Publications by authors named "M E Sheridan"
Unlabelled: Zika virus (ZIKV) infection can lead to a variety of clinical outcomes, including severe congenital abnormalities. The phosphatidylserine (PS) receptors AXL and TIM-1 are recognized as critical entry factors for ZIKV . However, it remains unclear if and how ZIKV regulates these receptors during infection.
View Article and Find Full Text PDFPreschool anxiety is highly prevalent and well known to predict risk for future psychopathology. The present study explores whether a diagnosis of an anxiety disorder in preschool interacts with (a) social skills and (b) cognitive ability to longitudinally predict psychopathology, two well-known protective factors, among a sample of 207 children measured at preschool (Mage = 4.34 years) and early childhood (Mage = 6.
View Article and Find Full Text PDFArticle Synopsis
- Childhood adversity (CA) is linked to higher risks of negative health outcomes, with differences in how various types of adversity affect brain structure during development.
- Recent research indicates that deprivation leads to slower decreases in cortical surface area in certain brain regions, while threat exposure results in increased surface area in areas related to socio-emotional processing as adolescents age.
- These findings suggest a need to reconsider how different forms of adversity affect brain development over time, highlighting the varying impacts on cognitive and emotional functions.
Article Synopsis
- - Pseudohypoparathyroidism type 1B (PHP1B) is caused by epigenetic changes affecting the GNAS gene, leading to parathyroid hormone resistance, especially in kidney cells due to inhibited Gsα protein expression from the maternal allele.
- - Genetic defects in PHP1B patients include loss of methylation in specific regions and additional methylation issues in some, prompting researchers to identify the genetic basis for autosomal dominant PHP1B in families with complex GNAS methylation problems.
- - Genome sequencing highlighted small GNAS variants and a microdeletion in affected families that possibly alter AS transcript expression, leading to reduced NESP transcription, thus suggesting a mechanism behind PHP1B development.
Prediction of Healing Trajectory of Chronic Wounds Using a Machine Learning Approach.
Adv Wound Care (New Rochelle)
November 2024
New treatment options are emerging for chronic wounds, which represent a growing problem because of population ageing and increasing burden of chronic disease. While promising, the existing evidence for advanced modalities is commonly derived from small and/or poorly controlled studies and clear criteria for selecting patients, who are likely to benefit from these expensive options are lacking. In this study, we develop and validate a machine learning model to predict if a chronic wound, independent of etiology, is expected to heal within 12 weeks to identify cases in potential need of advanced treatment options.
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