Validity and reliability of the toxic leadership behaviors of nurse managers scale among Chinese nurses.

Objectives: Toxic leadership is increasingly becoming common in the nursing field, but the measurement tools are lacking. Therefore, this study aimed to translate the toxic leadership behaviors of nurse managers (ToxBH-NM) scale into Chinese and test its psychometric properties among Chinese nurses. Methods: The data for this study were obtained from a cross-sectional survey of 1,195 nurses. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to examine the structural validity of the ToxBH-NM. The following psychometric properties of the scale were assessed: content validity, criterion validity, internal consistency reliability, and test-retest reliability. Results: The Chinese version of the ToxBH-NM (C-ToxBH-NM) scale had two dimensions and 30 items. The correlation coefficients between the scores of each item and the total scores were 0762-0.922 (p < 0.001), and the range of the CR determination values of all the items were 8.610-18.998, with statistical significance (p < 0.001). The total content validity index (CVI) was 0.996, the average CVI was 0.996, and the item-level CVI was 0.875-1.000. Two common factors were identified in the EFA, and 81.074% of the variation was explained cumulatively. The CFA showed that all the fitting indexes reached the standard, and the model fit degree was good. When the Chinese version of the Destructive Leadership Scale was used as calibration, the correlation coefficient was 0.378 (p < 0.001). The Cronbach's alpha coefficients of the overall scale were 0.989 and of the two dimensions were 0.969 and 0.987, respectively, with a split-half reliability of 0.966 and test-retest reliability of 0.978. Conclusion: The research results show that the C-ToxBH-NM scale has good reliability and validity and can be used to evaluate the severity of toxic leadership behavior among nursing managers.

Screening the Biomarkers and Related Medicines for Gastric Adenocarcinoma.

OBJECTIVE: To search for potential biomarkers and available medicines for gastric adenocarcinoma. STUDY DESIGN: Experimental study. Place and Duration of the Study: Scientific Research Section, Shenzhen Longhua District Central Hospital, Shenzhen, China, from January to April 2023. METHODOLOGY: Datasets were retrieved from the Gene Expression Omnibus (GEO). Differential gene expression analysis between gastric adenocarcinoma and normal samples was conducted using GEO2R. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed via the Enrichr website. Protein-protein interaction (PPI) networks were established using the STRING website. The central hub genes were identified using the cytoHubba plugin integrated within Cytoscape. Finally, the GEPIA2 and QuartataWeb websites were employed to validate the expression levels of the hub genes and to identify potential medicines for gastric adenocarcinoma. RESULTS: In total, 133 DEGs were identified. GO analysis revealed that these DEGs predominantly participate in processes such as cell adhesion, positive regulation of cell proliferation, and extracellular matrix organisation. In the KEGG pathways, DEGs were significantly enriched in gastric acid secretion, protein digestion and absorption, and ECM-receptor interaction. Following the construction of the PPI network, 10 central hub genes were identified and validated using GEPIA2. Notably, among these hub genes, SERPINE1 demonstrated a significant association with the prognosis of gastric adenocarcinoma, and potential therapeutic agents were subsequently predicted. CONCLUSION: SERPINE1 and potential therapeutic agents hold promise to enhance personalised diagnosis and treatment for gastric adenocarcinoma patients in the future. KEY WORDS: Biomarkers, Gastric adenocarcinoma, Bioinformatics, Differentially Expressed Genes (DEGs).

Exploring the impact of circular economy practices on ecological footprint, inflation rate, and renewable energy consumption: evidence from G20 economies.

The circular economy (CE) has acquired significant interest for its potential to contribute to sustainable development (SD). The present study utilizes empirical methodology, specifically panel data analysis, to examine the distinct effects and outcomes of the circular economy and its associated factors within a unified framework. The focus is on the G20 countries from 2008 to 2021. We evaluated the influence of various CE value sources (renewable energy consumption, composting rate, repair services availability, recycling rate) and a factor-analysis-derived measure of the CE on economic, environmental, and social aspects of SD. The objective was to assess the distinct effects and outcomes of CE and its components in a unified framework-the analysis utilized panel data from G20 countries from 2008 to 2021. Our findings show a substantial influence of CE in achieving SD, with positive implications for the economy, environment, and society. However, the impact of each CE value source on the SD dimensions shows variation. While renewable energy consumption (RENEC) and composting rate (CR) lessen environmental impact, recycling rate (RR) shows no significant effect, and repair services availability (RSA) increases the Ecological Footprint (EFP). Notably, RSA is the sole CE component, showing a positive economic impact at the national level. Additionally, RENEC, RSA, and RR contribute to reducing the inflation rate (INFR). Policymakers should undertake detailed impact assessments to develop effective, tailored strategies based on each country's unique goals. The findings of this study have important policy implications, particularly in terms of emphasizing targeted strategies for implementing CE practices to achieve sustainable development.

