Sign language in Landau-Kleffner syndrome.

This article reviews the history of sign language (SL) and the rationale for its use in children with profound auditory agnosia due to Landau-Kleffner syndrome (LKS), illustrated by studies of children and adults followed for many years and rare cases from the literature. The reasons that SL was successful and brought some children out of isolation while it could not be implemented in others are discussed. The nowadays earlier recognition and treatment of LKS and better awareness of the crucial need to maintain communication have certainly improved the outcome of affected children. Alternatives to oral language, even for less severe cases, are increasingly accepted. SL can be learned at different ages with a clear benefit, but the ambivalence of the patients and their families with the world and culture of the deaf may sometimes explain its refusal or limited acceptance. There are no data to support the fear that SL learning may delay or prevent oral language recovery in children with LKS. On the contrary, SL may even facilitate this recovery by stimulating functionally connected core language networks and by helping speech therapy and auditory training.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Towards the identification of a genetic basis for Landau-Kleffner syndrome.

OBJECTIVE: To establish the genetic basis of Landau-Kleffner syndrome (LKS) in a cohort of two discordant monozygotic (MZ) twin pairs and 11 isolated cases. METHODS: We used a multifaceted approach to identify genetic risk factors for LKS. Array comparative genomic hybridization (CGH) was performed using the Agilent 180K array. Whole genome methylation profiling was undertaken in the two discordant twin pairs, three isolated LKS cases, and 12 control samples using the Illumina 27K array. Exome sequencing was undertaken in 13 patients with LKS including two sets of discordant MZ twins. Data were analyzed with respect to novel and rare variants, overlapping genes, variants in reported epilepsy genes, and pathway enrichment. RESULTS: A variant (cG1553A) was found in a single patient in the GRIN2A gene, causing an arginine to histidine change at site 518, a predicted glutamate binding site. Following copy number variation (CNV), methylation, and exome sequencing analysis, no single candidate gene was identified to cause LKS in the remaining cohort. However, a number of interesting additional candidate variants were identified including variants in RELN, BSN, EPHB2, and NID2. SIGNIFICANCE: A single mutation was identified in the GRIN2A gene. This study has identified a number of additional candidate genes including RELN, BSN, EPHB2, and NID2. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

Quantitative multi-parameter mapping of R1, PD(*), MT, and R2(*) at 3T: a multi-center validation.

Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM) was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1 mm high-resolution maps of the longitudinal relaxation rate (R1 = 1/T1), effective proton density (PD(*)), magnetization transfer saturation (MT) and effective transverse relaxation rate (R2(*) = 1/T2(*)). MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV) for typical morphometric measures [i.e., gray matter (GM) probability maps used in voxel-based morphometry] and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1 and 8%, respectively, except for the inter-site CoV of R2(*) (<20%). The GM probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived GM probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Discrepancy between Visual Acuity and Microperimetry in AMD Patients: Visual Acuity Appears as an Inadequate Parameter to Test Macular Function.

BACKGROUND: Best corrected visual acuity (BCVA) of 0.8 or above in AMD patients can sometimes correspond to poor macular function inducing a serious visual handicap. Microperimetry can be used to objectivize this difference. PATIENTS AND METHODS: A retrospective study was undertaken on 233 files of AMD patients of whom 82 had had a microperimetry. BCVA was compared with microperimetry performance. All examinations were performed in an identical setting by the same team of 3 persons. RESULTS: Among the 82 patients included, 32 (39.0%) had a BCVA equal to or above 0.8 even though their microperimetry performance was lower than 200/560 db. 10 of them (12.2% of total) had an even poorer microperimetry below 120/560 db indicating poor macular function. CONCLUSIONS: More than a third of the AMD patients had a bad or very bad microperimetry performance in parallel with a good visual acuity. Microperimetry is a valuable tool to assess and follow real macular function in AMD patients when visual acuity alone can be misleading.