Relationship between emotional intelligence and academic support perception among nursing interns: The moderating role of bullying behaviors in nursing education.

AIM: This study aims to investigate the status of academic support perception among nursing interns and explore the correlation between academic support perception, emotional intelligence, and bullying behaviors in nursing education, especially the moderating role of bullying behavior on the relationship between emotional intelligence and academic support perception. BACKGROUND: Academic support perception is closely related to the nursing interns' mental health and academic performance. To some extent, it can reflect nursing interns' satisfaction and happiness during their internship, affecting their motivation to continue their studies. However, little is known about the nursing interns' academic support perception in China. METHODS: A total of 1020 nursing interns participated in this study. A sociodemographic information questionnaire, Bullying Behaviors in Nursing Education Scale, Wong and Law's Emotional Intelligence Scale, and Academic Support in the Practicum Scale were used to collect data. FINDINGS: Bullying behaviors and emotional intelligence were significantly associated with nursing interns' academic support perception. In addition, bullying behaviors in nursing education moderated the association between emotional intelligence and academic support perception. DISCUSSION: Nursing interns who possess high emotional intelligence and experience less bullying in nursing education tend to perceive higher academic support in clinical practice. The positive effects of emotional intelligence on nursing interns' academic support perceptions are contingent on the level of bullying behavior experienced in nursing education. Less bullying behaviors in nursing education enhance the impact of emotional intelligence on academic support perception. CONCLUSION AND IMPLICATIONS FOR NURSING: Strategies should be created to promote emotional intelligence and decrease bullying behaviors in nursing education to improve the perception of academic support among nursing interns.

Early blood immune molecular alterations in cynomolgus monkeys with a PSEN1 mutation causing familial Alzheimer's disease.

INTRODUCTION: More robust non-human primate models of Alzheimer's disease (AD) will provide new opportunities to better understand the pathogenesis and progression of AD. METHODS: We designed a CRISPR/Cas9 system to achieve precise genomic deletion of exon 9 in cynomolgus monkeys using two guide RNAs targeting the 3' and 5' intron sequences of PSEN1 exon 9. We performed biochemical, transcriptome, proteome, and biomarker analyses to characterize the cellular and molecular dysregulations of this non-human primate model. RESULTS: We observed early changes of AD-related pathological proteins (cerebrospinal fluid Aß42 and phosphorylated tau) in PSEN1 mutant (ie, PSEN1-ΔE9) monkeys. Blood transcriptome and proteome profiling revealed early changes in inflammatory and immune molecules in juvenile PSEN1-ΔE9 cynomolgus monkeys. DISCUSSION: PSEN1 mutant cynomolgus monkeys recapitulate AD-related pathological protein changes, and reveal early alterations in blood immune signaling. Thus, this model might mimic AD-associated pathogenesis and has potential utility for developing early diagnostic and therapeutic interventions. HIGHLIGHTS: A dual-guide CRISPR/Cas9 system successfully mimics AD PSEN1-ΔE9 mutation by genomic excision of exon 9. PSEN1 mutant cynomolgus monkey-derived fibroblasts exhibit disrupted PSEN1 endoproteolysis and increased Aß secretion. Blood transcriptome and proteome profiling implicate early inflammatory and immune molecular dysregulation in juvenile PSEN1 mutant cynomolgus monkeys. Cerebrospinal fluid from juvenile PSEN1 mutant monkeys recapitulates early changes of AD-related pathological proteins (increased Aß42 and phosphorylated tau).

Inhibition of JNK ameliorates rod photoreceptor degeneration in a mouse model of retinitis pigmentosa.

Retinitis pigmentosa (RP) is an inherited eye disease that causes progressive vision loss. Microglial activation and inflammation play essential roles in photoreceptor degeneration in RP, although the underlying mechanisms remain unclear. Here, we examined the progressive degeneration of photoreceptors in rd1 mice, a mouse model of RP. We investigated the molecular changes in various retinal cells in rd1 mice using single-cell RNA sequencing and found that potentiation of JNK signaling is associated with photoreceptor degeneration in RP. Moreover, inflammation-related molecules, which function downstream of JNK, are elevated in RP. Furthermore, inhibiting JNK alleviates microglial activation and rescues photoreceptor degeneration in rd1 mice. Thus, our findings suggest that targeting JNK is a promising approach for slowing RP progression.

