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Resource provisioning plays a pivotal role in determining the right amount of infrastructure resource to run applications and target the global decarbonization goal. A significant portion of production clusters is now dedicated to long-running applications (LRAs), which are typically in the form of microservices and executed in the order of hours or even months. It is therefore practically important to plan ahead the placement of LRAs in a shared cluster so that the number of compute nodes required by them can be minimized to reduce carbon footprint and lower operational costs. Existing works on LRA scheduling are often application-agnostic, without particularly addressing the constraining requirements imposed by LRAs, such as co-location affinity constraints and time-varying resource requirements. In this paper, we present an affinity-aware resource provisioning approach for deploying large-scale LRAs in a shared cluster subject to multiple constraints, with the objective of minimizing the number of compute nodes in use. We investigate a broad range of solution algorithms which fall into three main categories: Application-Centric, Node-Centric, and Multi-Node approaches, and tune them for typical large-scale real-world scenarios. Experimental studies driven by the Alibaba Tianchi dataset show that our algorithms can achieve competitive scheduling effectiveness and running time, as compared with the heuristics used by the latest work including Medea and LraSched., 22 pages, 7 figures

The postharvest physiological and metabolic activities caused fruits and vegetables (FV) quality deterioration. Therefore, developing an efficient preservation strategy is a promising approach to relieve this issue. In this study, a modified metal-organic framework (MOF; i.e., Cer@MHKUST-1) was encapsulated into a blended matrix of chitosan quaternary ammonium salt (CQAS)/gelatin to fabricate a multifunctional (water-locking, ethylene-removing, and antibacterial) packaging biopolymer-based film (i.e., CMCGF), the characteristics and preservative effects of the packaging were investigated. Results indicated that the physicochemical (e.g., mechanical, gas/light barrier, wettability) properties of CMCGF were improved compared with the control film (i.e., CGF). CMCGF have a higher ethylene adsorption performance of 65-69 cm

Due to the time-varying operation conditions, chemical processes are characterized by non-stationary characteristics, which makes it a great challenge for conventional process monitoring methods to capture the non-stationary variations In the non-stationary processes, the abnormality would cause the stationary variables to be non-stationary. In this article, a non-stationarity sensitive cointegration analysis monitoring method is proposed to explore potential non-stationary variations. First, the essential non-stationary variables are distinguished using Augmented Dickey-Fuller test to eliminate the influence of essential non-stationary under normal conditions. Then by further analyzing the faulty data, the variables which are sensitive to the non-stationary variations are selected. On this basis, cointegration analysis models are established for both the essential non-stationary variables and non-stationarity sensitive variables to explore long-term dynamic equilibrium relationship, respectively. With the selection of non-stationarity sensitive variables, the potential faulty information is emphasized in the process monitoring model, which makes the model capable to handle the non-stationary variations. Finally, the monitoring results are combined through Bayesian inference criterion. The proposed method is applied on the Tennessee Eastman process and a vinyl acetate monomer plant model, and the feasibility and performance are demonstrated.

Kentucky bluegrass (Poa pratensis L.) is an eminent turfgrass species with a complex genome, but it is sensitive to rust (Puccinia striiformis). The molecular mechanisms of Kentucky bluegrass in response to rust still remain unclear. This study aimed to elucidate differentially expressed lncRNAs (DELs) and genes (DEGs) for rust resistance based on the full-length transcriptome. First, we used single-molecule real-time sequencing technology to generate the full-length transcriptome of Kentucky bluegrass. A total of 33,541 unigenes with an average read length of 2,233 bp were obtained, which contained 220 lncRNAs and 1,604 transcription factors. Then, the comparative transcriptome between the mock-inoculated leaves and rust-infected leaves was analyzed using the full-length transcriptome as a reference genome. A total of 105 DELs were identified in response to rust infection. A total of 15,711 DEGs were detected (8,278 upregulated genes, 7,433 downregulated genes) and were enriched in plant hormone signal transduction and plant–pathogen interaction pathways. Additionally, through co-location and expression analysis, it was found that lncRNA56517, lncRNA53468, and lncRNA40596 were highly expressed in infected plants and upregulated the expression of target genes AUX/IAA, RPM1, and RPS2, respectively; meanwhile, lncRNA25980 decreased the expression level of target gene EIN3 after infection. The results suggest that these DEGs and DELs are important candidates for potentially breeding the rust-resistant Kentucky bluegrass.

