Update on the treatment of type 2 diabetes mellitus

A dissociated glucocorticoid receptor modulator mitigates glucolipotoxicity in the endocrine pancreas and peripheral tissues: Preclinical data from a mouse model of diet-induced type 2 diabetes

AIMS

Type 2 diabetes (T2D) is a prevalent metabolic disease linked to obesity and metabolic syndrome (MS). The glucolipotoxic environment (GLT) impacts tissues causing low-grade inflammation, insulin resistance and the gradual loss of pancreatic β-cell function, leading to hyperglycemia. We have previously shown that Compound A (CpdA), a plant-derived dissociative glucocorticoid receptor-modulator with inflammation-suppressive activity, displays protective effects on β-cells in type 1 diabetes murine models. This study aimed to evaluate whether the administration of CpdA can attenuate GLT effects and improve pathophysiological parameters in a murine model of T2D/MS.

MAIN METHODS

Eight-week-old male C57BL/6NCrl mice were fed either a standard chow diet or a high-fat/high-sucrose diet (HFHS) for 15 weeks. From week 5 of feeding, each group received i.p. injections of CpdA (2.5 μg/g) or vehicle three times a week. We also examined CpdA in vitro effect against GLT using the insulinoma cell line INS-1E and naïve isolated mouse islets.

KEY FINDINGS

CpdA administration in HFHS fed mice improved glucose homeostasis and insulin sensitivity with no apparent side effects. CpdA treatment also preserved pancreatic islet architecture and insulin expression, while reducing hepatic steatosis and visceral adipose tissue inflammation induced by HFHS diet. In vitro assays in INS-1E cells and naïve isolated mouse islets demonstrated that CpdA counteracted GLT-induced inhibition of glucose-stimulated insulin secretion and supported the expression of key β-cell identity genes under GLT conditions.

SIGNIFICANCE

These findings highlight the potential protective effect of CpdA in preserving β-cell functionality and peripheral tissue physiology in the context of T2D/MS.

Structure-based molecular docking and molecular dynamics simulations study for the identification of dipeptidyl peptidase 4 inhibitors in type 2 diabetes

Inhibition of dipeptidyl peptidase-4 (DPP4) activity has emerged as a promising therapeutic approach for the treatment of type 2 diabetes mellitus (T2DM). Bioinformatics-driven approaches have emerged as crucial tools in drug discovery. Molecular docking and molecular dynamics (MD) simulations are effective tools in drug discovery, as they reduce the time and cost associated with experimental screening. In this study, we employed structure-assisted in-silico methods, including molecular docking and MD simulations, to identify SRT2183, a small molecule that may potentially inhibit the activity of DPP4 enzyme. The interaction between the small molecule "SRT2183" and DPP4 exhibited a binding affinity of -9.9 Kcal/Mol, leading to the formation of hydrogen bonds with the amino acid residues MET348, SER376, and THR351 of DPP4. The MD simulations over a period of 100 ns indicated stable protein-ligand interactions, with no significant conformational rearrangements observed within the simulated timeframe. In conclusion, our results suggest that the small molecule SRT2183 may have the potential to inhibit the DPP4 enzyme and pave the way for the therapeutics of T2DM.Communicated by Ramaswamy H. Sarma.

SGLT2 inhibitor use in the management of feline diabetes mellitus

Sodium-glucose cotransporter-2 (SGLT2) inhibitors are routinely used in the management of human type 2 diabetes and have been shown to effectively mitigate hyperglycemia and reduce the risks of cardiovascular and renal compromise. Two SGLT2 inhibitors, namely bexagliflozin and velagliflozin, were recently FDA approved for the treatment of uncomplicated feline diabetes mellitus. These oral hypoglycemic agents are a suitable option for many newly diagnosed cats, with rapid improvements in glycemic control and clinical signs. Suitable candidates must have some residual β-cell function, as some endogenous insulin production is required to prevent ketosis. Appropriate patient selection and monitoring are necessary, and practitioners should be aware of serious complications such as euglycemic diabetic ketoacidosis.