Insight into selectivity of photocatalytic methane oxidation to formaldehyde on tungsten trioxide.

Tungsten trioxide (WO3) has been recognized as the most promising photocatalyst for highly selective oxidation of methane (CH4) to formaldehyde (HCHO), but the origin of catalytic activity and the reaction manner remain controversial. Here, we take {001} and {110} facets dominated WO3 as the model photocatalysts. Distinctly, {001} facet can readily achieve 100% selectivity of HCHO via the active site mechanism whereas {110} facet hardly guarantees a high selectivity of HCHO along with many intermediate products via the radical way. In situ diffuse reflectance infrared Fourier transform spectroscopy, electron paramagnetic resonance and theoretical calculations confirm that the competitive chemical adsorption between CH4 and H2O and the different CH4 activation routes on WO3 surface are responsible for diverse CH4 oxidation pathways. The microscopic mechanism elucidation provides the guidance for designing high performance photocatalysts for selective CH4 oxidation.

Steering Photooxidation of Methane to Formic Acid over A Priori Screened Supported Catalysts.

Efficient methane photooxidation to formic acid (HCOOH) has emerged as a sustainable approach to simultaneously generate value-added chemicals and harness renewable energy. However, the persistent challenge lies in achieving a high yield and selectivity for HCOOH formation, primarily due to the complexities associated with modulating intermediate conversion and desorption after methane activation. In this study, we employ first-principles calculations as a comprehensive guiding tool and discover that by precisely controlling the O2 activation process on noble metal cocatalysts and the adsorption strength of carbon-containing intermediates on metal oxide supports, one can finely tune the selectivity of methane photooxidation products. Specifically, a bifunctional catalyst comprising Pd nanoparticles and monoclinic WO3 (Pd/WO3) would possess optimal O2 activation kinetics and an intermediate oxidation/desorption barrier, thereby promoting HCOOH formation. As evidenced by experiments, the Pd/WO3 catalyst achieves an exceptional HCOOH yield of 4.67 mmol gcat-1 h-1 with a high selectivity of 62% under full-spectrum light irradiation at room temperature using molecular O2. Notably, these results significantly outperform the state-of-the-art photocatalytic systems operated under identical condition.

Coronin 2B deficiency induces nucleolar stress and neuronal apoptosis.

In eukaryotes, the nucleolus is the critical non-membranous organelle within nuclei that is responsible for ribosomal DNA (rDNA) transcription and ribosome biogenesis. The transcription of rDNA, a rate-limiting step for ribosome biogenesis, is tightly regulated to meet the demand for global protein synthesis in response to cell physiology, especially in neurons, which undergo rapid changes in morphology and protein composition during development and synaptic plasticity. However, it is unknown how the pre-initiation complex for rDNA transcription is efficiently assembled within the nucleolus in neurons. Here, we report that the nucleolar protein, coronin 2B, regulates rDNA transcription and maintains nucleolar function through direct interaction with upstream binding factor (UBF), an activator of RNA polymerase I transcriptional machinery. We show that coronin 2B knockdown impairs the formation of the transcription initiation complex, inhibits rDNA transcription, destroys nucleolar integrity, and ultimately induces nucleolar stress. In turn, coronin 2B-mediated nucleolar stress leads to p53 stabilization and activation, eventually resulting in neuronal apoptosis. Thus, we identified that coronin 2B coordinates with UBF to regulate rDNA transcription and maintain proper nucleolar function in neurons.

A high-permeability method for extracting purple yam saponins based on ultrasonic-assisted natural deep eutectic solvent.

The extraction of active ingredients from traditional Chinese medicine has received considerable attentions. In this study, 16 kinds of natural deep eutectic solvent (NADES) with ultrasonic were selected to extract saponins from purple yam root and the extraction mechanism was investigated. The results showed that chloride/acrylic acid (1:2; n/n) had the highest extraction yield for saponins. The optimal extraction process parameters were 24% water content, 20 mL/g liquid-solid ratio, and ultrasonic extraction for 85 min (81 °C, 600 W). The extraction rate (ER) of purple yam saponins was 0.935%, close to the fitted result of 96.5 mg/g. Molecular dynamics simulations and FT-IR results showed that the NADES may extract the saponin constituents from purple yam through hydrogen bonding. Compared with traditional extraction methods and molecularly imprinted polymer methods, NADES has a higher ER and lower cost (1.53 $/g), which provides a reference for subsequent industrial quantitative production.

