Objective: Tumor hypoxia, a predominant feature of solid tumor produces drug resistance that significantly impacts a patient's clinical outcomes. Hypoxia-inducible factor 1-alpha (HIF1α) is the major mutation involved in establishing the microenvironment. As a consequence of its involvement in pathways that enable rapid tumor growth, it creates resistance to chemotherapeutic treatments. The propensity of medications to demonstrate drug action often diverges according to the genetic composition. The aim of this study is therefore to examine the effect of population-dependent drug response variations using mutation models. Methods: Genetic variations distinctive to major super-populations were identified, and the mutated gene was acquired as a result of incorporating the variants. The mutated gene sequence was transcribed and translated to obtain the target amino acid sequence. To investigate the effects of mutations, protein models were developed using homology modeling. The target templates for the backbone structure were identified by characterization of primary and secondary protein structures. The modeled proteins were then validated for structural confirmation and flexibility. Potential models were used for interaction studies with hypoxia-specific molecules (tirapazamine, apaziquone, and ENMD) using docking analysis. To verify their stability under pre-defined dynamic conditions, the complexes were subjected to molecular dynamics simulation. Results: The current research models demonstrate with the pharmacogenomic-based mutation of HIF1α the impact of individual variants in altering the person-specific drug response under tumor hypoxic conditions. It also elucidates that the therapeutic effect is altered concerning population-dependent genetic changes in the individual. Conclusion: The study, therefore, asserts the need to set up a personalized drug design approach to enhance tumor hypoxia treatment efficacy.

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Background: The aim of this study was the comparison of the glycemic control and maternal outcomes in women affected with gestational diabetes mellitus (GDM) managed with metformin versus insulin. Materials and Methods: The participants included in this study were 140 women diagnosed with GDM. They were randomized into two groups, women included in the first group were treated with metformin and the women of the second group were managed with insulin. Results: The glycemic control was similar in both the treatment arms and the only noteworthy difference was found in the mean fasting blood glucose, which was significantly higher in the women receiving insulin as compared to the women receiving metformin. There were no substantial differences in the maternal outcome with the use of metformin compared to insulin in women with GDM. Conclusion: The incidence of operative delivery was higher in metformin-treated group, whereas the hospital admission rate was considerably elevated in insulin-treated group.

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Context: There is no straightforward method for estimating cinacalcet HCl in biological materials such as serum exists. As a result, the goal of this research is to develop a simple quality by design (QbD) enabled reverse phase-Ultra-Fast Liquid Chromatography (RP-UFLC) model for analyzing cinacalcet HCl in serum. Aim: The current study envisages the development and validation of an isocratic simple, precise, and rapid QbD enabled RP-UFLC method for the quantification of cinacalcet HCl in both solution form and blood samples. Subjects and Methods: The optimum conditions were outlined, selecting three influential factors (CMPs) i.e., mobile phase composition, flow rate, and injection volume. Systematic optimization was performed by 3²-Box Benkhen experimental design using response surface methodology. The selected variables are further assessed for observed responses Critical Analytical attributes, i.e., peak area, retention time (Rt), USP Plate count. The optimized method used a chromatographic C18 (100 mm × 4.6 mm i.d) column with mobile phase (acetonitrile and Tetrabutyl Ammonium Hydrogen Sulphate [TBSH]) in the ratio of 1:1, with a flow rate of 1 mL/min with UV at λ_max 223 nm. The developed method was found to be specific for cinacalcet HCl, enduring no interference of peaks with an overall analytical Rt of 4.3 min. Results: The Accuracy reported as % recovery was found to be 96.83%–101.32% and 95.18%–102.49% respectively. Inter-day precision (reproducibility) and intra-day precision (repeatability) were found to be 0.22–1.19 standard deviation (SD) and 0.14–2.12 SD respectively. The calibration curve was found to be linear with a regression equation Y = 195.8x + 21852, with R² 0.999 over a concentration range from 100 to 100,000 ng/mL. Conclusion: The required detection and quantitation limits (Limit of Detection and Limit of Quantitation) values were obtained within the acceptance limit based on S/N ratio which indicates the method was sensitive and rapidity of the method. Further, the developed QbD enabled UFLC method was approved and effectively entreated the blood tests to study the pharmacokinetic parameters which indicate a robust, accurate cost-effective method intended for quality control tool for routine systematic analysis in research labs.

