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Abstract Background & Aims There is no consensus on whether it is worthwhile for young people to undergo lipid screening. An estimate of the national prevalence of lipid screening in this population can serve as a basic parameter in analyses of the utilization and cost-effectiveness of health care services. Previous studies were mostly based on electronic health records or insurance claims data or were restricted to adolescents at younger ages. This study aimed to investigate the prevalence of lipid screening and the factors associated with it in young people aged 16– to 21 years in the United States based on a nationally representative sample. Methods A cross-sectional study of 16- to 21-year-old participants from the National Health and Nutrition Examination Survey (NHANES), 2013–March 2020 (four cycles), was conducted. The prevalence of lipid screening uptake was calculated for each cycle as well as for all four cycles combined, and the associations of lipid screening uptake with the covariates were analysed by logistic regression. An appropriate sample weight was incorporated into the analysis as recommended. Results A total of 3,600 participants were included in the analysis, and 32.02% of them had ever received lipid screening at the time of the survey, with no statistically significant secular changes observed over the four cycles. Among the participants, 28.83% received lipid screening within the past 5 years. In multivariable regression analysis adjusted for all covariates, non-Hispanic black ethnicity (adjusted odds ratio [AOR]: 1.43), having health insurance (AOR: 1.54), obesity (AOR: 1.65) and sufficient physical activity (AOR: 1.36) were significantly associated with a greater chance of ever receiving lipid screening. Conclusions Nearly one-third of young people aged 16– to 21 years in the United States have received lipid screening. Ethnicity, health insurance, weight problems, and physical activity level were associated with the likelihood of lipid screening uptake. These findings could help people understand the current situation of lipid screening in young people in the United States and may serve as fundamental parameters in the assessment of the utilization and cost-effectiveness of related health care services.

The nonprofit organizations rely on volunteers as key human resources. Recent literature emphasizes effective volunteer management to enhance the utilization of volunteers. At present, empirical knowledge on the subject exists in fragments causing difficulties in analyzing its growth. There is a need to evaluate its vast literature using a statistically rigorous method. The study aims to identify the internal structures and hidden inferences on volunteer management in nonprofit organizations using bibliometric data. The study collected 1,605 related journal articles indexed by Scopus from 1956 to 2022. The VOSviewer software was utilized to analyze the data. The results revealed diachronic growth in the area and identified its leading contributors. International collaboration and high-frequency keywords are also illustrated. The results are discussed in terms of article representations, area maturity, impacts of external environment, and emerging opportunities. The study provides insights into the state of knowledge surrounding volunteer management in nonprofit organizations.

With the aggravation of energy shortage and ecological deterioration, it becomes more and more essential for China to improve energy efficiency and realize the targets of energy conservation and emission reduction. This paper focuses on the measurement of the total factor energy efficiency (TFEE), the potentials of energy conservation and emission reduction, and the influencing factors of TFEE in China. Firstly, the model of Gray Weight Slack-Based Measure (GW-SBM) is established, with the weights of the indicators obtained via the grey relational analysis method, to calculate the TFEE of thirty provinces and six regions in China from 2009 to 2019. Then, the potentials of energy conservation and emission reduction are analyzed on the basis of TFEE measurements. Finally, the influencing factors of TFEE are identified via the truncated bootstrap model. The findings show that the TFEE values of 30 provinces fluctuate in the range of 0.20 and 1.0, varying significantly among provinces. Energy conservation potential reached 8.7490 million tons of standard coal (potential 39.06%), which means that more than one-third of energy consumption is inefficient. The top two factors in the TFEE measurement identified by the truncated bootstrap model, are energy consumption structure and environmental protection expenditure. Based on the research conclusions, this paper puts forward some countermeasures and suggestions.

Abstract Mechanical energy harvesting using triboelectric nanogenerators is a highly desirable and sustainable method for the reliable power supply of widely distributed electronics in the new era; however, its practical viability is seriously challenged by the limited performance because of the inevitable side-discharge and low Coulombic-efficiency issues arising from electrostatic breakdown. Here, we report an important progress on these fundamental problems that the spontaneously established reverse electric field between the electrode and triboelectric layer can restrict the side-discharge problem in triboelectric nanogenerators. The demonstration employed by direct-current triboelectric nanogenerators leads to a high Coulombic efficiency (increased from 28.2% to 94.8%) and substantial enhancement of output power. More importantly, we demonstrate this strategy is universal for other mode triboelectric nanogenerators, and a record-high average power density of 6.15 W m−2 Hz−1 is realized. Furthermore, Coulombic efficiency is verified as a new figure-of-merit to quantitatively evaluate the practical performance of triboelectric nanogenerators.

The attributes of the business model have become an essential factor affecting enterprise performance and competitive advantage. However, there still needs to be systematic identification of key attributes and empirical tests between key attributes and firm performance. To fill the research gap, we conducted a questionnaire and open-ended coding to identify five key attributes of successful business models, and then a measurement scale was developed. The empirical analysis based on 445 samples shows that the measurement scale of multi-dimensional business model attributes composed of novelty, sustainability, efficiency, expandability, and value co-creation has good reliability and validity. Our findings contribute to identifying key attributes of successful business models from different industries and examining the impact of key attributes on firm performance. Furthermore, the conclusion of this study will be an excellent enlightenment to understand better the key attributes of business models and the firm performance advantages brought by them for both research and practice.

Abstract Background Glioblastoma, the most common primary malignant tumor of the brain, is associated with poor prognosis. Glioblastoma cells exhibit high proliferative and invasive properties, and glioblastoma stem cells (GSCs) have been shown to play a crucial role in the malignant behavior of glioblastoma cells. This study aims to investigate the molecular mechanisms involved in GSCs maintenance and malignant progression. Methods Bioinformatics analysis was performed based on data from public databases to explore the expression profile of Mitotic arrest deficient 2 like 2 (MAD2L2) and its potential function in glioma. The impact of MAD2L2 on glioblastoma cell behaviors was assessed through cell viability assays (CCK8), colony formation assays, 5-Ethynyl-2ʹ-deoxyuridine (EDU) incorporation assays, scratch assays, and transwell migration/invasion assays. The findings from in vitro experiments were further validated in vivo using xenograft tumor model. GSCs were isolated from the U87 and LN229 cell lines through flow cytometry and the stemness characteristics were verified by immunofluorescence staining. The sphere-forming ability of GSCs was examined using the stem cell sphere formation assay. Bioinformatics methods were conducted to identified the potential downstream target genes of MAD2L2, followed by in vitro experimental validation. Furthermore, potential upstream transcription factors that regulate MAD2L2 expression were confirmed through chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays. Results The MAD2L2 exhibited high expression in glioblastoma samples and showed significant correlation with patient prognosis. In vitro and in vivo experiments confirmed that silencing of MAD2L2 led to decreased proliferation, invasion, and migration capabilities of glioblastoma cells, while decreasing stemness characteristics of glioblastoma stem cells. Conversely, overexpression of MAD2L2 enhanced these malignant behaviors. Further investigation revealed that MYC proto-oncogene (c-MYC) mediated the functional role of MAD2L2 in glioblastoma, which was further validated through a rescue experiment. Moreover, using dual-luciferase reporter gene assays and ChIP assays determined that the upstream transcription factor E2F-1 regulated the expression of MAD2L2. Conclusion Our study elucidated the role of MAD2L2 in maintaining glioblastoma stemness and promoting malignant behaviors through the regulation of c-MYC, suggesting its potential as a therapeutic target.