Supplementary figures showing that the gut microbiome variations over the course of nCRT associated with therapeutic response.

Supplementary figures showing that the gut microbiome in LARC patients differed significantly from that in healthy individuals.

Purpose:The gut microbiome is involved in antitumor immunotherapy and chemotherapy responses; however, evidence-based research on the role of gut microbiome in predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) remains scarce. This prospective, longitudinal study aimed to evaluate the feasibility of the gut microbiome in predicting nCRT responses.Experimental Design:We collected 167 fecal samples from 84 patients with LARC before and after nCRT and 31 specimens from healthy individuals for 16S rRNA sequencing. Patients were divided into responders and nonresponders according to pathologic response to nCRT. After identifying microbial biomarkers related to nCRT responses, we constructed a random forest classifier for nCRT response prediction of a training cohort of baseline samples from 37 patients and validated the classifier in another cohort of 47 patients.Results:We observed significant microbiome alterations represented by a decrease in LARC-related pathogens and an increase in Lactobacillus and Streptococcus during nCRT. Furthermore, a prominent microbiota difference between responders and nonresponders was noticed in the baseline samples. Microbes related with butyrate production, including Roseburia, Dorea, and Anaerostipes, were overrepresented in responders, whereas Coriobacteriaceae and Fusobacterium were overrepresented in nonresponders. Ten biomarkers were selected for the response-prediction classifier, including Dorea, Anaerostipes, and Streptococcus, which yielded an area under the curve value of 93.57% [95% confidence interval (CI), 85.76%–100%] in the training cohort and 73.53% (95% CI, 58.96%–88.11%) in the validation cohort.Conclusions:The gut microbiome offers novel potential biomarkers for predicting nCRT responses, which has important manifestations in the clinical management of these patients.

Supplementary figures showing the performance of the response-prediction classifier based on microbial and clinical variables.

Flow diagram of the study design and details on the establishment of response-prediction classifier.

Details on inclusion and exclusion criteria, and supplementary table showing the frequency of patients with discriminatory taxa in fecal samples.

Supplementary figures showing that baseline gut microbiome correlated with therapeutic response to nCRT in LARC patients.

Background: Gliomas are brain tumors that arise from glial cells, and they are the most common primary intracranial tumors with a poor prognosis. Cellular senescence plays a critical role in cancer, especially in glioma. In this study, we constructed a senescence-related lncRNA (SRlncRNA) signature to assess the prognosis of glioma.Methods: The Cancer Genome Atlas was used to collect SRlncRNA transcriptome profiles and clinical data about glioma. Patients were randomized to training, testing, and whole cohorts. LASSO and Cox regression analyses were employed to construct the SRlncRNA signature, and Kaplan–Meier (K-M) analysis was performed to determine each cohort’s survival. Receiver operating characteristic (ROC) curves were applied to verify the accuracy of this signature. Gene set enrichment analysis was used to visualize functional enrichment (GSEA). The CIBERSORT algorithm, ESTIMATE and TIMER databases were utilized to evaluate the differences in the infiltration of 22 types of immune cells and their association with the signature. RT–qPCR and IHC were used to identify the consistency of the signature in tumor tissue.Results: An SRlncRNA signature consisting of six long non-coding RNAs (lncRNAs) was constructed, and patients were divided into high-risk and low-risk groups by the median of their riskscore. The KM analysis showed that the high-risk group had worse overall survival, and the ROC curve confirmed that the riskscore had more accurate predictive power. A multivariate Cox analysis and its scatter plot with clinical characteristics confirmed the riskscore as an independent risk factor for overall survival. GSEA showed that the GO and KEGG pathways were mainly enriched in the immune response to tumor cells, p53 signaling pathway, mTOR signaling pathway, and Wnt signaling pathway. Further validation also yielded significant differences in the risk signature in terms of immune cell infiltration, which may be closely related to prognostic differences, and qRT–PCR and IHC confirmed the consistency of the expression differences in the major lncRNAs with those in the prediction model.Conclusion Our findings indicated that the SRlncRNA signature might be used as a predictive biomarker and that there is a link between it and immune infiltration. This discovery is consistent with the present categorization system and may open new avenues for research and personalized therapy.

