Publications by authors named "Zahra Azizi"

Background: Statin adherence impacts cardiovascular outcomes, yet disparities persist. Understanding sociodemographic factors and barriers is crucial for targeted interventions.

Objective: To investigate the relationship between sociodemographic factors and statin adherence across racial and ethnic groups.

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Sperm separation is pivotal in Assisted Reproductive Technology to address male infertility issues such as low sperm concentration or impaired motility. Traditional microfluidic devices, despite their fair success, often fall short due to complex fabrication and use, or lack of direct sample extraction methods. Our research introduces a microfluidic device designed to enhance sperm quality, focusing on improved motility and morphology, while remaining simple to fabricate and use in infertility clinics.

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Indoor radon exposure is the main form of radon exposure that causes health consequences including lung cancer. The aim of this study was to investigate indoor radon concentration affected by different geological characteristics in a mountainous area. For this purpose, three areas close to each other in the mountains of northern Iran, which were different in terms of the presence of hot springs, were studied.

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Objective: The plasma proteome holds promise as a diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of proteins to predict type 2 diabetes and related traits.

Study Design: We analyzed clinical, genetic, and proteomic data from three UK Biobank subcohorts for associations with truncal fat, estimated maximum oxygen consumption (VOmax), and type 2 diabetes.

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Introduction: Guideline-directed medical therapy (GDMT) for heart failure (HF) reduces adverse events, but is underused. Global barriers to GDMT optimisation include low frequency of visits, clinician inertia and poor patient knowledge, which may be mitigated by digital health interventions (DHI). In Brazil, low digital literacy and reduced access to technology may compromise these potential DHI's beneficial effects.

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Artificial intelligence (AI) is delivering value across all aspects of clinical practice. However, bias may exacerbate healthcare disparities. This review examines the origins of bias in healthcare AI, strategies for mitigation, and responsibilities of relevant stakeholders towards achieving fair and equitable use.

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Breast cancer, which is the most common cancer among women in Türkiye and throughout the world, is also one of the leading causes of cancer-related deaths. A significant factor in these deaths is metastatic breast cancer, which spreads to distant organs. The metastasis of the breast tumor follows a series of steps.

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Pancreatic cancer ranks as the fourth most common cause of cancer-related fatalities globally, with a notably low 5-year relative survival rate. We need to immediately develop fast, dependable, and noninvasive diagnostic techniques that can accurately identify pancreatic cancer at an early stage. The research project created a straightforward but effective method for detecting and increasing the amount of tumor cells that could bind to polystyrene (PS) well plates.

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Contactless and conventional dielectrophoresis (DEP) microfluidic devices are extensively utilized in lab-on-a-chip applications, particularly for cell isolation and analysis. Nonetheless, these devices typically operate at low throughput and require high applied voltages, posing limitations for microfluidic cell isolation and separation. Addressing these challenges, this study explores the utilization of diverse micro-pillar geometries within the microfluidic device to augment THP-1 cell trapping efficiency numerically using FEM modeling.

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Background: Paraquat (PQ) is a common herbicide, and its mortality results from injury to several organs, including the kidneys. Nanocurcumin and curcumin have anti-inflammatory and anti-oxidative activities, but their involvement in PQ-induced kidney damage is unclear. Therefore, the goal of our study was to compare nanocurcumin and curcumin in male rats whose kidneys were damaged by PQ.

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Purpose Of Review: This review aims to assess the role of mobile health (mHealth) interventions and wearable technologies in the prevention and management of atherosclerotic cardiovascular disease (ASCVD). We sought to explore the benefits, challenges, and equity implications of these digital health modalities, with a focus on improving patient outcomes and reducing ASCVD risk.

Recent Findings: Recent studies have shown that mHealth interventions and wearable devices effectively promote healthy behaviors, offer real-time physiological monitoring, and aid in the early prevention of ASCVD by targeting key risk factors such as metabolic syndrome and sedentary lifestyles.

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Background And Aims: Peripheral nerve block (PNB) is commonly used, but there is a lack of data on its effectiveness and safety in the clinic. Therefore, anesthesiologists have limited insight into how they are faring in terms of both safety and efficacy. Additionally, No PNB registry is recorded in IRAN.

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While gendered psycho-socio-cultural factors are recognized as major determinants of cardiovascular health, their contribution to our understanding of their effect on hypertension (HTN) in each country is poorly understood. Therefore, we investigated the role of these factors in HTN prevalence, focusing on sex- and gender-specific differences across countries. Data from the Canadian Community Health Survey (2015-2016, N = 109,659, women: 56.

