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Abstract Background Health-related quality of life (HRQOL) in cancer patients has attracted increasing attention, which may be associated with self-rated health (SRH), anxiety, and depression. However, limited studies have focused on the mediating role of anxiety and depression in the relationship between SRH and HRQOL among cancer patients. Therefore, this study aims to explore the serial multiple mediating effects of anxiety and depression between SRH and HRQOL in cancer patients. Methods This cross-sectional study investigated a total of 565 hospitalized cancer patients in Anhui province in China from November 2020 to October 2021. SRH was assessed using a single-item measure, anxiety and depression were assessed using the Hospital Anxiety and Depression Scale (HADS) and HRQOL was assessed using the EuroQol-5 Dimension (EQ-5D, three-level version). Socio-demographic and clinical characteristics were analyzed using descriptive statistics. The relationships between SRH, anxiety, depression, and HRQOL were evaluated by Pearson correlation analysis. The serial multiple mediation of anxiety and depression was assessed by SPSS PROCESS macro. Results SRH, anxiety, depression and HRQOL were significantly correlated(P

DNA and RNA methylation are essential epigenetic modifications that play a pivotal role in various physiological processes by modulating gene expression at the post-transcriptional level. Abnormal DNA/RNA methylation is closely linked to a range of human diseases, including cancer and neurological disorders. Therefore, the accurate and sensitive detection of DNA/RNA methylation is of great importance in both epigenetic biology research and disease diagnosis. Technological advancements have led to the comprehensive development of methylation detection methods. Among these, electrochemical techniques have garnered significant attention owing to their simplicity and effectiveness in detection. This review provides an overview of methylation detection technologies based on electrochemical principles developed over the past five years, including electrochemical, photoelectrochemical, electrochemiluminescence, and fluorescence methodologies. Additionally, it discusses the advantages and disadvantages of these approaches, challenges and advancements in methylation detection.

Abstract Background Extracellular vesicles (EVs) derived from various cell sources exert cardioprotective effects during cardiac ischemic injury. Our previous study confirmed that EVs derived from ischemic-reperfusion injured heart tissue aggravated cardiac inflammation and dysfunction. However, the role of EVs derived from normal cardiac tissue in myocardial ischemic injury remains elusive. Results In the present study, normal heart-derived EVs (cEVs) and kidney-derived EVs (nEVs) were isolated and intramyocardially injected into mice after myocardial infarction (MI). We demonstrated that administration of both cEVs and nEVs significantly improved cardiac function, reduced the scar size, and alleviated inflammatory infiltration into the heart. In addition, cardiomyocyte apoptosis was inhibited, whereas angiogenesis was enhanced in the hearts receiving cEVs or nEVs treatment. Moreover, intramyocardial injection of cEVs displayed much better cardiac protective efficacy than nEVs in murine MI models. RNA-seq and protein-protein interaction (PPI) network analysis revealed the protective mRNA clusters in both cEVs and nEVs. These mRNAs were involved in multiple signaling pathways, which may synergistically orchestrate to prevent the heart from further damage post MI. Conclusions Collectively, our results indicated that EVs derived from normal heart tissue may represent a promising strategy for cardiac protection in ischemic heart diseases.

Castanopsis hystrix Hook. f. & Thomson ex A. DC. 1863 (Fagaceae) is an evergreen broad-leaved tree with high economic and ecological value. In this study, the complete chloroplast genome of C. hystrix was sequenced, assembled and annotated. The plastome (plastid genome) of C. hystrix was 160,624 bp in size, consisting of a pair of inverted repeats (IRs, 25,699 bp), a large-single-copy (LSC, 90,276 bp) region, and a small-single-copy (SSC, 18,950 bp). The overall GC content of C. hystrix was 36.8%. A total of 133 genes were annotated, including 88 protein-coding genes (PCG), 37 transfer RNA genes (tRNA), and eight ribosomal RNA genes (rRNA). A maximum likelihood analysis showed that the Castanopsis species form a monophyletic clade. C. hystrix is most closely related to C. tibetana with 100% bootstrap support value. The result enriches the genomic data for the genus Castanopsis, which will contribute to future studies in phylogenetics and evolution.

