University of Balochistan

Sustainable groundwater management is essential for water security and human health protection. Fluoride contamination is a serious concern for the sustainable drinking water supply in many parts of Pakistan, including Balochistan, where arid climate conditions and geological formations support the enrichment of fluoride. The toxic nature of fluoride contamination has resulted in negative health impacts on the local population. Conventional geostatistical techniques are usually ineffective to delineate the nonlinear relationships that affect the distribution of fluoride. This study aims to develop a machine learning-driven spatial modelling framework for classifying the spatial distribution of fluoride contamination in groundwater across the study area. The model will help to understand the spatial variability of fluoride contamination and its controlling factors, essential for effective mitigation and early warning systems. Physiochemical elements were used as predictive features in this study, utilizing a unified feature importance framework combining hydrogeochemical analysis, spatial distribution assessment, and ensemble SHAP-based interpretation to identify consistent predictors. Model performance was evaluated using a nested cross-validation framework, followed by validation on an independent geology-informed spatial holdout test set to ensure realistic generalization. Among machine learning models, the Logistic Regression (LR), Support Vector Classifier (SVC), XGBoost (XGB), Decision Tree (DT), Gaussian Na & iuml;ve Bayes (GNB), and K-Nearest Neighbours (KNN) were evaluated. Support Vector Classifier (SVC) demonstrated a high predictive performance. On the independent spatial holdout dataset, SVC achieved an overall accuracy of 0.75 and an area under the receiver operating characteristic curve (AUC) of 0.821. In addition to classification, a human health risk assessment was conducted using chronic daily intake (CDI) and hazard quotient (HQ) calculations for children and adults, identifying several high-risk water supply schemes. The prediction maps successfully delineated high-risk fluoride points across specific areas, offering a tool for sustainable groundwater management. This study helps to achieve a Sustainable Development Goal (Clean Water and Sanitation, SDG#6) and promotes long-term sustainable planning in water-stressed areas by integrating spatial machine learning mapping and health risk assessment.

A two-year field study was conducted in soils with low and high electrical conductivity (EC): 0.25 dS m(-1), and 1.95 dS m(-1) respectively). The high EC soil was transported from agricultural land. Composted manures obtained from sheep/goat (SG), dairy (FYM), and poultry (PM) farms and manures co-composted with biochar made from Acacia nilotica L. wood (SG-B, FYM-B, and PM-B) were added to the soil for two consecutive years. The influence of these organic fertilizers on soil properties, flowering period, and fresh yield of saffron (Crocus sativus L.) stigma was examined. Analysis of soil collected after the harvest of the second-year crop revealed that organic fertilizers caused a significant two- to fourfold increase in the concentration of potassium and bioavailable phosphorus in both low EC soil and high EC soil. After two years of cropping, the EC of high EC soil dropped to 0.94 to 1.71 dS m(-1) under various treatments. In the low EC soil, FYM-B triggered 2-3 days of early flowering in both cropping years. However, this prolonged flowering period did not cause any increase in stigma yield. Furthermore, in this soil, for the first-year crop, all organic fertilizers reduced stigma yield by 41-44% compared with control treatment, whereas no difference among treatments was observed for the second-year crop. The stigma yield in the high EC control soil was significantly lower than in the low EC control soil by 26% and 56% for the first- and second-year crops, respectively. In high EC soil, no difference among treatments was observed in the stigma yield of the first-year crop. However, for the second-year crop in the high EC soil, all organic fertilizers prolonged the flowering period; moreover, the FYM and PM treatments also increased stigma yield by 78% and 70% respectively (p < 0.05). In conclusion, organic fertilizers influenced the flowering period of saffron and significantly increased the concentrations of potassium by 79%-218% and phosphorus by 187%-455% in the high and low EC soils. The PM in the high EC soil was found to be more suitable for stigma yield and soil properties when applied for two years; relative to control, this organic fertilizer caused the highest significant increase in potassium (218%), phosphorus (371%), and soil moisture (24%) during the critical flowering period. This treatment also prolonged the flowering period and the increased yield of stigma (70%) in the second-year crop in the high EC soil.

