Bahar Darouei

Chronic inflammation may contribute to breast cancer (BC). The Dietary Inflammatory Index (DII) and energy‐adjusted DII (E‐DII) quantify the inflammatory potential of diet. This case–control study evaluated associations of the DII and E‐DII with BC risk among Iranian women. We recruited 600 newly diagnosed BC cases and 600 population‐based controls from Isfahan, Iran. Dietary intake was assessed using a validated 168‐item food frequency questionnaire (FFQ). DII and E‐DII scores were calculated based on 26 and 25 food parameters, respectively. Logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Multivariable‐adjusted models accounted for confounders including age, body mass index, reproductive history, and sunlight exposure. Higher E‐DII scores were significantly associated with an increased odds of developing BC. In the fully adjusted models, women in the highest quartile of the E‐DII had 63% greater risk than those in the lowest quartile (adjusted OR: 1.63; 95% CI: 1.08–2.45). Analyses based on continuous E‐DII also showed that each unit increase in the E‐DII score was linked to a 14% increase in BC odds (adjusted OR: 1.14; 95% CI: 1.05–1.24). In contrast, DII scores were not significantly associated with BC risk in any of the models. This study demonstrated that diets with stronger inflammatory properties, indicated by elevated E‐DII scores, are associated with a higher risk of BC among Iranian women. These outcomes underline the value of using energy‐normalized inflammatory indices when assessing dietary influences on cancer risk.

Background: Ischemic heart disease (IHD) remains a major cause of morbidity and mortality in Iran, but evidence is dispersed across model‐based estimates, population studies, registries, hospital surveillance, and death‐registration data. We synthesized national and subnational evidence on IHD burden in Iran from 1990 to 2023. Methods: PubMed/MEDLINE and Scopus were searched through August 15, 2026, supplemented by Google Scholar and citation searching. Eligible studies reported incidence, prevalence, mortality, hospitalization, case fatality, post‐myocardial infarction survival, or burden‐of‐disease measures. Model‐based and empirical evidence were synthesized separately, overlapping data sources were mapped, and findings were narratively synthesized because of heterogeneity. Results: Fifty‐two reports representing 35 evidence‐source families were included. Within GBD 2019, age‐standardized IHD mortality declined from 285.7 to 163.6 per 100 000 between 1990 and 2019, incidence from 898.3 to 829.1, and prevalence from 6250.6 to 6198.5 per 100 000, while incident cases increased from 218 181 to 593 001. Successive GBD vintages also showed declining age‐standardized mortality but were not directly comparable because of modeling differences. Empirical studies generally showed higher coronary event rates in men, while Isfahan surveillance and the Iranian MI Registry indicated higher short‐term post‐MI case fatality among women. Burden increased with age, provincial variation was substantial, and urban‐rural patterns were inconsistent. Hospital surveillance suggested improving short‐term outcomes. Conclusions: Successive GBD analyses estimated substantial declines in age‐standardized IHD mortality, while absolute burden remained large and differences persisted by age, sex, geography, and data source. Stronger prevention and geographically representative surveillance are needed.

Background: Machine learning (ML) models are increasingly used to predict adverse outcomes after transcatheter aortic valve replacement (TAVR), but their generalizability and clinical readiness remain uncertain. We evaluated predictive performance across post-TAVR outcomes, emphasizing validation quality, transportability, methodological bias, and clinical utility. Methods: PubMed/MEDLINE, Embase, Scopus, and Web of Science were searched from inception through 6 August 2026 for supervised ML studies reporting out-of-sample performance for clinically relevant post-TAVR outcomes. Overlapping source populations were audited before synthesis. Areas under the receiver operating characteristic curve (AUCs) were pooled on the logit scale using restricted maximum likelihood (REML) random-effects models with modified Hartung–Knapp inference and prediction intervals. Prespecified analyses examined validation maturity, predictor timing, prediction horizon, data architecture, and risk of bias. Within-study dependence was addressed using multilevel meta-regression with bias-reduced cluster-robust variance estimation (CR2); Bayesian analyses complemented the primary synthesis. Results: Sixty-seven full-text reports were included. Twenty independent source/report families contributed to mortality meta-analysis, yielding a pooled AUC of 0.791 (95% confidence interval [CI], 0.732–0.840; I² = 91.5%; prediction interval, 0.480–0.940). The high heterogeneity and wide prediction interval indicate that this pooled AUC is an average across heterogeneous settings rather than a transportable performance guarantee. Stronger external, temporal, geographic, or inter-centre evaluation showed lower discrimination than internal/resampled evaluation (0.754 vs. 0.814; p = 0.299), while preprocedural models yielded 0.767 versus 0.866 for peri-/postprocedural or mixed models (p = 0.083). High-risk studies showed higher apparent mortality discrimination than low/unclear-risk studies (0.895 vs. 0.747; p for interaction = 0.0009); this observational comparison involved only five high-risk mortality studies and should not be interpreted causally. The Bayesian-adjusted difference was +0.118 AUC units (95% credible interval [CrI], +0.037 to +0.179). Pooled AUCs were 0.760 for permanent pacemaker implantation (PPMI), 0.778 for broader conduction abnormalities, and 0.747 for paravalvular leak (PVL). No algorithm family showed reproducible superiority (p = 0.775). Stronger independent evaluation, calibration/Brier assessment, and decision-curve analysis were reported in only 18/67, 23/67, and 10/67 reports, respectively. Conclusions: ML shows promising post-TAVR discrimination, particularly for mortality, but substantial heterogeneity, limited independent validation, and sparse calibration and decision utility assessment constrain clinical translation. A high AUC alone should not be interpreted as evidence of transportability or clinical usefulness.

