Outer Membrane Vesicles Released from Garlic Exosome-like Nanoparticles (GaELNs) Train Gut Bacteria that Reverses Type 2 Diabetes via the Gut-Brain Axis.

Gut microbiota function has numerous effects on humans and the diet humans consume has emerged as a pivotal determinant of gut microbiota function. Here, a new concept that gut microbiota can be trained by diet-derived exosome-like nanoparticles (ELNs) to release healthy outer membrane vesicles (OMVs) is introduced. Specifically, OMVs released from garlic ELN (GaELNs) trained human gut Akkermansia muciniphila (A. muciniphila) can reverse high-fat diet-induced type 2 diabetes (T2DM) in mice. Oral administration of OMVs released from GaELNs trained A. muciniphila can traffick to the brain where they are taken up by microglial cells, resulting in inhibition of high-fat diet-induced brain inflammation. GaELNs treatment increases the levels of OMV Amuc-1100, P9, and phosphatidylcholines. Increasing the levels of Amuc-1100 and P9 leads to increasing the GLP-1 plasma level. Increasing the levels of phosphatidylcholines is required for inhibition of cGas and STING-mediated inflammation and GLP-1R crosstalk with the insulin pathway that leads to increasing expression of Insulin Receptor Substrate (IRS1 and IRS2) on OMV targeted cells. These findings reveal a molecular mechanism whereby OMVs from plant nanoparticle-trained gut bacteria regulate genes expressed in the brain, and have implications for the treatment of brain dysfunction caused by a metabolic syndrome.

The impact of changes in radiographic sarcopenia on overall survival in older adults undergoing different treatment pathways for pancreatic cancer.

OBJECTIVE: Sarcopenia is associated with poor outcomes in patients undergoing surgery for pancreatic ductal adenocarcinoma (PDAC). However, few studies have assessed changes in sarcopenia during multimodality therapy or its effect on overall survival (OS). METHODS: Computed tomography (CT) total psoas area index (TPAI) and weighted average Hounsfield units (HU) were measured at each treatment interval in patients with resectable PDAC. Four cohorts were compared: 1. Neoadjuvant chemotherapy plus surgery plus adjuvant chemotherapy ("NSA"; n = 20); 2. surgery plus adjuvant chemotherapy ("SA"; n = 20); 3. neoadjuvant chemotherapy with intent to perform surgery ("Chemotherapy"; n = 24); and 4. treated with palliative intent ("Palliative"; n = 21). RESULTS: Fifty-nine deaths were identified. Median OS was 15.7 months (95% Confidence Interval (CI) 12.7-20.2). Patients who underwent surgery had a higher OS (p < 0.001), with the SA group having a longer OS than the NSA group. Cox regression models identified baseline TPAI (Hazard Ratio (HR) = 0.82; p = 0.04), but not psoas HU, as a significant predictor of OS. The mean decrease in TPAI following neoadjuvant chemotherapy was 0.6 cm2/m2 (p < 0.001; 95% CI -0.8--0.3) and the mean decrease in HU was 2.7 (p = 0.04, 95% CI -5.4--0.1). For patients who underwent surgery (NSA and SA cohorts), a decrease in TPAI was associated with worse OS (HR 0.52; p = 0.05). In contrast, decreased HU was associated with worse OS in patients who did not undergo surgery (HR 0.93; p = 0.01). CONCLUSIONS: In patients who received neoadjuvant chemotherapy, there was a significant decrease in TPAI and HU during treatment. Prospective studies are warranted to assess the impact of TPAI loss and HU changes on clinical outcomes to better individualize treatment pathways based on a patient's fitness.

Biomarkers for personalized medicine in GI cancers.

Gastrointestinal malignancies are a major health care challenge due to the high incidence and overall poor outcome. A biomarker is a molecular characteristic of a tumor that may be utilized in the initial risk assessment and the subsequent management of the patient. This review focuses on the most pertinent prognostic and predictive biomarkers used in the clinical management of gastric, pancreas, and colon cancer. The available assays, limitations and clinical use for each biomarker are reviewed. The clinical trials evaluating novel biomarkers in GI cancers are discussed.

Achieving a deeper understanding of the implemented provisions of the Affordable Care Act.

The Patient Protection and Affordable Care Act (ACA) was signed into law by President Barack Obama on March 23, 2010. Since that time, numerous regulations have been promulgated, legal battles continue to be fought and the major provisions of the law are being implemented. In the following article, we outline components of the ACA that are relevant to cancer health care, review current implementation of the new health care reform law, and identify challenges that may lie ahead in the post-ACA era. Specifically, among the things we explore are Medicaid expansion, health insurance exchanges, essential health benefits and preventive services, subsidies, access to clinical trials, the Medicare Part D donut hole, and physician quality payment reform.