Cynthia Al Hageh

Diabetic cardiomyopathy (DbCM) impairs cardiac performance through complex mechanisms, which limits effective therapies. We investigated the protein networks of calmodulin (CaM), a striatin (STRN)-binding protein implicated in DbCM, and compared them with the STRN network from the same tissues. Using CaM as bait, we precipitated protein clusters from left ventricles (LVs) of diabetic rat hearts at 8 and 24 weeks post-streptozotocin (post-STZ). Diabetic rats exhibited pathological remodeling, evidenced by increased heart-to-body weight ratio, β-MHC protein, and ANF mRNA expression. Western blotting showed elevated STRN, but not PP2A-A or -C subunits, in chronic stages. Proteomic analysis at 24 weeks revealed 49 differentially interacting proteins (DIPs) with CaM: 18 enhanced and 31 diminished in diabetic LVs. Functional annotation highlighted the recruitment of proteins in metabolic pathways (fatty acid elongation and lipid metabolism) and PPAR signaling, alongside reduced interactions in lipid response, glucocorticoid response, calcium signaling, and amino acid biosynthesis. Comparative analysis of CaM and STRN interactomes converged to 231 proteins implicated mainly in metabolic processes. Out of these, three proteins (Hnrnpm, Acot7, and Gsta3) surfaced as regulators of metabolic, oxidative, and post-transcriptional remodeling. These findings reveal novel functional roles for the CaM/STRN complex in DbCM and identify a shared signaling hub that may guide therapeutic strategies for diabetes-associated cardiac deterioration.

Identification de biomarqueurs de risque de la sténose aortique chez l'Homme : contribution des stratégies de profilage métabolomique non ciblée de biofluides: La sténose de la valve aortique (SVA) est la maladie cardiaque valvulaire fréquente. Elle se produit chez des personnes souvent âgées lorsque les feuillets de la valve deviennent épais, calcifiés et rétrécis, ce qui réduit le flux sanguin du ventricule gauche vers l'aorte. La SVA est souvent diagnostiquée tardivement, après le développement des symptômes et lorsque la maladie devient sévère. La progression de la maladie est rapide et, si elle n'est pas traitée, entraîne une insuffisance cardiaque et le décès des patients. Aucun traitement pharmacologique n'est efficace pour arrêter ou retarder sa progression. Le seul traitement disponible est le remplacement de la valve sténosée par une intervention chirurgicale ou par un cathéter. Ces méthodes sont invasives, coûteuses et présentent des complications. Il est important de comprendre l'étiologie et la pathogenèse de la SVA pour développer des solutions thérapeutiques et de diagnostic précoce efficaces. L'objectif de ma recherche a consisté dans l'identification de modifications métaboliques chez des patients atteints de SVA en utilisant des technologies complémentaires de profilage du métabolome. Des échantillons de 46 cas atteints de SVA et 46 sujets contrôles ont été utilisés. Les technologies d'analyse du métabolome utilisées ont été basées sur un profilage (1) non ciblé par chromatographie en phase gazeuse et la spectrométrie de masse (GC/MS) sur des échantillons d'urine et de plasma et (2) non ciblé et ciblé par spectroscopie de résonance magnétique nucléaire du proton (RMN 1H) sur des échantillons d'urine. De plus, une approche lipidomique non ciblée basée sur la spectrométrie de masse à temps de vol avec ionisation par désorption laser assistée par matrice (MALDI-TOF/MS) a été appliquée sur des échantillons de plasma pour analyser les lipides. La détection de différences quantitatives de métabolites entre cas et contrôles a été effectuée par analyses de régression. Des échantillons cardiaques de souris traités chroniquement par des métabolites candidats ont été utilisés pour tester leurs effets sur l'expression de gènes liés aux maladies cardiovasculaires. Des associations significatives ont été identifiées entre la SVA et 21 métabolites plasmatiques (GC/MS), et 22 (GC/MS) et 21 (RMN) métabolites urinaires. Environ 50% des associations étaient significatives dans les deux bio-fluides. En analyse ciblée par RMN, une association a été détectée entre la SVA et six métabolites connus, dont l'hippurate et la trigonelline. L'étude du lipidome a identifié des différences entre cas et contrôles pour 22 ions, dont plusieurs correspondent à des lysophosphatidylcholines, la lysophosphatidylcholine oxydée et les phosphatidylcholines. Le traitement de souris par l'hippurate et son précurseur le benzoate conduit à des altérations significatives de l'expression cardiaque de Bmp6, Cxcl9 et Mcp1. Mes résultats ont permis d'identifier des modifications significatives dans la régulation de métabolites plasmatiques et urinaires de patients atteints de SVA, qui peuvent servir d'outils moléculaires dans le diagnostic et le traitement de la maladie. En outre, ils soulignent l'importance de combiner plusieurs technologies complémentaires pour le profilage du métabolome d'échantillons humains et l'identification de biomarqueurs candidats de la maladie.