Copper is an essential trace element required for mitochondrial respiration, redox regulation, iron metabolism, and cellular signalling, but excessive or mislocalised copper can be cytotoxic. Cuproptosis is a recently identified form of regulated cell death in which copper binds to lipoylated mitochondrial proteins, promotes their aggregation, destabilises iron–sulfur cluster proteins, and induces mitochondrial proteotoxic stress. Copper therefore has context-dependent roles in cancer. Physiological copper supports tumour metabolism, angiogenesis, extracellular-matrix remodelling, and selected oncogenic signalling pathways, whereas therapeutic copper depletion can inhibit copper-dependent tumour processes. Conversely, copper ionophores and related approaches may increase intracellular copper sufficiently to induce cuproptosis in metabolically susceptible cancer cells. This review describes systemic and intracellular copper homeostasis, including intestinal absorption, intracellular trafficking, mitochondrial copper distribution, storage, and export. Particular attention is given to CTR1/SLC31A1, the functionally distinct copper-transporting ATPases ATP7A and ATP7B, metallothioneins, copper chaperones, and cytochrome c oxidase assembly factors. We also examine how cancer cells reprogramme copper handling to support proliferation, angiogenesis, metastasis, and immune evasion. Finally, we discuss the molecular basis of cuproptosis, including the roles of FDX1, FDXR, LIAS, DLAT, mitochondrial respiration, protein lipoylation, and iron–sulfur cluster destabilisation. Current evidence indicates that cuproptosis susceptibility varies among tumour types and depends on copper handling, mitochondrial metabolic state, and the integrity of the protein-lipoylation machinery. Defining these determinants will be necessary for the development of tumour-selective copper-targeted therapies. Graphical abstract

Background: The atherogenic index of plasma (AIP) is a lipid‐based indicator of cardiometabolic risk. We examined whether AIP is associated with prevalent type 2 diabetes mellitus (T2DM) and fasting blood sugar (FBS) in patients with premature coronary artery disease (PCAD) and explored whether this association differed across Iranian ethnic groups. Methods: We analysed 2143 patients with angiographically confirmed PCAD from the Iran Premature Coronary Artery Disease (IPAD) study, of whom 1945 had valid AIP data. CAD was defined as ≥ 50% stenosis in the left main artery or ≥ 75% stenosis in another major coronary vessel. AIP was calculated as log ₁₀ (triglycerides/high‐density lipoprotein cholesterol). Multivariable logistic regression was used to assess the association between AIP and prevalent T2DM, and generalized linear models were used to assess the association between AIP and FBS. Results: In the fully adjusted model, including lipid‐lowering medication use, participants in the highest AIP quartile had higher odds of prevalent T2DM than those in the lowest quartile (OR: 1.57; 95% CI: 1.14, 2.16; p = 0.005; P for trend = 0.002). Each 1‐unit increase in AIP was associated with higher odds of prevalent T2DM (OR: 1.99; 95% CI: 1.26, 3.14; p = 0.003). Higher AIP was also associated with higher FBS; compared with the lowest quartile, the highest quartile had a 15.23 mg/dL higher FBS level in the fully adjusted model (95% CI: 7.61, 22.84; p < 0.001). In exploratory ethnicity‐stratified analyses, the association was most evident in the Fars subgroup, while estimates in several smaller ethnic groups were imprecise. Conclusions: Higher AIP was associated with prevalent T2DM and higher FBS in patients with PCAD. Exploratory analyses suggested possible ethnicity‐related heterogeneity, but these subgroup findings should be interpreted cautiously. Prospective studies are needed to determine whether AIP has predictive or clinical risk‐stratification value in this population.