Abstract Extracellular vesicles (EVs) exist throughout our bodies. We recently revealed the important role of intracardiac EVs induced by myocardial ischemia/reperfusion on cardiac injury and dysfunction. However, the role of EVs isolated from normal tissues remains unclear. Here we found that EVs, derived from murine heart, lung, liver and kidney have similar effects on macrophages and regulate the inflammation, chemotaxis, and phagocytosis of macrophages. Interestingly, EV‐treated macrophages showed LPS resistance with reduced expressions of inflammatory cytokines and enhanced phagocytic activity. Furthermore, we demonstrated that the protein content in EVs contributed to the activation of inflammation, while the RNA component mainly limited the excessive inflammatory response of macrophages to LPS. The enrichment of miRNAs, including miR‐148a‐3p, miR‐1a‐3p and miR‐143‐3p was confirmed in tissue EVs. These EV‐enriched miRNAs contributed to the inflammation remission in LPS induced macrophages through multiple pathways, including STAT3, P65 and SAPK/JNK. Moreover, administration of both EVs and EV‐educated macrophages attenuated septic injury and cytokine storm in murine CLP models. Taken together, the present study disclosed that EVs from normal tissues can orchestrate the homeostasis of macrophages and attenuate inflammatory injury of sepsis. Therefore, tissue derived EVs or their derivatives may serve as potential therapeutic strategies in inflammatory diseases.

Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation sector. Deployment of charging infrastructure is needed to accelerate technology adoption; however, managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across regions. In this article, we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including Chinese. We investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously available. We find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of interest. This evidence contrasts with predictions in the U.S. and European markets, where the performance is closer to parity. We also find that networked stations with communication protocols provide a relatively higher quality of charging services, which favors policy support for connectivity, particularly for underserved or remote areas.

Abstract Background and objectives Research suggests that fibrinogen (Fib) concentrations are used to assess the occurrence and severity of diabetic foot (DF) and to monitor the progression of diabetic foot in patients. However, its correlation with Fib function has not been reported. Here, angle α and k value, reflecting the Fib function, were used to analyse its correlation with DF, and their potential as biological indicators for evaluating the occurrence and severity of DF was explored. Subjects and methods This clinical study enrolled 163 type 2 diabetes mellitus (T2DM) patients, who were divided into the diabetes with DF (84 cases) group, diabetes with no DF (79 cases) group. Meanwhile, 90 healthy unrelated subjects were enrolled as controls. Results Angle α and fibrinogen levels increased greatly in subjects with DF compared with those without. The k value levels greatly decreased in subjects with DF compared with those without (P

Abstract Background Human umbilical cord-derived mesenchymal stem cells (HucMSCs) have been recognized as a promising cell for treating myocardial infarction (MI). Inflammatory response post MI is critical in determining the cardiac function and subsequent adverse left ventricular remodeling. However, the local inflammatory effect of HucMSCs after intramyocardial injection in murine remains unclear. Methods HucMSCs were cultured and transplanted into the mice after MI surgery. Cardiac function of mice were analyzed among MI-N.S, MI-HucMSC and MI-HucMSC-C–C Motif Chemokine receptor 5 (CCR5) antagonist groups, and angiogenesis, fibrosis and hypertrophy, and immune cells infiltration of murine hearts were evaluated between MI-N.S and MI-HucMSC groups. We detected the expression of inflammatory cytokines and their effects on CD4+ T cells migration. Results HucMSCs treatment can significantly improve the cardiac function and some cells can survive at least 28 days after MI. Intramyocardial administration of HucMSCs also improved angiogenesis and alleviated cardiac fibrosis and hypertrophy. Moreover, we found the much higher numbers of CD4+ T cells and CD4+FoxP3+ regulatory T cells (Tregs) in the heart with HucMSCs than that with N.S treatment on day 7 post MI. In addition, the protein level of C–C Motif Chemokine Ligand 5 (CCL5) greatly increased in HucMSCs treated heart compared to MI-N.S group. In vitro, HucMSCs inhibited CD4+ T cells migration and addition of CCL5 antibody or CCR5 antagonist significantly reversed this effect. In vivo results further showed that addition of CCR5 antagonist can reduce the cardioprotective effect of HucMSCs administration on day 7 post MI injury. Conclusion These findings indicated that HucMSCs contributed to cardiac functional recovery and attenuated cardiac remodeling post MI. Intramyocardial injection of HucMSCs upregulated the CD4+FoxP3+ Tregs and contributed to the migration of CD4+ T cells into the injured heart via CCL5/CCR5 pathway.