Highly Dispersed Ni Atoms and O3 Promote Room-Temperature Catalytic Oxidation.

Transition metal oxides are promising catalysts for catalytic oxidation reactions but are hampered by low room-temperature activities. Such low activities are normally caused by sparse reactive sites and insufficient capacity for molecular oxygen (O2) activation. Here, we present a dual-stimulation strategy to tackle these two issues. Specifically, we import highly dispersed nickel (Ni) atoms onto MnO2 to enrich its oxygen vacancies (reactive sites). Then, we use molecular ozone (O3) with a lower activation energy as an oxidant instead of molecular O2. With such dual stimulations, the constructed O3-Ni/MnO2 catalytic system shows boosted room-temperature activity for toluene oxidation with a toluene conversion of up to 98%, compared with the O3-MnO2 (Ni-free) system with only 50% conversion and the inactive O2-Ni/MnO2 (O3-free) system. This leap realizes efficient room-temperature catalytic oxidation of transition metal oxides, which is constantly pursued but has always been difficult to truly achieve.

Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors.

The weighted nearest neighbors (WNN) estimator has been popularly used as a flexible and easy-to-implement nonparametric tool for mean regression estimation. The bagging technique is an elegant way to form WNN estimators with weights automatically generated to the nearest neighbors (Steele, 2009; Biau et al., 2010); we name the resulting estimator as the distributional nearest neighbors (DNN) for easy reference. Yet, there is a lack of distributional results for such estimator, limiting its application to statistical inference. Moreover, when the mean regression function has higher-order smoothness, DNN does not achieve the optimal nonparametric convergence rate, mainly because of the bias issue. In this work, we provide an in-depth technical analysis of the DNN, based on which we suggest a bias reduction approach for the DNN estimator by linearly combining two DNN estimators with different subsampling scales, resulting in the novel two-scale DNN (TDNN) estimator. The two-scale DNN estimator has an equivalent representation of WNN with weights admitting explicit forms and some being negative. We prove that, thanks to the use of negative weights, the two-scale DNN estimator enjoys the optimal nonparametric rate of convergence in estimating the regression function under the fourth-order smoothness condition. We further go beyond estimation and establish that the DNN and two-scale DNN are both asymptotically normal as the subsampling scales and sample size diverge to infinity. For the practical implementation, we also provide variance estimators and a distribution estimator using the jackknife and bootstrap techniques for the two-scale DNN. These estimators can be exploited for constructing valid confidence intervals for nonparametric inference of the regression function. The theoretical results and appealing finite-sample performance of the suggested two-scale DNN method are illustrated with several simulation examples and a real data application.

Intercalation in 2D materials and in situ studies.

Intercalation of atoms, ions and molecules is a powerful tool for altering or tuning the properties - interlayer interactions, in-plane bonding configurations, Fermi-level energies, electronic band structures and spin-orbit coupling - of 2D materials. Intercalation can induce property changes in materials related to photonics, electronics, optoelectronics, thermoelectricity, magnetism, catalysis and energy storage, unlocking or improving the potential of 2D materials in present and future applications. In situ imaging and spectroscopy technologies are used to visualize and trace intercalation processes. These techniques provide the opportunity for deciphering important and often elusive intercalation dynamics, chemomechanics and mechanisms, such as the intercalation pathways, reversibility, uniformity and speed. In this Review, we discuss intercalation in 2D materials, beginning with a brief introduction of the intercalation strategies, then we look into the atomic and intrinsic effects of intercalation, followed by an overview of their in situ studies, and finally provide our outlook.

Effect of Pretreatment and Drying on the Nutritional and Functional Quality of Raisins Produced with Seedless Purple Grapes.