Abstract Background Emerging evidence has shown that extracellular vesicles (EVs) derived from gut bacteria play a crucial role in microbiota-host interactions. Here, we aimed to evaluate the attenuating effect of EVs derived from a reduced commensal bacterium, F. prausnitzii (Fp-EVs), in inflammatory bowel disease (IBD) on dextran sulfate sodium (DSS)-induced colitis in mice. Results Fp-EVs isolated by ultracentrifugation and typically exhibited a double concave disc shape with an average diameter of 172 nm. Fp-EVs treatment reduced DSS-induced weight loss, disease activity index (DAI) score, colon length shortening, histological damage, neutrophil infiltration and increased intestinal epithelial apoptotic cells in DSS-induced colitis mice. Fp-EVs upregulated the protein expression of zona occludens (ZO)-1 and Occludin and increased the ratio of Tregs in the colon tissue of colitis mice. Furthermore, Fp-EVs downregulated the expression of the proinflammatory cytokines interleukin-1β (IL-1β), IL-2, IL-6, IL-12a, IL-17a, Interferon-γ (IFN-γ), tumor necrosis factor - α (TNF-α), granulocyte-macrophage colony stimulating factor (GM-CSF) and upregulated the anti-inflammatory cytokines IL-4, IL-10, and transforming growth factor β (TGF-β) in DSS-treated mice. Moreover, Fp-EV treatment markedly reduced the phosphorylation of these proteins Nuclear factor-κB (NF-κB) and Mitogen activated protein kinase (MAPK), and regulated the expression of nuclear factor erythroid 2-related factor (Nrf2) and heme oxygenase-1 (HO-1). Conclusion Our findings revealed that Fp-EVs attenuated DSS-induced colitis by modulating the intestinal mucosal barrier function and immunological profile. Our findings reveal that Fp-EVs attenuate DSS-induced colitis by modulating intestinal mucosal barrier function and the immunological profile.

Many people with diagnosed hypertension, high cholesterol, and/or diabetes are not receiving drug treatment, partly because they perceive their cardiovascular disease (CVD) risk as low. This study aimed to quantify the risk for future CVD events, either first or recurrent, in people with diagnosed hypertension, high cholesterol, and/or diabetes but not on medications for any of these conditions. Participants aged 40–79 years who had been diagnosed with hypertension, high cholesterol, and/or diabetes but were not on medications were identified from National Health and Nutrition Examination Surveys cycles 1999 to 2018. Among them, those with known CVD and those without known CVD but with complete data for estimating their 10-year CVD risk were included in this study. The participants were classified as (1) “high-risk” if they had known CVD or a 10-year predicted CVD risk ≥ 7.5% or (2) “low-risk” if they had a 10-year predicted CVD risk < 7.5%. Of the 5187 participants included, 2201 had known major CVD (n = 490, 9.45%) or a 10-year predicted CVD risk ≥ 7.5% (n = 1711, 32.99%), corresponding to a weighted proportion of 34.83% (95% CI: 33.15 to 36.51%) in the US general population. The proportions of high-risk participants were much higher in the elderly (65.50% for 60–69 years and 97.86% for 70–79 years), males (45.13%), and non-Hispanic Blacks (42.15%) than in others (all p < 0.001). These patterns were consistent across survey cycles during 1999–2018. Additional analyses that classified the participants into groups above or below the treatment threshold (rather than high- or low-risk groups) according to current guidelines yielded similar results. A comparison of the 2201 untreated high-risk participants with other participants who had been diagnosed with hypertension, high cholesterol, and/or diabetes and were on medications for these conditions showed that “lower BMI”, “smaller waist circumference”, and a “non-diabetic” status, among others, were associated with a higher likelihood of “not taking medications”. In conclusion, approximately one-third of the US adults aged 40 to 79 years with diagnosed hypertension, high cholesterol, and/or diabetes but not on medications had known CVD or a 10-year predicted CVD risk ≥ 7.5%, and this proportion was little changed over the past two decades. Interventions targeted at the subgroups with particular characteristics identified in this study may help improve the management of CVD and its risk factors.

Abstract Background The Procalcitonin (PCT) and C-reactive protein (CRP)/albumin ratio have recently been used to predict early prognosis for intensive care unit (ICU) patients and patients undergoing major surgery. But there were few clinical studies in patients after lung transplantation (LTX). Aim/Purpose The purpose of this study was to identify the association between PCT combined with CRP/albumin ratio and 30-day mortality and predict the accuracy of PCT combined with CRP/albumin ratio for 30-day mortality in patients after LTX. Method From January 1, 2016 to December 1, 2020, the clinical data of 77 patients undergoing LTX who died within 30 days were retrospectively collected, we randomly collected 87 patients survived more than 30 days after LTX. ROC curve was used to evaluate the prognostic value of PCT combined with CRP/albumin in predicting mortality at 30 days after ICU admission, Cox proportional hazard model analysis was used to identify risk factors, subgroup analyses was conducted. Results Postoperative PCT, CRP, albumin, CRP/albumin ratio, atrial fibrillation, primary graft dysfunction (PGD) grade, the hours of postoperative mechanical ventilation (MV) and length of ICU stay between survivor and non-survivor had a significant difference. On Cox proportional hazard regression analysis, both PCT [HR 1.02 (1.00–1.05), P = 0.037] and CRP/albumin ratio [HR 1.438 (1.26–1.65), P

Abstract Direct-current triboelectric nanogenerators arising from electrostatic breakdown can eliminate the bottleneck problem of air breakdown in conventional triboelectric nanogenerators, offering critical benefits of constant-current output, resistance to electromagnetic interference, and high output power density. Previous understanding is that its output characteristics are described by a capacitor-breakdown model or dictated by one or two discharge domains in direct-current triboelectric nanogenerators. Here, we demonstrate that the former holds only for ideal conditions and the latter cannot fully explain the dynamic process and output performance. We systematically image, define, and regulate three discharge domains in direct-current triboelectric nanogenerators, then a “cask model” is developed to bridge the cascaded-capacitor-breakdown dynamic model in ideal conditions and real outputs. Under its guidance, the output power is increased by an order of magnitude within a wide range of resistive loads. These unexplored discharge domains and optimization methods revolutionize the output performance and potential applications of direct-current triboelectric nanogenerators.