In large-scale wind turbines, the force state of the pitch system greatly influences safe operation and service life. This paper provides a novel method to estimate blade pitch load, bearing friction torque, and motor pitch torque. In this method, the force equilibrium equations are established by investigating the force of the pitch system under multiple operating conditions. The multidimensional BIN method is employed to classify the supervisory control and data acquisition (SCADA) data of wind turbines into several intervals. The multidimensional scatter data is processed in a single-valued way. Then, the estimating model of the pitch system forces is established by combining the obtained data and the equilibrium equations. Taking a 2 MW wind turbine as an example, the variation characteristics of blade pitch load, bearing friction torque, and motor pitch torque under multiple operating conditions are analyzed. Some interesting and valuable conclusions are obtained. For example, when the wind speed increases, the blade pitch load increases significantly in the maximum wind energy tracking region, but there is no obvious change in the observed constant power output region. The wind speed and azimuth have little effect on the bearing friction torque. The variation trend of motor pitch torque is consistent with that of blade pitch load in the maximum wind energy tracking region.

Excessive and chronic inflammation post myocardial infarction (MI) causes cardiac fibrosis and progressive ventricular remodeling, which leads to heart failure. We previously found high levels of IL-27 in the heart and serum until day 14 in murine cardiac ischemia‒reperfusion injury models. However, whether IL-27 is involved in chronic inflammation-mediated ventricular remodeling remains unclear. In the present study, we found that MI triggered high IL-27 expression in murine cardiac macrophages. The increased expression of IL-27 in serum is correlated with cardiac dysfunction and aggravated fibrosis after MI. Furthermore, the addition of IL-27 significantly activated the JAK/STAT signaling pathway in cardiac fibroblasts (CFs). Meanwhile, IL-27 treatment promoted the proliferation, migration and extracellular matrix (ECM) production of CFs induced by angiotensin II (Ang II). Collectively, high levels of IL-27 mainly produced by cardiac macrophages post MI contribute to the activation of CFs and aggravate cardiac fibrosis.

Abstract Mitochondrial dysfunction is considered to be a key contributor to the development of heart failure. Replacing injured mitochondria with healthy mitochondria to restore mitochondrial bioenergy in myocardium holds great promise for cardioprotection after infarction. This study aimed to investigate whether direct transplantation of exogenous mitochondria derived from mesenchymal stem cells (MSC‐mt) is beneficial and superior in protecting cardiac function in a mouse model of myocardial infarction (MI) compared to mitochondria derived from skin fibroblast (FB‐mt) and to explore the underlying mechanisms from their effects on the endothelial cells. The isolated MSC‐mt presented intact mitochondrial morphology and activity, as determined by electron microscopy, JC‐1 mitochondrial membrane potential assay, and seahorse assay. Direct injection of MSC‐mt into the peri‐infarct region in a mouse MI model enhanced blood vessel density, inhibited cardiac remodeling and apoptosis, thus improving heart function compared with FB‐mt group. The injected MSC‐mt can be tracked in the endothelial cells. In vitro, the fluorescence signal of MSC‐mt can be detected in human umbilical vein endothelial cells (HUVECs) by confocal microscopy and flow cytometry after coculture. Compared to FB‐mt, MSC‐mt more effectively protected the HUVECs from oxidative stress‐induced apoptosis and reduced mitochondrial production of reactive oxygen species. MSC‐mt presented superior capacity in inducing tube formation, enhancing SCF secretion, ATP content and cell proliferation in HUVECs compared to FB‐mt. Mechanistically, MSC‐mt administration alleviated oxidative stress‐induced endothelial senescence via activation of ERK pathway. These findings suggest that using MSCs as sources of mitochondria is feasible and that proangiogenesis could be the mechanism by which MSC‐mt transplantation attenuates MI. MSC‐mt transplantation might serve as a new therapeutic strategy for treating MI.