Raisins, known for their delicious taste and high nutritional value, are among the most widely consumed dried fruits globally. The natural waxy layer on the surface of grapes impedes water migration, making pretreatment necessary before drying. This study evaluated the effects of various pretreatment methods on the nutritional and functional quality of seedless purple raisins. By using non-pretreated dry seedless purple raisins as a control, the impact of physical and chemical pretreatment methods on the nutritional and functional qualities of seedless purple raisins was assessed through the analysis of nutrient content, phenolic compounds, and antioxidant activity. Our results demonstrate that physical pretreatment significantly increases the levels of vitamin C, fructose, glucose, total acid, total phenolics, total flavonoids, total anthocyanins, and antioxidant activity compared to chemical pretreatment and the control group. The correlation analysis revealed that phenolic substances were closely linked to antioxidant capacity. Additionally, phenolic compounds, including resveratrol, ferulic acid, chlorogenic acid, ethyl coumarate, and cinnamic acid, were more abundant following physical pretreatment. The OPLS-DA model effectively differentiated the three groups of processed samples, showing that different pretreatments significantly affect the nutritional and functional quality of seedless purple raisins. These findings suggest that physical pretreatment offers considerable potential for improving the drying quality of seedless purple raisins.

Seasonal patterns, fate and ecological risk assessment of pharmaceutical compounds in a wastewater treatment plant with Bacillus bio-reactor treatment.

Pharmaceutical compounds (PhCs) pose a growing concern with potential environmental impacts, commonly introduced into the environment via wastewater treatment plants (WWTPs). The occurrence, removal, and season variations of 60 different classes of PhCs were investigated in the baffled bioreactor (BBR) wastewater treatment process during summer and winter. The concentrations of 60 PhCs were 3400 ± 1600 ng/L in the influent, 2700 ± 930 ng/L in the effluent, and 2400 ± 120 ng/g dw in sludge. Valsartan (Val, 1800 ng/L) was the main contaminant found in the influent, declining to 520 ng/L in the effluent. The grit chamber and BBR tank were substantially conducive to the removal of VAL. Nonetheless, the BBR process showcased variable removal efficiencies across different PhC classes. Sulfadimidine had the highest removal efficiency of 87 ± 17% in the final effluent (water plus solid phase). Contrasting seasonal patterns were observed among PhC classes within BBR process units. The concentrations of many PhCs were higher in summer than in winter, while some macrolide antibiotics exhibited opposing seasonal fluctuations. A thorough mass balance analysis revealed quinolone and sulfonamide antibiotics were primarily eliminated through degradation and transformation in the BBR process. Conversely, 40.2 g/d of macrolide antibiotics was released to the natural aquatic environment via effluent discharge. Gastric acid and anticoagulants, as well as cardiovascular PhCs, primarily experienced removal through sludge adsorption. This study provides valuable insights into the intricate dynamics of PhCs in wastewater treatment, emphasizing the need for tailored strategies to effectively mitigate their release and potential environmental risks.

Comprehensive genomic analysis of the SARS-CoV-2 Omicron variant BA.2.76 in Jining City, China, 2022.

OBJECTIVE: This study aims to analyze the molecular characteristics of the novel coronavirus (SARS-CoV-2) Omicron variant BA.2.76 in Jining City, China. METHODS: Whole-genome sequencing was performed on 87 cases of SARS-CoV-2 infection. Evolutionary trees were constructed using bioinformatics software to analyze sequence homology, variant sites, N-glycosylation sites, and phosphorylation sites. RESULTS: All 87 SARS-CoV-2 whole-genome sequences were classified under the evolutionary branch of the Omicron variant BA.2.76. Their similarity to the reference strain Wuhan-Hu-1 ranged from 99.72 to 99.74%. In comparison to the reference strain Wuhan-Hu-1, the 87 sequences exhibited 77-84 nucleotide differences and 27 nucleotide deletions. A total of 69 amino acid variant sites, 9 amino acid deletions, and 1 stop codon mutation were identified across 18 proteins. Among them, the spike (S) protein exhibited the highest number of variant sites, and the ORF8 protein showed a Q27 stop mutation. Multiple proteins displayed variations in glycosylation and phosphorylation sites. CONCLUSION: SARS-CoV-2 continues to evolve, giving rise to new strains with enhanced transmission, stronger immune evasion capabilities, and reduced pathogenicity. The application of high-throughput sequencing technologies in the epidemic prevention and control of COVID-19 provides crucial insights into the evolutionary and variant characteristics of the virus at the genomic level, thereby holding significant implications for the prevention and control of the COVID-19 pandemic.

Best Practices for Experiments and Reports in Photocatalytic Methane Conversion.

