We report a patient with right-predominant semantic variant primary progressive aphsia linked with p.Asp40Gly variant of ANXA11, which is the first description of frontotemporal dementia without clinical and electrophysiological evidences of amyotrophic lateral sclerosis associated with a known pathogenic variant of ANXA11.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/ene.15455 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The Classification and Language Description of Patients with Primary Progressive Aphasia Using the Mini Linguistic State Examination Test.
Geriatrics (Basel)
December 2024
Department of Psychology, University of Oviedo, 33003 Oviedo, Spain.
Primary progressive aphasia (PPA) is a clinical syndrome characterized by a progressive deterioration in language and speech. It is classified into three variants based on symptom patterns: logopenic, semantic, and non-fluent. Due to the lack of fully reliable and valid screening tests for diagnosing PPA and its variants, a Spanish version of the Mini Linguistic State Examination (MLSE) has recently been introduced.
View Article and Find Full Text PDFPolycomb-associated and Trithorax-associated developmental conditions-phenotypic convergence and heterogeneity.
Eur J Hum Genet
January 2025
MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
Polycomb group (PcG) and Trithorax group (TrxG) complexes represent two major components of the epigenetic machinery. This study aimed to delineate phenotypic similarities and differences across developmental conditions arising from rare variants in PcG and TrxG genes, using data-driven approaches. 462 patients with a PcG or TrxG-associated condition were identified in the DECIPHER dataset.
View Article and Find Full Text PDFHow to Efficiently Annotate Images for Best-Performing Deep Learning-Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Model.
J Imaging Inform Med
January 2025
Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA.
Deep neural networks (DNNs) have demonstrated exceptional performance across various image segmentation tasks. However, the process of preparing datasets for training segmentation DNNs is both labor-intensive and costly, as it typically requires pixel-level annotations for each object of interest. To mitigate this challenge, alternative approaches such as using weak labels (e.
View Article and Find Full Text PDFPaying attention to the SARS-CoV-2 dialect : a deep neural network approach to predicting novel protein mutations.
Commun Biol
January 2025
Dept. Electrical Engineering and Computer Science, Florida Atlantic University, 777 Glades Road, Boca Raton, FL, 33431, USA.
Predicting novel mutations has long-lasting impacts on life science research. Traditionally, this problem is addressed through wet-lab experiments, which are often expensive and time consuming. The recent advancement in neural language models has provided stunning results in modeling and deciphering sequences.
View Article and Find Full Text PDFDeep learning segmentation architectures for automatic detection of pancreatic ductal adenocarcinoma in EUS-guided fine-needle biopsy samples based on whole-slide imaging.
Endosc Ultrasound
December 2024
Department of Gastroenterology, Ponderas Academic Hospital, Bucharest, Romania.
Background: EUS-guided fine-needle biopsy is the procedure of choice for the diagnosis of pancreatic ductal adenocarcinoma (PDAC). Nevertheless, the samples obtained are small and require expertise in pathology, whereas the diagnosis is difficult in view of the scarcity of malignant cells and the important desmoplastic reaction of these tumors. With the help of artificial intelligence, the deep learning architectures produce a fast, accurate, and automated approach for PDAC image segmentation based on whole-slide imaging.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!