs lower than 4000 m was human activities, while that of higher than 4500 m was atmospheric deposition. Community analysis was further conducted to explore the migration process and key points of MPs among different compartments in the basin. It was found that Lhasa (3600 m) and Shigatse (4100 m) were vital sources of MPs inputs in the midstream and downstream, respectively. This work would provide new insights into the fate of MPs in high-altitude areas.

Targeted co-delivery of PD-L1 monoclonal antibody and sorafenib to circulating tumor cells via platelet-functionalized nanocarriers.

BACKGROUND: Circulating tumor cells (CTCs) can adsorb and activate platelets to form a microthrombus protective barrier around them, so that therapeutic drugs and immune cells cannot effectively kill CTCs. The platelet membrane (PM) bionic carrying drug system has the powerful ability of immune escape, and can circulate in the blood for a long time. MATERIALS AND METHODS: we developed platelet membrane coated nanoparticles (PM HMSNs) to improve the precise delivery of drugs to tumor sites and to achieve more effective immunotherapy combined with chemotherapy strategy. RESULTS: Successfully prepared aPD-L1-PM-SO@HMSNs particles, whose diameter is 95-130 nm and presenting the same surface protein as PM. Laser confocal microscopy and flow cytometry experimental results showed that the fluorescence intensity of aPD-L1-PM-SO@HMSNs was greater than SO@HMSNs that are not coated by PM. Biodistribution studies in H22 tumor-bearing mice showed that due to the combined action of the active targeting effect and the EPR effect, the high accumulation of aPD-L1-PM-SO@HMSNs in the local tumor was more effective in inhibiting tumor growth than other groups of therapeutic agents. CONCLUSION: Platelet membrane biomimetic nanoparticles have a good targeted therapeutic effect, which can effectively avoid immune clearance and have little side effects. It provides a new direction and theoretical basis for further research on targeted therapy of CTCs in liver cancer.

S1PR1 attenuates pulmonary fibrosis by inhibiting EndMT and improving endothelial barrier function.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a chronic fatal disease of unknown etiology. Its pathological manifestations include excessive proliferation and activation of fibroblasts and deposition of extracellular matrix. Endothelial cell-mesenchymal transformation (EndMT), a novel mechanism that generates fibroblast during IPF, is responsible for fibroblast-like phenotypic changes and activation of fibroblasts into hypersecretory cells. However, the exact mechanism behind EndMT-derived fibroblasts and activation is uncertain. Here, we investigated the role of sphingosine 1-phosphate receptor 1 (S1PR1) in EndMT-driven pulmonary fibrosis. METHODS: We treated C57BL/6 mice with bleomycin (BLM) in vivo and pulmonary microvascular endothelial cells with TGF-ß1 in vitro. Western blot, flow cytometry, and immunofluorescence were used to detect the expression of S1PR1 in endothelial cells. To evaluate the effect of S1PR1 on EndMT and endothelial barrier and its role in lung fibrosis and related signaling pathways, S1PR1 agonist and antagonist were used in vitro and in vivo. RESULTS: Endothelial S1PR1 protein expression was downregulated in both in vitro and in vivo models of pulmonary fibrosis induced by TGF-ß1 and BLM, respectively. Downregulation of S1PR1 resulted in EndMT, indicated by decreased expression of endothelial markers CD31 and VE-cadherin, increased expression of mesenchymal markers α-SMA and nuclear transcription factor Snail, and disruption of the endothelial barrier. Further mechanistic studies found that stimulation of S1PR1 inhibited TGF-ß1-mediated activation of the Smad2/3 and RhoA/ROCK1 pathways. Moreover, stimulation of S1PR1 attenuated Smad2/3 and RhoA/ROCK1 pathway-mediated damage to endothelial barrier function. CONCLUSIONS: Endothelial S1PR1 provides protection against pulmonary fibrosis by inhibiting EndMT and attenuating endothelial barrier damage. Accordingly, S1PR1 may be a potential therapeutic target in progressive IPF.

Hexapeptide induces M2 macrophage polarization via the JAK1/STAT6 pathway to promote angiogenesis in bone repair.

Angiogenesis is essential for successful bone defect repair. In normal tissue repair, the physiological inflammatory response is the main regulator of angiogenesis through the activity of macrophages and the cytokines secreted by them. In particular, M2 macrophages which secrete high levels of PDGF-BB are typically considered to promote angiogenesis. A hexapeptide [WKYMVm, (Trp-Lys-Tyr-Met-Val-D-Met-NH2)] has been reported to modulate inflammatory activities. However, the underlying mechanisms by which WKYMVm regulates macrophages remain unclear. In this study, the possible involvement by which WKYMVm induces the polarization of macrophages and affects their behaviors was evaluated. In vitro results showed that macrophages were induced to an M2 rather than M1 phenotype and the M2 phenotype was enhanced by WKYMVm through activation of the JAK1/STAT6 signaling pathway. It was also found that WKYMVm played an important role in the PDGF-BB production increase and proangiogenic abilities in M2 macrophages. Consistent with the results in vitro, the elevated M2/M0 ratio induced by WKYMVm enhanced the formation of new blood vessels in a femoral defect mouse model. These findings suggest that WKYMVm could be a promising alternative strategy for angiogenesis in bone repair by inducing M2 macrophage polarization.

Determination of 44 major components and chemical profiling of saccharide in Chinese medicinal formula Lanqin Oral Liquid.