Bolanthus turcicus: a promising antidiabetic with in-vitro antioxidant, enzyme inhibitory and antiadipogenic activities

It is crucial to investigate new anti-diabetic agents and therapeutic approaches targeting molecules in potential signaling pathways for the treatment of Type 2 diabetes mellitus (T2DM). The objective of the study was to investigate the total phenolic content, antioxidant capacity, α-glucosidase, and α-amylase inhibitory activities of Bolanthus turcicus (B. turcicus), as well as their cytotoxic, anti-adipogenic, anti-diabetic, apoptotic, and anti-migration potential on adipocytes. B. turcicus samples were extracted with methanol (MeOH), ethyl acetate (EA) and aqueous (Aq) solvents. The MeOH extract had the highest phenolic content (81.14 mg GAE/g), followed by EA (74.93 mg GAE/g) and Aq (51.09 mg GAE/g). All extracts exhibited dose-dependent increases in α-glycosidase and α-amylase inhibitory activity. B. turcicus extracts showed cytotoxic effect on adipocytes with IC50 values of MeOH (141.0 µg/mL) < Aq (155.3 µg/mL) < EA (199.5 µg/mL). Furthermore, B. turcicus extracts reduced lipid droplet formation and adipocyte diameter size. All extracts altered cell morphology to resemble fibroblasts. B. turcicus extracts exhibited anti-migratory effect delaying wound healing for up to 96 h. The B. turcicus extracts showed a pro-apoptotic effects on adipocytes by increasing Caspase-3 enzyme activity and the population of DAPI-positive cell with apoptotic nuclear-morphology. B. turcicus extracts upregulated the expression of the Glut-4 gene at the mRNA, protein and intracellular level in adipocytes. In conclusion, our findings indicate that B. turcicus not only exhibits strong antioxidant properties and enzyme inhibitory activities but also exerts significant anti-adipogenic and pro-apoptotic effects in adipocytes, thereby providing a comprehensive mechanism through which it may contribute to the management of T2DM. These effects highlight the potential of B. turcicus as a therapeutic agent for improving glucose homeostasis and insulin sensitivity.

Exploring the DPP IV inhibitory potential: molecular docking and dynamic simulations of pyridine-3-carboxylic acid and pyrrolidine-2-carboxylic acid analogs

Diabetes mellitus remains a global challenge, with Type 2 Diabetes Mellitus (T2DM) prevalence increasing from 4% to 6.4% in the past 30 years. Presently oral hypoglycaemic agents like GLP-1 agonists, biguanides, sulphonylureas, glinides, and thiazolidinediones are employed in clinical practice. Very recently, novel targets including Dipeptidyl peptidase IV (DPP IV), PPAR, GIP, FFA1, and melatonin have been in the limelight for the development of novel treatment strategies. The present study focuses on the development of DPP IV inhibitors through computational approaches. DPP IV, also referred to as CD26 (cluster of differentiation 26) or adenosine deaminase complexing protein 2, is a protein that is encoded by the DPP IV gene in humans. This enzyme is involved in the metabolism of incretin hormones such as glucagon-like peptides (GLP-1). DPP IV inhibitors prevent the degradation of GLP-1, glucose-dependent insulinotropic peptide (GIP), thereby controlling the concentration of glucose in the blood. Considering the safety and efficacy of DPP IV inhibitors newer molecules were designed with better binding affinity with the protein as compared to existing Sitagliptin, and Vildagliptin-like drugs. Derivatives of nicotinic acid and proline were designed and studied using molecular docking and dynamic simulations. Docking results demonstrated that the NA-13 molecule possesses potent binding affinity with target protein 6B1E (-38.1498 kcal/mol) as compared to standard Sitagliptin (-33.3187 kcal/mol). MD simulation studies showcased that there are fewer variations of RMSD and RMSF for 6B1E-NA-13, 6B1E-P1, and 6B1E-P7 complexes, suggesting the potential of the designed DPP IV inhibitors in the management of T2DM.