Peripheral T-cell lymphomas (PTCL) - especially angioimmunoblastic (AITL) and follicular TCL - have a dismal prognosis due to lack of efficient therapies, and patients` symptoms are often dominated by an inflammatory phenotype including fever, night sweats, weight loss and skin rash. In this study, we investigated the role of inflammatory granulocytes and activated cytokine signaling on PTCL-TFH (T-follicular helper type) disease progression and symptoms. We show, that ITK-SYK driven murine PTCLs and primary human PTCL-TFH xenografts both induce inflammation in mice including murine neutrophil expansion and massive cytokine release. Granulocyte/lymphoma interactions were mediated by positive autoregulatory cytokine loops involving INF-γ (CD4+malignant T-cells) and IL-6 (activated granulocytes), ultimately inducing broad JAK kinase activation (Jak1/2/3, Tyk2) in both cell types. Depletion of inflammatory granulocytes via antibodies (Ly6G), genetic granulocyte depletion (LyzM-Cre/MCL1flox/flox) or the deletion of IL-6 within microenvironmental cells blocked inflammatory symptoms, reduced lymphoma infiltration and enhanced mouse survival. Furthermore, unselective JAK kinase inhibitors (ruxolitinib) inhibited both, TCL progression and granulocyte activation in various PTCL mouse models. Our results support the important role of granulocyte-driven inflammation, cytokine-induced granulocyte/CD4+ TCL interactions and the requirement of an intact JAK/STAT signaling pathway for PTCL-TFH development, and support broad JAK kinase inhibition as an effective treatment strategy in early disease stages.

As an emerging form of medical organization, Chinese mobile healthcare (mHealth) platforms are inherently linked to the continuous use of users, which depends on the quality of the health information provided. However, improving the health information quality of mHealth platforms is still a problem that needs to be studied and solved in order to make the platforms sustainable. Based on the reputation mechanism, this study creates a behavioral evolutionary game model for health information providers (physicians) and managers (mHealth platforms), explores the evolution process and evolutionarily stable strategy of the behaviors in various situations, and uses numerical simulation technology to analyze mHealth platforms' constraints and the influencing factors of health information quality. This study presents three key findings. First, considering reputation, health information managers and mHealth platform providers should not unilaterally optimize health information. Instead, mHealth platforms should have active quality control, and physician groups should provide high-quality health information, which is the ideal evolution of the model. Second, the rewards that physicians receive from patients and mHealth platforms for providing quality health information, the reputation benefits, the penalties that physicians suffer for providing low-quality health information, and the increased probability and cost of rent-seeking behavior that physicians may choose can effectively promote the choice of physicians to provide high-quality health information. Third, the reputation gain of mHealth platforms, the probability of mHealth platforms being exposed, and increased losses suffered from exposure can effectively promote the choice of mHealth platforms to control the quality of health information. This study can provide a theoretical basis for mHealth platforms' health information quality control, which is conducive to the healthy and sustainable development of mHealth platforms and the improvement of user satisfaction.

Based on the panel data of China’s A-share non-financial listed enterprises from 2011 to 2020, we empirically explore whether EGS performance can significantly promote corporate value and how to promote it, from the stakeholders’ perspective. We find that: 1) ESG performance significantly improves corporate value. 2) Both media attention and analyst coverage play an intermediary role in the impact of ESG performance on corporate value. 3) Further analysis of the single dimension of ESG illustrates that Environmental (E) and Social (S) have a positive impact on corporate value, but the effect size of Social (S) is smaller, and there is no evidence for a significant relationship between Governance (G) and corporate value. 4) The heterogeneity analysis shows that ESG performance of non-heavily polluting enterprises has a significant positive effect on corporate value, but not on heavily polluting enterprises. Meanwhile, ESG performance of enterprises with a low percentage of institutional investor ownership has a significant positive effect on corporate value, but not with a high percentage. Overall, our study shows that high-quality ESG performance triggers the attention of media and analysts, which in turn promotes corporate value by raising stakeholder pressure. We also analyze the possible causes of heterogeneous results from the perspective of stakeholders, and put forward reasonable suggestions to promote ESG performance and corporate value, as well as protect the interests of stakeholders.