Malicious social bots pose a serious threat to social network security by spreading false information and guiding bad opinions in social networks. The singularity and scarcity of single organization data and the high cost of labeling social bots have given rise to the construction of federated models that combine federated learning with social bot detection. In this paper, we first combine the federated learning framework with the Relational Graph Convolutional Neural Network (RGCN) model to achieve federated social bot detection. A class-level cross entropy loss function is applied in the local model training to mitigate the effects of the class imbalance problem in local data. To address the data heterogeneity issue from multiple participants, we optimize the classical federated learning algorithm by applying knowledge distillation methods. Specifically, we adjust the client-side and server-side models separately: training a global generator to generate pseudo-samples based on the local data distribution knowledge to correct the optimization direction of client-side classification models, and integrating client-side classification models’ knowledge on the server side to guide the training of the global classification model. We conduct extensive experiments on widely used datasets, and the results demonstrate the effectiveness of our approach in social bot detection in heterogeneous data scenarios. Compared to baseline methods, our approach achieves a nearly 3–10% improvement in detection accuracy when the data heterogeneity is larger. Additionally, our method achieves the specified accuracy with minimal communication rounds.

Abstract Background A reasonable supply of nitrogen (N) fertilizer is essential for obtaining high-quality, high-level, and stable potato yields, and an improvement in the N utilization efficiency can effectively reduce N fertilizer use. It is important to use accurate, straightforward, and efficient transgenic breeding techniques for the identification of genes that can improve nitrogen use efficiency, thus enabling us to achieve the ultimate goal of breeding N-efficient potato varieties. In recent years, some of the mechanisms of miRNAs have been elucidated via the analysis of the correlation between the expression levels of potato miRNA target genes and regulated genes under conditions of stress, but the role of miRNAs in the inhibition/expression of key genes regulating N metabolism under N stress is still unclear. Our study aimed to identify the role played by specific enzymes and miRNAs in the responses of plants to N stress. Results The roots and leaves of the N-efficient potato variety, Yanshu4 ("Y"), and N-inefficient potato variety, Atlantic ("D"), were collected at the seedling and budding stages after they were exposed to different N fertilizer treatments. The miRNAs expressed differentially under the two types of N stress and their corresponding target genes were first predicted using miRNA and degradome analysis. Then, quantitative polymerase chain reaction (qRT-PCR) was performed to verify the expression of differential miRNAs that were closely related to N metabolism. Finally, the shearing relationship between stu-miR396-5p and its target gene StNiR was determined by analyzing luciferase activity levels. The results showed that NiR activity increased significantly with an increase in the applied N levels from the seedling stage to the budding stage, and NiR responded significantly to different N treatments. miRNA sequencing enabled us to predict 48 families with conserved miRNAs that were mainly involved in N metabolism, carbon metabolism, and amino acid biosynthesis. The differences in the expression of the following miRNAs were identified via screening (high expression levels and P

This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4) research, state-of-the-art large language models (LLM) from the GPT series, and their prospective applications across diverse domains. Indeed, key innovations such as large-scale pre-training that captures knowledge across the entire world wide web, instruction fine-tuning and Reinforcement Learning from Human Feedback (RLHF) have played significant roles in enhancing LLMs' adaptability and performance. We performed an in-depth analysis of 194 relevant papers on arXiv, encompassing trend analysis, word cloud representation, and distribution analysis across various application domains. The findings reveal a significant and increasing interest in ChatGPT-related research, predominantly centered on direct natural language processing applications, while also demonstrating considerable potential in areas ranging from education and history to mathematics, medicine, and physics. This study endeavors to furnish insights into ChatGPT's capabilities, potential implications, ethical concerns, and offer direction for future advancements in this field.

ABSTRACT: The low reproductive efficiency (RE) of geese limits their production in the poultry industry. To select ganders with high breeding potential, the effect of 3 sperm mobility ranks (SMRs; high-, medium-, and low-SMR) on the RE of naturally mating geese was determined. To exclude the confounding effect of social rank (SR) on RE in naturally mating flocks, a 2-factor nested experimental design was used to differentiate the effects of SMR and SR on RE. Twenty-seven ganders and 135 geese (Zi geese, Anser cygnoides L.) at approximately 1 yr of age were divided into 3 flocks, each of which included the 3 SMR groups. Each SMR group included 3 ganders and 15 female geese. Relative genetic contribution (RGC) is defined as the number of offspring sired by 1 male as a percentage of the entire goslings in each flock, and it was used to compare the differences in RE among ganders. The frequency of agonistic behavioral interactions (ABIs) among the ganders was video recorded in each SMR group, and the SR of each gander was determined. In total, 1,026 eggs were incubated, and 609 goslings hatched. Parent-offspring relationships among 771 individuals from the 2 generations were identified using 20 microsatellite markers, and the RGC was calculated. Results showed that the SMR and SR had significant effects on RGC in naturally mating geese (P = 0.001 and P = 0.000, respectively). Significant differences in RGC were observed among the high- and medium- and low-SMR groups, with average RGCs of 14.3, 10.6, and 8.4%, respectively. The high-SMR group had the highest RGCs in each flock, and the ganders with high SR had the highest RGCs among the 3 SMRs. The study showed that in a naturally mating geese population, selecting for the sperm mobility traits of a gander can effectively improve the RE.