Engineered tools to study endocrine dysfunction of pancreas

Pancreas, a vital organ with intricate endocrine and exocrine functions, is central to the regulation of the body's glucose levels and digestive processes. Disruptions in its endocrine functions, primarily regulated by islets of Langerhans, can lead to debilitating diseases such as diabetes mellitus. Murine models of pancreatic dysfunction have contributed significantly to the understanding of insulitis, islet-relevant immunological responses, and the optimization of cell therapies. However, genetic differences between mice and humans have severely limited their clinical translational relevance. Recent advancements in tissue engineering and microfabrication have ushered in a new era of in vitro models that offer a promising solution. This paper reviews the state-of-the-art engineered tools designed to study endocrine dysfunction of the pancreas. Islet on a chip devices that allow precise control of various culture conditions and noninvasive readouts of functional outcomes have led to the generation of physiomimetic niches for primary and stem cell derived islets. Live pancreatic slices are a new experimental tool that could more comprehensively recapitulate the complex cellular interplay between the endocrine and exocrine parts of the pancreas. Although a powerful tool, live pancreatic slices require more complex control over their culture parameters such as local oxygenation and continuous removal of digestive enzymes and cellular waste products for maintaining experimental functionality over long term. The combination of islet-immune and slice on chip strategies can guide the path toward the next generation of pancreatic tissue modeling for better understanding and treatment of endocrine pancreatic dysfunctions.

A drug prescription recommendation system based on novel DIAKID ontology and extensive semantic rules

According to the World Health Organization (WHO) data from 2000 to 2019, the number of people living with Diabetes Mellitus and Chronic Kidney Disease (CKD) is increasing rapidly. It is observed that Diabetes Mellitus increased by 70% and ranked in the top 10 among all causes of death, while the rate of those who died from CKD increased by 63% and rose from the 13th place to the 10th place. In this work, we combined the drug dose prediction model, drug-drug interaction warnings and drugs that potassium raising (K-raising) warnings to create a novel and effective ontology-based assistive prescription recommendation system for patients having both Type-2 Diabetes Mellitus (T2DM) and CKD. Although there are several computational solutions that use ontology-based systems for treatment plans for these type of diseases, none of them combine information analysis and treatment plans prediction for T2DM and CKD. The proposed method is novel: (1) We develop a new drug-drug interaction model and drug dose ontology called DIAKID (for drugs of T2DM and CKD). (2) Using comprehensive Semantic Web Rule Language (SWRL) rules, we automatically extract the correct drug dose, K-raising drugs, and drug-drug interaction warnings based on the Glomerular Filtration Rate (GFR) value of T2DM and CKD patients. The proposed work achieves very competitive results, and this is the first time such a study conducted on both diseases. The proposed system will guide clinicians in preparing prescriptions by giving necessary warnings about drug-drug interactions and doses.

Non-lethal sonodynamic therapy inhibits high glucose and palmitate-induced macrophage inflammasome activation through mtROS-DRP1-mitophagy pathway

Obesity plays a crucial role in the development and progression of type 2 diabetes mellitus (T2DM) by causing excessive release of free fatty acid from adipose tissue, which in turn leads to systemic infiltration of macrophages. In individuals with T2DM, the infiltration of macrophages into pancreatic islets results in islet inflammation that impairs beta cell function, as evidenced by increased apoptosis and decreased glucose-stimulated insulin secretion. The present study aimed to investigate the effects of non-lethal sonodynamic therapy (NL-SDT) on bone marrow-derived macrophages (BMDMs) exposed to high glucose and palmitic acid (HG/PA). These findings indicate that NL-SDT facilitates the expression of DRP1 through the transient production of mitochondrial ROS, which subsequently promotes mitophagy. This mitophagy was shown to limit the activation of the NLRP3 inflammasome and the secretion of IL-1β in BMDMs exposed to HG/PA. In co-culture experiments, beta cells exhibited significant dysfunction when interacting with HG/PA-treated BMDMs. However, this dysfunction was markedly alleviated when the BMDMs had undergone NL-SDT treatment. Moreover, NL-SDT was found to lower blood glucose levels and elevate serum insulin concentrations in db/db mice. Furthermore, NL-SDT effectively reduced the infiltration of F4/80-positive macrophages and the expression of CASP1 within islets. These findings provide fundamental insights into the mechanisms through which NL-SDT may serve as a promising approach for the treatment of T2DM.

Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control

Background

Type 2 Diabetes (T2D) is a complex condition marked by insulin resistance and beta-cell dysfunction. Traditional dietary interventions, such as low-calorie or low-carbohydrate diets, typically overlook individual variability in postprandial glycemic responses (PPGRs), which can lead to suboptimal management of the disease. Recent advancements suggest that personalized nutrition, tailored to individual metabolic profiles, may enhance the effectiveness of T2D management.

