FOXM1, a proto-oncogenic transcription factor, plays a critical role in cancer development and treatment resistance in cancers, particularly in breast cancer. Thus, this study aimed to identify potential FOXM1 inhibitors through computational screening of drug databases, followed by in vitro validation of their inhibitory activity against breast cancer cells. In silico studies involved pharmacophore modeling using the FOXM1 inhibitor, FDI-6, followed by virtual screening of DrugBank and Selleckchem databases. The selected drugs were prepared for molecular docking, and the crystal structure of FOXM1 was pre-processed for docking simulations. In vitro studies included MTT assays to assess cytotoxicity, and Western blot analysis to evaluate protein expression levels. Our study identified Pantoprazole and Rabeprazole as potential FOXM1 inhibitors through in silico screening and molecular docking. Molecular dynamics simulations confirmed stable interactions of these drugs with FOXM1. In vitro experiments showed both Pantoprazole and Rabeprazole exhibited strong FOXM1 inhibition at effective concentrations and that showed inhibition of cell proliferation. Rabeprazole showed the inhibitor activity at 10 µM in BT-20 and MCF-7 cell lines. Pantoprazole exhibited FOXM1 inhibition at 30 µM and in BT-20 cells and at 70 µM in MCF-7 cells, respectively. Our current study provides the first evidence that Rabeprazole and Pantoprazole can bind to FOXM1 and inhibit its activity and downstream signaling, including eEF2K and pEF2, in breast cancer cells. These findings indicate that rabeprazole and pantoprazole inhibit FOXM1 and breast cancer cell proliferation, and they can be used for FOXM1-targeted therapy in breast or other cancers driven by FOXM1.

To evaluate the effects of a best practice advisory (BPA) and a change in the Clostridioides (Clostridium) difficile testing algorithm on nosocomial C. difficile infection (CDI) rates.
This was a retrospective analysis at a tertiary care hospital of adult patients who tested positive for CDI between July 1, 2017 and September 30, 2019. In June 2018, we implemented a BPA in our electronic health record recommending against testing for CDI in patients receiving laxatives. We reviewed the number of C. difficile tests ordered before and after initiating the BPA. In December 2018, we replaced nucleic acid amplification testing (NAAT) with a cell cytotoxicity assay (CCA) for stool specimens that were enzyme immunoassay toxin negative and glutamate dehydrogenase positive.
The number of C. difficile tests ordered per month decreased 14% after implementing the BPA (P = .0001). Following this intervention, the rate of nosocomial CDI (nCDI) decreased by 16.5% (P = .33). Following substitution of CCA for NAAT for enzyme immunoassay toxin-/glutamate dehydrogenase+ specimens, there was a 50% reduction in the rate of nCDI (7.1 cases/10,000 patient days to 3.5 cases/10,000 patient days; P < .0001).
Implementing a BPA to reduce inappropriate testing and changing the testing algorithm for C. difficile by substituting CCA for NAAT resulted in a lower rate of diagnosis of nCDI.

BACKGROUND: Several Clostridium difficile infection (CDI) surveillance programs do not specify laboratory strategies to use. We investigated the evolution in testing strategies used across Quebec, Canada, and its association with incidence rates.
METHODS: Cross-sectional study of 95 hospitals by surveys conducted in 2010 and in 2013-2014. The association between testing strategies and institutional CDI incidence rates was analyzed via multivariate Poisson regressions.
RESULTS: The most common assays in 2014 were toxin A/B enzyme immunoassays (EIAs) (61 institutions, 64%), glutamate dehydrogenase (GDH) EIAs (51 institutions, 53.7%), and nucleic acid amplification tests (NAATs) (34 institutions, 35.8%). The most frequent algorithm was a single-step NAAT (20 institutions, 21%). Between 2010 and 2014, 35 institutions (37%) modified their algorithm. Institutions detecting toxigenic C difficile instead of C difficile toxin increased from 14 to 37 (P < .001). Institutions detecting toxigenic C difficile had higher CDI rates (7.9 vs 6.6 per 10,000 patient days; P = .01). Institutions using single-step NAATs, GDH plus toxigenic cultures, and GDH plus cytotoxicity assays had higher CDI rates than those using an EIA-based algorithm (P < .05).
CONCLUSIONS: Laboratory detection of CDI has changed since 2010. There is an association between diagnostic algorithms and CDI incidence. Mitigation strategies are warranted.

Clostridium difficile infection (CDI) is the leading cause of hospital-acquired diarrhea and is associated with a considerable health and cost burden. However, there is still not a clear consensus on the best laboratory diagnosis approach and a wide variation of testing methods and strategies can be encountered.
We aim to review the most practical aspects of CDI diagnosis providing our own view on how to optimize CDI diagnosis. Expert commentary: Laboratory diagnosis in search of C. difficile toxins should be applied to all fecal diarrheic samples reaching the microbiology laboratory in patients > 2 years old, with or without classic risk factors for CDI. Detection of toxins either directly in the fecal sample or in the bacteria isolated in culture confirm CDI in the proper clinical setting. Nuclear Acid Assay techniques (NAAT) allow to speed up the process with epidemiological and therapeutic consequences.