Overactive inflammatory responses contribute to progressive cardiac dysfunction after myocardial infarction (MI). Mesenchymal stem cell (MSC) has generated significant interest as potent immune modulators that can regulate excessive immune responses. We hypothesized that intravenous (iv) administration of human umbilical cord-derived MSC (HucMSC) exerts systemic and local anti-inflammation effects, leading to improved heart function after MI. In murine MI models, we confirmed that single iv administration of HucMSC (30×104) improved cardiac performance and prevented adverse remodeling after MI. A small proportion of HucMSC is trafficked to the heart, preferentially in the infarcted region. HucMSC administration increased CD3+ T cell proportion in the periphery while decreased T cell proportion in both infarcted heart and mediastinal lymph nodes (med-LN) at 7-day post-MI, indicating a systematic and local T cell interchange mediated by HucMSC. The inhibitory effects of HucMSC on T cell infiltration in the infarcted heart and med-LN sustained to 21-day post-MI. Our findings suggested that iv administration of HucMSC fostered systemic and local immunomodulatory effects that contributed to the improvement of cardiac performance after MI.

Gynura japonica (Asteraceae) is a folk herbal medicine with multi-pharmacological functions involving analgesic, hemostatic and antiangiogenic activities. The study was conducted to assemble the complete chloroplast (cp) genome of G. japonica through a genome-skimming approach. The assembled cp genome was 151,023 bp in size, with 62.8% AT content, consisting of a large single copy (LSC) of 83,185 bp, two copies of inverted repeat (IRa and IRb) of 24,847 bp, and a small single copy (SSC) of 18,144 bp. The cp genome of G. japonica contained 133 genes, including eight ribosomal RNA genes (rRNAs), 37 transfer RNA genes (tRNAs), 86 protein-coding genes (PCGs), and two pseudogenes (ψycf1 and ψrps19). Our phylogenomic analysis based on whole plastid genomes strongly supports G. japonica is a sister to the clade including Crassocephalum crepidioides and Jacobaea vulgaris.

The key problem to be solved in the process of wind turbine (WT) operation and maintenance is to obtain the wind turbine performance accurately. The power curve is an important indicator to evaluate the performance of wind turbines. How to model and obtain the power curve of wind turbines has always been one of the hot topics in research. This paper proposes a novel idea to get the actual power curve of wind turbines. Firstly, the basic data preprocessing algorithm is designed to process the zero value and null value in the original supervisory control and data acquisition (SCADA) data. The moving average filtering (MAF) method is employed to deal with the wind speed, the purpose of which is to consider the comprehensive result of wind on the wind turbine power in a certain period. According to the momentum theory of the ideal wind turbine and combined with the characteristics of the anemometer installation position, the deviation between the measured wind speed and the actual wind speed is approximately corrected. Here, the influence of dynamic changes in air density is also considered. Then, the Gaussian fitting algorithm is used to fit the wind-power curve. The characteristics of the power curve before and after wind speed correction are compared and analyzed. At the same time, the influence of the parameter uncertainty on the reliability of the power curve is considered and investigated. Finally, the characteristics of the power curves of four wind turbines are compared and analyzed. The research results show that among these power curves, WT3 and WT4 are the closest, WT2 is the next, and WT1 has the farthest deviation from the others. The research work provides a valuable basis for on-site performance evaluation, overhaul, and maintenance of wind turbines.

Data pre-processing is the first step of using SCADA data to study the performance of wind turbines. However, there is a lack of knowledge of how to obtain more effective data pre-processing algorithms. This paper fully explores multiple data pre-processing algorithms for power curve modeling. A three-stage data processing mode is proposed, namely, preliminary data filtering and compensation (Stage I), secondary data filtering (Stage II), and single-valued processing (Stage Ⅲ). Different data processing algorithms are selected at different stages and are finally merged into nine data processing algorithms. A novel evaluation method based on energy characteristic consistency (ECC) is proposed to evaluate the reliability of various algorithms. The influence of sliding mode and benchmark of Binning on data processing has been fully investigated through indicators. Four wind turbines are selected to verify the advantages and disadvantages of the nine data processing methods. The result shows that at the same wind speed, the rotational speed and power values obtained by MLE (maximum likelihood estimation) are relatively high among the three single-valued methods. Among the three outlier filtering methods, the power value obtained by KDE (kernel density estimation) is relatively large. In general, KDE-LSM (least square method) has good performance in general. The sum of four evaluating index values obtained by KDE-LSM from four wind turbines is the smallest.

