Publications by authors named "A Rezaei"

Traditional polymer systems often rely on toxic initiators or catalysts for cross-linking, posing significant safety risks. For bone tissue engineering, another issue is that the scaffolds often take a longer time to degrade, inconsistent with bone formation pace. Here, we developed an enzyme-responsive biodegradable poly(propylene fumarate) (PPF) and polycaprolactone (PCL) polyphosphoester (PPE) dendrimer cross-linked utilizing click chemistry (EnzDeg-click-PFCLPE scaffold) for enhanced biocompatibility and degradation.

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Motivation: Whole-body Positron Emission Tomography (PET) imaging is often hindered by respiratory motion during acquisition, causing significant degradation in the quality of reconstructed activity images. An additional challenge in PET/CT imaging arises from the respiratory phase mismatch between CT-based attenuation correction and PET acquisition, leading to attenuation artifacts. To address these issues, we propose two new, purely data-driven methods for the joint estimation of activity, attenuation, and motion in respiratory self-gated time-of-flight (TOF) PET.

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Background: Back muscles simultaneously drive spinal movements and stabilize the trunk. Paraspinal muscle activity is presumed to be symmetric and gender-insensitive, and more activated with aging to protect the spine during functional tasks.

Research Question: Does over-activated and asymmetric behaviors exist in the pain-free elderly population which is affected by their physical activity levels?

Methods: Forty healthy participants (aged 64.

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Sulfur mustard (SM) induced pulmonary disorder is a heterogeneous disease characterized by uncontrolled inflammatory immune responses. In this cross-sectional study carried out in Isfahan-Iran, our objective was to thoroughly evaluate the clinical health and peripheral blood leukocyte profiles of adult veterans exposed to SM 25-30 years. In total, 361 people were studied in two groups, 287 chemical veterans with pulmonary complications and 64 healthy individuals as a control group.

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Pre-training strategies based on self-supervised learning (SSL) have demonstrated success as pretext tasks for downstream tasks in computer vision. However, while SSL methods are often domain-agnostic, their direct application to medical imaging is challenging due to the distinct nature of medical images, including specific anatomical and temporal patterns relevant to disease progression. Additionally, traditional SSL pretext tasks often lack the contextual knowledge that is essential for clinical decision support.

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