Citations

AbstractBackgroundSleep’s crucial role in maintaining brain health is increasingly recognized, particularly due to the rising prevalence of neurodegenerative diseases. It not only supports cognitive function but also aids in clearing brain metabolic waste through cerebrospinal fluid (CSF) dynamics. During sleep, especially in the non‐rapid eye movement (NREM) phase, CSF flow increases, essential for removing neurotoxic substances like amyloid‐beta proteins. This study explores the link between sleep respiratory patterns and CSF flow promotion.MethodElectroencephalography (EEG), and functional magnetic resonance imaging (fMRI) were simultaneously acquired during sleep from Gu, et al. (n = 29) (Gu et al. 2022). Respiration, measured via a respiratory belt, calculated respiratory volume (RV) as the standard deviation within a 5 second sliding window. EEG data processed delta band power (1‐4Hz) averaged across channels. Parcellated fMRI data using the brain template followed by the calculation of the averaged gray matter (GM) blood‐oxygen‐level‐dependent (BOLD) signal using the GM mask. CSF inflow was manually extracted from the fMRI’s bottom slice at the foramen magnum level. Subsequently, all signals were temporally aligned to the peak of the CSF inflow signal.ResultAt the time of CSF inflow (time = 0 sec. in the Figure 1A‐D), we observed an earlier increase in RV and EEG delta power, followed by changes in the GM BOLD signal (Figure 1). EEG and RV changes preceded the BOLD signal changes, which, in turn, preceded changes in CSF flow. Sensitivity to detect RV involvement during MRI varied with the placement of the respiratory belt, being least sensitive on the chest and more on the abdomen.ConclusionThese findings raise an interesting question on the role respiratory patterns during sleep, particularly in the NREM phase. Speculatively, RV change may influence CSF circulation during NREM sleep (Figure 1E). This enhancement in CSF flow is crucial for the clearance of metabolic waste from the brain, potentially reducing the risk of neurodegenerative diseases. Our findings indicate that respiratory volume may serve as a significant marker for CSF circulation during sleep.

Women with type 2 diabetes (T2D) have a higher risk of being diagnosed with breast cancer and have worse survival than non-diabetic women if they do develop breast cancer. However, more research is needed to elucidate the biological underpinnings of these relationships. Here, we found that forkhead box A1 (FOXA1), a forkhead family transcription factor, and metformin (1,1-dimethylbiguanide hydrochloride), a medication used to treat T2D, may impact hormone-receptor-positive (HR+) breast cancer (BC) tumor cell growth and metastasis. Indeed, fourteen diabetes-associated genes are highly expressed in only three HR+ breast cancer cell lines but not the other subtypes utilizing a 53,805 gene database obtained from NCBI GEO. Among the diabetes-related genes, FOXA1, MTA3, PAK4, FGFR3, and KIF22 were highly expressed in HR+ breast cancer from 4032 breast cancer patient tissue samples using the Breast Cancer Gene Expression Omnibus. Notably, elevated FOXA1 expression correlated with poorer overall survival in patients with estrogen-receptor-positive/progesterone-receptor-positive (ER+/PR+) breast cancer. Furthermore, experiments demonstrated that loss of the FOXA1 gene inhibited tumor proliferation and invasion in vitro using MCF-7 and T47D HR+ breast cancer cell lines. Metformin, an anti-diabetic medication, significantly suppressed tumor cell growth in MCF-7 cells. Additionally, either metformin treatment or FOXA1 gene deletion enhanced tamoxifen-induced tumor growth inhibition in HR+ breast cancer cell lines within an ex vivo three-dimensional (3D) organoid model. Therefore, the diabetes-related medicine metformin and FOXA1 gene inhibition might be a new treatment for patients with HR+ breast cancer when combined with tamoxifen, an endocrine therapy.