Objective

This study aims to present the development and application of a Digital Twin (DT) technology-a machine learning (ML)-powered platform designed to predict and modulate PPGRs in T2D patients. By integrating continuous glucose monitoring (CGM), dietary data, and other physiological inputs, the DT provides individualized dietary recommendations to improve insulin sensitivity, reduce hyperinsulinemia, and support the remission of T2D.

Methods

We developed a sophisticated DT platform that synthesizes real-time data from CGM, dietary logs, and other biometric inputs to create personalized metabolic models for T2D patients. The intervention is delivered via a mobile application, which dynamically adjusts dietary recommendations based on predicted PPGRs. This methodology is validated through a randomized controlled trial (RCT) assessing its impact on various metabolic markers, including HbA1c, metabolic-associated fatty liver disease (MAFLD), blood pressure, body weight, ASCVD risk, albuminuria, and diabetic retinopathy.

Results

Preliminary data from the ongoing RCT and real-world study demonstrate the DT's capacity to generate significant improvements in glycemic control and metabolic health. The DT-driven personalized nutrition plan has been associated with reductions in HbA1c, enhanced beta-cell function, and normalization of hyperinsulinemia, supporting sustained T2D remission. Additionally, the DT's predictions have contributed to improvements in MAFLD markers, blood pressure, and cardiovascular risk factors, highlighting its potential as a comprehensive management tool.

Conclusion

The DT technology represents a novel and scalable approach to personalized nutrition in T2D management. By addressing individual variability in PPGRs, this method offers a promising alternative to conventional dietary interventions, with the potential to improve long-term outcomes and reduce the global burden of T2D.

Impact of Opuntia ficus-indica Juice and Empagliflozin on Glycemic Control in Rats

Diabetes mellitus (DM) is a major global health concern characterized by high blood glucose levels. This study investigates the effects of Opuntia ficus-indica (cactus) juice and empagliflozin, both alone and in combination, on glycated hemoglobin (HbA1c) levels in healthy and streptozotocin-induced diabetic rats. Eighty Wistar albino male rats were divided into eight groups, with four groups being diabetic. Treatment options included cactus juice, empagliflozin, or both. HbA1c levels were measured at baseline and 100 days later using ELISA. In diabetic and non-diabetic rats treated with cactus juice or empagliflozin, HbA1c levels were significantly reduced, but diabetic rats had significantly lower HbA1c values than non-diabetic rats. The combined treatment provided no additional benefits over individual therapies. These findings indicate that cactus juice and empagliflozin effectively lower HbA1c levels, making their use a promising complementary approach to diabetes management. However, the combined treatment of Opuntia ficus-indica juice and empagliflozin did not yield additional reductions in HbA1c levels compared to individual treatments, with no significant synergistic effects observed throughout the study period. More research is needed to better understand the clinical applications and mechanisms in humans.

Ligandrol Ameliorates High-Fat Diet- and Streptozotocin-Induced Type 2 Diabetes Mellitus and Prevents Pancreatic Islets Degeneration

Androgen therapy has been shown to alleviate type 2 diabetes mellitus (T2DM) but is also associated with severe side effects such as prostate cancer. The present study aims to identify the best hit selective androgen receptor (AR) modulator by in silico studies and then investigates its antidiabetic effects in high-fat diet- and streptozotocin (STZ)-induced T2DM male rat model. Molecular docking and molecular dynamics (MD) studies were carried out using Maestro 13.1 and Desmond (2023-2024). Cytotoxicity and insulin secretion were measured in MIN6 cell lines. T2DM was induced using high-fat diet (HFD) for 4 weeks, followed by single STZ (40 mg/kg, intraperitoneally). OneTouch Ultra glucometer was used to measure fasting blood glucose. Gene expression was determined using reverse transcription polymerase chain reaction. Histopathology was carried out using hematoxylin and eosin stain. Through molecular docking, we identify ligandrol as a potential hit. Ligandrol showed a good binding affinity (-10.74 kcal/mol). MD showed that ligandrol is stable during the 100 ns simulation. Ligandrol increases insulin secretion in a dose-dependent manner in vitro in 2 h. Ligandrol (0.3 and 1 mg/kg, orally) significantly decreased the body weight and fasting blood glucose levels compared with the HFD and STZ group. Gene expression showed that ligandrol significantly increased the AR-targeted gene, neurogenic differentiation 1, compared with the HFD and STZ group. Histopathological staining studies showed that ligandrol prevents pancreatic islet degeneration compared with the HFD and STZ group. Our findings suggest that ligandrol's protective effect on pancreatic islets leading to its antidiabetic effect occurs through the activation of AR.

