Computational Analysis of Surface Pressure Distribution over a 2D Wedge in the Supersonic and Hypersonic Flow Regimes

The complex fluid-dynamic instabilities and shock waves occurring along the surface of a two-dimensional wedge at high values of the Mach number are studied here through numerical solution of the governing equations.Moreover,a regression model is implemented to determine the pressure distribution for various Mach numbers and angles of incidence.The Mach number spans the interval from 1.5 to 12.The wedge angles(θ)are from 5°to 25°.The pressure ratio(P2/P1)is reported at various locations(x/L)along the 2D wedge.The results of the numerical simulations are compared with the regression model showing good agreement.

Engineered hydrogels for brain tumor culture and therapy

Brain tumors’severity ranges from benign to highly aggressive and invasive.Bioengineering tools can assist in understanding the pathophysiology of these tumors from outside the body and facilitate development of suitable antitumoral treatments.Here,we first describe the physiology and cellular composition of brain tumors.Then,we discuss the development of threedimensional tissue models utilizing brain tumor cells.In particular,we highlight the role of hydrogels in providing a biomimetic support for the cells to grow into defined structures.Microscale technologies,such as electrospinning and bioprinting,and advanced cellular models aim to mimic the extracellular matrix and natural cellular localization in engineered tumor tissues.Lastly,we review current applications and prospects of hydrogels for therapeutic purposes,such as drug delivery and co-administration with other therapies.Through further development,hydrogels can serve as a reliable option for in vitro modeling and treatment of brain tumors for translational medicine.

Maillard reaction and immunogenicity of protein therapeutics

The recombinant DNA technology enabled the production of a variety of human therapeutic proteins.Accumulated clinical experience,however,indicates that the formation of antibodies against such proteins is a general phenomenon rather than an exception.The immunogenicity of therapeutic proteins results in inefficient therapy and in the development of undesired,sometimes life-threatening,side reactions.The human proteins,designed for clinical application,usually have the same amino acid sequence as their native prototypes and it is not yet fully clear what the reasons for their immunogenicity are.In previous studies we have demonstrated for the first time that interferon-b(IFN-b)pharmaceuticals,used for treatment of patients with multiple sclerosis,do contain advanced glycation end products(AGEs)that contribute to IFN-b immunogenicity.AGEs are the final products of a chemical reaction known as the Maillard reaction or glycation,which implication in protein drugs' immunogenicity has been overlooked so far.Therefore,the aim of the present article is to provide a comprehensive overview on the Maillard reaction with emphasis on experimental data and theoretical consideration telling us why the Maillard reaction warrants special attention in the context of the welldocumented protein drugs' immunogenicity.

Implementation of alternative methods in the health system through evidence-based medicine

Alternative healing methods and non-pharmacological interventions have been used empirically by humans for centuries to reduce pain,improve psyche and socialize.From the point of view of modern medicine and society,where there is a high level of health care,40-65%of patients today still use alternative methods in various regions of the world[1,2].The use of such methods is most common when patients are suffering from malignant or other diseases where modern methods of treatment did not give good results.

Real-time estimation and prediction of the mortality caused due to COVID-19 using particle swarm optimization and finding the most influential parameter

On March 11,2020,the World Health Organization has declared the outbreak of COVID-19 as Pandemic,which is the massive challenges faced globally.Previous studies have indicated that the meteorological parameters can play a vital role in transmissibility and Mortality.In the present work,the influence of Comorbidity and meteorological parameters are investigated for Mortality caused due to COVID.For this,the most affected city by COVID-19 is considered,i.e.,Mumbai,India,as a case study.It was found that Comorbidity is the most influential parameter on the Mortality of COVID-19.The Spearman correlation coefficient for meteorological parameters lies between 0.386 and 0.553,whereas for Comorbidity was found as 0.964.A regression model is developed using particle swarm optimization to predict the mortality cases for Mumbai,India.Further,the developed model is validated for the COVID-19 cases of Delhi,India,to emphasize the utility of the developed model for other cities.The measured and predicted curve shows a good fit with a mean percentage error of 0.00957%and a coefficient of determination of 0.9828.Thus,particle swarm optimization techniques demonstrate very high potential for the prediction of Mortality caused due to COVID-19.It is insisted that by providing constant health monitoring and adequate care for the comorbidity patients,the Mortality can be suppressed drastically.The present work can serve as an input to the policymakers to overcome the COVID-19 pandemic in India as well as other parts of the world.