Dairy cows experience an increased demand for glucose to support milk production. However, negative energy balance is a common condition in peripartum cows. In response, fat mobilization provides non-esterified fatty acids (NEFAs) for oxidation in the liver to generate ATP. To investigate the effects of NEFAs on gluconeogenesis, the expression and enzyme activity of pyruvate carboxylase (PC) and phosphoenolpyruvate carboxylase (PEPCK) in cultured bovine hepatocytes were evaluated by quantitative polymerase chain reaction and spectrophotometry, respectively. The results showed that PC and PEPCK mRNA levels were marked decreased when the NEFAs concentrations exceeded 0.5 and 1.5 mmol/l, respectively. The PC and PEPCK enzyme activity showed significantly decreased when the NEFAs concentrations exceeded 1.5 and 0.5 mmol/l, respectively. These findings indicate that high circulating levels of NEFAs inhibit hepatocyte gluconeogenesis, thereby promoting negative energy balance.
Chondrocytes from the lateral trochlear ridge of the distal femur taken from 1-day-old piglets were cultured in medium supplemented with 0, 7.8, 15.6, 31.2, and 62.5 μmol/L copper. Insulin-like growth factor-1 (IGF-1) and IGF-binding protein 3 (IGFBP-3) levels in culture medium were determined by radioimmunoassay. DNA synthesis in chondrocytes was measured by tritiated thymidine ((3)H-TdR) incorporation. Proliferation-promoting activity and incorporation of (3)H-TdR in chondrocytes were increased in all culture media supplemented with copper and 15% fetal calf serum (FCS). The contents of IGF-1 and IGFBP-3 were also enhanced significantly in culture media containing 15% FCS and supplemented with copper at 15.6, 31.2, and 62.5 μmol/L. The optimal copper concentration for promoting chondrocyte proliferation and autocrine secretion of IGF-1 and IGFBP-3 was 31.2 μmol/L.
Hidden Markov Model (HMM) is currently the most popular approach to speech recognition. The problem of optimizing model parameters is of great interest to the researchers in this area. Genetic Algorithm (GA) has been used in the optimization of HMM. However, GA lacks hill-climbing capacity. A novel GA based on Tabu Search (TS) called GATS is brought forward, which maintains the merits of GA and TS. Furthermore, combining the Baum-Welch algorithm with the GATS algorithm, a hybrid algorithm named GATSBW is proposed to train the continuous HMM in continuous speech recognition. The GATSBW algorithm not only overcomes the shortcoming of the slow convergence speed of the GATS algorithm but also helps the BaumWelch algorithm escape from local optimum. The experimental results show that the GATS algorithm has stronger hill-climbing ability than GA and the GATSBW algorithm is superior to the Baum-Welch algorithm in terms of the recognition ability generally.
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