Sperm acquire the ability to fertilize ova through a complex process of epididymal maturation. To identify the functions of genes expressed in the proximal epididymis, mouse models specific to this region are needed. A Lcn8-Cre knock-in mouse line was generated using CRISPR/Cas9 technology. A 37 bp coding sequence of Lcn8 from the ATG start codon was replaced by an NLS-Cre-polyA cassette, resulting in Cre expression and the absence of Lcn8. Epididymal initial segment-specific Cre expression was identified using RT-PCR and western blotting, and the spatial–temporal Cre activity was further confirmed by using the Rosa26tdTomato reporter mice. Immunofluorescence staining showed that active Cre recombinase was present in the principal cells. Histological analyses of sperm and epididymides, and the four-month mating tests, were used to confirm that Cre expression did not affect normal development and male fecundity. The novel Lcn8-Cre mice can be used to establish epididymal initial segment-specific conditional knock-out mouse models.

The consumption of fresh fruits and vegetables is restricted by the susceptibility of fresh produce to deterioration caused by postharvest physiological and metabolic activities. Developing efficient preservation strategies is thus among the most important scientific issues to be urgently addressed in the field of food science. The incorporation of active agents into a polymer matrix to prepare biodegradable active packaging is being increasingly explored to mitigate the postharvest spoilage of fruits and vegetables during storage. This paper reviews the composition of biodegradable polymers and the methods used to prepare biodegradable active packaging. In addition, the interactions between bioactive ingredients and biodegradable polymers that can lead to plasticizing or cross-linking effects are summarized. Furthermore, the applications of biodegradable active (i.e., antibacterial, antioxidant, ethylene removing, barrier, and modified atmosphere) packaging in the preservation of fruits and vegetables are illustrated. These films may increase sensory acceptability, improve quality, and prolong the shelf life of postharvest products. Finally, the challenges and trends of biodegradable active packaging in the preservation of fruits and vegetables are discussed. This review aims to provide new ideas and insights for developing novel biodegradable active packaging materials and their practical application in the preservation of postharvest fruits and vegetables.

The study aimed to develop a novel noninvasive model to detect advanced fibrosis based on routinely available clinical and laboratory tests.A total of 309 patients who underwent liver biopsy were randomly divided into the estimation group (n = 201) and validation group (n = 108). The model was developed using multiple regression analysis in the estimation group and further verified in the validation group. Diagnostic accuracy was evaluated using the receiver operating characteristic (ROC) curve.The model was named NAFLD Fibrosis Index (NFI): -10.844 + 0.046 × age - 0.01 × platelet count + 0.19 × 2h postprandial plasma glucose (PG) + 0.294 × conjugated bilirubin - 0.015 × ALT + 0.039 × AST + 0.109 × total iron binding capacity -0.033 × parathyroid hormone (PTH). The area under the ROC curve (AUC) of NFI was 0.86 (95% CI: 0.79-0.93, p 0.001) in the estimation group and 0.80 (95% CI: 0.69-0.91, p 0.001) in the validation group, higher than NFS, FIB4, APRI, and BARD, and similar to FibroScan (NFI AUC = 0.77, 95% CI: 0.66-0.89, p = 0.001 vs. FibroScan AUC = 0.76, 95% CI: 0.62-0.90, p = 0.002). By applying the low cut-off value (-2.756), advanced fibrosis could be excluded among 49.3% and 48% of patients in the estimation group (sensitivity: 93.1%, NPV: 97.9%, specificity: 55.2%, and PPV: 26.0%) and validation group (sensitivity: 81.3%, NPV: 94.2%, specificity: 53.3%, and PPV: 23.2%), respectively, allowing them to avoid liver biopsy.The study has established a novel model for advanced fibrosis, the diagnostic accuracy of which is superior to the current clinical scoring systems and is similar to FibroScan.

