Arailym Yessenbekova

Plant-derived natural products remain a major source of anticancer chemical diversity, yet much of the preclinical literature still describes their activity through compound-centered readouts such as IC₅₀ values, reactive oxygen species generation, mitochondrial depolarization, BCL-2-family remodeling, caspase activation, and PI3K/Akt or NF-κB inhibition. Although informative, these mechanisms do not fully explain why the same phytochemical induces apoptosis in some cancer cells, and cytostasis or adaptation in others, while normal cells frequently activate cytoprotective responses. Rather than replacing conventional compound-centered approaches, we integrate established concepts into a complementary vulnerability-state framework for interpreting plant-derived natural-product-induced selective apoptosis. In this framework, selective apoptosis occurs when phytochemical-induced stress intersects with pre-existing cancer-cell vulnerabilities, overwhelms adaptive buffering, and remains below the injury threshold of normal cells. We organize current evidence around redox imbalance, mitochondrial priming, membrane remodeling, ion-channel and cell-volume dysregulation, and survival-pathway addiction, emphasizing that pathway modulation becomes mechanistically meaningful when linked to differential cellular sensitivity. We further highlight membrane–ion biology as an underexplored contributor to phytochemical responses and discuss how chemical standardization, orthogonal cell-death assays, matched normal-cell models, organoids, and pharmacokinetic/pharmacodynamic considerations can advance the field from descriptive cytotoxicity toward mechanism-informed phytopharmacology.

Diabetic kidney disease (DKD) remains one of the most severe microvascular complications of type 2 diabetes mellitus (T2DM) and a leading cause of chronic kidney disease (CKD) worldwide. Nevertheless, despite considerable progress in elucidating its molecular background, early diagnosis and accurate stratification of disease progression remain challenging when relying on conventional clinical biomarkers such as albuminuria and estimated glomerular filtration rate (eGFR). Growing evidence indicates that DKD is driven by interconnected pathogenic mechanisms, including chronic hyperglycemia, activation of the protein kinase C (PKC) signaling pathway, renin–angiotensin–aldosterone system (RAAS) dysregulation, oxidative stress, inflammatory cascades, and immune system activation involving Toll-like receptors (TLR) and the NLRP3 inflammasome. These processes collectively contribute to endothelial dysfunction, podocyte injury, extracellular matrix accumulation, and progressive renal fibrosis. Exosomes and their molecular cargo, particularly miRNAs, have emerged as promising regulators and non-invasive biomarkers reflecting ongoing renal injury. Urinary exosomal microRNAs (uEV-miRNAs) are of interest due to their stability in biological fluids and their direct origin from nephron segments, enabling real-time reflection of renal pathophysiology. Accumulating studies suggest that differentially expressed microRNAs (miRNAs), including miR-21-5p, miR-30a-5p, miR-192-5p, and miR-142-3p, are closely associated with key pathways in DN. However, their clinical translation remains limited by methodological heterogeneity, the lack of standardized isolation protocols, and insufficient validation in large longitudinal cohorts. This review navigates the current landscape of knowledge on the molecular mechanisms underlying DKD and examines the emerging role of uEV-miRNAs as diagnostic biomarkers. Altogether, uEV-miRNAs offer a promising avenue for improving early detection, risk stratification, and disease monitoring in DKD.

Age-associated metabolic dysfunction is commonly defined by abnormalities in adiposity, glucose regulation, lipid metabolism, and blood pressure. Although clinically useful, these criteria do not fully capture the biological heterogeneity that explains why older adults with similar metabolic profiles may follow divergent trajectories toward type 2 diabetes, cardiovascular disease, metabolic dysfunction-associated steatotic liver disease, frailty or multimorbidity. This narrative Review summarizes clinical, translational, and mechanistic evidence on the biological processes that shape metabolic aging, with particular emphasis on inflammaging, immunosenescence, cellular senescence, oxidative stress, mitochondrial dysfunction, adipose tissue dysfunction, endothelial injury, and inflammation-related microRNAs. We first discuss how chronic low-grade inflammation and immune remodeling alter the interpretation of conventional metabolic syndrome components in older adults. We then review redox imbalance and mitochondrial stress as amplifiers of insulin resistance, lipid injury, vascular dysfunction, and tissue remodeling. The review also examines inflammation-related microRNAs, including circulating and extracellular-vesicle-associated miRNAs, as post-transcriptional regulators that may connect inflammatory, metabolic, and redox pathways. Finally, we discuss how conventional metabolic markers may be integrated with inflammatory mediators, oxidative-stress indicators, adipokines, endothelial and senescence-related markers, and miRNA profiles to improve biological interpretation of metabolic risk. Within this context, we present the Inflammaging–Redox–InflammamiR Axis as a conceptual framework for organizing these overlapping mechanisms rather than as an established diagnostic or causal model. The proposed biomarker tiers and candidate risk phenotypes are author-derived, hypothesis-generating constructs intended to guide future longitudinal and interventional research. Clinical translation will require standardized assays, longitudinal validation, external replication, and intervention studies.