This article reports an empirical study on embedding digital literacies in the language teacher education curriculum with pre-service and in-service teachers enrolled in a graduate-level language teaching method course. Two different types of technology-mediated collaborative tasks were implemented, one being collaborative reading for writing using Perusall and Google Docs, and the other being collaborative infographic composing using Canva. The analyses of the participants' semi-structured individual interviews revealed multiple benefits of digital practices that the pre-service and in-service teachers perceived, including enhancing content learning, providing cognitive scaffolding, fostering communication/collaboration skills, fostering creativity, enhancing learning motivation, improving pedagogic skills, and developing digital literacy skills. They also reported detailed plans or practices for implementing digital pedagogy using the same technology tools, adopting similar tasks, and extending the digital tasks. This study contributes to the underrepresented research domain on digital pedagogy for language teacher training.

Profiling bodily fluids is crucial for monitoring and discovering metabolic markers of disease. In this study, a comprehensive analysis approach based on 1D-LC-MS/MS and 2D-LC-MS/MS was applied to profile normal human urine metabolites from 348 children and 315 adults. A total of 2357 metabolites were identified, including 1831 endogenous metabolites and 526 exogenous ones. In total, 1005 metabolites were identified in urine for the first time. The urinary metabolites were mainly involved in amino acid metabolism, small molecule biochemistry, lipid metabolism and cellular compromise. The comparison of adult’s and children’s urine metabolomes showed adults urine had more metabolites involved in immune response than children’s, but the function of binding of melatonin, which belongs to the endocrine system, showed a higher expression in children. The urine metabolites detected by the 1D-LC-MS/MS method were mainly related to amino acid metabolism and lipid metabolism, and the 2D-LC-MS/MS method not only explored metabolites from 1D-LC-MS/MS but also metabolites related to cell signaling, cell function and maintenance, etc. Our analysis comprehensively profiled and functionally annotated the metabolome of normal human urine, which would benefit the application of urinary metabolome to clinical research.

The primary wind turbines’ in-service performance evaluation method is mining and analyzing the SCADA data. However, there are complex mathematical and physical relationships between multiple operating parameters, and so far, there is a lack of systematic understanding. To solve this issue, the distribution of wind turbines’ operating parameters was first analyzed according to the characteristics of the energy flow of wind turbines. Then, the correlation calculation was performed using the Spearman correlation coefficient method based on the minute-level data and second-level data. According to the numerical characteristics of the nacelle vibration acceleration, the data preprocessing technology sliding window maximum (SWM) was proposed during the calculation. In addition, taking temperature correlation as an example, two-dimensional scatter (including single-valued scatter) and three-dimensional scatter features were combined with numerical analysis and physical mechanism analysis to understand the correlation characteristics better. On this basis, a quantitative description model of the temperature characteristics of the gearbox oil pool was constructed. Through this research work, the complex mathematical and physical relationships among the multi-parameters of the wind turbines were comprehensively obtained, which provides data and theoretical support for the design, operation, and maintenance.

This paper discusses the increasingly prominent role of ChatGPT in providing feedback and assessment for L2 writing in the digital age. It reviews representative studies that address five research strands about the use of ChatGPT in L2 writing contexts. After a critical evaluation of the existing literature, the author extensively explains four innovative sub-topics on leveraging ChatGPT for L2 writing feedback and assessment, drawing on multiple creative projects undertaken by her research team. These include: 1) ChatGPT-student collaboration in the L2 writing process; 2) ChatGPT-supported teacher feedback; 3) collaborative processing of ChatGPT feedback; and 4) the potential of ChatGPT for L2 writing assessment. This paper also addresses the importance of teacher training on the use of GenAI in language and writing instruction.

