Validation study of "Santé-Cerveau", a digital tool for early cognitive changes identification.

BACKGROUND: There is a need for a reliable, easy-to-use, widely available, and validated tool for timely cognitive impairment identification. We created a computerized cognitive screening tool (Santé-Cerveau digital tool (SCD-T)) including validated questionnaires and the following neuropsychological tests: 5 Word Test (5-WT) for episodic memory, Trail Making Test (TMT) for executive functions, and a number coding test (NCT) adapted from the Digit Symbol Substitution Test for global intellectual efficiency. This study aimed to evaluate the performance of SCD-T to identify cognitive deficit and to determine its usability. METHODS: Three groups were constituted including 65 elderly Controls, 64 patients with neurodegenerative diseases (NDG): 50 AD and 14 non-AD, and 20 post-COVID-19 patients. The minimum MMSE score for inclusion was 20. Association between computerized SCD-T cognitive tests and their standard equivalent was assessed using Pearson's correlation coefficients. Two algorithms (a simple clinician-guided algorithm involving the 5-WT and the NCT; and a machine learning classifier based on 8 scores from the SCD-T tests extracted from a multiple logistic regression model, and data from the SCD-T questionnaires) were evaluated. The acceptability of SCD-T was investigated through a questionnaire and scale. RESULTS: AD and non-AD participants were older (mean ± standard deviation (SD): 72.61 ± 6.79 vs 69.91 ± 4.86 years old, p = 0.011) and had a lower MMSE score (Mean difference estimate ± standard error: 1.74 ± 0.14, p < 0.001) than Controls; post-COVID-19 patients were younger than Controls (mean ± SD: 45.07 ± 11.36 years old, p < 0.001). All the computerized SCD-T cognitive tests were significantly associated with their reference version. In the pooled Controls and NDG group, the correlation coefficient was 0.84 for verbal memory, -0.60 for executive functions, and 0.72 for global intellectual efficiency. The clinician-guided algorithm demonstrated 94.4% ± 3.8% sensitivity and 80.5% ± 8.7% specificity, and the machine learning classifier 96.8% ± 3.9% sensitivity and 90.7% ± 5.8% specificity. The acceptability of SCD-T was good to excellent. CONCLUSIONS: We demonstrate the high accuracy of SCD-T in screening cognitive disorders and its good acceptance even in individuals with prodromal and mild dementia stages. SCD-T would be useful in primary care to faster refer subjects with significant cognitive impairment (and limit unnecessary referrals) to specialized consultation, improve the AD care pathway and the pre-screening in clinical trials.

Deep Learning Forecasts the Occurrence of Sleep Apnea from Single-Lead ECG.

OBJECTIVES: Sleep apnea is the most common sleep disorder that leads to serious health complications if not treated early. Forecasting apnea occurrence ahead in time provides the opportunity to take appropriate actions to control and manage it. METHODS: A novel framework for forecasting the occurrence of apnea from single-lead electrocardiogram (ECG) based on deep recurrent neural networks is proposed. ECG R-peak amplitudes and R-R intervals are extracted and aligned using power spectral analysis, and recurrent deep learning models are developed to extract the most predictive ECG features and forecast the occurrence of apnea. RESULTS: The performance of the proposed approach was validated in forecasting apnea events up to five minutes in future on a dataset of 70 sleep recordings. A forecasting accuracy of up to 94.95% was achieved which was higher than the performance of conventional multilayer perceptron (p < 0.05) and other state-of-the-art techniques. CONCLUSIONS: The proposed deep learning approach was successful in forecasting the occurrence of sleep apnea from single-lead ECG. It can therefore be adopted in wearable sleep monitors for the management of sleep apnea. Our developed algorithms are publicly available on GitHub.

An Experience with Frame-Based Stereotactic Biopsy of Posterior Fossa Lesions via Transcerebellar Route.

BACKGROUND: Tissue diagnosis for lesions in the posterior fossa, such as the brainstem, cerebellar peduncle, and cerebellum, is an important determinant of the next treatment option. Herein, we present our 10-year experience with magnetic resonance imaging (MRI)-guided frame-based stereotactic biopsy for 39 patients with posterior fossa lesions, the largest case series in this matter. METHODS: We performed a retrospective cross-sectional study on all patients with posterior fossa lesion admitted to 2 referral centers between 2006 and 2016. We used Leksell Frame G for stereotactic biopsy of all patients. MRI systems of both hospitals were 1.5 T. RESULTS: We performed analysis on the 39 cases (21 men and 18 women). Age of the patients ranged between 9 and 73 years (mean, 35.4 ± 15.7 years). Localization success rate was 100%. For 38 patients (97.4%), tissue sample size was enough for tissue diagnosis. For 1 case, it was insufficient and nondiagnostic. In this series, we had no surgery-related complications. CONCLUSIONS: We present the largest reported series of MRI-guided frame-based stereotactic biopsy of the posterior fossa lesions via a transcerebellar route. We prefer oblique positioning of the frame on the skull and use a transcerebellar route to reduce surgical complications and achieve a greater localization success rate.

Variation in antioxidant enzyme activities, growth and some physiological parameters of bitter melon (Momordica charantia) under salinity and chromium stress.

In general, salinity and heavy metals interfere with several physiological processes and reduce plant growth. In order to evaluate of three levels of salinity (0, 4 and 8 ds m(-1)) and three concentration of chromium (0, 10 and 20 mg kg(-1) soil) in bitter melon (Momordica charantia), a plot experiment was conducted in greenhouse at university of Shahrood, Iran. The results revealed that chromium treatment had no significant affect on fresh and dry weight, but salinity caused reduction of fresh and dry weight in growth parameter. Salinity and chromium enhanced antioxidant enzymes activities like catalase (CAT), guaiacol peroxidase (GPX) and sodium content in leaves. However salinity and chromium treatments had no effect on potassium, phosphorus in leaves, soluble carbohydrate concentration in leaves and root, but decreased the carotenoid content in leaves. On increasing salinity from control to 8 ds m(-1) chlorophyll a, b and anthocyanin content decreased by 41.6%, 61.1% and 26.5% respectively but chromium treatments had no significant effect on these photosynthetic pigments.