TGF-β Signaling and the Epithelial-Mesenchymal Transition during Palatal Fusion

Signaling by transforming growth factor (TGF)-β plays an important role in development, including in palatogenesis. The dynamic morphological process of palatal fusion occurs to achieve separation of the nasal and oral cavities. Critically and specifically important in palatal fusion are the medial edge epithelial (MEE) cells, which are initially present at the palatal midline seam and over the course of the palate fusion process are lost from the seam, due to cell migration, epithelial-mesenchymal transition (EMT), and/or programed cell death. In order to define the role of TGF-β signaling during this process, several approaches have been utilized, including a small interfering RNA (siRNA) strategy targeting TGF-β receptors in an organ culture context, the use of genetically engineered mice, such as Wnt1-cre/R26R double transgenic mice, and a cell fate tracing through utilization of cell lineage markers. These approaches have permitted investigators to distinguish some specific traits of well-defined cell populations throughout the palatogenic events. In this paper, we summarize the current understanding on the role of TGF-β signaling, and specifically its association with MEE cell fate during palatal fusion. TGF-β is highly regulated both temporally and spatially, with TGF-β3 and Smad2 being the preferentially expressed signaling molecules in the critical cells of the fusion processes. Interestingly, the accessory receptor, TGF-β type 3 receptor, is also critical for palatal fusion, with evidence for its significance provided by Cre-lox systems and siRNA approaches. This suggests the high demand of ligand for this fine-tuned signaling process. We discuss the new insights in the fate of MEE cells in the midline epithelial seam (MES) during the palate fusion process, with a particular focus on the role of TGF-β signaling.Dentistry, Faculty ofNon UBCOral Biological and Medical Sciences (OBMS), Department ofReviewedFacult

Advanced qEEG analyses discriminate between dementia subtypes

Background: Dementia is caused by neurodegenerative conditions and characterizedby cognitive decline. Diagnostic accuracy for dementia subtypes, such as Alzheimer’sDisease (AD), Dementia with Lewy Bodies (DLB) and Parkinson’s Disease withdementia (PDD), remains challenging.Methods: Here, different methods of quantitative electroencephalography (qEEG)analyses were employed to assess their effectiveness in distinguishing dementiasubtypes from healthy controls under eyes closed (EC) and eyes open (EO)conditions.Results: Classic Fast-Fourier Transform (FFT) and autoregressive (AR) poweranalyses differentiated between all conditions for the 4-8 Hz theta range. Onlyindividuals with dementia with Lewy Bodies (DLB) differed from healthy subjects for thewider 4-15 Hz frequency range, encompassing the actual dominant frequency of allindividuals. FFT results for this range yielded wider significant discriminators vs AR,also detecting differences between AD and DLB. Analyses of the inclusive dominant /peak frequency range (4-15 Hz) indicated slowing and reduced variability, alsodiscriminating between synucleinopathies vs controls and AD.Dissociation of periodic oscillations and aperiodic components of AR spectra usingFitting-Oscillations-&-One-Over-F (FOOOF) modelling delivered a reliable andsubtype-specific slowing of brain oscillatory peaks during EC and EO for all groups.Distinct and robust differences were particularly strong for aperiodic parameters,suggesting their potential diagnostic power in detecting specific changes resulting fromage and cognitive status.Conclusion: Our findings indicate that qEEG methods can reliably detect dementiasubtypes. Spectral analyses comprising an integrated, multi-parameter EEG approachdiscriminating between periodic and aperiodic components under EC and EOconditions may enhance diagnostic accuracy in the future

A <i>Saccharomyces cerevisiae</i> model and screen to define the functional consequences of oncogenic histone missense mutations

AbstractSomatic missense mutations in histone genes turn these essential proteins into oncohistones, which can drive oncogenesis. Understanding how missense mutations alter histone function is challenging in mammals as mutations occur in a single histone gene. For example, described oncohistone mutations predominantly occur in the histone H3.