Antagonists to TRPV1, ASICs and P2X have a potential role to prevent the triggering of regional bone metabolic disorder and pain-like behavior in tail-suspended mice

尾部懸垂マウスにおける局所性骨代謝障害においてTRPV1・ASICs・P2X拮抗薬は疼痛行動の抑制と骨代謝マーカー発現増強の抑制を示した．これらの拮抗薬は疼痛の誘発と骨粗鬆化に対する予防効果を有する可能性がある

Close association of water channel AQP1 with amyloid-β deposition in Alzheimer disease brains

Aquaporin-1 (AQP1), a membrane water channel protein, is expressed exclusively in the choroid plexus epithelium in the central nervous system under physiological conditions. However, AQP1 expression is enhanced in reactive astrocytes, accumulating in brain lesions of Creutzfeldt-Jakob disease and multiple sclerosis, suggesting a role of AQP1-expressing astrocytes in brain water homeostasis under pathological conditions. To clarify a pathological implication of AQP1 in Alzheimer disease (AD), we investigated the possible relationship between amyloid-beta (Aβ) deposition and astrocytic AQP1 expression in the motor cortex and hippocampus of 11 AD patients and 16 age-matched other neurological disease cases. In all cases, AQP1 was expressed exclusively in a subpopulation of multipolar fibrillary astrocytes. The great majority of AQP1-expressing astrocytes were located either on the top of or in close proximity to Aβ plaques in AD brains but not in non-AD cases, whereas those independent of Aβ deposition were found predominantly in non-AD brains. By Western blot, cultured human astrocytes constitutively expressed AQP1, and the levels of AQP1 protein expression were not affected by exposure to Aβ1-42 peptide, but were elevated by hypertonic sodium chloride. By immunoprecipitation, the C-terminal fragment-beta (CTFβ) of amyloid precursor protein interacted with the N-terminal half of AQP1 spanning the transmembrane helices H1, H2 and H3. These observations suggest the possible association of astrocytic AQP1 with Aβ deposition in AD brains

Fat-distribution patterns and future type-2 diabetes.

Fat accumulation in the liver, pancreas, skeletal muscle, and visceral bed relates to type-2 diabetes (T2D). However, the distribution of fat among these compartments is heterogenous and it is unclear whether specific distribution patterns indicate high T2D risk. We therefore investigated fat-distribution patterns and their link to future T2D. From 2168 individuals without diabetes who underwent computed tomography in Japan, this case-cohort study included 658 randomly selected individuals and 146 incident cases of T2D over 6 years of follow-up. Using data-driven analysis (k-means) based on fat content in the liver, pancreas, muscle, and visceral bed, we identified four fat-distribution clusters: Hepatic steatosis, Pancreatic steatosis, Trunk myosteatosis, and Steatopenia. Compared with the Steatopenia cluster, the adjusted hazard ratios (95% CIs) for incident T2D were 4.02 (2.27-7.12) for the Hepatic steatosis cluster, 3.38 (1.65-6.91) for the Pancreatic steatosis cluster, and 1.95 (1.07-3.54) for the Trunk myosteatosis cluster. The clusters were replicated in 319 German individuals without diabetes who underwent magnetic resonance imaging and metabolic phenotyping. The distribution of AUC-glucose across the four clusters found in Germany was similar to the distribution of T2D risk across the four clusters in Japan. Insulin sensitivity and insulin secretion differed across the four clusters. Thus, we identified patterns of fat distribution with different T2D risks presumably due to differences in insulin sensitivity and insulin secretion