No abstract

No abstract

Pandemic coronavirus disease-2019, commonly known as COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a highly contagious disease with a high mortality rate. Various comorbidities and their associated symptoms accompany SARS-CoV-2 infection. Among the various comorbidities like hypertension, cardiovascular disease and chronic obstructive pulmonary disease, diabetes considered as one of the critical comorbidity, which could affect the survival of infected patients. The severity of COVID-19 disease intensifies in patients with elevated glucose level probably via amplified pro-inflammatory cytokine response, poor innate immunity and downregulated angiotensin-converting enzyme 2. Thus, the use of ACE inhibitors or angiotensin receptor blockers could worsen the glucose level in patients suffering from novel coronavirus infection. It also observed that the direct β-cell damage caused by virus, hypokalemia and cytokine and fetuin-A mediated increase in insulin resistance could also deteriorate the diabetic condition in COVID-19 patients. This review highlights the current scenario of coronavirus disease in pre-existing diabetic patients, epidemiology, molecular perception, investigations, treatment and management of COVID-19 disease in patients with pre-existing diabetes. Along with this, we have also discussed unexplored therapies and future perspectives for coronavirus infection.

Although extensive research is being done to combat SARS-CoV-2, we are yet far away from a robust conclusion or strategy. With an increased amount of vaccine research, nanotechnology has found its way into vaccine technology. Researchers have explored the use of various nanostructures for delivering the vaccines for enhanced efficacy. Apart from acting as delivery platforms, multiple studies have shown the application of inorganic nanoparticles in suppressing the growth as well as transmission of the virus. The present review gives a detailed description of various inorganic nanomaterials which are being explored for combating SARS-CoV-2 along with their role in suppressing the transmission of the virus either through air or by contact with inanimate surfaces. The review further discusses the use of nanoparticles for development of an antiviral coating that may decrease adhesion of SARS-CoV-2. A separate section has been included describing the role of nanostructures in biosensing and diagnosis of SARS-CoV-2. The role of nanotechnology in providing an alternative therapeutic platform along with the role of radionuclides in SARS-CoV-2 has been described briefly. Based on ongoing research and commercialization of this nanoplatform for a viral disease, the nanomaterials show the potential in therapy, biosensing, and diagnosis of SARS-CoV-2.

No abstract

No abstract

No abstract

In the present investigation, a quality by design (QbD) strategy was successfully applied to the fabrication of chitosan-coated nanoliposomes (CH-NLPs) encapsulating a hydrophilic drug. The effects of the processing variables on the particle size, encapsulation efficiency (%EE) and coating efficiency (%CE) of CH-NLPs (prepared using a modified ethanol injection method) were investigated. The concentrations of lipid, cholesterol, drug and chitosan; stirring speed, sonication time; organic:aqueous phase ratio; and temperature were identified as the key factors after risk analysis for conducting a screening design study. A separate study was designed to investigate the robustness of the predicted design space. The particle size, %EE and %CE of the optimized CH-NLPs were 111.3 nm, 33.4% and 35.2%, respectively. The observed responses were in accordance with the predicted response, which confirms the suitability and robustness of the design space for CH-NLP formulation. In conclusion, optimization of the selected key variables will help minimize the problems related to size, %EE and %CE that are generally encountered when scaling up processes for NLP formulations. The robustness of the design space will help minimize both intra-batch and inter-batch variations, which are quite common in the pharmaceutical industry.