Background: Artificial intelligence (AI) has the potential to revolutionize the way medicine is learned, taught, and practiced, and medical education must prepare learners for these inevitable changes. Academic medicine has, however, been slow to embrace recent AI advances. Since its launch in November 2022, ChatGPT has emerged as a fast and user-friendly large language model that can assist health care professionals, medical educators, students, trainees, and patients. While many studies focus on the technology’s capabilities, potential, and risks, there is a gap in studying the perspective of end users. Objective: The aim of this study was to gauge the experiences and perspectives of graduating medical students on ChatGPT and AI in their training and future careers. Methods: A cross-sectional web-based survey of recently graduated medical students was conducted in an international academic medical center between May 5, 2023, and June 13, 2023. Descriptive statistics were used to tabulate variable frequencies. Results: Of 325 applicants to the residency programs, 265 completed the survey (an 81.5% response rate). The vast majority of respondents denied using ChatGPT in medical school, with 20.4% (n=54) using it to help complete written assessments and only 9.4% using the technology in their clinical work (n=25). More students planned to use it during residency, primarily for exploring new medical topics and research (n=168, 63.4%) and exam preparation (n=151, 57%). Male students were significantly more likely to believe that AI will improve diagnostic accuracy (n=47, 51.7% vs n=69, 39.7%; P=.001), reduce medical error (n=53, 58.2% vs n=71, 40.8%; P=.002), and improve patient care (n=60, 65.9% vs n=95, 54.6%; P=.007). Previous experience with AI was significantly associated with positive AI perception in terms of improving patient care, decreasing medical errors and misdiagnoses, and increasing the accuracy of diagnoses (P=.001, P<.001, P=.008, respectively). Conclusions: The surveyed medical students had minimal formal and informal experience with AI tools and limited perceptions of the potential uses of AI in health care but had overall positive views of ChatGPT and AI and were optimistic about the future of AI in medical education and health care. Structured curricula and formal policies and guidelines are needed to adequately prepare medical learners for the forthcoming integration of AI in medicine.

Diabetes mellitus is a metabolic disorder denoted by chronic hyperglycemia that drives maladaptive structural changes and functional damage to the vasculature. Attenuation of this pathological remodeling of blood vessels remains an unmet target owing to paucity of information on the metabolic signatures of this process. Ca²⁺/calmodulin-dependent kinase II (CaMKII) is expressed in the vasculature and is implicated in the control of blood vessels homeostasis. Recently, CaMKII has attracted a special attention in view of its chronic upregulated activity in diabetic tissues, yet its role in the diabetic vasculature remains under investigation.This review highlights the physiological and pathological actions of CaMKII in the diabetic vasculature, with focus on the control of the dialogue between endothelial (EC) and vascular smooth muscle cells (VSMC). Activation of CaMKII enhances EC and VSMC proliferation and migration, and increases the production of extracellular matrix which leads to maladaptive remodeling of vessels. This is manifested by activation of genes/proteins implicated in the control of the cell cycle, cytoskeleton organization, proliferation, migration, and inflammation. Endothelial dysfunction is paralleled by impaired nitric oxide signaling, which is also influenced by CaMKII signaling (activation/oxidation). The efficiency of CaMKII inhibitors is currently being tested in animal models, with a focus on the genetic pathways involved in the regulation of CaMKII expression (microRNAs and single nucleotide polymorphisms). Interestingly, studies highlight an interaction between the anti-diabetic drugs and CaMKII expression/activity which requires further investigation. Together, the studies reviewed herein may guide pharmacological approaches to improve health-related outcomes in patients with diabetes.

BACKGROUND Artificial intelligence (AI) has the potential to revolutionize the way medicine is learned, taught, and practiced, and medical education must prepare learners for these inevitable changes. Academic medicine has, however, been slow to embrace recent AI advances. Since its launch in November 2022, ChatGPT has emerged as a fast and user-friendly large language model that can assist health care professionals, medical educators, students, trainees, and patients. While many studies focus on the technology’s capabilities, potential, and risks, there is a gap in studying the perspective of end users. OBJECTIVE The aim of this study was to gauge the experiences and perspectives of graduating medical students on ChatGPT and AI in their training and future careers. METHODS A cross-sectional web-based survey of recently graduated medical students was conducted in an international academic medical center between May 5, 2023, and June 13, 2023. Descriptive statistics were used to tabulate variable frequencies. RESULTS Of 325 applicants to the residency programs, 265 completed the survey (an 81.5% response rate). The vast majority of respondents denied using ChatGPT in medical school, with 20.4% (n=54) using it to help complete written assessments and only 9.4% using the technology in their clinical work (n=25). More students planned to use it during residency, primarily for exploring new medical topics and research (n=168, 63.4%) and exam preparation (n=151, 57%). Male students were significantly more likely to believe that AI will improve diagnostic accuracy (n=47, 51.7% vs n=69, 39.7%; P=.001), reduce medical error (n=53, 58.2% vs n=71, 40.8%; P=.002), and improve patient care (n=60, 65.9% vs n=95, 54.6%; P=.007). Previous experience with AI was significantly associated with positive AI perception in terms of improving patient care, decreasing medical errors and misdiagnoses, and increasing the accuracy of diagnoses (P=.001, P<.001, P=.008, respectively). CONCLUSIONS The surveyed medical students had minimal formal and informal experience with AI tools and limited perceptions of the potential uses of AI in health care but had overall positive views of ChatGPT and AI and were optimistic about the future of AI in medical education and health care. Structured curricula and formal policies and guidelines are needed to adequately prepare medical learners for the forthcoming integration of AI in medicine.

