Transient Periictal Brain Imaging Abnormality in a Saudi Patient with Probable Celiac Disease Epilepsy and Occipital Calcification Syndrome

Celiac disease epilepsy and occipital calcification (CEC) syndrome is a rare, emerging disease first described in 1992. To date, fewer than 200 cases have been reported worldwide. CEC syndrome is generally thought to be a genetic, noninherited, and ethnically and geographically restricted disease in Mediterranean countries. However, we report the first ever case of probable CEC in a Saudi patient. Furthermore, the patient manifested a magnitude of brain magnetic resonance imaging (MRI) signal abnormalities during the periictal period which, to the best of our knowledge, has never been described in CEC. The brain MRI revealed diffusion-weighted imaging (DWI) restriction with a concordant area of apparent diffusion coefficient (ADC) hypointensity around bilateral occipital area of calcification. An imbalance between the heightened energy demand during ictal phase of the seizure and unadjusted blood supply may have caused an electric pump failure and cytotoxic edema, which then led to DWI/ADC signal alteration

Analysis of causes of mortality in patients with autosomal dominant polycystic kidney disease: A single center study

This study was aimed at determining the median survival and most frequent causes of death in patients with the Autosomal Dominant Polycystic Kidney Disease (ADPKD). A retrospective, observational analysis was made on patients registered with a diagnosis of ADPKD, in the computer records of the Sheffield Kidney Institute (SKI), United Kingdom, during the years 1981 to 1999. Data on 363 patients were analyzed from these computer records and further infor-mation, if any, was obtained from the patients′ clinical notes. During this period, 88 patients died. The median age of the patients who died was 60.5 years, with the youngest being 37 years old and the oldest being 82 years. The major causes of death in this study group were cardiovascular (46.6%), infection (15.9%), central nervous system (CNS) disorders (11.36%), and miscellaneous causes (11.36%). Our study suggests that the major cause of death in patients with ADPKD was cardiovascular followed by infection, of which 42% of the deaths were due to septicemia. CNS causes of death comprised 11.36% of whom 60% had cerebrovascular events including sub-arachnoid hemorrhage in 20% of the patients. Uremia was the cause of death in only 2.2% of the patients in this series

Data from: Individual Magnetoencephalography Response Profiles to Short-Duration L-Dopa in Parkinson’s Disease

The .csv files contain all the motor factor scores, cross-validated feature weights, and cross-validated accuracy for figures 1, 2A, and 2B from the publication entitled "Individual Magnetoencephalography Response Profiles to Short- Duration L-Dopa in Parkinson's Disease" (Peña et al 2021 Frontiers in Human Neuroscience, DOI: 10.3389/fnhum.2021.640591).Clinical responses to dopamine replacement therapy for individuals with Parkinson’s disease (PD) are often difficult to predict. We characterized changes in MDS-UPDRS motor factor scores resulting from a short-duration L-Dopa response (SDR), and investigated how the inter-subject clinical differences could be predicted from motor cortical magnetoencephalography (MEG). MDS-UPDRS motor factor scores and resting-state MEG recordings were collected during SDR from twenty individuals with a PD diagnosis. We used a novel subject-specific strategy based on linear support vector machines to quantify motor cortical oscillatory frequency profiles that best predicted medication state. Motor cortical profiles differed substantially across individuals and showed consistency across multiple data folds. There was a linear relationship between classification accuracy and SDR of lower limb bradykinesia, although this relationship did not persist after multiple comparison correction, suggesting that combinations of spectral power features alone are insufficient to predict clinical state. Factor score analysis of therapeutic response and novel subject-specific machine learning approaches based on subject-specific neuroimaging provide tools to predict outcomes of therapies for PD.King Fahad Medical CityNational Science Foundation (00039202 to E.P.)National Institutes of Health (R01-NS094206 and P50-NS098573