Lipocalin family members, LCN8 and LCN9, are specifically expressed in the initial segment of mouse caput epididymis. However, the biological functions of the molecules in vivo are yet to be clarified. In this study, CRISPR/Cas9 technology was used to generate Lcn8 and Lcn9 knockout mice, respectively. Lcn8−/− and Lcn9−/− male mice showed normal spermatogenesis and fertility. In the cauda epididymis of Lcn8−/− male mice, morphologically abnormal sperm was increased significantly, the proportion of progressive motility sperm was decreased, the proportion of immobilized sperm was elevated, and the sperm spontaneous acrosome reaction (AR) frequency was increased. Conversely, the knockout of Lcn9 did not have any effect on the ratio of morphologically abnormal sperm, sperm motility, and sperm spontaneous AR frequencies. These results demonstrated the role of LCN8 in maintaining the sperm quality in the epididymis, and suggested that the deficiency of LCN8 leads to epididymal sperm maturation defects.

Artemisia selengensis Turcz. is a valuable edible and medicinal vegetable crop widely cultivated in Northeast China. Powdery mildew (PM) disease occurs during field and greenhouse cultivation, resulting in production losses and quality deterioration. The pathogen in A. selengensis was Golovinomyces artemisiae identified using optical microscopic and scanning electron microscopic observations, morphological identification, and molecular biological analyses. Parameters of chlorophyll fluorescence (ChlF) and antioxidant system responses as well as callose and lignin contents in A. selengensis were analyzed with inoculating G. artemisiae. Obvious of PM-infected leaves were confirmed with significantly lower values in electron transport rate (ETR), non-photochemical quenching (NPQ), photochemical quenching (qP), and actual photochemical efficiency [Y(II)], but higher values in non-adjusting energy dissipation yield [Y(NO)], supposed that maximal photosystem II quantum yield (Fv/Fm) value and images could be used to monitor PM degree on infectedA. selengensis. In addition, malondialdehyde (MDA), superoxide anion (O2–), callose, lignin contents, and peroxidase (POD) activity increased, while superoxide dismutase (SOD) activity, catalase (CAT) activity, and ascorbic acid (AsA) content decreased significantly in infected leaves compared to mock-inoculated leaves, indicated that lignin and protective enzymes are the key indicators for detecting PM resistant in A. selengensis. These results suggest that PM caused by G. artemisiae disrupted the photosynthetic capacity and induced imbalance of antioxidant system inA. selengensis. The findings were of great significance for designing a feasible approach to effectively prevent and control the PM disease in A. selengensis as well as in other vegetable crops.

Phase I clinical trials play an important role in the follow-up clinical trials and even the drug registration and marketing. However, the screening success ratio in phase I clinical trials is low, and the screening process of the trials consumes a significant amount of human and material resources, but the results are unsatisfactory. At present, there is no large sample data analysis for screening failure in phase I clinical trials. It is therefore urgent to find the reasons for screening failure in phase I clinical trials.A total of 1,058 healthy volunteers who failed the screening in 11 phase I clinical trials were retrospectively collected from October 2018 to June 2021 in Cangzhou Central Hospital. Data on all participants who failed screening for the study were analyzed (descriptive analysis) and reasons for their non-randomization were classified, as well as the differences of main screening failures between four years.A total of 1,466 healthy volunteers were enrolled in the 11 trials, and among them 1,058 subjects failed the screening. The total screening success ratio of our study was only 27.8%, the highest being 38.5% and the lowest being 18.2%. The top 3 reasons for non-randomization were abnormalities in blood biochemistry tests (23.3%), vital sign examination (19.3%), and electrocardiogram (ECG) (16.6%). Abnormal blood biochemistry was the main reason between 2019 and 2021, except for 2018 in which it was the second reason.Screening failure is a burdensome issue which various clinical trial sites must contend with. Investigators can still take some effective measures by strengthening the in-depth understanding of informed consent, paying attention to the quality of test samples, a correcting definition of no clinical significance (NCS). Also, low-cost and non-invasive examinations can be arranged first to better protect the volunteers and reduce the screening costs of clinical trials. To our delight, we find people's attention to the annual physical examination may help to screen healthy volunteers. Overall, this study shows that it is crucial and professional to develop a screening plan to minimize the resultant impact on timelines and budgets of phase I clinical trials enrolling healthy volunteers.

