Background: Presently available anti-seizure drugs cannot control seizures in 20-40% epilepsy patients who develop refractory epilepsy. None of the currently available anti-seizure drugs target ...hypersynchronization of epileptogenic impulses. Process of hypersynchronization involves gap junction activity. Quinine blocks gap junctions, and prevents seizures in animal models. Since comparative studies were lacking, this animal study compared anticonvulsant activity of quinine with that of valproate and phenytoin. METHODS: Seizures were induced in adult albino Sprague/Dawley rats (n=72) using pentylenetetrazole (PTZ) and maximum electroshock (MES) methods, comparator drugs being valproate (90 mg/kg) and phenytoin (27 mg/kg) respectively. Quinine was given in three doses (28, 35 and 42 mg/kg). RESULTS: Higher doses of quinine (35 and 42 mg/kg) controlled PTZ seizures; efficacy was similar to valproate. MES seizures were not suppressed. CONCLUSION: Quinine has in-vivo anticonvulsant activity in rats in PTZ model at higher doses, but not in MES model in the doses tested.
Background: According to the World Health Organization (WHO), substance abuse is “persistent or sporadic drug use inconsistent with or unrelated to acceptable medical practice.” Recently, substance ...abuse has been increasing among children and adolescents. Alcohol is one of the leading causes of death and disability globally and in India. Tobacco consumption is a major preventable cause of death, accounting for 13,000 deaths per day globally. This study was conducted to identify the prevalence of substance abuse and its pattern among adolescents in rural and urban community of Surendranagar district.Methods: It was a cross-sectional study carried out among 300 rural (150 from school and 150 from community) and 300 urban (150 from school and 150 from community) adolescents selected by simple random sampling. Data was collected and analysed by Statistical Package for Social Sciences and Microsoft excel have been used to generate graphs, tables, etc.Results: Prevalence of substance abuse in our study was 30.17%. Adolescents from rural community had higher prevalence (37.67%). Prevalence was significantly higher in males (55.33%) than compared to females (5%). Tobacco was most common substance abused by the adolescents.Conclusions: Prevalence of substance abuse was higher in rural compared to urban community and in males compared to females. Chewing form being the most common form of abusing the tobacco followed by smoking and drinking form in our study.
The paraventricular nucleus (PVN) of the hypothalamus is known to be involved in the control of sympathetic outflow. Nitric oxide (NO) has been shown to have a sympathoinhibitory effect in the PVN. ...The goal of the present study was to examine the influence of overexpression of neuronal NO synthase (nNOS) within the PVN on renal sympathetic nerve discharge (RSND). Adenovirus vectors encoding either nNOS (Ad.nNOS) or beta-galactosidase (Ad.beta-Gal) were transfected into the PVN in vivo. Initially, the dose of adenovirus needed for infection was determined from in vitro infection of cultured fibroblasts. In Ad.nNOS-treated rats, the local expression of nNOS within the PVN was confirmed by histochemistry for NADPH-diaphorase-positive neurons. There was a robust increase in staining of NADPH-diaphorase-positive cells in the PVN on the side injected with Ad.nNOS. The staining peaked at 3 days after injection of the virus. In alpha-chloralose- and urethane-anesthetized rats, microinjection of N(G)-monomethyl-L-arginine (L-NMMA), a NO antagonist, into the PVN produced a dose-dependent increase in RSND, blood pressure, and heart rate. There was a potentiation of the increase in RSND, blood pressure, and heart rate due to L-NMMA in Ad.nNOS-injected rats compared with Ad.beta-Gal-injected rats. These results suggest that the endogenous NO-mediated effect in the PVN of Ad.nNOS-treated rats is more effective in suppressing RSND compared with Ad.beta-Gal-treated rats. These observations support the contention that an overexpression of nNOS within the PVN may be responsible for increased suppression of sympathetic outflow. This technique may be useful in pathological conditions know to have increased sympathetic outflow, such as hypertension or heart failure.
A Scaleable Synthesis of Fiduxosin Haight, Anthony R; Bailey, Anne E; Baker, William S ...
Organic process research & development,
11/2004, Letnik:
8, Številka:
6
Journal Article
Recenzirano
Fiduxosin (1) has been under development at Abbott Laboratories for the treatment of benign prostatic hyperplasia. A convergent strategy required methodologies for preparation of an enantiomerically ...pure 3,4-cis-disubstituted pyrrolidine and a 2,3,5-trisubstituted thienopyrazine in a regiospecific manner. A 3+2 cycloaddition of an enantiopure azomethine ylide followed by a diastereoselective crystallization was employed to prepare the benzopyranopyrrolidine in high diastereomeric and enantiomeric purity. Conditions for reduction of an O-aryl lactone susceptible to epimerization were developed, and cyclization of the alcohol/phenol to the ether was accomplished in high yield. The thienopyrazine was prepared by condensation of methyl thioglycolate and a regiospecifically prepared 2-bromo-3-cyano-5-phenylpyrazine. Conditions for effective halogen substitutive deamination to prepare regiospecific trisubstituted pyrazines will be described.
The continuous rise in CO2 emission into the environment is one of the most crucial issues facing the whole world. Many countries are making crucial decisions to control their carbon footprints to ...escape some of their catastrophic outcomes. There has been a lot of research going on to project the amount of carbon emissions in the future, which can help us to develop innovative techniques to deal with it in advance. Machine learning is one of the most advanced and efficient techniques for predicting the amount of carbon emissions from current data. This paper provides the methods for predicting carbon emissions (CO2 emissions) for the next few years. The predictions are based on data from the past 50 years. The dataset, which is used for making the prediction, is collected from World Bank datasets. This dataset contains CO2 emissions (metric tons per capita) of all the countries from 1960 to 2018. Our method consists of using machine learning techniques to take the idea of what carbon emission measures will look like in the next ten years and project them onto the dataset taken from the World Bank's data repository. The purpose of this research is to compare how different machine learning models (Decision Tree, Linear Regression, Random Forest, and Support Vector Machine) perform on a similar dataset and measure the difference between their predictions.
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