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Aim: To find out possible to determine effect of C. reflexa extract on spontaneous contractions of rabbit jejunum. Methods: Animal experimental in vitro study from 1st October 2017 to 30 September 2018 at Pharmacology experimental lab, Wah Medical College Wah Cantt. Study model was Isolated pieces of rabbit jejunum and ileum. Sampling Technique used was Simple Random. Tissue considered fit for experiment after initial equilibration and stabilization. Result: Three increasing concentrations (0.1mg/ml, 0.2mg/ml and 0.4mg/ml) of C. reflexa extract decreased the response to 3.83±0.40, 2.33±0.33 and 1.33± 0.21mm. Decrease in response was significant with p- value 0.04, 0.008 and 0.003 respectively. Conclusion: Freshly prepared aqueous solution of crude extract of C. reflexa decreases the amplitude of spontaneous contractions of isolated rabbit jejunum. Keywords: Rabbit jejunum, effect of drug

A new glycoside, azralidoside, has been isolated from the flowers of Cassia nodosa and characterized as 3-ethyl-23-methyl-22-β-rutinosyloxy)-5-pentacosanolide on the basis of spectral and degradative studies.

Aim: To find out the prevalence and susceptibility of MDR klebsiella isolates in Karachi. Study Design: Pre-clinical in-vitro study. Place and Duration of Study: Study was conducted at the microbiology lab of the tertiary care hospital of Karachi, Pakistan during May to October 2021. Methodology:  About 550 samples of blood, urine and wound swab were inoculated on blood agar and MacConkey agar and incubated at 37° Celsius for 24 hours. The antibiotic susceptibility was identified by Kirby Bauer’s disc diffusion method. Antibiotic disc of amoxicillin-clavulanate 20 µg, Fosfomycin 200 µg, Ciprofloxacin 5 μg, Moxifloxacin µg, Gentamicin 10 μg and Ceftolozane/tazobactam (30/10 μg) were placed on agar plate and then incubated at 35°C for 16-24 hours. Data was analyzed by using Statistical Package for Social Sciences (SPSS) version 20. Results: Out of total 550 strains of Klebsiella 35% were multidrug resistant while 64% were not. Sensitivity and resistance pattern of multiple antibiotics against Klebsiella showed that majority of antibiotics were resistant to Klebsiella. The highest resistance was noted with amoxicillin that was 90%, followed by amoxiclave, nitrofurantoin, doxycycline, ceftazidime and ciprofloxacin with frequency of 86%, 75%, 64% 56% and 54% respectively. On the other hand, combination of Ceftolozane and tazobactam were highly sensitive against klebsiella followed by fosfomycin, Imipenem and combination of piperacillin and tazobactam with frequency of 95%, 89%, 88% and 68% respectively. Conclusion: It can be concluded that klebsiella species have developed high resistance against a number of antibiotics resulting in high morbidity and mortality. Currently combination of Ceftolozane and tazobactam is highly sensitive so it should be preserved as a future lifesaving drug. Beside this, fosfomycin, Imipenem and combination of piperacillin and tazobactam also reported high sensitivity.

Abstract-Text to Speech (TTS) Conversion Systems havebeen an area of research for decades and have been developed for both handwritten and typed text in various languages. Existing research shows that it has been a challenging task to deal with Urdu language due to the complexity of Urdu 'Nastaliq' (rich variety in writing styles), therefore, to the best of our knowledge, not much work has been carried out in this area. Keeping in view the importance of Urdu language and the lack of development in this domain, our research focuses on 'handwritten' Urdu TTS system. The idea is to first recognize a handwritten Urdu character and then convert it into an audible human speech. Since handwriting styles of different people vary greatly from each other, a machine learning technique for the recognition part is used i.e., Artificial Neural Networks (ANN). Correctly recognized characters, then, undergo processing which converts them into human speech. Using this methodology, a working prototype has been successfully implemented in MATLAB that gives an overall accuracy of 91.4%. Our design serves as a platform for further research and future enhancements for word and sentence processing, especially for visually impaired people.