Enhancement of Amygdaloid Neuronal Dendritic Arborization by Fresh Leaf Juice of Centella asiatica (Linn) During Growth Spurt Period in Rats

Centella asiatica (CeA) is a creeping herb, growing in moist places in India and other Asian Countries. Ayurvedic system of medicine, an alternate system of medicine in India, uses leaves of CeA for memory enhancement. Here, we have investigated the role of CeA fresh leaf juice treatment during growth spurt period of rats on dendritic morphology of amygdaloid neurons, one of the regions concerned with learning and memory. The present study was conducted on neonatal rat pups. The rat pups (7-days-old) were fed with 2, 4 and 6 ml/kg body of fresh leaf juice of CeA for 2, 4 and 6 weeks. After the treatment period, the rats were killed, brains removed and amygdaloid neurons impregnated with Silver nitrate (Golgi staining). Amygdaloid neurons were traced using camera lucida and dendritic branching points (a measure of dendritic arborization) and intersections (a measure dendritic length) quantified. These data were compared with those of age-matched control rats. The results showed a significant increase in dendritic length (intersections) and dendritic branching points along the length of dendrites of the amygdaloid neurons of rats treated with 4 and 6 ml/kg body weight/day of CeA for longer periods of time (i.e. 4 and 6 weeks). We conclude that constituents/active principles present in CeA fresh leaf juice has neuronal dendritic growth stimulating property; hence it can be used for enhancing neuronal dendrites in stress and other neurodegenerative and memory disorders

Asiatic Acid Inhibits Liver Fibrosis by Blocking TGF-beta/Smad Signaling In Vivo and In Vitro

Liver fibrosis is a major cause of liver failure, but treatment remains ineffective. In the present study, we investigated the mechanisms and anti-hepatofibrotic activities of asiatic acid (AA) in a rat model of liver fibrosis induced by carbon tetrachloride (CCl4) and in vitro in TGF-beta1-stimulated rat hepatic stellate cell line (HSC-T6). Treatment with AA significantly attenuated CCl4-induced liver fibrosis and functional impairment in a dosage-dependent manner, including blockade of the activation of HSC as determined by inhibiting de novo alpha smooth muscle actin (a-SMA) and collagen matrix expression, and an increase in ALT and AST (all p<0.01). The hepatoprotective effects of AA on fibrosis were associated with upregulation of hepatic Smad7, an inhibitor of TGF-beta signaling, thereby blocking upregulation of TGF-beta1 and CTGF and the activation of TGF-beta/Smad signaling. The anti-fibrosis activity and mechanisms of AA were further detected in vitro in HSC-T6. Addition of AA significantly induced Smad7 expression by HSC-T6 cells, thereby inhibiting TGF-beta1-induced Smad2/3 activation, myofibroblast transformation, and collagen matrix expression in a dosage-dependent manner. In contrast, knockdown of Smad7 in HSC-T6 cells prevented AA-induced inhibition of HSC-T6 cell activation and fibrosis in response to TGF-beta1, revealing an essential role for Smad7 in AA-induced anti-fibrotic activities during liver fibrosis in vivo and in vitro. In conclusion, AA may be a novel therapeutic agent for liver fibrosis. Induction of Smad7-dependent inhibition of TGF-beta/Smad-mediated fibrogenesis may be a central mechanism by which AA protects liver from injury

An Analog Scheme for Fixed-Point Computation - Part II: Applications

In a companion paper [6] we presented theoretical analysis of an analog network for fixed-point computation. This paper applies these results to several applications from numerical analysis and combinatorial optimization, in particular: 1) solving systems of linear equations; 2) nonlinear programming; 3) dynamic programing; and 4) network how computations, Schematic circuits are proposed for representative cases and implementation issues are discussed. Exponential convergence is established for a fixed-point computation that determines the stationary probability vector for a Markov chain. A fixed-point formulation of the single source shortest path problem (SPP) that will always converge to the exact shortest path is described. A proposed implementation, on a 2-mu complementary metal-oxide-semiconductor (CMOS) process, for a fully connected eight-node network is described in detail. The accuracy and settling time issues associated with: the proposed design approach are presented

An analog scheme for fixed-point computation - Part II. Applications

In a companion paper [see ibid., vol. 44, p. 351-4, 1997] we presented theoretical analysis of an analog network for fixed-point computation. This paper applies these results to several applications from numerical analysis and combinatorial optimization, in particular: (1) solving systems of linear equations; (2) nonlinear programming; (3) dynamic programing; and (4) network flow computations. Schematic circuits are proposed for representative cases and implementation issues are discussed. Exponential convergence is established for a fixed-point computation that determines the stationary probability vector for a Markov chain. A fixed-point formulation of the single source shortest path problem (SPP) that will always converge to the exact shortest path is described. A proposed implementation, on a 2-μ complementary metal-oxide-semiconductor (CMOS) process, for a fully connected eight-node network is described in detail. The accuracy and settling time issues associated with the proposed design approach are presented

Microprocessor-based polynomial generator

A new method of generating polynomials using microprocessors is proposed. The polynomial is generated as a 16-bit digital word. The algorithm for generating a variety of basic 'building block' functions and its implementation is discussed. A technique for generating a generalized polynomial based on the proposed algorithm is indicated. The performance of the proposed generator is evaluated using a commercially available microprocessor kit