The riparian zone (RZ) is an important region connecting surface water and groundwater, and it has widely been acknowledged for its pollutant buffering capacity. However, the decontaminating effect of RZ on trace organic compounds such as antibiotics has received little attention. This study explored the distribution of 21 antibiotics and 4 sulfonamide metabolites in river water and groundwater in the lower reaches of the Hanjiang River. The diffusion and exchange of contaminants between the river and riverbanks under the influence of water conservancy projects (Xinglong Dam and the Yangtze-Hanjiang Water Diversion Project) were investigated. Macrolide antibiotics were prevalent in river water (62.5–100%) and groundwater samples (42.9–80.4%). Ofloxacin and chlortetracycline were detected with the highest concentrations in river water (12.2 ng L−1) and groundwater (9.3 ng L−1) respectively. Higher levels of antibiotics were observed in spring and winter than in other seasons. The river-groundwater interaction has a certain interception effect on antibiotics, especially near riverbanks. Redox sensitive element Fe2+ showed significantly positive correlations with some tetracycline and macrolide antibiotics (p

ObjectThis study measured cerebral blood oxygen changes in patients with myofascial pain syndrome (MPS) using functional near-infrared spectroscopy (fNIRS). The aim was to investigate the effect of music intervention on pain relief in MPS patients.Materials and methodsA total of 15 patients with MPS participated in this study. A self-controlled block task design was used to collect the oxy-hemoglobin ([HbO2]) and deoxy-hemoglobin ([HbR]) concentrations in the prefrontal cortex (PFC) and motor cortex using fNIRS. The cerebral cortex response and channel connectivity were further analyzed. In the experiment, the therapist was asked to apply compression of 3–4 kg/cm2 vertically using the thumb to induce pain. Soothing synthetic music with frequencies of 8–150 Hz and 50–70 dB was used as the audio for the music intervention.ResultCompared to the group without music intervention, the activation of brain regions showed a decreasing trend in the group with music intervention under the onset of pain. The results of paired t-tests showed that nine of the data were significantly different (p < 0.05). It was also found that with music intervention, inter-channel connectivity was diminished. Besides, their dorsolateral prefrontal cortex (dlPFC) was significantly correlated with the anterior prefrontal cortex (aPFC) for pain response (r = 0.82), and weakly correlated with the premotor cortex (r = 0.40).ConclusionThis study combines objective assessment indicators and subjective scale assessments to demonstrate that appropriate music interventions can be effective in helping to relieve pain to some extent. The analgesic mechanisms between relevant brain regions under music intervention were explored in depth. New insights into effective analgesic methods and quantitative assessment of pain conditions are presented.

ABSTRACT Salmonella enterica serovar Enteritidis (S. Enteritidis), one of the zoonotic pathogens, not only results in significant financial losses for the global poultry industry but also has the potential to spread to humans through poultry and poultry products. Vaccination is an effective method to prevent Salmonella infections. In this study, we constructed a live attenuated DIVA (differentiation of infected and vaccinated animals) vaccine candidate, Z11ΔrfbG, and evaluated its protective effectiveness and DIVA potential in chickens. Compared to that of the virulent wild-type strain, the 50% lethal dose (LD50) of the rfbG mutant strain increased 56-fold, confirming its attenuation. High serum levels of S. Enteritidis-specific IgG titers indicated that a significant humoral immune response was induced in the vaccinated group. After challenge, the nonvaccinated group showed serious clinical symptoms (diarrhea, depression, decreased appetite, ruffled feathers, and weight loss), pathological changes (white nodules in the liver and fatty lesions in liver cells), and death. In contrast, there were no clinical symptoms, pathological changes, or death in the 5 × 106- and 5 × 107-CFU-vaccinated groups. Z11ΔrfbG vaccination significantly reduced S. Enteritidis colonization in the spleen, liver, and cecum. In addition, the Z11ΔrfbG-vaccinated group exhibited a negative response to the serological test, whereas the virulent wild-type Z11 infection group was strongly positive for the serological test, showing a DIVA capability of Z11ΔrfbG vaccination. Overall, our findings demonstrate the viability of the rfbG mutant as a live attenuated chicken vaccine that can discriminate between animals that have been immunized and those that have been infected. IMPORTANCE S. Enteritidis is a highly adapted pathogen that causes significant economic losses in the poultry industry around the world. Vaccination is an effective method of controlling S. Enteritidis infections. Here, we demonstrated that S. Enteritidis Z11ΔrfbG has the potential to be a safe, immunogenic, and DIVA vaccine candidate for the control of Salmonella infections in chickens. Z11ΔrfbG not only provided effective protection in chickens but also distinguished between infected and vaccinated chickens by serological tests.

In the past, most threshold models considered a single threshold variable. However, for some practical applications, models with two threshold variables may be needed. In this paper, we propose a two-threshold-variable integer-valued autoregressive model based on the binomial thinning operator and discuss some of its basic properties, including the mean, variance, strict stationarity, and ergodicity. We consider the conditional least squares (CLS) estimation and discuss the asymptotic normality of the CLS estimator under the known and unknown threshold values. The performances of the CLS estimator are compared via simulation studies. In addition, two real data sets are considered to underline the superior performance of the proposed model.

Multidrug-resistant bacteria have become a major threat to global public health. Bacteriophages are regarded as a promising substitute. Here, we present a novel lytic Stenotrophomonas maltophilia phage, vB_SM_ytsc_ply2008005c, which was isolated from sewage water samples in Qingdao, east China. Virion morphology of phage particles indicated that ply2008005c has an icosahedral head (56 ± 5 nm in diameter) and a noncontractile sheathed tail (129 ± 6 nm in length), which are the typical characteristics of phages belonging to the family Siphoviridae. Phage ply2008005c could be used for phage therapy for its stability in a wide pH (4 to 12) range and high temperature (up to 70°C) environment. Genome analysis revealed that ply2008005c has a circular double-strand DNA of 42,318 bp with a G+C content of 63.02%. It shared the closest relationship with phage vB_PaeS_PAO1_Ab18, but the homology coverage is just 20%. There were 54 open reading frames predicted in its genome, including three unique proteins and 34 functional genes in different modules. The phylogenetic analysis revealed that ply2008005c forms a distinct branch of the family Siphoviridae. These results demonstrated that ply2008005c was supposed to be a representative new member within the family Siphoviridae, which could be considered a potential bioagent against multidrug-resistant S. maltophilia.

Moving packed bed heat exchanger has been key equipment in the waste energy recovery and concentrated solar power. However, the effect of tube arrangement still deserve investigation to optimize heat transfer. In the present paper, the flow and heat transfer of gravity-driven particles flowing around the tube bank are numerically studied by the discrete element method. It was found that the stagnation zone of the staggered tubes is less than 45° and the cavity zone is in the range of 160° - 180°. The stagnation zone of the aligned tubes is in the range of 0° - 65° and 125° - 180°, and there is no cavity zone below the aligned tubes. The heat transfer performance of the staggered tubes is better than that of the aligned tubes. The best heat transfer region of the staggered tubes is at the top of the tube, and that of the aligned tubes is at the side of the tube. The bottom of the tube has the worst heat transfer in both the staggered and aligned tubes. It is necessary to improve the performance of the staggered tubes by optimizing the particle flow in the range 0° - 45° and 160° - 180°. Reducing the vertical tube spacing may be an effective option for the aligned tubes.