Plant-Based Diets and Phytochemicals in the Management of Diabetes Mellitus and Prevention of Its Complications: A Review

Diabetes mellitus (DM) is currently regarded as a global public health crisis for which lifelong treatment with conventional drugs presents limitations in terms of side effects, accessibility, and cost. Type 2 diabetes (T2DM), usually associated with obesity, is characterized by elevated blood glucose levels, hyperlipidemia, chronic inflammation, impaired β-cell function, and insulin resistance. If left untreated or when poorly controlled, DM increases the risk of vascular complications such as hypertension, nephropathy, neuropathy, and retinopathy, which can be severely debilitating or life-threatening. Plant-based foods represent a promising natural approach for the management of T2DM due to the vast array of phytochemicals they contain. Numerous epidemiological studies have highlighted the importance of a diet rich in plant-based foods (vegetables, fruits, spices, and condiments) in the prevention and management of DM. Unlike conventional medications, such natural products are widely accessible, affordable, and generally free from adverse effects. Integrating plant-derived foods into the daily diet not only helps control the hyperglycemia observed in DM but also supports weight management in obese individuals and has broad health benefits. In this review, we provide an overview of the pathogenesis and current therapeutic management of DM, with a particular focus on the promising potential of plant-based foods.

One-year outcomes of a digital twin intervention for type 2 diabetes: a retrospective real-world study

This retrospective observational study, building on prior research that demonstrated the efficacy of the Digital Twin (DT) Precision Treatment Program over shorter follow-up periods​​, aimed to examine glycemic control and reduced anti-diabetic medication use after one-year in a DT commercial program. T2D patients enrolled had adequate hepatic and renal function and no recent cardiovascular events. DT intervention powered by artificial intelligence utilizes precision nutrition, activity, sleep, and deep breathing exercises. Outcome measures included HbA1c change, medication reduction, anthropometrics, insulin markers, and continuous glucose monitoring (CGM) metrics. Of 1985 enrollees, 132 (6.6%) were lost to follow-up, leaving 1853 participants who completed one-year. At one-year, participants exhibited significant reductions in HbA1c [mean change: -1.8% (SD 1.7%), p < 0.001], with 1650 (89.0%) achieving HbA1c below 7%. At baseline, participants were on mean 1.9 (SD 1.4) anti-diabetic medications, which decreased to 0.5 (SD 0.7) at one-year [change: -1.5 (SD 1.3), p < 0.001]. Significant reductions in weight [mean change: -4.8 kg (SD 6.0 kg), p < 0.001], insulin resistance [HOMA2-IR: -0.1 (SD 1.2), p < 0.001], and improvements in β-cell function [HOMA2-B: +21.6 (SD 47.7), p < 0.001] were observed, along with better CGM metrics. These findings suggest that DT intervention could play a vital role in the future of T2D care.

Analyzing Amylin Aggregation Inhibition Through Quantum Dot Fluorescence Imaging

Protein aggregation is associated with various diseases caused by protein misfolding. Among them, amylin deposition is a prominent feature of type 2 diabetes. At present, the mechanism of amylin aggregation remains unclear, and this has hindered the treatment of type 2 diabetes. In this study, we analyzed the aggregation process of amylin using the quantum dot (QD) imaging method. QD fluorescence imaging revealed that in the presence of 100 μM amylin, aggregates appeared after 12 h of incubation, while a large number of aggregates formed after 24 h of incubation, with a standard deviation (SD) value of 5.435. In contrast, 50 μM amylin did not induce the formation of aggregates after 12 h of incubation, although a large number of aggregates were observed after 24 h of incubation, with an SD value of 2.883. Confocal laser microscopy observations revealed that these aggregates were deposited in three dimensions. Transmission electron microscopy revealed that amylin existed as misfolded fibrils in vitro and that QDs were uniformly bound to the amylin fibrils. In addition, using a microliter-scale high-throughput screening (MSHTS) system, we found that rosmarinic acid, a polyphenol, inhibited amylin aggregation at a half-maximal effective concentration of 852.8 μM. These results demonstrate that the MSHTS system is a powerful tool for evaluating the inhibitory activity of amylin aggregation. Our findings will contribute to the understanding of the pathogenesis of amylin-related diseases and the discovery of compounds that may be useful in the treatment and prevention of these diseases.