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a major global health challenge due to its high prevalence and association with chronic complications, highlighting the need for reliable predictive tools to support clinical decision-making. Methods: This study proposes a two-stage hierarchical prediction system based on a Random Forest (RF) classifier. In Stage 1, the model performs multiclass classification into healthy (H), T2DM without complications (D), and T2DM with complications (C). In Stage 2, patients classified as C are further stratified into microvascular or macrovascular complications. The dataset included 31 biochemical, molecular, inflammatory, and oxidative stress variables from Mexican and Spanish cohorts. Feature selection was performed using Pearson correlation, and feature relevance was further assessed using RF importance measures. Model training used stratified cross-validation, with additional evaluation on a hold-out set to approximate real-world performance. Results: The optimized RF achieved an accuracy of 92% and a macro F1-score of 0.92, outperforming baseline models, with an AUC-ROC of 0.89 for complication prediction. Key predictive features included IL-18, miR-126, duration of T2DM, HbA1c, and IL-10. Conclusions: The novelty of this study lies in integrating heterogeneous biomarkers within a hierarchical predictive framework, rather than in the machine learning algorithm itself. This multimodal approach, combined with interpretable machine learning techniques, is designed to deliver clinically meaningful insights for patient stratification and personalized management in T2DM.

Type 2 diabetes mellitus (T2DM) is a major driver of chronic kidney disease and cardiovascular morbidity worldwide. Extracellular vesicles (EVs), particularly exosomes, carry microRNAs (miRNAs) that reflect the pathophysiological state of their parent cells and represent promising non-invasive biomarkers. This review comprehensively examines the diagnostic and mechanistic roles of EV-derived miRNAs in diabetic nephropathy (DN) and cardiovascular diseases (CVDs) associated with T2DM. A PRISMA-guided literature search of PubMed, Scopus, Web of Science, and Embase identified 847 articles published between January 2020 and June 2026, of which 156 studies met the inclusion criteria. Several urinary exosomal miRNAs demonstrated significant diagnostic performance for DN, including miR-4534 (AUC = 0.786), miR-136-5p (sensitivity 72.2%, specificity 78.4%), and miR-142-3p. A meta-analysis of circulating miRNAs in diabetic kidney disease reported a pooled AUC of 0.79. In the cardiovascular setting, exosomal miR-155-5p (AUC = 0.901), miR-15a-3p (AUC = 0.874), and a four-miRNA panel (miR-433-3p/let-7b/miR-30-5p/miR-122-5p; AUC = 0.833) demonstrated strong diagnostic performance for ischemic heart disease and carotid atherosclerosis in T2DM. Mechanistically, key EV-associated miRNAs, including miR-21, miR-192, and the anti-fibrotic miR-29 family, participate in fibrosis, inflammation, oxidative stress, endothelial dysfunction, and cardiac remodeling pathways. EV-derived miRNAs therefore represent highly promising non-invasive biomarkers for the early diagnosis and monitoring of diabetic renal and cardiovascular complications. However, clinical translation requires standardized EV isolation and miRNA detection protocols, together with validation in large multicenter prospective cohorts. This review highlights the considerable diagnostic and translational potential of EV-derived miRNAs for precision medicine and liquid biopsy applications in T2DM complications.