Machine learning-based estimation of riverine nutrient concentrations and associated uncertainties caused by sampling frequencies.

Accurate and sufficient water quality data is essential for watershed management and sustainability. Machine learning models have shown great potentials for estimating water quality with the development of online sensors. However, accurate estimation is challenging because of uncertainties related to models used and data input. In this study, random forest (RF), support vector machine (SVM), and back-propagation neural network (BPNN) models are developed with three sampling frequency datasets (i.e., 4-hourly, daily, and weekly) and five conventional indicators (i.e., water temperature (WT), hydrogen ion concentration (pH), electrical conductivity (EC), dissolved oxygen (DO), and turbidity (TUR)) as surrogates to individually estimate riverine total phosphorus (TP), total nitrogen (TN), and ammonia nitrogen (NH4+-N) in a small-scale coastal watershed. The results show that the RF model outperforms the SVM and BPNN machine learning models in terms of estimative performance, which explains much of the variation in TP (79 ± 1.3%), TN (84 ± 0.9%), and NH4+-N (75 ± 1.3%), when using the 4-hourly sampling frequency dataset. The higher sampling frequency would help the RF obtain a significantly better performance for the three nutrient estimation measures (4-hourly > daily > weekly) for R2 and NSE values. WT, EC, and TUR were the three key input indicators for nutrient estimations in RF. Our study highlights the importance of high-frequency data as input to machine learning model development. The RF model is shown to be viable for riverine nutrient estimation in small-scale watersheds of important local water security.

Temporal and spatial diagnostic model of vehicle gas pollutants.

In this paper, the gas pollutants in motor vehicle exhaust are taken as the research object. The diagnostic index system of motor vehicle gas pollutants on environmental pollution is constructed, based on the environmental pollution caused by motor vehicle exhaust. The emission intensity of various types of vehicles was studied. The least-square method is used to construct the diagnostic functions of different types of vehicle gas pollutants; the vehicle emission factors of different types of motor vehicle gas pollutants are obtained. By exploring the spatial-temporal correlation of vehicle emissions under traffic conditions, uncertainty mathematical theory is used to establish a spatial-temporal diagnosis model of vehicle gas pollutants on environmental pollution, and multiple correlation coefficients are used to conduct accuracy test. The research results can not only determine the pollution problem of motor vehicle emissions to the environment but also effectively evaluate the emission level of gas pollutants in the exhaust gas of motor vehicles. The application results show that the spatial-temporal diagnostic model of vehicle gas pollutants for environmental pollution has better guiding significance and practical value in solving environmental pollution problems.

Long noncoding RNA GAS6 antisense RNA1 silencing attenuates the tumorigenesis of acute myeloid leukemia cells through targeting microRNA-370-3p/Tetraspanin3 axis.

PURPOSE: Acute myeloid leukemia (AML) is a type of hematologic malignancy. This study was attempt to explore the effect of long noncoding RNA GAS6 antisense RNA1 (GAS6-AS1) on pediatric AML and the regulation mechanisms. METHODS: GAS6-AS1, microRNA-370-3p (miR-370-3p), and Tetraspanin3 (TSPAN3) expression in bone marrow (BM) tissues and cells was determined by qRT-PCR. The correlation between GAS6-AS1 and clinicopathological features of pediatric patients with AML was assessed. In vitro, viability and migration and invasion of AML cells were evaluated via MTT and transwell assays, respectively. Interactions among GAS6-AS1, miR-370-3p, and TSPAN3 were revealed by dual-luciferase reporter assays. Western blot was applied to confirm the protein expression of TSPAN3. RESULTS: GAS6-AS1 and TSPAN3 expression was elevated in BM tissues of pediatric patients with AML and AML cells, but miR-370-3p expression was reduced. GAS6-AS1 expression was positively related to French-American-British (FAB) classification in pediatric patients with AML. In vitro, GAS6-AS1 deficiency restrained the viability, migration, and invasion of AML cells. Additionally, GAS6-AS1 mediated miR-370-3p expression indeed and TSPAN3 was identified as a target of miR-370-3p. Furthermore, miR-370-3p overexpression repressed the protein expression of TSPAN3. The feedback experiments demonstrated that miR-370-3p inhibition or TSPAN3 overexpression mitigated the suppressive effect of sh-GAS6-AS1 on the tumorigenesis of AML cells. CONCLUSION: GAS6-AS1 silencing restrained AML cell viability, migration, and invasion by targeting miR-370-3p/TSPAN3 axis, affording a novel therapeutic target for pediatric AML.