Chronic obstructive pulmonary disease (COPD) is highly underdiagnosed, and early detection is urgent to prevent advanced progression. Circulating microRNAs (miRNAs) have been diagnostic candidates for multiple diseases. However, their diagnostic value has not yet been fully established in COPD. The purpose of this study was to develop an effective model for the diagnosis of COPD based on circulating miRNAs. We included circulating miRNA expression profiles of two independent cohorts consisting of 63 COPD and 110 normal samples, and then we constructed a miRNA pair-based matrix. Diagnostic models were developed using several machine learning algorithms. The predictive performance of the optimal model was validated in our external cohort. In this study, the diagnostic values of miRNAs based on the expression levels were unsatisfactory. We identified five key miRNA pairs and further developed seven machine learning models. The classifier based on LightGBM was selected as the final model with the area under the curve (AUC) values of 0.883 and 0.794 in test and validation datasets, respectively. We also built a web tool to assist diagnosis for clinicians. Enriched signaling pathways indicated the potential biological functions of the model. Collectively, we developed a robust machine learning model based on circulating miRNAs for COPD screening.

Abstract Background Maize (Zea mays L.) is one of the main agricultural crops with the largest yield and acreage in the world. However, maize germplasm is very sensitive to low temperatures, mainly during germination, and low temperatures significantly affect plant growth and crop yield. Therefore, the identification of genes capable of increasing tolerance to low temperature has become necessary. Results In this study, fourteen phenotypic traits related to seed germination were used to assess the genetic diversity of maize through genome-wide association study (GWAS). A total of 30 single-nucleotide polymorphisms (SNPs) linked to low-temperature tolerance were detected (−log10(P) > 4), fourteen candidate genes were found to be directly related to the SNPs, further additional 68 genes were identified when the screen was extended to include a linkage disequilibrium (LD) decay distance of r 2 ≥ 0.2 from the SNPs. RNA-sequencing (RNA-seq) analysis was then used to confirm the linkage between the candidate gene and low-temperature tolerance. A total of ten differentially expressed genes (DEGs) (|log2 fold change (FC)| ≥ 0.585, P

Abstract Neural networks provide new possibilities to uncover semantic relationships between words by involving contextual information, and further a way to learn the matching pattern from document-query word contextual similarity matrix, which has brought promising results in IR. However, most neural IR methods rely on the conventional word-word matching framework for finding a relevant document for a query. Its effect is limited due to the wide gap between the lengths of query and document. To address this problem, we propose a salient context-based semantic matching (SCSM) method to build a bridge between query and document. Our method locates the most relevant context in the document using a shifting window with adapted length and then calculates the relevance score within it as the representation of the document. We define the notion of contextual salience and the corresponding measures to calculate the relevance of a context to a given query, in which the interaction between the query and the context is modeled by semantic similarity. Experiments on various collections from TREC show the effectiveness of our model as compared to the state-of-the-art methods.

Binomial autoregressive models are frequently used for modeling bounded time series counts. However, they are not well developed for more complex bounded time series counts of the occurrence of n exchangeable and dependent units, which are becoming increasingly common in practice. To fill this gap, this paper first constructs an exchangeable Conway–Maxwell–Poisson-binomial (CMPB) thinning operator and then establishes the Conway–Maxwell–Poisson-binomial AR (CMPBAR) model. We establish its stationarity and ergodicity, discuss the conditional maximum likelihood (CML) estimate of the model’s parameters, and establish the asymptotic normality of the CML estimator. In a simulation study, the boxplots illustrate that the CML estimator is consistent and the qqplots show the asymptotic normality of the CML estimator. In the real data example, our model takes a smaller AIC and BIC than its main competitors.

The purpose of this study was to investigate the influence of social rank (SR) on paternity efficiency (PE) in competitive mating flocks of geese. Thirty ganders and 150 geese (Zi geese, Anser cygnoides L.) aged approximately one, were divided into 3 groups. Flock 1 included 10 ganders and 50 female geese, flock 2 included 11 ganders and 55 female geese, and flock 3 included 9 ganders and 45 female geese. The frequency of the agonistic behavioral interactions (ABI) of the ganders and mating activity (MA) were video recorded in each flock. The SR of each gander was determined by the frequency of ABI with a score of 1 to 3 (1 being the dominant and 3 the most subordinate). To clarify the difference between being dominant and submissive, we collapsed rank 2 and rank 3 into a “subordinate” category. In total, 280 eggs were collected, and 219 goslings were hatched. Parent–offspring relationships among 399 individuals from the 2 generations were identified via 20 microsatellite markers, and the PE of each gander was calculated. There was no significant difference in individual body weight and semen quality factor among the different SR groups (dominant and subordinate), and the SR of the ganders was significantly correlated to PE for the 3 flocks. Goslings of high-ranking ganders contributed 48.68% in flock 1, 37.50% in flock 2, and 47.62% in flock 3. Approximately 45% of all goslings were sired by the 7 dominant ganders of the 30 total ganders across the 3 flocks. As SR has been shown to be heritable in geese, the selection of high-ranking ganders might be an effective way to improve reproductive efficiency in commercial geese flocks.

In Chinese megacity centers, substandard housing is being removed. The inhabitants are relocated to peripheral large-scale residential areas, and we call them “relocatees”. After the relocation, their housing quality is improved but travel quality may worsen. Little attention has been paid to the change in travel equity over time for shopping-related trips of relocatees and non-relocatees in these areas in rapidly developing countries, especially for the change before and after the major built environment development, such as a shopping plaza’s opening. To fill this research gap, we conducted two surveys before and after Wanda Shopping Plaza’s opening. We used statistical analysis, estimated discrete choice models focusing on mode choice, and calculated consumer surplus as a measurement of travel equity. Results show a relocatee has a lower travel quality for shopping-related trips. Travel equity between relocatees and non-relocatees for shopping-related trips becomes worse after Wanda’s opening. Differences in consumer surplus between relocatees and non-relocatees provide a reference for the travel subsidy policy.