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The hydro-alcoholic extract of Withania coagulans fruits was investigated for preliminary phytochemical screening and characterized by high-performance thin-layer chromatography. Column chromatography of the hydro-alcoholic extract of W. coagulans eluted with four different combinations of ethyl acetate and methanol yielded four fractions (WCF₀₁, WCF₀₂, WCF_03, and WCF₀₄). One of these fractions, WCF₀₂, significantly (P < 0.05) inhibited in vitro α-amylase and α-glucosidase activity with IC₅₀ values of 104.71 μg/mL and 70.79 μg/mL, respectively. WCF₀₂ further reduced blood glucose levels in comparison to control in the starch tolerance test. The extract showed a relative dose-dependent effect. It was observed that none of the extracts could delay the peak blood glucose that was achieved after 60 min of carbohydrate challenge, but these blunted the glycemic peak.

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Background: Orthosiphon stamineus was reported to have diuretic effects in experimental rats, and this leads to inhibition of kidney stones through the abundant levels of minerals and flavonoids in it. This study aimed to determine the in vitro effects of O. stamineus water extract as a potential chemolytic agent in urolithiasis. Materials and Methods: In this prospective experiment, a total of 15 stone samples collected from patients who underwent stone extraction were used in each concentration (4 mg/ml, 2 mg/ml, and 1 mg/ml) of the O. stamineus extract and control solution. The effects of pH change in the chemolysis of the stones were assessed using the O. stamineus extract 4 mg/ml under pH 7 and 8. Results: The percentage weight reduction of calcium oxalate stone was highest in the 4 mg/ml concentration. O. stamineus extract 4 mg/ml showed a better effect in terms of chemolytic action on calcium oxalate stone than the potassium citrate solution (70% vs. 41%). Regarding the calcium oxalate stone, the percentage weight reduction has shown about 70% in the pH 5, 48% in pH 7, and <10% in pH 8. The percentage weight reduction of uric acid stone was determined as 47%, 11%, and 14% for pH 5, 7, and 8, respectively. The percentage weight reduction of combination stone was 40%, 60%, and 80% in the pH 5, pH 7, and pH 8, respectively. Data analysis showed that the percentage weight reduction of combination stone was significantly different between acidic, neutral, and alkaline conditions (P = 0.027). Conclusions: In this in vitro study, we are able to show that O. stamineus water extract do have some dissolving capability of urinary stones.

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Background: Asthma is a chronic inflammatory disease characterized by reversible airway obstruction, hyperresponsiveness, and remodeling. Asthma prevalence has increased significantly globally over the last decade, and it remains incurable to this date. Aims and Objectives: The present study evaluated some of the antiasthmatic medicinal plants to assess their mode of action. Materials and Method: Animal models for milk-induced leukocytosis, milk-induced eosinophilia, mast cell degranulation, clonidine-induced catalepsy, and active paw anaphylaxis were used to assess the pharmacological effects of Ammi visnaga, Medicago sativa, and Urtica dioica. Results: Mice pretreated with diazepam, methanolic extract of M. sativa, and U. dioica exhibited significant (P < 0.05) inhibition in milk-induced leukocytosis. However, only M. sativa showed statistically significant (P < 0.05) results. All plants showed a statistically significant (P < 0.05) tendency to decrease milk-induced eosinophilia. Methanolic extracts of all plants significantly (P < 0.05) protected mast cells against degranulation by clonidine. A. visnaga and U. dioica significantly (P < 0.05) protected mice against clonidine-induced catalepsy. An acute treatment by M. sativa potentiated the catalepsy, while it significantly inhibited the catalepsy (P < 0.05) upon chronic treatment. In the allergic inflammation model, methanolic extracts of all plants under study decreased paw thickness in a statistically significant manner (P < 0.05). Conclusion: All the three plants in this study demonstrated anti-inflammatory and antihistaminic effects, as well as decreased paw thickness, validate anti-allergic properties. A. visnaga showed a mast cell-stabilizing effect. A. visnaga and U. dioica inhibited the histamine-mediated clonidine-induced catalepsy from mast cells which proves the antihistaminic activity of these plants.

