Purpose To build and inquire a statistically significant mathematical model for manufacturing methotrexate loaded chitosan nanoparticles (CsNP) of desired particle size. The study was also performed to evaluate the effect of formulation variables in the explored design space. Method Ionotropic gelation technique was followed for chitosan nanocarriers by changing formulation variables suggested as per Design Expert software. Altering the levels of Chitosan, tripolyphosphate, methotrexate by 23 factorial design served the purpose. The CsNP were characterized for nanocarrier formation, particle size, and statistical analysis. Then mathematical model was statistically analyzed for fabricating desired formulation having particle size less than 200nm. Results FT-IR, XRD reports confirmed the structural change in chitosan which lead to the formation of CsNP. For particle size, linear model was found to be best fit to explain effect of variables. Besides, high R2 (0.9958) defends the constancy of constructed model. Chitosan exhibited higher t-value in Pareto chart and a p-value <0.0001. Based on maximum desirability, optimization was performed and amount of variables for preparing CsNP of 180nm was predicted. The experiment was carried out with software suggested combination and particle size was found to be 176±4nm. Conclusion Low p-value endorsed the greater dominance of chitosan on particle size. Good model adequacy and small percentage error between predicted and experimented value established the reliability of constructed model for robust preparation of CsNP.
Despite being announced as a global health concern and emergency in January by WHO, designing specific treatment for SARS-CoV-2 is still a summit yet to be conquered. Currently, many drugs are being tested in the clinical scenario and vitamins play a significant role in therapeutic management. Based on the available evidence, we postulate that maintaining normal vitamin D
3
levels may reduce severity, mortality risk of COVID-19. This review elucidates the alarming need for randomized clinical trials to determine the role of vitamin D in patient prognosis in COVID-19 infection and on latitude bases epidemiological outcome.
Rainfall prediction accuracy in meteorological department is still a major research area. Accuracy in prediction of rainfall may help in knowing heavy rainfall prior and preventing disasters. This mainly associated with economy and human life. There is necessary for efficient prediction
system to identify drought and flood prior, so that people and government can get prepared for any disaster. Our country economy are mainly depends on agriculture, there is a great importance for rainfall prediction in India. Dynamics in atmosphere is the major cause for failure of existing
statistical techniques for rainfall prediction. Taking these in consideration, we propose, Neural network based rain fall prediction for better showing better performance. We exploit machine learning, in which neural network model is used from Keras package available in Python. The objective
of the work is to make this model more reliable for non-technical persons.
Background:
Sutures which are used for wound approximation can act as a reservoir of microbes at the surgical site leading to increased chances of surgical site infection (SSI). Sutures used in oral cavity are continuously bathed in saliva which results in wicking. Several studies on sutures treated with nanoparticles, antibacterial agent and various drugs to advance the therapeutical value of surgical sutures are in consideration, drug-eluting sutures has been notable in research to deliver localized effect on the site of incision. Ciprofloxacin and Aloe vera are routinely used agents in coating sutures.
Aim:
This study is to evaluate the antibacterial efficacy and oral biofilm inhibition of Ciprofloxacin and Aloe vera coated 3-0 silk sutures in comparison to uncoated sutures against E.coli.
Material and Methods:
Equal segments of ciprofloxacin and aloe vera coated 3-0 silk sutures are to be incubated in E.coli culture media (blood agar) at 37°C for 24 hours in aerobic atmosphere. Plain uncoated suture served as control. Assessment was done using Total Colony Forming Units and biofilm inhibition potential of sutures. Results awaited.
Results:
The zone of inhibition around ciprofloxacin coated suture is nearly double than that of with Aloe vera indicted that antibacterial efficacy of ciprofloxacin is more comparatively. No inhibition zone around uncoated plain 3-0 braided silk shows that it has no significant antibacterial activity.
Conclusion:
Within limitation of our study, it can be concluded that both ciprofloxacin and Aloe vera coated sutures have antibacterial property against gram negative E. coli and can have a promising role in prevention of SSI although it would require further in vivo validation.
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