A panel of three plasma microRNAs for colorectal cancer diagnosis.

BACKGROUND: Differential microRNA (miRNA) expression profiles in plasma or serum were identified, providing foundation for studying their potentially diagnostic role in colorectal cancer (CRC). METHODS: We performed S-poly(T) Plus PCR assay to select and validate differentially expressed plasma miRNAs from a sample set including 101 CRC patients, 20 patients with colorectal noncancerous polyps (NCP), and 134 healthy controls. And bioinformatics methods was used to integrated predicted or validated targets of the differentially dysregulated miRNAs and analyzed their overrepresented pathways. RESULTS: After the two-phase selection and validation process, we identified a miRNA panel (miR-144-3p, miR-425-5p, and miR-1260b) with high diagnostic efficiency for CRC; the panel distinguished CRC patients from controls with 93.8% sensitivity and 91.3% specificity. Results indicated that the dysregulated miRNAs in CRC were functionally involved in several key cancer-related pathways, such as axonal guidance, PI3K, and calcium signaling pathways. CONCLUSIONS: Our study demonstrated that a plasma 3-miRNA panel may serve as a novel noninvasive biomarker to diagnose CRC. This plasma 3-miRNA panel may be related to CRC development. However, further studies are needed to highlight its theoretical strengths.

Direct chemiluminescence detection of circulating microRNAs in serum samples using a single-strand specific nuclease-distinguishing nucleic acid hybrid system.

We developed a microplate-based enhanced chemiluminescence system for the direct detection of circulating miRNAs. The system exhibited a high target sensitivity and specificity, with a detection limit of 3.02 fM.

A Systematic Study of Dysregulated MicroRNA in Type 2 Diabetes Mellitus.

MicroRNAs (miRNAs) are small noncoding RNAs that modulate the cellular transcriptome at the post-transcriptional level. miRNA plays important roles in different disease manifestation, including type 2 diabetes mellitus (T2DM). Many studies have characterized the changes of miRNAs in T2DM, a complex systematic disease; however, few studies have integrated these findings and explored the functional effects of the dysregulated miRNAs identified. To investigate the involvement of miRNAs in T2DM, we obtained and analyzed all relevant studies published prior to 18 October 2016 from various literature databases. From 59 independent studies that met the inclusion criteria, we identified 158 dysregulated miRNAs in seven different major sample types. To understand the functional impact of these deregulated miRNAs, we performed targets prediction and pathway enrichment analysis. Results from our analysis suggested that the altered miRNAs are involved in the core processes associated with T2DM, such as carbohydrate and lipid metabolisms, insulin signaling pathway and the adipocytokine signaling pathway. This systematic survey of dysregulated miRNAs provides molecular insights on the effect of deregulated miRNAs in different tissues during the development of diabetes. Some of these miRNAs and their mRNA targets may have diagnostic and/or therapeutic utilities in T2DM.

A systematic study on dysregulated microRNAs in cervical cancer development.

MicroRNAs (miRNAs) are short regulatory RNAs that modulate the transcriptome and proteome at the post-transcriptional level. To obtain a better understanding on the role of miRNAs in the progression of cervical cancer, meta-analysis and gene set enrichment analysis were used to analyze published cervical cancer miRNA studies. From 85 published reports, which include 3,922 cases and 2,099 noncancerous control tissue samples, 63 differentially expressed miRNAs (DEmiRNAs) were identified in different stages of cervical cancer development (CIN 1-3 and CC). It was found that some of the dysregulated miRNAs were associated with specific stages of cervical cancer development. To illustrate the impact of miRNAs on the pathogenesis of cervical cancer, a miRNA-mRNA interaction network on selected pathways was built by integrating viral oncoproteins, dysregulated miRNAs and their predicted/validated targets. The results indicated that the deregulated miRNAs at the different stages of cervical cancer were functionally involved in several key cancer related pathways, such as cell cycle, p53 and Wnt signaling pathways. These dysregulated miRNAs could play an important role in cervical cancer development. Some of the stage-specific miRNAs can also be used as biomarkers for cancer classification and monitoring the progression of cancer development.