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Background: Metabolic Syndrome (MetS) is a multifactor condition associated with cardiovascular risk. Thyroid hormones regulate MetS components via controlling energy homeostasis, lipids, and glucose metabolism. The risk ratio for MetS and related disorders changes between males and females. Aim and Objectives: Study aim to access thyroid functions in Saudi population with metabolic syndrome. Materials and Methods: The current study sought to evaluate the impact of thyroid stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) in predicting the risk of MetS. A total of 200 (MetS 100 and control 100) Saudi Arabian males were enrolled for the study, and after applying eligibility criteria, the eligible study size was examined for the physical test (chest, abdominal, and general examination with stress on blood pressure measurement) and anthropometric parameters (bodyweight, body mass index, and waist circumference). Results: In the present study, the biochemical parameters, such as TSH, FT3, FT4, total cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), high-density lipoprotein (LDL), fasting glucose, and fasting insulin were measured in the study group, and statistical analysis was also performed. The results revealed that the MetS and control differ in terms of physical, anthropometric, and biochemical markers. The study showed that thyroid dysfunction (TD) and MetS are closely associated with the difference in physical, anthropometric, and metabolic characteristics. Conclusion: The result demonstrated hypothyroidism major risk factor due to TD in MetS. These findings provide a scientific basis for diagnosis and the management of TD, associated MetS, and cardiovascular disease (CVD).

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Type 2 diabetes mellitus is the most prevalent and progressive in nature. As the time progress, the multifaceted complications and comorbidities associated to diabetes worsen in the form of macrovascular or microvascular or both. Pharmacometrics modeling is a step forward in minimizing the risk or at least understanding the factors associated to its progression with the passage of time. These models investigate diabetes treatments effects and the progression factors with different viewpoints incorporating insulin-glucose dynamics, dose-response and pharmacokinetics, and pharmacodynamics relationships. Pharmacometrics modeling is an innovative approach in a sense that it is taking us away from the conventional analysis by providing all the opportunities in improving the decision-making in health sector. It has been suggested that we can achieve greater statistical power for determining drug effects through model-based evaluation than through traditional evaluations. The main aim of this review was to evaluate pharmacometrics approaches used in modeling diabetes progression through time and also the integrated models describing glucose-insulin dynamics.

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Type 2 diabetes mellitus (T2DM) is progressive in nature and leads to hyperglycemia-associated microvascular and macrovascular complications. Diabetic nephropathy (DN) is one of the most prominent microvascular complication induced by T2DM and is characterized by albuminuria and progressive loss of kidney function. Aggressive management of hyperglycemia and hypertension has been found effective in delaying the development and progression of DN. Although the conventional antidiabetic treatment is effective in the earlier management of hyperglycemia, the progressive loss of beta cells ultimately needs the addition of insulin to the therapy. The emergence of newer antidiabetic agents may address the limitations associated with conventional antidiabetic therapies, which not only improve the glycemic status but also effective in improving cardio-renal outcomes. Nevertheless, the exact role of these agents and their role in minimizing diabetes progression to DN still needs elaboration. The present review aimed to highlights the impact of these newer antidiabetic agents in the management of hyperglycemia and their role in delaying the progression of diabetes to DN/management of DN in patients with T2DM.

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