Diabetes mellitus and Alzheimer's disease: Vacuolar adenosine triphosphatase as a potential link.

Globally, the incidence of diabetes mellitus (DM) and Alzheimer's disease (AD) is increasing year by year, causing a huge economic and social burden, and their pathogenesis and aetiology have been proven to have a certain correlation. In recent years, more and more studies have shown that vacuolar adenosine triphosphatases (v-ATPases) in eukaryotes, which are biomolecules regulating lysosomal acidification and glycolipid metabolism, play a key role in DM and AD. This article describes the role of v-ATPase in DM and AD, including its role in glycolysis, insulin secretion and insulin resistance (IR), as well as its relationship with lysosomal acidification, autophagy and ß-amyloid (Aß). In DM, v-ATPase is involved in the regulation of glucose metabolism and IR. v-ATPase is closely related to glycolysis. On the one hand, v-ATPase affects the rate of glycolysis by affecting the secretion of insulin and changing the activities of key glycolytic enzymes hexokinase (HK) and phosphofructokinase 1 (PFK-1). On the other hand, glucose is the main regulator of this enzyme, and the assembly and activity of v-ATPase depend on glucose, and glucose depletion will lead to its decomposition and inactivation. In addition, v-ATPase can also regulate free fatty acids, thereby improving IR. In AD, v-ATPase can not only improve the abnormal brain energy metabolism by affecting lysosomal acidification and autophagy but also change the deposition of Aß by affecting the production and degradation of Aß. Therefore, v-ATPase may be the bridge between DM and AD.

[Study on the low temperature drying of components of municipal solid waste and its model analysis].

The drying behaviors of four typical municipal solid waste (MSW) components (including waste paper, textile, pericarp and wood) were studied under low temperature. Effects of temperature on drying characteristic, thin layer drying models, effective moisture diffusion coefficient and activation energy were investigated in this paper. Experimental results showed that with increasing temperature, the drying rate increased, but the added value reduced gradually. Four mathematical models were used to simulate drying curves of MSW components. Modified Page model was found to give better predictions when moisture content was more than 25%. Based on the Fick's second law, the effective moisture diffusion coefficient for waste paper, textile, pericarp and wood were 8.24 x 10(-8)-23.67 x 10(-8), 7.73 x 10(-8)-12.56 x 10(-8), 3.57 x 10(-8)-14.18 x 10(-8) and 6.51 x 10(-8)-23.84 x 10(-8)m2 x s(-1). The activation energy determined through Arrhenius equation were 25.26, 10.75, 32.16 and 29.49 kJ x mol(-1), respectively. Carried on the similar dry experiments to practical MSW, It was found that Modified Page model was also suitable for simulating the drying process of practical MSW, its effective moisture diffusion coefficient and activation energy were 6.78 x 10(-8)-18.65 x 10(-8)m2 x s(-1) and 22.36 kJ x mol(-1), respectively.

[Coupling effects of temperature, moisture, and nitrogen application on greenhouse soil pH and EC].

A laboratory incubation experiment was conducted to study the effects of temperature (T), moisture (W), nitrogen application (N), and their combinations on the pH and EC of greenhouse soil having cultivated for 5 years. The results showed that with the increase of incubation time, soil pH was decreasing, which could be well described by the first-order kinetic model, and the pH decreasing rate (k) under effects of test factors was in the order of N > W > W x N > T x W. Soil EC increased quickly to the maxima in the first week of incubation, decreased slightly then, and finally reached to a constant (EC(sty)). The EC(sty) value was significantly affected by N, W, T x W, T, and W x N. Reducing nitrogen application and rational deficit irrigation could effectively postpone the soil acidification and EC increase. A regression equation of k and EC(sty) was established, which could be used to predict the changes of soil pH and EC under different conditions of moisture regime and nitrogen application.