As multimodal texts become ubiquitous in the digital age, analyzing how writers interact with readers via visuals is becoming increasingly important. Enlightened by Kress and van Leeuwen's (1996, 2001) semiotic work, D'Angelo (2010) extended Hyland's (2000) text-based metadiscourse model and proposed a new framework for analyzing the visual metadiscourse of multimodal texts. We used D'Angelo's (2016) visual metadiscourse framework to evaluate the comprehensibility and organization of the EFL students' infographics in this study. Two research questions guided our inquiry: (1) How do EFL students use diverse visual metadiscourse resources in their infographic posters? (2) In what ways, if any, does the use of visual interactive resources relate to the assessed quality of the infographics? We collected a total of 122 infographic posters and coded 5 categories of interactive resources for each poster (i.e., information value, framing, connective elements, graphic elements, and fonts), and then carried out frequency counts for each category and subcategories, taking all the posters into account. Moreover, we graded the EFL students' infographics according to a multi-traits grading rubric, and then conducted multiple regression analyses of their use of visual interactive resources and the scores for their infographics in the aspect of visual effects. The results show that the students used diverse visual interactive resources to guide their audience through the text. The assessed quality of the infographics was found to be significantly correlated with the use of graphic elements and fonts. This study sheds new light on digital multimodal pedagogy, particularly on the role of visual metadiscourse in teaching and assessing multimodal texts in language/writing classrooms.

ABSTRACT Background Early detection of bladder cancer (BCa) can have a positive impact on patients' prognosis. However, there is currently no widely accepted method for early screening of BCa. We aimed to develop an efficient, clinically applicable, and noninvasive method for the early screening of BCa by detecting specific serum miRNA levels. Methods A mixed‐cohort (including BCa, 12 different other cancers, benign disease patients, and health population) study was conducted using a sample size of 16,189. Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. The performance of the model was evaluated using receiver operating characteristic curve and decision curve analysis on the testing dataset, and subsequently, the model with the best predictive power was selected. Furthermore, the selected model's screening performance was evaluated using both the validation set and external set. Results The BCaS3miR model, utilizing only three serum miRNAs (miR‐6087, miR‐1343‐3p, and miR‐5100) and based on the KNN algorithm, is the superior screening model chosen for BCa. BCaS3miR consistently performed well in both the testing, validation, and external sets, exceeding 90% sensitivity and specificity levels. The area under the curve was 0.990 (95% CI: 0.984–0.991), 0.964 (95% CI: 0.936–0.984), and 0.917 (95% CI: 0.836–0.953) in the testing, validation, and external set. The subgroup analysis revealed that the BCaS3miR model demonstrated outstanding screening accuracy in various clinical subgroups of BCa. In addition, we developed a BCa screening scoring model (BCaSS) based on the levels of miR‐1343‐3p/miR‐6087 and miR‐5100/miR‐6087. The screening effect of BCaSS is investigated and the findings indicate that it has predictability and distinct advantages. Conclusions Using a mixed cohort with the largest known sample size to date, we have developed effective screening models for BCa, namely BCaS3miR and BCaSS. The models demonstrated remarkable screening accuracy, indicating potential for the early detection of BCa.

Abstract Drug induced liver injury (DILI) is a kind of liver dysfunction which caused by drugs, and gut microbiota could affect liver injury. However, the relationship between gut microbiota and its metabolites in DILI patients is not clear. The total gut microbiota DNA was extracted from 28 DILI patient and 28 healthy control volunteers (HC) and 16S rDNA gene were amplified. Next, differentially metabolites were screened. Finally, the correlations between the diagnostic strains and differentially metabolites were studied.The richness and uniformity of the bacterial communities decreased in DILI patients, and the structure of gut microbiota changed obviously. Enterococcus and Veillonella which belong to Firmicutes increased in DILI, and Blautia and Ralstonia which belong to Firmicutes, Dialister which belongs to Proteobacteria increased in HC. In addition, these diagnostic OTUs of DILI were associated with the DILI damage mechanism. On the other hands, there were 66 differentially metabolites between DILI and HC samples, and these metabolites were mainly enriched in pyrimidine metabolism and steroid hormone biosynthesis pathways. Furthermore, the collinear network map of the key microbiota-metabolites were constructed and the results indicated that Cortodoxone, Prostaglandin I1, Bioyclo Prostaglandin E2 and Anacardic acid were positively correlated with Blautia and Ralstonia, and negatively correlated with Veillonella.This study analyzed the changes of DILI from the perspective of gut microbiota and metabolites. Key strains and differentially metabolites of DILI were screened and the correlations between them were studied. This study further illustrated the mechanism of DILI.