Hallmarks of diabetes mellitus and insights into the therapeutic potential of synergy-based combinations of phytochemicals in reducing oxidative stress-induced diabetic complications

Diabetes mellitus (DM) is a serious health issue and is still one of the major causes of mortality around the globe. Natural products have progressively integrated into modern, advanced medical practices. Phytoconstituents from some medicinal plants have demonstrated therapeutic activity in treating different metabolic disorders and have been used to treat DM and its severe complications. The present review provides details of the major anti-diabetic targets identified in the literature and also provides comprehensive information regarding the therapeutic role of a synergy-based combination of phytoconstituents that functions by controlling specific molecular pathways synchronously by inhibiting certain key regulators involved in the development and progression of DM. The review also implicated the role of oxidative stress in diabetic complications and presented scientific validations of phytochemicals and their synergy-based combination using in vitro and or in vivo approaches.

Anticipatory in silico vaccine designing based on specific antigenic epitopes from Streptococcus mutans against diabetic pathogenesis

The metabolic disorder Type 2 Diabetes Mellitus (T2DM) is characterized by hyperglycaemia, causing increased mortality and healthcare burden globally. Recent studies emphasize the impact of metabolites in the gut microbiome on T2DM pathogenesis. One such microbial metabolite, imidazole propionate (Imp) derived from histidine metabolism, is shown to interfere with insulin signalling and other key metabolic processes. The key enzyme urocanate reductase (UrdA) is involved in ImP production. Hence, we propose to develop a novel therapeutic vaccine against the gut microbe producing Imp based on UrdA as a target for treating T2DM using immunoinformatics approach. Antigenic, non-allergic, non-toxic, and immunogenic B cell and T cell potential epitopes were predicted using immunoinformatics servers and tools. These epitopes were adjoined using linker sequences, and to increase immunogenicity, adjuvants were added at the N-terminal end of the final vaccine construct. Further, to confirm the vaccine's safety, antigenic and non-allergic characteristics of the developed vaccine construct were assessed. The tertiary structure of the UrdA vaccine sequence was predicted using molecular modelling tools. A molecular docking study was utilized to understand the vaccine construct interaction with immune receptors, followed by molecular dynamics simulation and binding free energy calculations to assess stability of the complex. In silico cloning techniques were employed to evaluate the expression and translation effectiveness of the developed vaccine in pET vector. In conclusion, this study developed an in silico epitope-based vaccine construct as a novel adjunct therapeutic for T2DM.

Graphical Abstract

Exploring Holy Basil's Bioactive Compounds for T2DM Treatment: Docking and Molecular Dynamics Simulations with Human Omentin-1

Type 2 Diabetes Mellitus (T2DM) presents a substantial health concern on a global scale, driving the search for innovative therapeutic strategies. Phytochemicals from medicinal plants, particularly Ocimum tenuiflorum (Holy Basil), have garnered attention for their potential in T2DM management. The increased focus on plant-based treatments stems from their perceived safety profile, lower risk of adverse effects, and the diverse range of bioactive molecules they offer, which can target multiple pathways involved in T2DM. Computational techniques explored the binding interactions between O. tenuiflorum phytochemicals and Human Omentin-1, a potential T2DM target. ADMET evaluation and targeted docking identified lead compounds: Luteolin (-4.84 kcal/mol), Madecassic acid (-4.12 kcal/mol), Ursolic acid (-5.91 kcal/mol), Stenocereol (-5.59 kcal/mol), and Apigenin (-4.64 kcal/mol), to have a better binding affinity to target protein compared to the control drug, Metformin (-2.01 kcal/mol). Subsequent molecular dynamics simulations evaluated the s