Publications by authors named "A Leconte"

Ultrasound Localization Microscopy (ULM) has proven effective in resolving microvascular structures and local mean velocities at sub-diffraction-limited scales, offering high-resolution imaging capabilities. Dynamic ULM (DULM) enables the creation of angiography or velocity movies throughout cardiac cycles. Currently, these techniques rely on a Localization-and-Tracking (LAT) workflow consisting in detecting microbubbles (MB) in the frames before pairing them to generate tracks.

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Background: In oncology, the suffering of patients and the burnout of health professionals are key issues. Mindfulness meditation is a holistic approach that can help to improve well-being. While numerous studies have shown the benefits of meditation for both patients and health professionals, the added value of offering shared meditation to groups of patients, health professionals and third persons has not been assessed.

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The brain's microvascular cerebral capillary network plays a vital role in maintaining neuronal health, yet capillary dynamics are still not well understood due to limitations in existing imaging techniques. Here, we present Single Capillary Reporters (SCaRe) for transcranial Ultrasound Localization Microscopy (ULM), a novel approach enabling non-invasive, whole-brain mapping of single capillaries and estimates of their transit-time as a neurovascular biomarker. We accomplish this first through computational Monte Carlo and ultrasound simulations of microbubbles flowing through a fully-connected capillary network.

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Apple scab, caused by the hemibiotrophic fungus Venturia inaequalis, is currently the most common and damaging disease in apple orchards. Two strains of V. inaequalis (S755 and Rs552) with different sensitivities to azole fungicides and the bacterial metabolite fengycin were compared to determine the mechanisms responsible for these differences.

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Article Synopsis
  • Ovarian cancer, a leading cause of gynecological cancer deaths, often becomes resistant to chemotherapy, highlighting the urgency for new treatment approaches and predictive biomarkers.
  • The OVAREX study investigates the feasibility of creating patient-derived tumor models (like PDX, PDTO, and ADS) to predict clinical outcomes for ovarian cancer patients undergoing treatment.
  • This research aims to validate the predictive capabilities of these models by comparing their responses to treatments with actual patient outcomes, potentially enhancing clinical decision-making.
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