The article analyzes the prevalence of the metabolically healthy obesity (MHO) phenotype concerning age and gender. Similar to global studies, the criteria for this phenotype are actively being investigated in Kazakhstan. In 2017, the Kazakhstan Cardiology Center (KCC) presented a draft of recommendations regarding obesity. A key question revolves around the feasibility of classifying patients with metabolically healthy obesity phenotypes. It has been suggested that phenotype should be defined for each body mass index (BMI) group based on the waist-to-hip ratio. The findings indicate that the frequency of metabolic syndrome varies significantly depending on the classification used. Among women, metabolically healthy obesity phenotype occurs more frequently than in men, though its prevalence decreases with age. Individuals with metabolic syndrome, an increase in mean arterial pressure while maintaining normal levels of cholesterol, triglycerides, and high-density lipoproteins, regardless of the classification used. When using the KCC criteria to define MHO, the frequency of cardiometabolic risk factors was higher compared to other criteria. The conducted study revealed variability in the frequency of metabolic syndrome depending on the criteria used for classification: International Diabetes Federation (IDF) (2021) — 23.2 %, KCC (2021) — 27.1 %, NCEP ATP III (2021) — 41.8 %. Depending on age, the frequency of MHO phenotype in menopausal women showed a sta[1]tistically significant increase across all classifications. A notable decline in the prevalence of is observed in statistical indicators among women over the age of 55.

To assay new circulating markers related to macrovascular complications (MVC) in type 2 diabetes mellitus (T2DM), we carried out a descriptive cross-sectional study. We recruited 30 controls (CG), 34 patients with T2DM (DG), and 28 patients with T2DM and vascular complications (DG+C); among them, 22 presented MVC. Peripheral blood was used to determine redox status (superoxide dismutase, SOD; catalase, CAT; glutathione reductase, GRd; glutathione peroxidase, GPx; glucose-6-phosphate dehydrogenase, G6PD) and markers of oxidative damage (advanced oxidation protein products, AOPP; lipid peroxidation, LPO), nitrite levels in plasma (NOx). Inflammatory markers (IL-1β, IL-6, IL-10, IL-18, MCP-1, TNF-α) and the relative expression of c-miRNAs were analyzed. The real-time PCR results showed that the expressions of miR-155-5p, miR-21-5p, miR-146a-3p, and miR-210-3p were significantly higher in the DG group compared to the CG. The DG+C group presented statistically relevant differences with CG for four miRs: the increased expression of miR-484-5p, miR-21-5p, and miR-210-3p, and decreased expression of miR-126a-3p. Moreover, miR-126a-3p was significantly less expressed in DG+C compared to DG. The application of binary logistic regression analysis and construction of receiving operator characteristic curves (ROC) revealed two models with high predictive values for vascular complications presence: (1) HbAc1, creatinine, total cholesterol (TC), LPO, GPx, SOD, miR-126, miR-484 (Exp(B) = 0.926, chi² = 34.093, p < 0.001; AUC = 0.913). (2) HbAc1, creatinine, TC, IL-6, LPO, miR-126, miR-484 (Exp(B) = 0.958, Chi² = 33.863, p < 0.001; AUC = 0.938). Moreover, our data demonstrated that gender, TC, GPx, CAT, and miR-484 were associated with MVC and exhibited higher predictive values (Exp(B) = 0.528, p = 0.024, Chi² = 28.214, AUC = 0.904) than classical variables (Exp(B) 0.462, p = 0.007, Chi² = 18.814, AUC = 0.850). miR-126, miR-484, IL-6, SOD, CAT, and GPx participate in vascular damage development in the studied diabetic population and should be considered for future studies.

