Strength of association of classical vascular risk factors in young patients with ischaemic stroke: a case-control study.

INTRODUCTION: Recent studies have reported an increasing incidence of ischaemic stroke among young adults. However, the strength of the association between traditional vascular risk factors has not been fully established. METHODS: We compared 120 patients with a first ischaemic stroke before the age of 55 years admitted to the stroke unit of our centre with 600 healthy non-stroke controls from a population-based cohort study (HERMEX), matched for sex. Risk factors assessed included: hypertension, obesity, auricular fibrillation, current smoking, estimated glomerular filtration rate (eGFR), total cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides, high-density lipoprotein cholesterol (HDL-C) and diabetes mellitus. We used logistic regression analysis and calculated population attributable risk. We performed an overall analysis, by sex and aetiological subgroup. RESULTS: Using logistic regression analysis, we found that overall, the significant risk factors were: hypertension (OR: 1.58; 95%CI: 1.01-2.50), atrial fibrillation (OR: 4.77; 95%CI: 1.20-19.00), low eGFR (OR: 4.74; 95%CI: 1.3-21.94) and low HDL-C (OR: 5.20; 95%CI: 3.29-8.21), as well as smoking for males (OR: 1.86; 95%CI: 1.14-3.03). LDL-C showed an inverse association with stroke. The population attributable risk for HDL-C was 37.8% and for hypertension 21.1%. In terms of aetiological subgroups, only low HDL-C was associated with stroke of undetermined aetiology. CONCLUSIONS: Hypertension, auricular fibrillation, low eGFR, and low HDL-C, plus tobacco use in men, are the main risk factors among patients under 55 years of age with a first ischaemic stroke. We believe that it would be of particular interest to further explore the management of low HDL-C levels as part of preventive strategies in young stroke patients.

Axin2-lineage cells contribute to neonatal tendon regeneration.

PURPOSE: Tendon injuries are a challenging clinical problem with few treatment options. Identifying the molecular regulators of tendon is required for the development of new therapies. While the Wnt pathway is critical for the maintenance and differentiation of many tissues, the role of Wnt signaling in tendon cell biology remains largely unexplored. METHODS: The effects of Wnt activation were tested in vitro using neonatal tendon-derived cells cultured in 2D and 3D conditions. The inducible Axin2CreERT2 was then used to label Axin2+ cells in vivo and cells were traced during neonatal tendon regeneration. RESULTS: We showed that activation of Wnt signaling results in proliferation of neonatal tendon cells. While tendon marker expression was inhibited by Wnt activation under 2D conditions, Scx expression was not affected under 3D uniaxial tension, suggesting that the microenvironment contextualizes tendon cell response to Wnt signaling. Using an in vivo model of neonatal tendon regeneration, we further showed that Wnt signaling cells comprise a subpopulation of tenocyte and epitenon cells that proliferate after injury and are recruited during regeneration. DISCUSSION: Collectively, these studies suggest that Wnt signaling may play a role in tendon cell proliferation, differentiation, and regeneration.

Domain adversarial networks and intensity-based data augmentation for male pelvic organ segmentation in cone beam CT.

In radiation therapy, a CT image is used to manually delineate the organs and plan the treatment. During the treatment, a cone beam CT (CBCT) is often acquired to monitor the anatomical modifications. For this purpose, automatic organ segmentation on CBCT is a crucial step. However, manual segmentations on CBCT are scarce, and models trained with CT data do not generalize well to CBCT images. We investigate adversarial networks and intensity-based data augmentation, two strategies leveraging large databases of annotated CTs to train neural networks for segmentation on CBCT. Adversarial networks consist of a 3D U-Net segmenter and a domain classifier. The proposed framework is aimed at encouraging the learning of filters producing more accurate segmentations on CBCT. Intensity-based data augmentation consists in modifying the training CT images to reduce the gap between CT and CBCT distributions. The proposed adversarial networks reach DSCs of 0.787, 0.447, and 0.660 for the bladder, rectum, and prostate respectively, which is an improvement over the DSCs of 0.749, 0.179, and 0.629 for "source only" training. Our brightness-based data augmentation reaches DSCs of 0.837, 0.701, and 0.734, which outperforms the morphons registration algorithms for the bladder (0.813) and rectum (0.653), while performing similarly on the prostate (0.731). The proposed adversarial training framework can be used for any segmentation application where training and test distributions differ. Our intensity-based data augmentation can be used for CBCT segmentation to help achieve the prescribed dose on target and lower the dose delivered to healthy organs.