Mucoadhesive microcapsules of glipizide formulated with gum kondagogu: in vitro and in vivo evaluation

Mucoadhesive microcapsules are proposed for the antidiabetic drug glipizide, to obtain controlled release. Glipizide microcapsules with a coat consisting of alginate and gum kondagogu were prepared by employing ionic gelation process and emulsification ionotropic gelation process. The microcapsules were evaluated for flow properties, Carr’s index, Hausner factor, microencapsulation efficiency, drug release characteristics, surface characteristics, compatibility studies, mucoadhesive properties and in-vivo hypoglycemic activity. These two methods showed individual, large sized, free flowing spherical microcapsules without any interactions. Glipizide release from the microcapsules was slow and followed zero order kinetics and followed non–fickian release and depended on the coat: core ratio and the method employed in the preparation of microcapsules. Among the two methods emulsification ionotropic gelation method was found to be more suitable for slow and complete release of glipizide over a long period of time. These microcapsules exhibited good mucoadhesive property in the in vitro wash-off test. In vivo evaluation in rabbits demonstrated significant hypoglycemic effect of glipizide.Colegio de Farmacéuticos de la Provincia de Buenos Aire

A population-based study of human immunodeficiency virus in south India reveals major differences from sentinel surveillance-based estimates

BACKGROUND: The human immunodeficiency virus (HIV) burden among adults in India is estimated officially by direct extrapolation of annual sentinel surveillance data from public-sector antenatal and sexually transmitted infection (STI) clinics and some high-risk groups. The validity of these extrapolations has not been systematically examined with a large sample population-based study. METHODS: We sampled 13838 people, 15–49 years old, from 66 rural and urban clusters using a stratified random method to represent adults in Guntur district in the south Indian state of Andhra Pradesh. We interviewed the sampled participants and obtained dried blood spots from them, and tested blood for HIV antibody, antigen and nucleic acid. We calculated the number of people with HIV in Guntur district based on these data, compared it with the estimate using the sentinel surveillance data and method, and analysed health services use data to understand the differences. RESULTS: In total, 12617 people (91.2% of the sampled group) gave a blood sample. Adjusted HIV prevalence was 1.72% (95% confidence interval 1.35–2.09%); men 1.74% (1.27–2.21%), women 1.70% (1.36–2.04%); rural 1.64% (1.10–2.18%), urban 1.89% (1.39–2.39%). HIV prevalence was 2.58% and 1.20% in people in the lower and upper halves of a standard of living index (SLI). Of women who had become pregnant during the past 2 years, 21.1% had used antenatal care in large public-sector hospitals participating in sentinel surveillance. There was an over-representation of the lowest SLI quartile (44.7%) in this group, and 3.61% HIV prevalence versus 1.08% in the remaining pregnant women. HIV prevalence was higher in that group even when women were matched for the same SLI half (lower half 4.39%, upper 2.63%) than in the latter (lower 1.06%, upper 1.05%), due to referral of HIV-positive/suspected women by private practitioners to public hospitals. The sentinel surveillance method (HIV prevalence: antenatal clinic 3%, STI clinic 22.8%, female sex workers 12.8%) led to an estimate of 112635 (4.38%) people with HIV, 15–49 years old, in Guntur district, which was 2.5 times the 45942 (1.79%) estimate based on our population-based study. CONCLUSION: The official method in India leads to a gross overestimation of the HIV burden in this district due to addition of substantial extra HIV estimates from STI clinics, the common practice of referral of HIV-positive/suspected people to public hospitals, and a preferential use of public hospitals by people in lower socioeconomic strata. India may be overestimating its HIV burden with the currently used official estimation method

The role of VEGF and a functional link between VEGF and p27(Kip1) in acute myeloid leukemia.

Alterations in the expression and signalling pathways of vascular endothelial growth factor (VEGF) have been linked to the clinical features and pathogenesis of hematologic malignancies. In this study, we showed that VEGF protein expression was statistically significantly higher in the leukemic blasts than in the normal hematopoietic counterparts. A statistically significant correlation between expression of VEGF and p27(Kip1) was observed in bone marrows from 42 patients with acute myeloid leukemia (P<0.001). We further demonstrated that forced VEGF overexpression or autocrine VEGF stimulation of VEGFR-2 triggers proliferation and migration/invasion of U-937 leukemic cells, thereby inducing a more invasive tumor phenotype. U-937 cells overexpressing VEGF were resistant to all-trans-retinoic acid-(ATRA) or camptothecin-induced apoptosis. Finally, we showed that increased p27(Kip1) expression enhanced the ability of VEGF and VEGFR-2 to promote the migration of U-937 cells. Taken together, our results suggest that elevated level of VEGF may contribute to the adverse patient outcome by promoting cell growth, survival and migration of leukemic cells and by reducing the sensitivity of leukemic cells to therapeutic agents-induced apoptosis.Leukemia advance online publication, 6 November 2008; doi:10.1038/leu.2008.300

Current state of artificial intelligence applications in ophthalmology and their potential to influence clinical practice

Artificial intelligence (AI) has emerged as a major frontier in healthcare and finds broad range of applications. It has the potential to revolutionize current procedures of disease diagnosis and treatment, thus influencing the clinical practice. Artificial intelligence (AI) in ophthalmology, primarily concentrates on diagnostic and treatment pathways for eye conditions such as cataract, glaucoma, age-related macular degeneration (MDA) and diabetic retinopathy (DR). The purpose of this article is to systematically review the existing state of literature on the various AI techniques and its applications in the diagnosis and treatment of eye diseases and conduct an in-depth enquiry to identify the challenges in accurate detection, pre-processing of data, monitoring and assessment through various AI algorithms. The results suggest that all AI models proposed reduce the detection time considerably. The potential limitations and challenges in the development and application play a significant role in clinical practice. There is a need for the development of AI-assisted technologies that shall consider the clinical implications based on experience and guided by patient-centred healthcare principles. The diagnostic models should assist ophthalmologists on making quick and accurate decisions in determining the progression of various ocular diseases