Patterns and predictors of statin therapy after ischemic stroke and TIA: insights from the LIPYDS multicenter study.

Background: Patients with ischemic stroke (IS) or TIA face an elevated cardiovascular risk, warranting intensive lipid-lowering therapy. Despite recommendations, adherence to guidelines is suboptimal, leading to frequent undertreatment. This study aims to evaluate the statin use after IS and TIA.

EEG-based emotional valence and emotion regulation classification: a data-centric and explainable approach.

Emotion classification using electroencephalographic (EEG) data is a challenging task in the field of Artificial Intelligence. While many researchers have focused on finding the best model or feature extraction technique to achieve optimal results, few have attempted to select the best methodological steps for working with the dataset. In this study, we applied two different theoretical approaches based on the noise of the dataset: curriculum learning and confident learning.

Stimulus Inversion and Emotional Expressions Independently Affect Face and Body Perception: An ERP Study.

Faces and bodies provide critical cues for social interaction and communication. Their structural encoding depends on configural processing, as suggested by the detrimental effect of stimulus inversion for both faces (i.e.

Brain-Derived Neurotrophic Factor-Loaded Low-Temperature-Sensitive liposomes as a drug delivery system for repairing podocyte damage.

Podocytes, cells of the glomerular filtration barrier, play a crucial role in kidney diseases and are gaining attention as potential targets for new therapies. Brain-Derived Neurotrophic Factor (BDNF) has shown promising results in repairing podocyte damage, but its efficacy via parenteral administration is limited by a short half-life. Low temperature sensitive liposomes (LTSL) are a promising tool for targeted BDNF delivery, preserving its activity after encapsulation.

Combining Different Wearable Devices to Assess Gait Speed in Real-World Settings.

Assessing mobility in daily life can provide significant insights into several clinical conditions, such as Chronic Obstructive Pulmonary Disease (COPD). In this paper, we present a comprehensive analysis of wearable devices' performance in gait speed estimation and explore optimal device combinations for everyday use. Using data collected from smartphones, smartwatches, and smart shoes, we evaluated the individual capabilities of each device and explored their synergistic effects when combined, thereby accommodating the preferences and possibilities of individuals for wearing different types of devices.