Efficiently converting methane into valuable chemicals via photocatalysis under mild condition represents a sustainable route to energy storage and value-added manufacture. Despite continued interest in this area, the achievements have been overshadowed by the absence of standardized protocols for conducting photocatalytic methane oxidation experiments as well as evaluating the corresponding performance. In this review, we present a structured solution aimed at addressing these challenges. Firstly, we introduce the norms underlying reactor design and outline various configurations in the gas-solid and gas-solid-liquid reaction systems. This discussion helps choosing the suitable reactors for methane conversion experiments. Subsequently, we offer a comprehensive step-by-step protocol applicable to diverse methane-conversion reactions. Emphasizing meticulous verification and accurate quantification of the products, this protocol highlights the significance of mitigating contamination sources and selecting appropriate detection methods. Lastly, we propose the standardized performance metrics crucial for evaluating photocatalytic methane conversion. By defining these metrics, the community could obtain the consensus of assessing the performance across different studies. Moving forward, the future of photocatalytic methane conversion necessitates further refinement of stringent experimental standards and evaluation criteria. Moreover, development of scalable reactor is essential to facilitate the transition from laboratory proof-of-concept to potentially industrial production.

Machine Learning Radiomics-Based Prediction of Non-sentinel Lymph Node Metastasis in Chinese Breast Cancer Patients with 1-2 Positive Sentinel Lymph Nodes: A Multicenter Study.

RATIONALE AND OBJECTIVES: This study aimed to construct a machine learning radiomics-based model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) images to evaluate non-sentinel lymph node (NSLN) metastasis in Chinese breast cancer (BC) patients who underwent total mastectomy (TM) and had 1-2 positive sentinel lymph nodes (SLNs). MATERIALS AND METHODS: In total, 494 patients were retrospectively enrolled from two hospitals, and were divided into the training (n = 286), internal validation (n = 122), and external validation (n = 86) cohorts. Features were extracted from DCE-MRI images for each patient and screened. Six ML classifies were trained and the best classifier was evaluated to calculate radiomics (Rad)-scores. A combined model was developed based on Rad-scores and clinical risk factors, then the calibration, discrimination, reclassification, and clinical usefulness were evaluated. RESULTS: 14 radiomics features were ultimately selected. The random forest (RF) classifier showed the best performance, with the highest average area under the curve (AUC) of 0.833 in the validation cohorts. The combined model incorporating RF-based Rad-scores, tumor size, lymphovascular invasion, and proportion of positive SLNs resulted in the best discrimination ability, with AUCs of 0.903, 0.890, and 0.836 in the training, internal validation, and external validation cohorts, respectively. Furthermore, the combined model significantly improved the classification accuracy and clinical benefit for NSLN metastasis prediction. CONCLUSION: A RF-based combined model using DCE-MRI images exhibited a promising performance for predicting NSLN metastasis in Chinese BC patients who underwent TM and had 1-2 positive SLNs, thereby aiding in individualized clinical treatment decisions.

Comparative genomics analysis reveals sequence characteristics potentially related to host preference in Cryptosporidium xiaoi.

Cryptosporidium spp. are important diarrhea-associated pathogens in humans and livestock. Among the known species, Cryptosporidium xiaoi, which causes cryptosporidiosis in sheep and goats, was previously recognized as a genotype of the bovine-specific Cryptosporidium bovis based on their high sequence identity in the ssrRNA gene. However, the lack of genomic data has limited characterization of the genetic differences between the two closely related species. In this study, we sequenced the genomes of two C. xiaoi isolates and performed comparative genomic analysis to identify the sequence uniqueness of this ovine-adapted species compared with other Cryptosporidium spp. Our results showed that C. xiaoi is genetically related to C. bovis as shown by their 95.8% genomic identity and similar gene content. Consistent with this, both C. xiaoi and C. bovis appear to have fewer genes encoding mitochondrial metabolic enzymes and invasion-related protein families. However, they appear to possess several species-specific genes. Further analysis indicates that the sequence differences between these two Cryptosporidium spp. are mainly in 24 highly polymorphic genes, half of which are located in the subtelomeric regions. Some of these subtelomeric genes encode secretory proteins that have undergone positive selection. In addition, the genomes of two C. xiaoi isolates, identified as subtypes XXIIIf and XXIIIh, share 99.9% nucleotide sequence identity, with six highly divergent genes encoding putative secretory proteins. Therefore, these species-specific genes and sequence polymorphism in subtelomeric genes probably contribute to the different host preference of C. xiaoi and C. bovis.

