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It is well accepted that diabetes is associated with heart diseases and hyperlipidemia as a risk factor. In traditional medicines, some herbs such as Aloe vera seem to be effective in controlling diabetes. Owing to lack of human studies, this study aims to examine the effect of Aloe vera consumption on fasting blood sugar (FBS), lipid profiles and body composition in type 2 diabetic patients.

This double-blind, placebo-controlled trial study was conducted in 2019, in Shiraz, Iran. A total of 56 diabetic subjects were randomized by block randomization to receive a daily supplement of 1,000 mg Aloe vera powder capsules (n = 28) or placebo (n = 28) for eight weeks. At baseline and after eight weeks of treatment, dietary intake and physical activity were assessed by three-day food recall and international physical activity questionnaire. Meanwhile, after an overnight fasting, FBS and lipid profiles were measured. Blood pressure and anthropometric parameters were assessed in the beginning and the end of the study. Independent t-tests were used for between-group analysis and paired t-tests for within-group analysis.

After intervention, weight, body mass index and waist circumference significantly decreased in comparison to the placebo group (p-value: < 0.001, 0.001 and 0.02). Although, FBS, total triglyceride and systolic blood pressure decreased significantly (p-value: 0.03, 0.001 and 0.01), no change has been seen in low density lipoprotein, high density lipoprotein and total cholesterol blood level and diastolic blood pressure.

The limitations of this study are the short study duration and lack of Aloe vera powder’s ingredient analysis.

This study is one of few human studies investigating the effect of Aloe vera on metabolic syndrome’s indices in diabetic patients. Because pharmacological therapy is tough, not comfort and correlated with potential adverse drug interactions, it is important to find an alternative or complementary measure to aid the diabetic patients. This study shows that Aloe vera has positive effect on body weight and blood sugar.

The purpose of this study was to address waste management in the food supply chain (FSC) through the integration of inspection processes in production and distribution centers under uncertain conditions, aiming to enhance sustainability across environmental, economic and social dimensions. The study introduces a sustainable forward and reverse FSC network using a closed-loop supply chain network approach to prevent the transfer of spoiled products, ultimately providing competitive advantages to stakeholders.

A robust multi-objective mathematical programming model is proposed, incorporating inspection processes to manage perishable products effectively. The model is solved using the Augmented Epsilon Constraint technique implemented in GAMS software, providing Pareto-optimal solutions tailored to decision-makers’ preferences. Furthermore, the methodology is applied in a real-world case study and solved with the Benders Decomposition algorithm to validate its practicality and effectiveness.

The proposed methodology effectively minimizes waste and enhances sustainability in the FSC by optimizing decision-making processes under uncertainty. The illustrative examples and real case study demonstrate the efficiency of the model and solution approach, highlighting the significant role of inspection in improving all three dimensions of sustainability.

The study offers valuable insights into and tools for food industry managers to make informed strategic and tactical decisions. By addressing waste management through advanced supply chain modeling, the research helps organizations reduce costs, improve sustainability and gain a competitive edge in the market.

This research is novel in its focus on integrating inspection into the FSC network and addressing uncertainty through robust mathematical modeling. It contributes to the existing literature by demonstrating the impact of inspection on sustainability in FSCs and providing practical solutions for real-world implementation.