Abstract Objective Diabetes mellitus is a global epidemic disease. Long-time exposure of patients to hyperglycemia can lead to various type of chronic tissue damage. Early diagnosis of and screening for diabetes are crucial to population health. Methods We collected the national physical examination data in Xinjiang, China, in 2020 (a total of more than 4 million people). Three types of physical examination indices were analyzed: questionnaire, routine physical examination and laboratory values. Integrated learning, deep learning and logistic regression methods were used to establish a risk model for type-2 diabetes mellitus. In addition, to improve the convenience and flexibility of the model, a diabetes risk score card was established based on logistic regression to assess the risk of the population. Results An XGBoost-based risk prediction model outperformed the other five risk assessment algorithms. The AUC of the model was 0.9122. Based on the feature importance ranking map, we found that hypertension, fasting blood glucose, age, coronary heart disease, ethnicity, parental diabetes mellitus, triglycerides, waist circumference, total cholesterol, and body mass index were the most important features of the risk prediction model for type-2 diabetes. Conclusions This study established a diabetes risk assessment model based on multiple ethnicities, a large sample and many indices, and classified the diabetes risk of the population, thus providing a new forecast tool for the screening of patients and providing information on diabetes prevention for healthy populations.

Licorice is widespread in arid and semi-arid areas, but high soil salinity has always been a limiting factor for vegetation growth in these areas. Gamma-aminobutyric acid (GABA) is a signaling molecule that can regulate tolerance in plant. However, the mechanism by which exogenous GABA regulates the response of licorice to saline-alkali stress is not yet clear. In this study, we investigated the effects of exogenous GABA on growth parameters, oxidative damage, hormone levels and photosynthetic indices of licorice seedlings under different combinations of saline and alkali stress conditions. The experiment involved eight treatments: CK, distilled water (control); CK + GABA, 0.1 mM GABA; salt stress (SS), 150 mM NaCl; SS + GABA, 150 mM NaCl + 0.1 mM GABA; alkali stress (AS), 10 mM Na2CO3; AS + GABA, 10 mM Na2CO3 + 0.1 mM GABA; mixed saline-alkali stress (MAS), 150 mM NaCl + 10 mM Na2CO3; MAS + GABA, 150 mM NaCl + 10 mM Na2CO3 + 0.1 mM GABA. Our results showed that the inhibitory effects of SS and MAS on the seedling height, root length and root-shoot ratio were significantly alleviated by exogenous GABA. Although soluble sugars, chlorophyll a, total chlorophyll, and superoxide dismutase (SOD) activity were lower in the leaves of the seedlings in the SS treatment compared with the control, these physiological parameters increased significantly after GABA application. Exogenous GABA improved glutathione (GSH) activity in both the leaves and roots of the seedlings during the AS treatment. Additionally, take advantage of GABA led to an increase in ABA, GA and IAA contents in leaves under SS, AS and MAS treatments. Furthermore, the photosynthetic parameters, including Pn, gs, Tr, ETR and qP, significantly increased following the utilization of GABA in both the SS and MAS treatments. Therefore, the application of exogenous GABA can reduce the accumulation of harmful substances, preserve cell morphology, and enhance cell function under saline, alkali, and saline-alkali stress. This enhances the resistance of licorice seedlings to stress conditions and reduces physiological damage.