Background: The triglyceride-glucose (TyG) index is an accessible marker of insulin resistance and may reflect metabolic susceptibility to kidney stone disease (KSD). This review synthesizes observational evidence on TyG and KSD and examines whether the association varies with increasing TyG. Methods: PubMed, Embase, Web of Science, Scopus, the Cochrane Library, and ProQuest were searched up to May 22, 2026 according to PRISMA 2020 and a PROSPERO-registered protocol. Eligible studies enrolled adults, assessed TyG as either a continuous or categorical exposure, reported KSD as the outcome, and provided extractable effect estimates. Study quality was evaluated using the Joanna Briggs Institute (JBI) tools. Maximally adjusted odds ratios (ORs) were synthesized using the restricted maximum likelihood (REML) random-effects model. One-stage dose-response meta-analyses using linear and restricted cubic spline models were also conducted, and the certainty of evidence was judged using GRADE. Results: Fourteen studies (total n = 1,066,215; KSD cases = 50,286) met the inclusion criteria. In the continuous analysis, each 1-unit increment in TyG corresponded to higher KSD odds (pooled adjusted OR: 1.33; 95% confidence interval [CI]: 1.15–1.54). Compared with the lowest TyG category, the highest had 52% higher odds of KSD (OR: 1.52; 95% CI: 1.26–1.84). In a one-stage random-effects dose-response meta-analysis, restricted cubic spline models provided the best fit but showed no statistical evidence of non-linearity, supporting a linear association with a 26% increase in odds per 1-unit increase in TyG (OR: 1.26; 95% CI: 1.12–1.42; 95% PI: 0.91–1.75). Conclusion: A higher TyG index was associated with greater odds of KSD in a broadly linear manner; however, the marked heterogeneity across studies suggests that TyG should be viewed as a potential metabolic risk marker rather than a routine screening tool. These findings may support broader cardiometabolic risk assessment and standard preventive counseling in patients at risk of KSD.

Constrictive pericarditis (CP) is characterized by the thickening and scarring of the pericardium, often leading to impaired cardiac function. CP can have systemic effects, including congestive hepatopathy, which may increase liver stiffness and, in chronic cases, contribute to fibrosis. A pericardiectomy is the best choice of treatment in these patients and can alleviate cardiac dysfunction, potentially improving associated systemic conditions; however, concomitant liver dysfunction and three-vessel disease can make pericardiectomy a challenging surgery in these patients. Also, marked improvement in liver stiffness after surgical relief of constrictive physiology is rarely documented in the literature. A 62-year-old man with a history of coronary artery disease (CAD) presented with abdominal pain and distention, edema, unintentional weight loss, and dyspnea. Transient elastography showed markedly elevated liver stiffness compatible with advanced fibrosis, although congestion-related overestimation could not be excluded. Due to concern for cardiac etiology, cardiac magnetic resonance imaging (CMR) was performed, which indicated constrictive pericarditis (CP). Also, the patient was a candidate for coronary artery bypass grafting (CABG) due to three-vessel disease shown in his recent angiography. The patient underwent simultaneous pericardiectomy and coronary CABG with subsequent improvement of his symptoms. Follow-up at six months showed normal heart function and reduced liver size, and follow-up transient elastography 19 months later showed marked reduction in liver stiffness. This case highlights that severe liver stiffness abnormalities in CP may substantially improve after surgical relief of constrictive physiology. The concomitant performance of CABG likely contributed to improved overall cardiac function and systemic hemodynamics, further facilitating liver recovery. Early recognition using multimodality imaging, including CMR, and timely intervention in patients with CP and liver stiffness abnormalities may facilitate hepatic recovery and prevent persistent end-organ dysfunction.

Background: Kidney dysfunction is common in patients with advanced heart failure and is associated with adverse clinical outcomes. Left ventricular assist device (LVAD) implantation may influence renal function through hemodynamic and cardiorenal changes. We performed a meta-analysis to evaluate longitudinal changes in estimated glomerular filtration rate (eGFR) following LVAD implantation. Results: We systematically searched six databases for studies reporting eGFR before and after LVAD implantation until March 2026. The primary analysis used a multivariate random-effects meta-analysis to jointly pool repeated follow-up estimates while accounting for within-study dependence across time points. Pooled mean changes in eGFR and 95% confidence intervals (CIs) were estimated at 1 week, 2 weeks, 1 month, 3 months, 6 months, 9 months, 1 year, 2 years, and 3 years after implantation. A total of 38 studies contributing 95 effect sizes were included. Compared with baseline, pooled mean eGFR was significantly higher at 1 week (18.83 mL/min/1.73 m²; 95% CI: 13.21, 24.46), 2 weeks (18.29; 95% CI: 12.11, 24.48), 1 month (23.77; 95% CI, 19.48, 28.07), 3 months (15.20; 95% CI: 10.95, 19.46), 6 months (7.97; 95% CI: 3.72, 12.22), 9 months (8.27; 95% CI: 2.10, 14.44), and 1 year (7.34; 95% CI: 2.83, 11.85), but not at 2 or 3 years. In subgroup analyses, studies with baseline eGFR < 60 mL/min/1.73 m² showed significant increases across all evaluated follow-up intervals, whereas those with baseline eGFR ≥ 60 mL/min/1.73 m² showed significant increases only through 3 months. Conclusions: LVAD implantation was associated with higher eGFR during the early postoperative period, with the largest increase observed at 1 month. However, because most included studies were pre-post analyses without non-LVAD comparator groups, these findings should be interpreted cautiously and do not establish a causal effect. Future research should explore the long-term impact of LVAD on renal health to optimize care strategies and outcomes.