Two new benzophenone glycosides, hypersens A and B, along with four known compounds, (S)-(+)-5,7-dihydroxy-2-(1-methylpropyl) chromone (3), 5,7-dihydroxy-2-isopropylchromone (4), urachromone B (5), and 3-8′′ bisapigenin (6), were isolated from Hypericum seniawinii. The structures of new compounds (1 and 2) were elucidated according to comprehensive spectroscopic data analyses. The absolute configurations of 1 and 2 were determined by electronic circular dichroism (ECD) calculations. All isolated compounds were evaluated for their neuroprotective effect using corticosterone-induced PC12 cell injury. In addition, compounds 1–6 were evaluated for their anti-inflammatory activity in lipopolysaccharide-induced RAW 264.7 cells. Compound 6 was a biflavonoid and significantly inhibited the production of nitric oxide with an IC50 value of 11.48 ± 1.23 μM.

The coronavirus disease 2019 (COVID-19) emerged by end of 2019, and became a serious public health threat globally in less than half a year. The generation interval and latent period, though both are of importance in understanding the features of COVID-19 transmission, are difficult to observe, and thus they can rarely be learnt from surveillance data empirically. In this study, we develop a likelihood framework to estimate the generation interval and incubation period simultaneously by using the contact tracing data of COVID-19 cases, and infer the pre-symptomatic transmission proportion and latent period thereafter. We estimate the mean of incubation period at 6.8 days (95 %CI: 6.2, 7.5) and SD at 4.1 days (95 %CI: 3.7, 4.8), and the mean of generation interval at 6.7 days (95 %CI: 5.4, 7.6) and SD at 1.8 days (95 %CI: 0.3, 3.8). The basic reproduction number is estimated ranging from 1.9 to 3.6, and there are 49.8 % (95 %CI: 33.3, 71.5) of the secondary COVID-19 infections likely due to pre-symptomatic transmission. Using the best estimates of model parameters, we further infer the mean latent period at 3.3 days (95 %CI: 0.2, 7.9). Our findings highlight the importance of both isolation for symptomatic cases, and for the pre-symptomatic and asymptomatic cases.

Background: O6-methylguanine-DNA methyltransferase (MGMT) methylation status affects tumor chemo-resistance and the prognosis of glioblastoma (GBM) patients. We aimed to investigate the role of MGMT methylation in the regulation of GBM immunophenotype and discover an effective biomarker to improve prognosis prediction of GBM patients.Methods: A total of 769 GBM patients with clinical information from five independent cohorts were enrolled in the present study. Samples from the Cancer Genome Atlas (TCGA) dataset were used as the training set, whereas transcriptome data from the Chinese Glioma Genome Atlas (CGGA) RNA-seq, CGGA microarray, GSE16011, and the Repository for Molecular Brain Neoplasia (REMBRANDT) cohort were used for validation. A series of bioinformatics approaches were carried out to construct a prognostic signature based on immune-related genes, which were tightly related to the MGMT methylation status. In silico analyses were performed to investigate the influence of the signature on immunosuppression and remodeling of the tumor microenvironment. Then, the utility of this immune gene signature was analyzed by the development and evaluation of a nomogram. In vitro experiments were further used to verify the immunologic function of the genes in the signature.Results: We found that MGMT unmethylation was closely associated with immune-related biological processes in GBM. Sixty-five immune genes were more highly expressed in the MGMT unmethylated than the MGMT-methylated group. An immune gene-based risk model was further established to divide patients into high and low-risk groups, and the prognostic value of this signature was validated in several GBM cohorts. Functional analyses manifested a universal up-regulation of immune-related pathways in the high-risk group. Furthermore, the risk score was highly correlated to the immune cell infiltration, immunosuppression, inflammatory activities, as well as the expression levels of immune checkpoints. A nomogram was developed for clinical application. Knockdown of the five genes in the signature remodeled the immunosuppressive microenvironment by restraining M2 macrophage polarization and suppressing immunosuppressive cytokines production.Conclusions:MGMT methylation is strongly related to the immune responses in GBM. The immune gene-based signature we identified may have potential implications in predicting the prognosis of GBM patients and mechanisms underlying the role of MGMT methylation.

Alternative splicing (AS) of pre-mRNA has been widely reported to be associated with the progression of malignant tumors. However, a systematic investigation into the prognostic value of AS events in glioblastoma (GBM) is urgently required. The gene expression profile and matched AS events data of GBM patients were obtained from The Cancer Genome Atlas Project (TCGA) and TCGA SpliceSeq database, respectively. 775 AS events were identified as prognostic factors using univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) cox model was performed to narrow down candidate AS events, and a risk score model based on several AS events were developed subsequently. The risk score-based signature was proved as an efficient predictor of overall survival and was closely related to the tumor purity and immunosuppression in GBM. Combined similarity network fusion and consensus clustering (SNF-CC) analysis revealed two distinct GBM subtypes based on the prognostic AS events, and the associations between this novel molecular classification and clinicopathological factors, immune cell infiltration, as well as immunogenic features were further explored. We also constructed a regulatory network to depict the potential mechanisms that how prognostic splicing factors (SFs) regulate splicing patterns in GBM. Finally, a nomogram incorporating AS events signature and other clinical-relevant covariates was built for clinical application. This comprehensive analysis highlights the potential implications for predicting prognosis and clinical management in GBM.

[This corrects the article DOI: 10.1371/journal.pone.0240662.].

Chinese economic development has continuously increased national municipal solid waste (MSW) output. However, the existing MSW classification method is insufficient and exacerbates several urgent problems. There are many factors to consider in Chinese waste classification (population, MSW production, food waste content, water content, economy, environment, and waste disposal methods). Based on research and analysis, MSW classification should highlight and implement treatment methods that focus on incineration, the distinct treatment of kitchen waste, and landfills as a waste disposal supplement. MSW is divided into five categories: kitchen waste, incineration, recyclable, hazardous waste, and other waste. Using economic benefit analysis, life cycle assessment, and radar chart analysis, a quantitative study is conducted on the classification methods of MSW used in Germany, the US, the UK, Sweden, Japan, China, and this study. The results indicate that a more refined classification can effectively improve many aspects of MSW management, especially regarding economic and environmental benefits, which are significantly affected. Effective MSW management can reduce the cost of waste disposal by 69.4% and greenhouse gas and acidic substance emissions and increase the energy utilisation rate four fold. This research is of great significance to environmental protection and the development of a circular economy and provides a reference for the management of MSW.