In order to further understand the effect of solid impurities on pipeline wall during erosion, the particle impact process without fluid was extracted for specific study. The effect of multi-impact particles on the wall of pipeline was studied experimentally and simulated. In this experiment, an improved ejection apparatus was implemented to carry out multi-impacts non-overlapping impingement by rhombic particles made of high speed steel(W18Cr4V) on the AA6061 aluminum alloy plate through changing particle angle, incident angle, orientation angle and impact velocity. As a result, each particle's penetration depth was investigated and particles' rebound trajectory can be described through this experiment as well as surface morphology of the target material after impingement. The ductile damage criterion, shear damage criterion and MSFLD damage criterion were jointly implemented in ABAQUS/CAE software to simulate the whole process of collision which proved to be effective by getting consistent result compared with experimental data. It is found that under the condition of continuous non-overlapping impact, the target material produces a small work hardening effect in the impact area by converting kinetic energy of moving particles into internal energy of plate so as to reduce the penetration depth of each impact particle.

Soil carbon (C) reservoirs held in forests play a significant role in the global C cycle. However, harvesting natural forests tend to lead to soil C loss, which can be countered by the establishment of plantations after clear cutting. Therefore, there is a need to determine how forest management can affect soil C sequestration. The management of stand density could provide an effective tool to control soil C sequestration, yet how stand density influences soil C remains an open question. To address this question, we investigated soil C storage in 8-year pure hybrid larch (Larix spp.) plantations with three densities (2000 trees ha−1, 3300 trees ha−1 and 4400 trees ha−1), established following the harvesting of secondary mixed natural forest. We found that soil C storage increased with higher tree density, which mainly correlated with increases of dissolved organic C as well as litter and root C input. In addition, soil respiration decreased with higher tree density during the most productive periods of warm and moist conditions. The reduced SOM decomposition suggested by lowered respiration was also corroborated with reduced levels of plant litter decomposition. The stimulated inputs and reduced exports of C from the forest floor resulted in a 40% higher soil C stock in high- compared to low-density forests within 8 years after plantation, providing effective advice for forest management to promote soil C sequestration in ecosystems.

Osteocalcin regulates energy metabolism in an active undercarboxylated/uncarboxylated form. However, its role on the development of non-alcoholic fatty liver disease (NAFLD) is still controversial. In the current study, we investigated the causal relationship of circulating osteocalcin with NAFLD in two human cohorts and studied the effect of uncarboxylated osteocalcin on liver lipid metabolism through animal models. We analyzed the correlations of serum total/uncarboxylated osteocalcin with liver steatosis/fibrosis in a liver biopsy cohort of 196 participants, and the causal relationship between serum osteocalcin and the incidence/remission of NAFLD in a prospective community cohort of 2055 subjects from Shanghai Changfeng Study. Serum total osteocalcin was positively correlated with uncarboxylated osteocalcin (r = 0.528, p < .001). Total and uncarboxylated osteocalcin quartiles were inversely associated with liver steatosis, inflammation, ballooning, and fibrosis grades in both male and female participants (all p for trend

Word embedding and deep learning methods have shown to be very effective in automated text information mining. In this work, a chemical accident case analysis method is proposed and tested based on the methods. Firstly, word vectors for the text corpus of chemical accident cases were produced based on word2vec. And then Bidirectional LSTM model with attention mechanism for text classification was constructed. Finally, case studies on the correlation analysis of the common trends of chemical accidents and automated text classification of chemical accident cases documents were performed respectively. The results revealed that the proposed method can identify common principles of chemical accidents and classify chemical accident cases. These findings highlight the feasibility of chemical accident case information mining based on word embedding through case studies. Compared with rule-based information mining, our method improves the efficiency, automation, and intelligence of information mining from chemical accident cases documents.

