Factors associated with work engagement among specialist nurses in china: a cross-sectional study.

BACKGROUND: The positive impacts of work engagement among specialist nurses on retention, organizational commitment, and quality of care are well-documented. However, there is a lack of research on the specific differences in work engagement among specialist nurses. Therefore, the purpose of this study is to assess the level of work engagement among specialist nurses in China and identify its influencing factors. METHODS: A descriptive cross-sectional study was conducted in China from April to July, 2023, with 724 nurses selected from 22 hospitals through convenience sampling involved. The survey was conducted by using self-administered general information questionnaires and work engagement scales. Questionnaire Star was employed as the online data collection tool. The collected data was analyzed by using descriptive statistics and stepwise regression analysis to draw meaningful conclusions from the study. RESULTS: Among specialist nurses in Xiamen, China, who had a response rate of 97.10%, an average work engagement score is 140.35 (SD=18.17), with the highest score for the work attitude at 4.65 (SD=0.52) and the lowest score for the work recognition at 4.09 (SD=0.85). It was shown through regression analysis that factors such as career satisfaction, involvement in challenging case discussions, marital status, gender, presence of promotion advantage and title accounted for 14.5% of the total variance in the model and were significant explanatory variables that could predict work engagement. CONCLUSION: It is shown that specialist nurses in Xiamen, China have a high level of work engagement. It is imperative for nursing managers to prioritize the work engagement of specialist nurses, provide the specialist nurses with ample development opportunities and room for growth, and effectively promote the overall development of specialist nurses by improving work engagement in various aspects.

[Determination of cyclohexanone concentration in the plasma separator by gas chromatography].

This essay is to determine the cyclohexanone concentration of the plasma separator. The compound was introduced into the GC analytical system by the carrier gas. The determination was performed by the measurement of their peak area and by the external standard method.

Identifying hQC Inhibitors of Alzheimer's Disease by Effective Customized Pharmacophore-Based Virtual Screening, Molecular Dynamic Simulation, and Binding Free Energy Analysis.

Human glutaminyl cyclase (hQC) appeared as a promising new target with its inhibitors attracted much attention for the treatment of Alzheimer's disease (AD) in recent years. But so far, only a few compounds have been reported as hQC inhibitors. To find novel and potent hQC inhibitors, a high-specificity ZBG (zinc-binding groups)-based pharmacophore model comprising customized ZBG feature was first generated using HipHop algorithm in Discovery Studio software for screening out hQC inhibitors from the SPECS database. After purification by docking studies and drug-like ADMET properties filters, four potential hit compounds were retrieved. Subsequently, these hit compounds were subjected to 30-ns molecular dynamic (MD) simulations to explore their binding modes at the active side of hQC. MD simulations demonstrated that these hit compounds formed a chelating interaction with the zinc ion, which was consistent with the finding that the electrostatic interaction was the major driving force for binding to hQC confirmed with MMPBSA energy decomposition. Higher binding affinities of these compounds were also verified by the binding free energy calculations comparing with the references. Thus, these identified compounds might be potential hQC candidates and could be used for further investigation.

Mechanical segregation and capturing of clonal circulating plasma cells in multiple myeloma using micropillar-integrated microfluidic device.

Multiple myeloma (MM), the disorder of plasma cells, is the second most common type of hematological cancer and is responsible for approximately 20% of deaths from hematological malignancies. The current gold standard for MM diagnosis includes invasive bone marrow aspiration. However, it lacks the sensitivity to detect minimal residual disease, and the nonuniform distribution of clonal plasma cells (CPCs) within bone marrow also often results in inaccurate reporting. Serum and urine assessment of monoclonal proteins, such as Kappa light chains, is another commonly used approach for MM diagnosis. Although it is noninvasive, the level of paraprotein elevation is still too low for detecting minimal residual disease and nonsecretive MM. Circulating CPCs (cCPCs) have been reported to be present in the peripheral blood of MM patients, and high levels of cCPCs were shown to correlate with poor survival. This suggests a potential noninvasive approach for MM disease progress monitoring and prognosis. In this study, we developed a mechanical property-based microfluidic platform to capture cCPCs. Using human myeloma cancer cell lines spiked in healthy donor blood, the microfluidic platform demonstrates high enrichment ratio (>500) and sufficient capture efficiency (40%-55%). Patient samples were also assessed to investigate the diagnostic potential of cCPCs for MM by correlating with the levels of Kappa light chains in patients.

Investigating the binding mechanism of novel 6-aminonicotinate-based antagonists with P2Y12 by 3D-QSAR, docking and molecular dynamics simulations.

P2Y12 receptor is an attractive target for the anti-platelet therapies, treating various thrombotic diseases. In this work, a total of 107 6-aminonicotinate-based compounds as potent P2Y12 antagonists were studies by a molecular modeling study combining three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking and molecular dynamics (MD) simulations to explore the decisive binding conformations of these antagonists with P2Y12 and the structural features for the activity. The optimum CoMFA and CoMSIA models identified satisfactory robustness and good predictive ability, with R2 = .983, q2 = .805, [Formula: see text] = .881 for CoMFA model, and R2 = .935, q2 = .762, [Formula: see text] = .690 for CoMSIA model, respectively. The probable binding modes of compounds and key amino acid residues were revealed by molecular docking. MD simulations and MM/GBSA free energy calculations were further performed to validate the rationality of docking results and to compare the binding modes of several compound pairs with different activities, and the key residues (Val102, Tyr105, Tyr109, His187, Val190, Asn191, Phe252, His253, Arg256, Tyr259, Thr260, Val279, and Lys280) for the higher activity were pointed out. The binding energy decomposition indicated that the hydrophobic and hydrogen bond interactions play important roles for the binding of compounds to P2Y12. We hope these results could be helpful in design of potent and selective P2Y12 antagonists.