Background: Type 2 Diabetes mellitus, is a metabolic disorder responsible for disturbance in carbohydrate, protein and lipid metabolism. The objective of current study was to evaluate the effect of Quercetin and Metformin on serum lipid profile and gene expression involved in lipid metabolism. Methods: Sixty-four specialIntscript Wistar rats in a range of live body weight 196.75-198.19 grams, were divided in eight specialIntscript groups (n=8 each); CONTROL, DIABETIC, DIAB+MET, DIAB+25Q, DIAB+50Q, NONDIAB+MET, NONDIAB+25Q and NONDIAB+50Q. A single dose of Streptozotocin drug @ 35 mg per kg was used for the induction of diabetes. The particular doses of Metformin and Quercetin were given by gavage on daily basis in their respective groups till the end of 14-week trial. Result: In case of FAS gene expression in liver, DIAB+MET (1.26 +/- 0.03), DIAB+25Q (1.31 +/- 0.02) and DIAB+50Q (1.19 +/- 0.04), suppresses the elevated expression compared to Diabetic group, while in case of SREBP-1c, both DIAB+MET (1.31 +/- 0.05) and DIAB+50Q (1.38 +/- 0.04) showed predominant results compared to DIAB+25Q. Moreover, for PPAR-alpha, DIAB+MET (0.87 +/- 0.06) exhibited considerable upregulation in comparison with DIAB+25Q (0.65 +/- 0.03) and DIAB+50Q (0.76 +/- 0.04). In adipose, FAS gene was significantly downregulated in DIAB+50Q (1.28 +/- 0.03) group as compared to other two diabetic treatment groups, however, for PPAR-alpha gene, in term of significance both DIAB+MET (0.84 +/- 0.05) and DIAB+50Q (0.88 +/- 0.06) displayed statistically similar level of upregulation. In muscles, PPAR-gamma expression was best observed in DIAB+50Q (0.80 +/- 0.03) and DIAB+MET (0.76 +/- 0.02) compared to DIAB+25Q (0.59 +/- 0.03). Moreover, serum lipid profile (TC, HDL, TG, LDL and VLDL) was also significantly improved in Metformin and Quercetin treatment groups. In non-diabetic treatment groups, a non-significant difference was observed when compared to CONTROL group.

Earlier therapeutic strategies primarily focused on combating diseases caused by external pathogens; recent advancements have highlighted the pivotal role of endogenous enzymes in the progression of non-infectious disorders. Enzymes such as urease and thymidine phosphorylase have been implicated in various pathological conditions, prompting the need for effective enzyme-targeted inhibitors. In this study, a novel series of bis-thiazole linked linked Schiff Bases (1–10) was designed and synthesized as potential dual enzyme inhibitors. The structural integrity of the synthesized compounds was confirmed by FTIR, 1H-NMR, 13C-NMR and HRMS analyses. The derivatives were screened for their inhibitory activity against urease and thymidine phosphorylase. Among them, the synthesized analogues 4, 5, 7, and 8 exhibited significant activity, surpassing the reference inhibitors thiourea (IC50 = 13.45 ± 0.95 µM) and 7-deazaxanthine (IC50 = 17.61 ± 0.92 µM). In particular, compound-8 emerged as the most potent dual inhibitor, with IC50 values of 8.20 ± 0.98 M and 9.29 ± 0.51 µM against urease and thymidine phosphorylase, respectively. To elucidate the binding mechanism, molecular docking studies were conducted, revealing favorable interactions between the active compounds and key residues within the active sites of the target enzymes. These findings suggest that the bis-thiazole linked Schiff Bases scaffold holds strong potential as a promising chemotype for the development of future enzyme-inhibiting therapeutics.

Recent advances in molecular therapeutics underscore the central role of dysregulated endogenous enzymes in the onset and progression of non-infectious diseases. Urease and thymidine phosphorylase are two clinically relevant enzymes implicated in microbial virulence, inflammation, and cancer biology, yet potent dual modulators remain limited. Here, we report the design and synthesis of a novel library of bis-thiazole linked oxazine Schiff base hybrids (1-10) as candidate dual-enzyme inhibitors. Structural elucidation using FT-IR, 1HNMR, 13C NMR spectroscopy, and HRMS confirmed the structural integrity of the synthesized scaffolds. Biological evaluation revealed potent inhibitory activity across the series, with compounds 1, 2, 5 and 8 demonstrating superior efficacy compared with the standard inhibitors thiourea and 7-deazaxanthine. Notably, compound-1 acted as the most effective dual inhibitor, achieving IC50 values of 4.30 +/- 0.73 mu M (thymidine phosphorylase) and 3.90 +/- 0.84 mu M (urease). Molecular docking analyses further identify stable binding conformations and extensive interaction networks within the catalytic sites of both targets, providing a structural rationale for the observed potencies. These findings position the bis-thiazole linked oxazine Schiff base scaffold as a compelling chemotype for next-generation enzyme-directed therapeutics. The strong inhibitory profiles and well-defined molecular interactions provide a clear rationale for further structure-guided optimization. Together, these results lay the groundwork for advancing this scaffold toward translational development.