To evaluate new circulating markers related to macrovascular complications (MVC) in type 2 diabetes mellitus (T2DM), we recruited 30 controls (CG), 34 patients with T2DM (DG), and 28 patients with T2DM and vascular complications (DG+C), among them, 22 presented MVC. Pe-ripheral blood was used to determine redox status (superoxide dismutase, SOD; catalase, CAT; glutathione reductase, GRd; glutathione peroxidase, GPx; glucose-6-phosphate dehydrogenase, G6PD) and markers of oxidative damage (advanced oxidation protein products, AOPP; lipid pe-roxidation, LPO). Inflammatory markers (IL-1β, IL-6, IL-10, IL-18, MCP-1, TNF-α) and the relative expression of c-miRNAs were analyzed. The real-time PCR results showed that the expressions of miR-155-5p, miR-21-5p, miR-146a-3p, and miR-210-3p were significantly higher in the DG group compared to CG. DG+C group presented statistically relevant differences with CG for four miRs: the increased expression of miR-484-5p, miR-21-5p, and miR-210-3p, and decreased for miR-126a-3p. Moreover, miR-126a-3p was significantly less expressed in DG+C compared to DG. The application of binary logistic regression analysis and construction of receiving operator characteristic curves (ROC) revealed two models with high predictive value for vascular complications presence: 1) HbAc1, creatinine, total cholesterol (TC), LPO, GPx, SOD, miR-126, miR-484. 2) HbAc1, creatinine, TC, IL-6, LPO, miR-126, miR-484. Moreover, our data demonstrated that gender, TC, GPx, CAT, and miR-484 were associated with MVC and exhibited higher predictive values than classical variables. miR-126, miR-484, IL-6, SOD, CAT, and GPx participate in vascular damage development in the studied diabetic population and should be considered for future studies.

The development of type 2 diabetes mellitus (T2DM) vascular complications (VCs) is associated with oxidative stress and chronic inflammation and can result in endothelial dysfunctions. Circulating microRNAs play an important role in epigenetic regulation of the etiology of T2DM. We studied 30 healthy volunteers, 26 T2DM patients with no complications, and 26 T2DM patients with VCs, to look for new biomarkers indicating a risk of developing VCs in T2DM patients. Peripheral blood samples were used to determine redox state, by measuring the endogenous antioxidant defense system (superoxide dismutase, SOD; catalase, CAT; glutathione reductase, GRd; glutathione peroxidase, GPx; and glucose-6-phosphate dehydrogenase, G6DP) and markers of oxidative damage (advanced oxidation protein products, AOPP; lipid peroxidation, LPO). Additionally, inflammatory marker levels (IL-1, IL-6, IL-18, and TNF-α), c-miR-21, and c-miR-126 expression were analyzed. T2DM patients showed the highest oxidative damage with increased GSSG/GSH ratios, LPO, and AOPP levels. In both diabetic groups, we found that diminished SOD activity was accompanied by increased CAT and decreased GRd and G6PD activities. Diabetic patients presented with increased relative expression of c-miR-21 and decreased relative expression of c-miR-126. Overall, c-miR-21, SOD, CAT, and IL-6 had high predictive values for diabetes diagnoses. Finally, our data demonstrated that IL-6 exhibited predictive value for VC development in the studied population. Moreover, c-miR-21 and c-miR-126, along with GPx and AOPP levels, should be considered possible markers for VC development in future studies.

Pancreatic cancer (PC) is a lethal malignancy cancer, and its mortality rates have been increasing worldwide. Diagnosis of this cancer is complicated, as it does not often present symptoms, and most patients present an irremediable tumor having a 5‐year survival rate after diagnosis. Regarding treatment, many concerns have also been raised, as most tumors are found at advanced stages. At present, anticancer compounds‐rich foods have been utilized to control PC. Among such bioactive molecules, flavonoid compounds have shown excellent anticancer abilities, such as quercetin, which has been used as an adjunctive or alternative drug to PC treatment by inhibitory or stimulatory biological mechanisms including autophagy, apoptosis, cell growth reduction or inhibition, EMT, oxidative stress, and enhancing sensitivity to chemotherapy agents. The recognition that this natural product has beneficial effects on cancer treatment has boosted the researchers’ interest towards more extensive studies to use herbal medicine for anticancer purposes. In addition, due to the expensive cost and high rate of side effects of anticancer drugs, attempts have been made to use quercetin but also other flavonoids for preventing and treating PC. Based on related studies, it has been found that the quercetin compound has significant effect on cancerous cell lines as well as animal models. Therefore, it can be used as a supplementary drug to treat a variety of cancers, particularly pancreatic cancer. This review is aimed at discussing the therapeutic effects of quercetin by targeting the molecular signaling pathway and identifying antigrowth, cell proliferation, antioxidative stress, EMT, induction of apoptotic, and autophagic features.