Amlodipine inhibits the proliferation and migration of esophageal carcinoma cells through the induction of endoplasmic reticulum stress.

BACKGROUND: L-type calcium channels are the only protein channels sensitive to calcium channel blockers, and are expressed in various cancer types. The Cancer Genome Atlas database shows that the mRNA levels of multiple L-type calcium channel subunits in esophageal squamous cell carcinoma tumor tissue are significantly higher than those in normal esophageal epithelial tissue. Therefore, we hypothesized that amlodipine, a long-acting dihydropyridine L-type calcium channel blocker, may inhibit the occurrence and development of esophageal cancer (EC). AIM: To investigate the inhibitory effects of amlodipine on EC through endoplasmic reticulum (ER) stress. METHODS: Cav1.3 protein expression levels in 50 pairs of EC tissues and corresponding paracancerous tissues were examined. Subsequently, the inhibitory effects of amlodipine on proliferation and migration of EC cells in vitro were detected using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide and Transwell assays. In vivo experiments were performed using murine xenograft model. To elucidate the underlying mechanisms, in vitro cell studies were performed to confirm that ER stress plays a role in inhibition proliferation and migration of EC cells treated with amlodipine. RESULTS: The expression level of Cav1.3 in esophageal carcinoma was 1.6 times higher than that in paracancerous tissues. Amlodipine treatment decreased the viability of esophageal carcinoma cells in a dose- and time-dependent manner. In vivo animal experiments also clearly indicated that amlodipine inhibited the growth of EC tumors in mice. Additionally, amlodipine reduces the migration of tumor cells by inhibiting epithelial-mesenchymal transition (EMT). Mechanistic studies have demonstrated that amlodipine induces ER stress-mediated apoptosis and suppresses EMT. Moreover, amlodipine-induced autophagy was characterized by an increase in autophagy lysosomes and the accumulation of light chain 3B protein. The combination of amlodipine with the ER stress inhibitor 4-phenylbutyric acid further confirmed the role of the ER stress response in amlodipine-induced apoptosis, EMT, and autophagy. Furthermore, blocking autophagy increases the ratio of apoptosis and migration. CONCLUSION: Collectively, we demonstrate for the first time that amlodipine promotes apoptosis, induces autophagy, and inhibits migration through ER stress, thereby exerting anti-tumor effects in EC.

Anji white tea relaxes precontracted arteries, represses voltage-gated Ca2+ channels and voltage-gated K+ channels in the arterial smooth muscle cells: Comparison with green tea main component (-)-epigallocatechin gallate.

ETHNOPHARMACOLOGICAL RELEVANCE: Tea (Camellia sinensis) is a favorite drink worldwide. Tea extracts and green tea main component (-)-epigallocatechin gallate (EGCG) are recommended for various vascular diseases. Anji white tea is a very popular green tea. Its vascular effect profile, the mechanisms, and the contribution of EGCG to its integrated effect need elucidation. AIM: To characterize the vasomotion effects of Anji white tea and EGCG, and to explore possible involvement of voltage-gated Ca2+ channels (VGCCs) and voltage-gated K+ (Kv) channels in their vasomotion effects. MATERIALS AND METHODS: Anji white tea water soaking solution (AJWT) was prepared as daily tea-making process and concentrated to a concentration amounting to 200 mg/ml of dry tea leaves. The tension of rat arteries including aorta, coronary artery (RCA), cerebral basilar artery (CBA), intrarenal artery (IRA), intrapulmonary artery (IPA) and mesenteric artery (MA) was recorded with myographs. In arterial smooth muscle cells (ASMCs) freshly isolated from RCA, the levels of intracellular Ca2+ were measured with Ca2+-sensitive fluorescent probe fluo 4-AM, and Kv currents were recorded with patch clamp. The expressions of VGCCs and Kv channels were assayed with RT-qPCR and immunofluorescence staining. RESULTS: At 0.4-12.8 mg/ml of dry tea leaves, AJWT profoundly relaxed all tested arteries precontracted with various vasoconstrictors about half with a small transient potentiation on the precontractions before the relaxation. KCl-induced precontraction was less sensitive than precontractions induced by phenylephrine (PE), U46619 and serotonin (5-HT). IPA was less sensitive to the relaxation compared with other arteries. AJWT pretreatment for 1 h, 24 h and 72 h time-dependently inhibited the contractile responses of RCAs. In sharp contrast, at equivalent concentrations according to its content in AJWT, EGCG intensified the precontractions in most small arteries, except that it induced relaxation in PE-precontracted aorta and MA, U46619-precontracted aorta and CBA. EGCG pretreatment for 1 h and 24 h did not significantly affect RCA contractile responses. In RCA ASMCs, AJWT reduced, while EGCG enhanced, intracellular Ca2+ elevation induced by depolarization which activates VGCCs. Patch clamp study showed that both AJWT and EGCG reduced Kv currents. RT-qPCR and immunofluorescence staining demonstrated that both AJWT and EGCG reduced the expressions of VGCCs and Kv channels. CONCLUSION: AJWT, but not EGCG, consistently induces vasorelaxation. The vasomotion effects of either AJWT or EGCG vary with arterial beds and vasoconstrictors. Modulation of VGCCs, but not Kv channels, contributes to AJWT-induced vasorelaxation. It is suggested that Anji white tea water extract instead of EGCG may be a promising food supplement for vasospastic diseases.

