Imidacloprid induced osmotic fragility in erythrocytes of rats: Protective role of vit.C and tea

Abstract: The presen

Hydroxyurea treatment of sickle cell disease: towards a personalized model-based approach

Hydroxyurea is a commonly used drug for the treatment of sickle cell disease. Several studies have demonstrated the efficacy of hydroxyurea in ameliorating disease pathophysiology. However, a lack of consensus on optimal dosing and the need for ongoing toxicity monitoring for myelosuppression limits its utilization. Pharmacokinetic (PK) and pharmacodynamic (PD) studies describe drug-body interactions, and hydroxyurea PK-PD studies have reported wide inter-patient variability. This variability can be explained by a mathematical model taking into consideration different sources of variation such as genetics, epigenetics, phenotypes, and demographics. A PK-PD model provides us with a tool to capture these variant responses of patients to a given drug. The development of an integrated population PK-PD model that can predict individual patient responses and identify optimal dosing would maximize efficacy, limit toxicity, and increase utilization. In this review, we discuss various treatment challenges associated with hydroxyurea. We summarize existing population PK-PD models of hydroxyurea, the gap in the existing models, and the gap in the mechanistic understanding. Lastly, we address how mathematical modeling can be applied to improve our understanding of hydroxyurea’s mechanism of action and to tackle the challenge of inter-patient variability, dose optimization, and non-adherence

Leveraging mathematical modeling to analyze nonadherence for hydroxyurea therapy in sickle cell disease

Abstract Nonadherence is common in individuals with sickle cell disease (SCD) on hydroxyurea therapy and can be observed with waning improvements in hematologic parameters or biomarkers like mean cell volume and fetal hemoglobin level over time. We modeled the impact of hydroxyurea nonadherence on longitudinal biomarker profiles. We estimated the potential nonadherent days in individuals exhibiting a drop in biomarker levels by modifying the dosing profile using a probabilistic approach. Incorporating additional nonadherence using our approach besides existing ones in the dosing profile improves the model fits. We also studied how different patterns in adherence give rise to various physiological profiles of biomarkers. The key finding is consecutive days of nonadherence are less favorable than when nonadherence is interspersed. These findings improve our understanding of nonadherence and how appropriate intervention strategies can be applied for individuals with SCD susceptible to the severe impacts of nonadherence

Mathematical Modeling of Hydroxyurea Therapy in Individuals with Sickle Cell Disease

Sickle cell disease (SCD) is a chronic hemolytic anemia affecting millions worldwide with acute and chronic clinical manifestations and early mortality. While hydroxyurea (HU) and other treatment strategies managed to ameliorate disease severity, high inter-individual variability in clinical response and a lack of an ability to predict those variations need to be addressed to maximize the clinical efficacy of HU. We developed pharmacokinetics (PK) and pharmacodynamics (PD) models to study the dosing, efficacy, toxicity, and clinical response of HU treatment in more than eighty children with SCD. The clinical PK parameters were used to model the HU plasma concentration for a 24 h period, and the estimated daily average HU plasma concentration was used as an input to our PD models with approximately 1 to 9 years of data connecting drug exposure with drug response. We modeled the biomarkers mean cell volume and fetal hemoglobin to study treatment efficacy. For myelosuppression, we modeled red blood cells and absolute neutrophil count. Our models provided excellent fits for individuals with known or correctly inferred adherence. Our models can be used to determine the optimal dosing regimens and study the effect of non-adherence on HU-treated individuals

The two-component signalling networks of Mycobacterium tuberculosis display extensive cross-talk in vitro

Two-component systems (TCSs), which contain paired sensor kinase and response regulator proteins, form the primary apparatus for sensing and responding to environmental cues in bacteria. TCSs are thought to be highly specific, displaying minimal cross-talk, primarily due to the co-evolution of the participating proteins. To assess the level of cross-talk between the TCSs of Mycobacterium tuberculosis, we mapped the complete interactome of the M. tuberculosis TCSs using phosphotransfer profiling. Surprisingly, we found extensive crosstalk among the M. tuberculosis TCSs, significantly more than that in the TCSs in Escherichia coli or Caulobacter crescentus, thereby offering an alternate to specificity paradigm in TCS signalling. Nearly half of the interactions we detected were significant novel cross-interactions, unravelling a potentially complex signalling landscape. We classified the TCSs into specific `one-to-one' and promiscuous `one-to-many' and `many-to-one' circuits. Using mathematical modelling, we deduced that the promiscuous signalling observed can explain several currently confounding observations about M. tuberculosis TCSs. Our findings suggest an alternative paradigm of bacterial signalling with significant cross-talk between TCSs yielding potentially complex signalling landscapes

Pesticide Risk and Recurrent Pregnancy Loss in Females of Subhumid Region of India

Objective: The objective of this study is to determine the level of pesticides and their role in cases of recurrent pregnancy loss (RPL). Materials and Methods: This was designed as a case–control study. Gas chromatography was used to characterize the pesticide level in 70 cases and 70 controls. Case refers to women with RPL, whereas controls refer to women with full‑term delivery. Results: A higher level of pesticide, namely beta‑hexachlorocyclohexane, malathion, chlorpyrifos, and fenvalerate was found in the case group as compared to control group (P < 0.05). Conclusions: The present study suggests that high exposure of pesticide (organochlorine and organophosphates) may increase the risk of RPL in females of the subhumid region of India