Objective. Gestational diabetes mellitus (GDM) is a common metabolic disorder with onset during pregnancy. However, the etiology and pathogenesis of GDM have not been fully elucidated. In this study, we used a metabolomics approach to investigate the relationship between maternal serum metabolites and GDM in early pregnancy. Methods. A nested case-control study was performed. To establish an early pregnancy cohort, pregnant women in early pregnancy (10‐13+6 weeks) were recruited. In total, 51 patients with GDM and 51 healthy controls were included. Serum samples were analyzed using an untargeted high-performance liquid chromatography mass spectrometry metabolomics approach. The relationships between metabolites and GDM were analyzed by an orthogonal partial least-squares discriminant analysis. Differential metabolites were evaluated using a KEGG pathway analysis. Results. A total of 44 differential metabolites were identified between GDM cases and healthy controls during early pregnancy. Of these, 26 significant metabolites were obtained in early pregnancy after false discovery rate (FDR

Nitrogen (N2) is the most important source of mineral N for plant growth, which was mainly transported by nitrate transporters (NRTs). However, little is known about the NRT gene family in potato. In this study, StNRT gene family members were identified in potato. In addition, we performed StNRT subfamily classification, gene structure and distribution analysis, and conserved domain prediction using various bioinformatics tools. Totally, 39 StNRT gene members were identified in potato genome, including 33, 4 and 2 member belong to NRT1, NRT2, and NRT3, respectively. These 39 StNRT genes were randomly distributed on all chromosomes. The collinearity results show that StNRT members in potato are closely related to Solanum lycopersicum and Solanum melongena. For the expression, different members of StNRT play different roles in leaves and roots. Especially under sufficient nitrogen conditions, different members have a clear distribution in different tissues. These results provide valuable information for identifying the members of the StNRT family in potato and could provide functional characterization of StNRT genes in further research.

Data is presented to explain why birds can recover their ruffled feather vanes by shaking wings and preening feathers with the beak [1]. Presented data includes the SEM microscopic images of rachis, barbs and barbules of pigeon's feather and the images recording the experiments of observing and mimicking the recovering performance of pigeons. Besides, based on the measurement and observation of the micro structure of feathers, the mechanical models of barbules were developed to better understand the wings performance. These high-quality images and models could be used for future research on feathers. Data helps to better understand the micro structure of feathers and the reason birds can fly. Data also support bioinspired mechanical structure development, especially for flapping robot development. Keywords: Feather, Hierarchical vane structure, Self-healing, Flapping robot

The feather of a bird consists of barbs which again comprise numerous barbules with micro-hooklets. This hierarchically organized feather structure provides a smooth vane to bear the load from the airflow; however, the feather vane is vulnerable to disruption by external pulling forces during collision with the branches of a tree and hitting some small obstacles in flight or strong turbulence. The feather is unable to carry the weight of the bird's body if the vane could not be recovered immediately. Here we discovered that the feather vane can be re-established easily by birds themselves. A bird can always recover its feather vane from ruffled state by shaking its wings and preening its feathers with its beak because of the cascaded geometries of barbs and barbules. This biophysical mechanism of self-healing suggests that the hierarchical vane structure can be used to design artificial feathers for a flapping robot. Keywords: Feather, Hierarchical vane structure, Self-healing, Flapping robot

Background: Dysbiosis of human gut microbiota is associated with a wide range of metabolic disorders, including gestational diabetes mellitus (GDM). Yet whether gut microbiota dysbiosis participates in the etiology of GDM remains largely unknown.Objectives: Our study was initiated to determine whether the alternations in gut microbial composition during early pregnancy linked to the later development of GDM, and explore the feasibility of microbial biomarkers for the early prediction of GDM.Study design: This nested case-control study was based upon an early pregnancy follow-up cohort (ChiCTR1900020652). Gut microbiota profiles of 98 subjects with GDM and 98 matched healthy controls during the early pregnancy (10–15 weeks) were assessed via 16S rRNA gene amplicon sequencing of V4 region. The data set was randomly split into a discovery set and a validation set, the former was used to analyze the differences between GDM cases and controls in gut microbial composition and functional annotation, and to establish an early identification model of GDM, then the performance of the model was verified by the external validation set.Results: Bioinformatic analyses revealed changes to gut microbial composition with significant differences in relative abundance between the groups. Specifically, Eisenbergiella, Tyzzerella 4, and Lachnospiraceae NK4A136 were enriched in the GDM group, whereas Parabacteroides, Megasphaera, Eubacterium eligens group, etc. remained dominant in the controls. Correlation analysis revealed that GDM-enriched genera Eisenbergiella and Tyzzerella 4 were positively correlated with fasting blood glucose levels, while three control-enriched genera (Parabacteroides, Parasutterella, and Ruminococcaceae UCG 002) were the opposite. Further, GDM functional annotation modules revealed enrichment of modules for sphingolipid metabolism, starch and sucrose metabolism, etc., while lysine biosynthesis and nitrogen metabolism were reduced. Finally, five genera and two clinical indices were included in the linear discriminant analysis model for the prediction of GDM; the areas under receiver operating characteristic curves of the training and validation sets were 0.736 (95% confidence interval: 0.663–0.808) and 0.696 (0.575–0.818), respectively.Conclusions: Gut bacterial dysbiosis in early pregnancy was found to be associated with the later development of GDM, and gut microbiota-targeted biomarkers might be utilized as potential predictors of GDM.

Nitrogen (N) is a key element for the production of potato. The N uptake efficiency, N use efficiency and increased N utilization efficiency can be decreased by N deficiency treatment. We performed this study to investigate the association between transcriptomic profiles and the efficiencies of N in potato. Potato cultivars "Yanshu 4" (short for Y), "Xiabodi" (cv. Shepody, short for X) and "Chunshu 4" (short for C) were treated with sufficient N fertilizer and deficient N fertilizer. Then, the growth parameters and tuber yield were recorded; the contents of soluble sugar and protein were measured; and the activities of enzymes were detected. Leaf and root transcriptomes were analyzed and differentially expressed genes (DEGs) in response to N deficiency were identified. The results showed that N deficiency decreased the nitrate reductase (NR), glutamine synthetase (GS) and root activity. Most of the DEGs between N-treated and N-deficiency participate the processes of transport, nitrate transport, nitrogen compound transport and N metabolism in C and Y, not in X, indicating the cultivar-dependent response to N deficiency. DEGs like glutamate dehydrogenase (StGDH), glutamine synthetase (StGS) and carbonic anhydrase (StCA) play key roles in these processes mentioned above. DEGs related to N metabolism showed a close relationship with the N utilization efficiency (UTE), but not with N use efficiency (NUE). The Major Facilitator Superfamily (MFS) members, like nitrate transporter 2.4 (StNRT2.4), 2.5 (StNRT2.5) and 2.7 (StNRT2.7), were mainly enriched in the processes associated with response to stresses and defense, indicating that N deficiency induced stresses in all cultivars.