Background and Objective: Coronary artery disease (CAD) is a major cause of death worldwide. Revascularization via stent placement or coronary artery bypass grafting (CABG) are standard treatments for CAD. Despite a high success rate, these approaches are associated with long-term failure due to restenosis. Risk factors associated with restenosis were investigated using a case-control association study design. Methods: Five thousand two hundred and forty-two patients were enrolled in this study and were assigned as follows: Stenosis Group: 3570 patients with CAD > 50% without a prior stent or CABG (1394 genotyped), and Restenosis Group: 1672 patients with CAD > 50% and prior stent deployment or CABG (705 genotyped). Binomial regression models were applied to investigate the association of restenosis with diabetes, hypertension, and dyslipidemia. The genetic association with restenosis was conducted using PLINK 1.9. Results: Dyslipidemia is a major risk factor (Odds Ratio (OR) = 2.14, P-value < 0.0001) for restenosis particularly among men (OR = 2.32, P < 0.0001), while type 2 diabetes (T2D) was associated with an increased risk of restenosis in women (OR = 1.36, P = 0.01). The rs9349379 (PHACTR1) and rs264 (LPL) were associated with an increased risk of restenosis in our patients. PHACTR1 variant was associated with increased risk of restenosis mainly in women and in diabetic patients, while the LPL variant was associated with increased risk of restenosis in men. Conclusion: The rs9349379 in PHACTR1 gene is significantly associated with restenosis, this association is more pronounced in women and in diabetic patients. The rs264 in LPL gene was associated with increased risk of restenosis in male patients.

Backgrounds and Aims: The role of Lipoprotein(a) (Lp(a)) in increasing the risk of cardiovascular diseases is reported in several populations. The aim of this study is to investigate the correlation of high Lp(a) levels with the degree of coronary artery stenosis. Methods: Two hundred and sixty-eight patients were enrolled for this study. Patients who underwent coronary artery angiography and who had Lp(a) measurements available were included in this study. Binomial logistic regressions were applied to investigate the association between Lp(a) and stenosis in the four major coronary arteries. The effect of LDL and HDL Cholesterol on modulating the association of Lp(a) with coronary artery disease (CAD) was also evaluated. Multinomial regression analysis was applied to assess the association of Lp(a) with the different degrees of stenosis in the four major coronary arteries. Results: Our analyses showed that Lp(a) is a risk factor for CAD and this risk is significantly apparent in patients with HDL-cholesterol ≥ 35 mg/dL and in non-obese patients. A large proportion of the study patients with elevated Lp(a) levels had CAD even when exhibiting high HDL serum levels. Increased HDL with low Lp(a) serum levels were the least correlated with stenosis. A significantly higher levels of Lp(a) were found in patients with > 50% stenosis in at least two major coronary vessels arguing for pronounced and multiple stenotic lesions. Finally, the derived variant (rs1084651) of the LPA gene was significantly associated with CAD. Conclusion: Our study highlights the importance of Lp(a) levels as an independent biological marker of severe and multiple coronary artery stenosis.

Familial Mediterranean fever (FMF) is a recessively inherited autoinflammatory disorder. The caspase-1-dependent cytokine, IL-1β, plays an important role in FMF pathogenesis, and RAC1 protein has been recently involved in IL-1β secretion. This study aims to investigate RAC1 expression and role in IL-1β and caspase-1 production and oxidative stress generation in FMF. The study included 25 FMF patients (nine during attack and remission, and 16 during remission only), and 25 controls. RAC1 expression levels were analyzed by real-time PCR. Ex vivo production of caspase-1, IL-1β, IL-6 and markers of oxidative stress (malondialdehyde, catalase, and glutathione system) were evaluated respectively in supernatants of patients' and controls' PBMC and PMN cultures, in the presence and absence of RAC1 inhibitor. RAC1 gene expression and IL-1β levels were increased in patients in crises compared to those in remission or controls. RAC1 expression levels were correlated with MEFV genotypes, patients carrying the M694V/M694V genotype having a two-fold increase in the expression levels compared to those carrying other genotypes. Caspase-1 levels were higher in LPS-induced PBMC of patients in remission than controls. Spontaneous and LPS-induced IL-1β production were comparable in patients in remission and controls, whereas LPS-induced IL-6 production was enhanced in patients, compared to controls. RAC1 inhibition resulted in a decrease in caspase-1 and IL-1β, but not IL-6, levels. Malondialdehyde levels produced by LPS-stimulated PMNs were increased in patients in remission compared to those in controls, but decreased following RAC1 inhibition. Catalase and GSH activities were reduced in unstimulated PMN culture supernatants of patients in remission compared to controls and were increased in the presence of RAC1 inhibitor. These results show the involvement of RAC1 in the inflammatory process of FMF by enhancing IL-1β production, through caspase-1 activation, and generating oxidative stress, even during asymptomatic periods.