INTRODUCTION: Lanqin Oral Liquid (LQL) is a traditional Chinese medicine preparation (TCMP) containing five herbal medicines and has been commonly used for the treatment of pharyngitis and hand-foot-and-mouth disease in clinic. The material basis of LQL has been reported in our previous study, but the contents of the major components and the features of saccharide in LQL are still unclear. OBJECTIVES: This study aimed to establish accurate and rapid methods for the quantification of the major components and profiling of saccharide in LQL. The quantitative results combined with similarity evaluation were applied to improve the quality control of LQL. METHODOLOGY: An ultra-high performance liquid chromatography coupled with triple-quadrupole tandem mass spectrometry (UPLC-QQQ-MS) method was utilised to determine 44 major components. Cosine similarity was used to evaluate the similarities among 20 batches of LQL based on the quantitative results of 44 major components. The physicochemical properties, structure, composition, and contents of saccharide in LQL were detected by a combination of chemical and instrumental analysis. RESULTS: A total of 44 compounds, including flavonoids, iridoid glycosides, alkaloids, and nucleosides, were accurately determined. The 20 batches of LQL were remarkably similar (> 0.95). In addition, d-glucose, galactose, d-glucuronic acid, arabinose, and d-mannose were detected in saccharide of LQL. The contents of saccharide in LQL were 13.52-21.09 mg/ml. CONCLUSIONS: The established methods can be applied for the comprehensive quality control of LQL, including characterisation of saccharide and quantification of representative components. Our study will provide a robust chemical foundation for disclosing the quality markers of its therapeutic effect.

Further mitigating carbon footprint pressure in urban agglomeration by enhancing the spatial clustering.

The increasing environmental pressure of anthropogenic CO2 emissions is impeding the sustainability of urban agglomerations (UAs). Recent research has shown that the spatial clustering of UA elements reduces CO2 emissions but underestimates its impact on vegetation carbon sequestration. Using an extended IPAT equation analysis framework and the Logarithmic Mean Divisia Index decomposition approach, this study revealed the positive effects of the economy and population spatial clustering on carbon footprint pressure (CFP) mitigation. Specifically, improving economic spatial clustering mitigated the rise in UA's CFP caused by affluence and population growth. Furthermore, population clustering in core cities effectively mitigated CFP in neighboring cities. Additionally, we found that the efficiency improvement, i.e., the decrease in the ratio of carbon emissions and gross domestic product, should be the dominant driver of CFP mitigation, followed by improved vegetation carbon sequestration. However, these drivers have limited future potential. We believe that by improving UA's spatial clustering of the economy and population, future urban environmental pressures and climate risks will be mitigated.

Enhancing sustainability of vegetation ecosystems through ecological engineering: A case study in the Qinghai-Tibet Plateau.

Ecological engineering is an important measure to promote ecosystem adaptation and restoration to deal with environmental change and human disturbance. To assess the effectiveness of ecological construction and analyze the influencing factors of ecosystem changes in the Qinghai-Tibet Plateau (QTP), this study detected the spatial changes and dynamic hotspots of vegetation ecosystems in the ecological construction regions of the QTP (QTPE) and regions without ecological construction (QTPWE) using hot spot analysis and comprehensive dynamic degree model. Then the random forest (RF) model and geographical weighted regression model were used to study the degree and spatial heterogeneity of impacts of climate and human activities on normalized difference vegetation index (NDVI). Results showed that the vegetation restoration of the QTPE was obvious during 2001-2018 as the area of the increasing NDVI accounted for 74.15%. In addition, the effects of climate and human activities on NDVI of vegetation ecosystem showed significant spatial heterogeneity. The RF model showed that population density was the most significant factor affecting ecosystem vegetation in the QTPE, and its relative importance was between 26.1-32.6%, followed by downward shortwave radiation (7.9-16.8%). However, climate factors still had the greatest impact in the QTPWE, with the relative importance of precipitation and temperature being 45% and 15%, respectively. These findings provide a scientific basis for the restoration and management of vegetation on the QTP, and are of great significance for the deployment of future ecological engineering projects.

High-quality Fagopyrum esculentum genome provides insights into the flavonoid accumulation among different tissues and self-incompatibility.

Common buckwheat (Fagopyrum esculentum) and Tartary buckwheat (Fagopyrum tataricum), the two most widely cultivated buckwheat species, differ greatly in flavonoid content and reproductive mode. Here, we report the first high-quality and chromosome-level genome assembly of common buckwheat with 1.2 Gb. Comparative genomic analysis revealed that common buckwheat underwent a burst of long terminal repeat retrotransposons insertion accompanied by numerous large chromosome rearrangements after divergence from Tartary buckwheat. Moreover, multiple gene families involved in stress tolerance and flavonoid biosynthesis such as multidrug and toxic compound extrusion (MATE) and chalcone synthase (CHS) underwent significant expansion in buckwheat, especially in common buckwheat. Integrated multi-omics analysis identified high expression of catechin biosynthesis-related genes in flower and seed in common buckwheat and high expression of rutin biosynthesis-related genes in seed in Tartary buckwheat as being important for the differences in flavonoid type and content between these buckwheat species. We also identified a candidate key rutin-degrading enzyme gene (Ft8.2377) that was highly expressed in Tartary buckwheat seed. In addition, we identified a haplotype-resolved candidate locus containing many genes reportedly associated with the development of flower and pollen, which was potentially related to self-incompatibility in common buckwheat. Our study provides important resources facilitating future functional genomics-related research of flavonoid biosynthesis and self-incompatibility in buckwheat.