Time-Series Transcriptome of Cucumis melo Reveals Extensive Transcriptomic Differences with Different Maturity.

As the most important melon cultivar grown in the north-western provinces of China, Hami melon (Cucumis melo) produces large edible fruits that serve as an important dietary component in the world. In general, as a climacteric plant, melon harvested at 60% maturity results in a product with bad quality, while the highest-quality product can be guaranteed when harvesting at 90% maturity. In order to clarify the genetic basis of their distinct profiles of metabolite accumulation, we performed systematic transcriptome analyses between 60% and 90% maturity melons. A total of 36 samples were sequenced and over 1.7 billion reads were generated. Differentially expressed genes in 60% and 90% maturity melons were detected. Hundreds of these genes were functionally enriched in the sucrose and citric acid accumulation process of C. melo. We also detected a number of distinct splicing events between 60% and 90% maturity melons. Many genes associated with sucrose and citric acid accumulation displayed as differentially expressed or differentially spliced between different degrees of maturity of Hami melons, including CmCIN2, CmSPS2, CmBGAL3, and CmSPS2. These results demonstrate that the phenotype pattern differences between 60% and 90% maturity melons may be largely resulted from the significant transcriptome regulation.

The mediating role of academic support perception in the relationship between emotional intelligence and bullying behaviours in clinical practice: A cross-sectional study.

BACKGROUND: Bullying behaviours experienced by nursing interns in clinical practice are a considerable and serious concern. Understanding the factors that influence such behaviours in clinical practice is crucial for developing effective preventive measures and fostering a supportive learning environment. PURPOSE: This study aims to investigate the prevalence and influencing factors of bullying behaviours experienced by nursing interns and examine the mediating role of academic support perception in the relationship between emotional intelligence and bullying behaviours in clinical practice. METHODS: This is a cross-sectional study that used convenience sampling. A socio-demographic information questionnaire, Bullying Behaviours in Nursing Education Scale, Wong and Law's Emotional Intelligence Scale, and Academic Support in the Practicum Scale were used to collect data from nursing interns (n = 813) at seven tertiary hospitals in Changsha, China. Binary logistic regression and mediating analyses were used to explore the factors influencing bullying behaviours in nursing practice and examine the potential mediating role of academic support perception. RESULTS: The prevalence of bullying behaviours in clinical practice among 813 nursing interns was 82.7 %. Binary logistic regression analyses indicated that attitude toward the nursing profession, emotional intelligence, and academic support perception were significantly associated with bullying behaviours in clinical practice. Academic support perception (ß = 0.375, p < 0.001) played a significant mediating role in the relationship between emotional intelligence and bullying behaviours in clinical practice, accounting for 55.7 % of the total effect. CONCLUSION: Nursing educators and administrators should recognise that improving emotional intelligence and enhancing academic support perception among nursing interns can reduce the occurrence of bullying behaviours in clinical practice.