Current State of Circulating MicroRNAs as Cancer Biomarkers.

BACKGROUND: Numerous studies have demonstrated the existence of stable regulatory RNAs, microRNAs (miRNAs), in the circulation and have shown that the spectrum of these extracellular miRNAs is affected by various pathologic conditions including cancers. CONTENT: Circulating miRNAs have been the focus of numerous cancer biomarker discovery efforts over the past few years; however, a considerable number of these studies have yielded inconsistent and irreproducible findings. Here, we have summarized and compared the results of studies covering 8 different cancer types to address key questions, including the possibility of using circulating miRNA to detect cancers and what factors may affect miRNA signatures. Although identifying circulating miRNA signatures to detect specific types of early stage cancers can be challenging, study results suggest that it may be possible to use miRNAs to detect cancers in general. SUMMARY: Circulating miRNA is a rich source for potential disease biomarkers; however, factors, both intrinsic and extrinsic, that may affect measurement of circulating miRNA have not been fully characterized. Better understanding of intra- and intercellular miRNA trafficking and the fundamental biology of cancer cell-derived lipid vesicles may facilitate the development of circulating miRNA-based biomarkers for cancer detection and classification.

Association of miR-146a rs2910164 polymorphism with cardio-cerebrovascular diseases: A systematic review and meta-analysis.

The microRNA146a rs2910164 polymorphism has been associated with the development of cardio-cerebrovascular diseases (CCDs); however, the results were inconsistent among different studies. The present report was aimed to investigate the association between rs2910164 G/C polymorphism and the risk of CCDs. Based on the data extracted from 12 eligible studies with a total of 5433 CCD cases and 6278 controls, we performed a meta-analysis to assess the diseases risk of rs2910164 G/C polymorphism under allelic contrast (C vs. G), homozygote comparisons (CC vs. GG), heterozygote comparisons (GC vs. GG), dominant model (CC+GC vs. GG) and recessive models (CC vs. GC+GG) in fixed or random effects models. We also conducted pathway enrichment analyses using the putative and validated miR-146a interacting targets to explore the functional impacts of rs2910164. The current meta-analysis results showed that rs2910164 CC genotype has a decreased risk with overall cardiovascular diseases and the specific coronary artery disease. Stratified analysis based on ethnicity showed that the CC genotype has a decreased risk with CCDs in Chinese population, but has an increased risk with CCDs in Korean and Indian populations. The results from pathway enrichment analysis also revealed the association of rs2910164 G allele with heart function and disease related pathways. Our findings suggested that miR-146a CC genotype might be a protective factor for cardiovascular diseases in Chinese population, but a risk factor in Korean and Indian populations.

Structure and antitumor and immunomodulatory activities of a water-soluble polysaccharide from Dimocarpus longan pulp.

A new water-soluble polysaccharide (longan polysaccharide 1 (LP1)) was extracted and successfully purified from Dimocarpus longan pulp via diethylaminoethyl (DEAE)-cellulose anion-exchange and Sephacryl S-300 HR gel chromatography. The chemical structure was determined using Infrared (IR), gas chromatography (GC) and nuclear magnetic resonance (NMR) analysis. The results indicated that the molecular weight of the sample was 1.1 × 10(5) Da. Monosaccharide composition analysis revealed that LP1 was composed of Glc, GalA, Ara and Gal in a molar ratio of 5.39:1.04:0.74:0.21. Structural analysis indicated that LP1 consisted of a backbone of → 4)-α-D-Glcp-(1 → 4)-α-D-GALPA-(1 → 4)-α-D-Glcp-(1 → 4)-ß-D-Glcp-(1 → units with poly saccharide side chains composed of → 2)-ß-D-Fruf-(1 → 2)-L-sorbose-(1 → attached to the O-6 position of the α-D-Glcp residues. In vitro experiments indicated that LP1 had significantly high antitumor activity against SKOV3 and HO8910 tumor cells, with inhibition percentages of 40% and 50%, respectively. In addition, LP1 significantly stimulated the production of the cytokine interferon-γ (IFN-γ), increased the activity of murine macrophages and enhanced B- and T-lymphocyte proliferation. The results of this study demonstrate that LP1 has potential applications as a natural antitumor agent with immunomodulatory activity.

The valence overall wiener index for unsaturated hydrocarbons.

By replacing the distances between pairs of vertices with the relative distances, we define a novel valence overall Wiener index (VOW); the valence overall Wiener index extends the usefulness of the Wiener index and the overall Wiener index to unsaturated hydrocarbons.