BACKGROUND:No disorder-specific patient-reported outcome measure (PROM) has yet been validated for functional movement disorders (FMDs), leaving a critical gap in clinical care and research. OBJECTIVE:To validate the FMD questionnaire (FMDQ) in a prospectively recruited sample through a multicentre study. METHODS:Confirmatory factorial analysis (CFA) tested the assumed structure of the questionnaire with factors reflecting severity of motor symptoms, impairment of everyday activities, impact of non-motor symptoms and impairment of social functioning. Internal consistency and floor/ceiling effects were examined. The 36-item short form health survey (SF-36), patient health questionnaire-15 (PHQ-15), the fatigue assessment scale (FAS) and a clinician-rated scale corresponding to motor symptom items of the FMDQ (FMDQ-CR) were used to test criterion and construct validity. The minimally clinically important difference (MCID) was assessed through distribution-based and anchor-based methods in a convenience sample of patients with follow-up assessments. RESULTS:Complete datasets from 157 patients were analysed; follow-up assessments were available from 30 patients. CFA confirmed that a four-factor model provides a better fit to the data compared with a more restrictive one-factor model. Internal consistency was appropriate for all factors/subscales. No floor or ceiling effects were detected. Criterion and content validity were supported by significant correlations with respective SF-36 subscores, PHQ-15, FAS and FMDQ-CR. Anchor-based MCID was estimated at 8 to 20 points, with the central value aligning with the distribution-based MCID of 12 points (8% of the total score range). CONCLUSIONS:The FMDQ is a psychometrically robust PROM, making it a useful tool for clinical practice and treatment trials.
The field of identifying retinal biomarkers of Alzheimer’s Disease has seen tremendous growth in recent years. The retina has great potential for being used in screening for Alzheimer’s disease (AD); it is the only part of the CNS not shielded by bone, and AD patients have several visual complaints. A number of major biomarkers in the retina have been found, including retinal nerve fiber layer (RNFL) thinning, retinovascular changes, pericyte loss and blood-retinal barrier (BRB) weakening, β-Amyloid (Aβ) deposits, Hyperphosphorylated tau and neurofibrillary tangles (NFTs), and gliosis/inflammation. All of these parallel brain biomarkers. Furthermore, new ocular biomarkers have been found (the efficacy of which is not yet fully proven) - Aβ in the lens, choroid thinning, and visual symptoms. Amyloid biomarkers probably have the most potential among these for screening; however, a multivariable model will be more effective. In the future, the Atlas of Retinal Imaging in Alzheimer’s Study (ARIAS) study, which has already commenced, will search for a wide range of retinal biomarkers in many patients in varying stages of AD and risk levels of AD; it will also explore the interrelationships between those biomarkers to find a potential multivariate screening test for AD. Also, tear fluid could be a potential future biomarker that will be relatively easy to screen. Overall, this field has made great strides in recent years, and has great potential for groundbreaking advances in the near future. The promise of course is to enable simple, inexpensive, widespread and regular screening for AD using retinal biomarkers.
This paper investigates the morpho-syntactic features of language contact in the endangered Greek dialect Romeyka with Turkish. We analyze the use of the borrowed negative existential jok to (a) determine its role in Romeyka’s negation patterns (b) examine the effects of contact in Romeyka through cross-linguistic comparisons of jok with Turkish and forms of the dialect as spoken in Greece and (c) apply the identified grammatical patterns of jok to Myers-Scotton’s linguistic explanations for the code switching phenomena in the Matrix Language Turnover Hypothesis. The analysis demonstrates the pervasive influence of Turkish on the morpho-syntax of Romeyka through the incorporation of Turkish grammatical structures. We observe changes in the fundamental predicate grammar that are aligned with Turkish and that are inconsistent with Pontic’s existential constructions where the verb indicating existence is used. The patterns of contact confirm the Matrix Language hypothesis and provide evidence that indicate that Romeyka may be undergoing language turnover. Our findings are relevant to further understanding code switching among speakers of minority languages and assessing the vitality of Romeyka in Turkey.
Automated recognition of facial expressions is a central component of systems used in an expanding array of domains. For a computer to automatically recognize affect, copious amounts of data are required to successfully train the model. It can often take a lot of work to collect and label data. In recent years, researchers have applied numerous data augmentation strategies to increase the diversity of the data within training datasets. Here, I examined the most common data augmentation strategies to determine which strategies result in higher performance for the facial expression recognition machine learning model. I first tested each data augmentation technique by itself and compared their performances. I next ran an ablation study with the augmentation strategies. I then analyzed the effect of dataset size on the marginal contribution of data augmentation. I find that augmentation does not always improve performance. When the dataset size is small, it results in a degradation of model performance. The accuracy of models with data augmentation starts to outperform the models with no data augmentation when the training dataset size is greater than a certain threshold. These results highlight the importance of considering dataset size when applying data augmentation to computer vision.