Type 2 diabetes (T2DM) is closely related to nonalcoholic fatty liver disease (NAFLD) and is an important risk factor for the progression of liver fibrosis, but the role of 2-h postprandial blood glucose (PPG) as a biomarker in this process remains unclear. This study was designed to investigate the relationship between PPG and liver fibrosis in Chinese NAFLD populations with or without T2DM.This study included three independent NAFLD populations: 1) 618 inpatients with T2DM or pre-diabetes, 2) 255 patients with T2DM or pre-diabetes who underwent liver biopsy, and 3) a prospective community-based cohort without diabetes who completed a median of 4.22 years follow-up. The degree of liver fibrosis was assessed by liver fibrosis stage in subjects with a liver biopsy, and by NAFLD fibrosis score (NFS) in subjects without liver biopsy.In the first population, PPG {OR 0.02, [95% CI (0.01-0.03)], P0.001} was positively correlated with NFS. In the second population, an increasing PPG was associated with increase in the proportion of advanced liver fibrosis (P = 0.012). Multivariate line regression revealed that PPG {OR 0.03 [95% CI (0.00-0.06)], P = 0.049}was positively associated with liver fibrosis stages. In the third population, PPG {OR 0.103, [95% CI (0.011-0.194) P = 0.028} at baseline was positively associated with NFS at follow-up. Furthermore, changes in PPG were significantly associated with NFS change after follow-up. We did not find a similar association between fasting glucose or HbA1c and liver fibrosis.PPG was independently associated with the severity of liver fibrosis in the Chinese NAFLD population.

Excessive nitrogen (N) application may induce powdery mildew (PM) in perennial grasses, but the resistance mechanisms to PM remain unclear. This study evaluated the physiological and molecular mechanisms of PM resistance affected by N supplies in Kentucky bluegrass (Poa pratensis L.). Cultivar ‘Bluemoon’ (N tolerant) and ‘Balin’ (N sensitive) were treated with low N (0.5 mM), normal N (15 mM), and high N (30 mM) for 21 d in a greenhouse. With increasing N levels, the disease growth was more severe in ‘Balin’ than in ‘Bluemoon’. RNA-seq and weighted gene coexpression network analysis revealed that the PpGS1.1 gene encoding glutamine synthetase was a potential hub gene for PM resistance after comparisons across cultivars and N treatments. The N metabolism pathway was connected with the plant–pathogen interaction pathway via PpGS1.1. The expression of PpGS1.1 in rice protoplasts indicated that the protein was located in the nucleus and cytoplasm. Overexpression of PpGS1.1 in wild-type Kentucky bluegrass increased carbon and N contents, and the transgenic plants became more susceptible to PM with a lower wax density. The most differentially expressed genes (DEGs) for N metabolism were upregulated and DEGs for fatty acid metabolism pathway were downregulated in the overexpression lines. The results elucidated mechanisms of PM resistance in relation to N metabolism in Kentucky bluegrass.

Background With an increasing demand for edible protein, research on new extraction methods is attracting more attention. The effects of such methods on functional properties are important. The present study aimed to evaluate the effect of ultrasound-assisted extraction on the extraction efficiency, structure, and the emulsifying properties of peanut protein isolate (PPI). Results Ultrasound-assisted extraction significantly improved extraction efficiency and shortened the processing time. The nanostructure, molecular weight distribution, and particle size of PPI were altered by ultrasound-assisted extraction. The emulsifying properties of the PPI from ultrasound-assisted extraction were significantly improved compared with alkaline extraction. Peanut protein isolate had lower molecular weight fractions, higher levels of hydrophobic amino acids, and the highest fluorescence intensity with ultrasound intensity, temperature, and time of 3.17 W cm-3 , 35 °C, and 30 min, respectively. These contributed to the higher emulsifying activity index and emulsifying stability index of the PPI emulsions. The uniform distribution of droplets and smaller particle size of the PPI emulsions was also observed. Conclusion The results suggested that ultrasound can be used to induce the conformational changes to modify the interfacial association between protein-oil phases, thereby improving the emulsifying properties of peanut protein. © 2020 Society of Chemical Industry.