As a metabolic disorder during pregnancy, gestational diabetes mellitus (GDM) has an important effects on fetal development, neonatal health and maternal long-term health, and is one of the pregnancy complications with high incidence. It is of great significance that we have an accurate understanding of the etiology and risk factors of GDM for its prevention and control. GDM is a complex disease with multiple etiologies. Current studies have shown that the occurrence of GDM may be the result of combined effect of heredity and environment, but the exact etiology is still unclear. In this paper, we summarized the possible etiologies and risk factors of GDM, so as to understand the occurrence and development of GDM better and to provide possible references for prevention and further etiological studies of GDM.

Rice black-streaked dwarf virus (RBSDV), a ds-RNA virus in Fijivirus genus with family Reoviridae, which is transmitted by the small brown planthopper, is responsible for incidence of maize rough dwarf disease (MRDD) and rice black-streaked dwarf disease (RBSDD). To understand the variation and evolution of S5, a unique fragment in the genome of RBSDV which encodes two partially overlapping ORFs (ORF5-1 and ORF5-2), we analyzed 127 sequences from maize and rice exhibiting symptoms of dwarfism. The nucleotide diversity of both ORF5-1 (π = 0.039) and ORF5-2 (π = 0.027) was higher than that of the overlapping region (π = 0.011) (P < 0.05). ORF5-2 was under the greatest selection pressure based on codon bias analysis, and its activation was possibly influenced by the overlapping region. The recombinant fragments of three recombinant events (14NM23, 14BM20, and 14NM17) cross the overlapping region. Based on neighbor-joining tree analysis, the overlapping region could represent the evolutionary basis of the full-length S5, which was classified into three main groups. RBSDV populations were expanding and haplotype diversity resulted mainly from the overlapping region. The genetic differentiation of combinations (T127-B35, T127-J34, A58-B35, A58-J34, and B35-J34) reached significant or extremely significant levels. Gene flow was most frequent between subpopulations A58 and B35, with the smallest |Fst| (0.02930). We investigated interactions between 13 RBSDV proteins by two-hybrid screening assays and identified interactions between P5-1/P6, P6/P9-1, and P3/P6. We also observed self-interactive effects of P3, P6, P7-1, and P10. In short, we have proven that RBSDV populations were expanding and the overlapping region plays an important role in the genetic variation and evolution of RBSDV S5. Our results enable ongoing research into the evolutionary history of RBSDV-S5 with two partly overlapping ORFs.

Background. Previous studies showed that probiotics could improve glycemic control and attenuate some of the adverse effects of type 2 diabetes. However, whether the effects are generalizable to gestational diabetes mellitus (GDM) remains uncertain. Objective. We conducted a systematic review and meta-analysis to evaluate the effects of probiotic supplement in GDM. Method. PubMed, EMBASE, the Cochrane Library, and EBSCO were systematically searched for relevant literature published through January 2019. Randomized controlled trials (RCTs) assessing the effects of probiotic supplement on one or more of the following in GDM were included: pregnancy outcome (the primary outcome), glycemic control, blood lipid profile, and inflammation and oxidative stress. Two reviewers independently extracted data and assessed the risk of bias in studies. Meta-analysis was conducted by using the fixed effects model unless substantial heterogeneity was found among studies. Results. Eleven randomized trials involving 719 participants were included for analysis. Eight of the trials were from Iran. Probiotics were given alone in eight trials and synbiotics in three trials. Though the components of probiotics varied, Lactobacillus was included in all trials and Bifidobacterium in all except one. The duration of intervention ranged from 4 to 8 weeks. Almost all trials (10/11) had a low risk of bias. Probiotic supplementation reduced the risk of a newborn’s hyperbilirubinemia by 74% and improved four biomarkers for glycemic control (fasting blood glucose, fasting serum insulin, homeostasis model assessment insulin resistance, and quantitative insulin sensitivity check index), two biomarkers for lipid profile (triglycerides and HDL-cholesterol), and four biomarkers for inflammation and oxidative stress (total glutathione, malondialdehyde, nitric oxide, and total antioxidant capacity). But significant heterogeneity was observed in the meta-analyses on the four biomarkers related to glycemic control and on triglycerides, which could not be explained by prespecified subgroup analyses according to the mean age of participants and intervention type (i.e., probiotics or synbiotics). The effects on the risk of preterm delivery, macrosomia and a newborns’ hypoglycemia, gestational age, total cholesterol, and LDL-cholesterol were not statistically significant. Conclusion. Probiotic supplementation seemed to be able to reduce the risk of a newborn’s hyperbilirubinemia and improve glycemic control, blood lipid profiles and inflammation and oxidative stress in pregnant women with GDM. However, due to the heterogeneity among existing studies, the surrogate nature of outcomes, and/or the fact that most studies were from Iran, the clinical significance and generalizability of the above findings remain uncertain. Further studies are warranted to address the limitations of existing evidence and better inform the management of GDM.

Lyocell fabrics are widely applied in textiles, however, its high flammability increases the risk of fire. Therefore, to resolve the issue, a novel biomass-based flame retardant with phosphorus and nitrogen elements was designed and synthesized by the reaction of arginine with phosphoric acid and urea. It was then grafted onto the lyocell fabric by a dip-dry-cure technique to prepare durable flame-retardant lyocell fabric (FR-lyocell). X-ray photoelectron spectroscopy (XPS) and Fourier-transform infrared spectroscopy (FTIR) analysis demonstrated that the flame retardant was successfully introduced into the lyocell sample. Thermogravimetric (TG) and Raman analyses confirmed that the modified lyocell fabric featured excellent thermal stability and significantly increased char residue. Vertical combustion results indicated that FR-lyocell before and after washing formed a complete and dense char layer. Thermogravimetric Fourier-transform infrared (TG-FTIR) analysis suggested that incombustible substances (such as H2O and CO2) were produced and played a significant fire retarding role in the gas phase. The cone calorimeter test corroborated that the peak of heat release rate (PHRR) and total heat release (THR) declined by 89.4% and 56.4%, respectively. These results indicated that the flame retardancy of the lyocell fabric was observably ameliorated.