Linoleic acid (LA), the primary ω-6 polyunsaturated fatty acid (PUFA) found in the epidermis, plays a crucial role in preserving the integrity of the skin's water permeability barrier. Additionally, vegetable oils rich in LA have been shown to notably mitigate ultraviolet (UV) radiation-induced effects, including the production of reactive oxygen species (ROS), cellular damage, and skin photoaging. These beneficial effects are primarily ascribed to the LA in these oils.
View Article and Find Full Text PDFIntroduction: Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention for late-life depression (LLD) but may have lower rates of response and remission owing to age-related brain changes. In particular, rTMS induced electric field strength may be attenuated by cortical atrophy in the prefrontal cortex. To identify clinical characteristics and treatment parameters associated with response, we undertook a pilot study of accelerated fMRI-guided intermittent theta burst stimulation (iTBS) to the right dorsolateral prefrontal cortex in 25 adults aged 50 or greater diagnosed with LLD and qualifying to receive clinical rTMS.
View Article and Find Full Text PDFObjective: We developed and evaluated an online learning module for teaching wound care basics to junior medical learners, which was assessed for its ability to increase theoretical knowledge of wound care, and medical learners' perceptions on the use of an online module to teach wound care practices.
Design: Between February 2022 to November 2022, participants were enrolled into our unblinded, matched-pair single-arm study. Participants completed a pre- and postquiz prior to and after completing the online module, respectively.
Entropy (Basel)
February 2023
A Schrödinger bridge is a stochastic process connecting two given probability distributions over time. It has been recently applied as an approach for generative data modelling. The computational training of such bridges requires the repeated estimation of the drift function for a time-reversed stochastic process using samples generated by the corresponding forward process.
View Article and Find Full Text PDFIn this paper, we propose to leverage the Bayesian uncertainty information encoded in parameter distributions to inform the learning procedure for Bayesian models. We derive a first principle stochastic differential equation for the training dynamics of the mean and uncertainty parameter in the variational distributions. On the basis of the derived Bayesian stochastic differential equation, we apply the methodology of stochastic optimal control on the variational parameters to obtain individually controlled learning rates.
View Article and Find Full Text PDFTraditionally, Hawkes processes are used to model time-continuous point processes with history dependence. Here, we propose an extended model where the self-effects are of both excitatory and inhibitory types and follow a Gaussian Process. Whereas previous work either relies on a less flexible parameterization of the model, or requires a large amount of data, our formulation allows for both a flexible model and learning when data are scarce.
View Article and Find Full Text PDFBackground: Despite increased reporting of resting-state magnetoencephalography (MEG), reliability of those measures remains scarce and predominately reported in healthy controls (HC). As such, there is limited knowledge on MEG resting-state reliability in schizophrenia (SZ).
Methods: To address test-retest reliability in psychosis, a reproducibility study of 26 participants (13-SZ, 13-HC) was performed.