High G9a Expression in DLBCL and Its Inhibition by Niclosamide to Induce Autophagy as a Therapeutic Approach.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is a malignant lymphoid tumor disease that is characterized by heterogeneity, but current treatment does not benefit all patients, which highlights the need to identify oncogenic genes and appropriate drugs. G9a is a histone methyltransferase that catalyzes histone H3 lysine 9 (H3K9) methylation to regulate gene function and expression in various cancers. METHODS: TCGA and GTEx data were analyzed using the GEPIA2 platform. Cell viability under drug treatment was assessed using Alamar Blue reagent; the interaction between G9a and niclosamide was assessed using molecular docking analysis; mRNA and protein expression were quantified in DLBCL cell lines. Finally, G9a expression was quantified in 39 DLBCL patient samples. RESULTS: The TCGA database analysis revealed higher G9a mRNA expression in DLBCL compared to normal tissues. Niclosamide inhibited DLBCL cell line proliferation in a time- and dose-dependent manner, reducing G9a expression and increasing p62, BECN1, and LC3 gene expression by autophagy pathway regulation. There was a correlation between G9a expression in DLBCL samples and clinical data, showing that advanced cancer stages exhibited a higher proportion of G9a-expressing cells. CONCLUSION: G9a overexpression is associated with tumor progression in DLBCL. Niclosamide effectively inhibits DLBCL growth by reducing G9a expression via the cellular autophagy pathway; therefore, G9a is a potential molecular target for the development of therapeutic strategies for DLBCL.

Design and evaluation of the bed-cleaning mobile application.

AIM: To develop a mobile application (App) that enhances bed-cleaning management. BACKGROUND: Bed cleaning affects clinical work in hospitals. The nursing department needed an App to enhance bed-cleaning management, especially one on the status of all beds to be cleaned. METHODS: Bed-Cleaning App (BedCApp) was developed. Then, a survey was administered to 50 BedCApp users. RESULTS: BedCApp helped the administrative staff and nurse managers in adjusting their workload effectively. A complete presentation of beds to be cleaned and reminders were found to be the most satisfactory features. The average time from receiving the notice to completing bed cleaning was shortened by 25.5 min. The user satisfaction survey comprised 50 valid questionnaires, with a satisfaction rate of 3.6/5. CONCLUSION: BedCApp provides the actual workload status; therefore, the administrative staff and nurse managers can optimize the workload during rush hours. The software is user-oriented, with good user acceptance. IMPLICATIONS FOR NURSING MANAGEMENT: Proactive workload management would improve outcomes during rush hours and avoid interference in clinical care. The user interfaces for the elderly staff has special design-simple to use, larger font size than that in the interface for non-elderly staff and workflow reminders.