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The semi-automatic and automatic extraction of land features such as buildings, trees, and roads using aerial laser scan data is crucial in land use change studies and urban management. This research introduces the "BTR" extractor, a novel software package designed to enhance classification accuracy of phenomena identified in the super points obtained from aerial laser scanners. Our method focuses on:-Comparing classification methods using airborne laser scanning data.

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Article Synopsis
  • Large language models (LLMs) like ChatGPT struggle with private data interpretation, specifically electronic health records (EHRs), but prompt engineering could improve their accuracy.
  • Through systematic testing of prompt techniques on 490 EHR notes, the study found that structured prompts significantly enhanced LLM accuracy from 64.3% to 91.4%, outperforming traditional natural language processing methods.
  • The results indicate that LLMs, with proper prompt strategies, can effectively identify clinical insights from EHRs without requiring expert knowledge, suggesting potential applications in other fields for automated data analysis.
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  • Medication adjustments for Parkinson's disease are based on patient feedback and clinicians' assessments of motor symptoms like bradykinesia and tremor.
  • This study evaluates how consistently different clinicians assess upper limb motor function in Parkinson's patients during video recordings of standardized hand movements.
  • Results show that initial agreement among clinicians was poor, especially for certain movements, but training improved their consistency in ratings significantly.
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Historically marginalized communities are disproportionately affected by cardiometabolic diseases yet are underrepresented in clinical trials that investigate needed interventions. This review investigates the barriers to equitable inclusion in clinical trials, identifying opportunities for improvement at the institutional, trial, community, and individual level. It proposes a social determinants-based approach that serves as a toolkit to target these barriers using structural, economic, community, healthcare access, and technology solutions, supporting constructive improvement in the clinical trial recruitment process.

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  • This study explored how traditional risk factors and plasma proteins can predict carotid intima-media thickness (cIMT), an important measure for cardiovascular risk, nearly a decade later in participants from the UK Biobank.
  • It analyzed data from over 6,000 participants, finding that age, blood pressure, and specific body composition measurements were the strongest predictors of cIMT.
  • The research concluded that incorporating plasma proteins alongside traditional risk factors improved prediction accuracy, pointing to the significance of blood pressure and certain proteins related to the extracellular matrix in understanding cIMT development.
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A novel cell-penetrating peptide (CPP) called -YR, with as a fluorescent probe, was developed. Initially, we aimed to use Y as a supramolecular host for water-insoluble drugs, with R driving the complex into cells. However, an unexpected hurdle was discovered; the peptide self-assembled into amorphous aggregates, rendering it ineffective for our intended purpose.

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One of the critical challenges in managing colorectal cancer (CRC) is the development of oxaliplatin (OXP) resistance. Long non-coding RNAs (lncRNAs) have a crucial role in CRC progression and chemotherapy resistance, with exosomal lncRNAs emerging as potential biomarkers. This study aimed to predict key lncRNAs involved in OXP-resistance using in-silico methods and validate them using RT-qPCR methods in CRC cells and their isolated exosomes.

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Background Type 1 diabetes (T1D) is an autoimmune disorder that results in the destruction of pancreatic beta cells, causing a shortage of insulin secretion. The development of T1D is influenced by both genetic predisposition and environmental factors, such as vitamin D. This vitamin is known for its ability to regulate the immune system and has been associated with a decreased risk of T1D.

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Background: While risk stratification for atherosclerotic cardiovascular disease (ASCVD) is essential for primary prevention, current clinical risk algorithms demonstrate variability and leave room for further improvement. The plasma proteome holds promise as a future diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to predict ASCVD.

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Article Synopsis
  • The study evaluates the potential of plasma proteins to predict the risk of type 2 diabetes mellitus (T2DM) and related traits using data from UK Biobank participants.
  • Different analysis methods, like LASSO regression, were employed to compare the effectiveness of proteomic data against traditional clinical and genetic data for predicting traits like truncal fat and fitness levels.
  • Results showed that integrating proteomic signatures enhanced prediction accuracy for T2DM and other traits beyond existing clinical risk scores, indicating their value in disease prognostics.
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Background: Catheter ablation atrial fibrillation (AF) is effective, but 20% to 40% of patients will require a repeat ablation. The role of more than 1 repeat ablation is not well known.

Objectives: The purpose of this study was to evaluate the effectiveness and incremental benefits of multiple repeat catheter ablations to treat AF in patients.

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Background Acquired resistance to 5-fluorouracil (5-FU) frequently results in chemotherapy failure and disease recurrence in advanced colorectal cancer (CRC) patients. Research has demonstrated that dysregulation of long non-coding RNAs (lncRNAs) mediates the development of chemotherapy resistance in cancerous cells. The present study aims to identify key lncRNAs associated with 5-FU resistance in CRC using bioinformatic and experimental validation approaches.

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