BackgroundAs researchers are increasingly interested in real-world studies (RWSs), improving data collection efficiency and data quality has become an important challenge. An electronic source (eSource) generally includes direct capture, collection, and storage of electronic data to simplify clinical research. It can improve data quality and patient safety and reduce clinical trial costs. Although there are already large projects on eSource technology, there is a lack of experience in using eSource technology to implement RWSs. Our team designed and developed an eSource record (ESR) system in China. In a preliminary prospective study, we selected a cosmetic medical device project to evaluate ESR software’s effect on data collection and transcription. As the previous case verification was simple, we plan to choose more complicated ophthalmology projects to further evaluate the ESR. ObjectiveWe aimed to evaluate the data transcription efficiency and quality of ESR software in retrospective studies to verify the feasibility of using eSource as an alternative to traditional manual transcription of data in RWS projects. MethodsThe approved ophthalmic femtosecond laser project was used for ESR case validation. This study compared the efficiency and quality of data transcription between the eSource method using ESR software and the traditional clinical research model of manually transcribing the data. Usability refers to the quality of a user’s experience when interacting with products or systems including websites, software, devices, or applications. To evaluate the system availability of ESR, we used the System Usability Scale (SUS). The questionnaire consisted of the following 2 parts: participant information and SUS evaluation of the electronic medical record (EMR), electronic data capture (EDC), and ESR systems. By accessing log data from the EDC system previously used by the research project, all the time spent from the beginning to the end of the study could be counted. ResultsIn terms of transcription time cost per field, the eSource method can reduce the time cost by 81.8% (11.2/13.7). Compared with traditional manual data transcription, the eSource method has higher data transcription quality (correct entry rate of 2356/2400, 98.17% vs 47,991/51,424, 93.32%). A total of 15 questionnaires were received with a response rate of 100%. In terms of usability, the average overall SUS scores of the EMR, EDC, and ESR systems were 50.3 (SD 21.9), 51.5 (SD 14.2), and 63.0 (SD 11.3; contract research organization experts: 69.5, SD 11.5; clinicians: 59.8, SD 10.2), respectively. The Cronbach α for the SUS items of the EMR, EDC, and ESR systems were 0.591 (95% CI −0.012 to 0.903), 0.588 (95% CI −0.288 to 0.951), and 0.785 (95% CI 0.576-0.916), respectively. ConclusionsIn real-world ophthalmology studies, the eSource approach based on the ESR system can replace the traditional clinical research model that relies on the manual transcription of data.

Dry eye disease is a common condition that affects the eyes. It is caused by problems with the tear film and the tear dynamics. Dry eye can be caused by an increase in the amount of reactive oxygen species (ROS) in the corneal epithelium. The treatment for dry eye typically focuses on relieving the uncomfortable symptoms by using eye drops such as artificial tears, antibiotics, and by using anti-inflammatory/immunosuppressive agents such as cyclosporine, and lifitegrast. However, the recovery of patients with dry eye can take several years particularly if the symptoms are severe. This is because the present treatment approaches for dry eye are not based on its cause, e.g., the oxidative stress arising from the rapid increase in ROS. This work describes a new type of antioxidant made from pterostilbene (PS) and carboxyl-chitosan modified graphene (CG). The use of a hydrophilic two-dimensional CG nanosheet to improve the properties of PS is reported. Superior enhanced properties including better cellular permeability, long sustained release period (over 30 h), and antioxidant properties, were realized by using PS-CG. A hyperosmotic (HS) damaged human corneal epithelial cell (HCEC) model was used for antioxidant tests. This model has an intracellular ROS level 4 times more than that of a control group. The ROS content was declined efficiently to the same amount as normal cells in the PS-CG treated HS group. There was a significant decline in the content of lactate dehydrogenase (LDH) and the apoptosis rate of HCEC in the PS-CG treated HS group when compared to that seen in the HS model. Real-time polymerase chain reaction (PCR) and western blots (WB) were used to understand the antioxidant mechanism of PS-CG. The results showed that the antioxidant was working by activating the Keap1-Nrf2-ARE signalling pathway. In vivo testing testing using a dry eye mouse model suggested that the PS-CG acted as an efficient antioxidant. More tear production and healthier corneal and conjunctival epithelial cells were achieved when PC-CG was applied to this model. The use of PS-CG could be a new strategy for treating dry eye and other ocular diseases caused by ROS.