Rates of colorectal cancer diagnosis and mortality in people with severe mental illness: results from Australia's National Bowel Cancer Screening Programme.

Aims: Studies show that people with severe mental illness (SMI) have a greater risk of dying from colorectal cancer (CRC). These studies mostly predate the introduction of national bowel cancer screening programmes (NBCSPs) and it is unknown if these have reduced disparity in CRC-related mortality for people with SMI.

Methods: We compared mortality rates following CRC diagnosis at colonoscopy between a nationally representative sample of people with and without SMI who participated in Australia's NBCSP.

Manipulating button mushroom casing affects the disease dynamics of blotch and green mold disease.

Productive cultivation of the button mushroom (Agaricus bisporus) relies on the use of selective substrates and effective disease management. In extending our previous work on manipulating the developmental microbiome (devome), this study employs the strategy of substrate passaging to explore its effects on crop outcomes and disease dynamics. Here we subjected the casing substrate to ten cycles of passaging.

Targeting the PREX2/RAC1/PI3Kβ Signaling Axis Confers Sensitivity to Clinically Relevant Therapeutic Approaches in Melanoma.

Metastatic melanoma remains a major clinical challenge. Large-scale genomic sequencing of melanoma has identified bona fide activating mutations in RAC1, which are associated with resistance to BRAF-targeting therapies. Targeting the RAC1-GTPase pathway, including the upstream activator PREX2 and the downstream effector PI3Kβ, could be a potential strategy for overcoming therapeutic resistance, limiting melanoma recurrence, and suppressing metastatic progression.

Dual gene set enrichment analysis (dualGSEA); an R function that enables more robust biological discovery and pre-clinical model alignment from transcriptomics data.

Gene set enrichment analysis (GSEA) tools can identify biological insights within gene expression-based studies. Although their statistical performance has been compared, the downstream biological implications that arise when choosing between the range of pairwise or single sample forms of GSEA methods remain understudied. We compare the statistical and biological results obtained from various pre-ranking methods/options for pairwise GSEA, followed by a stand-alone comparison of GSEA, single sample GSEA (ssGSEA) and gene set variation analysis (GSVA).