A case study of Duchenne muscular dystrophy caused by Alu element insertion in gene and analysis of its gray-hair symptoms.

Duchenne muscular dystrophy (DMD) is a severe X-linked recessive genetic disorder caused by mutations in the gene, which leads to a deficiency of the dystrophin protein. The main mutation types of this gene include exon deletions and duplications, point mutations, and insertions. These mutations disrupt the normal expression of dystrophin, ultimately leading to the disease.

A curious case of retrogenesis in language: Automated analysis of language patterns observed in dementia patients and young children.

Introduction: While linguistic retrogenesis has been extensively investigated in the neuroscientific and behavioral literature, there has been little work on retrogenesis using computerized approaches to language analysis.

Methods: We bridge this gap by introducing a method based on comparing output of a pre-trained neural language model (NLM) with an artificially degraded version of itself to examine the transcripts of speech produced by seniors with and without dementia and healthy children during spontaneous language tasks. We compare a range of linguistic characteristics including language model perplexity, syntactic complexity, lexical frequency and part-of-speech use across these groups.

Caffeine Ameliorates Age-Related Hearing Loss by Downregulating the Inflammatory Pathway in Mice.

Objective: Age-related hearing loss (ARHL), also known as presbycusis, is a debilitating sensory impairment that affects the elderly population. There is currently no ideal treatment for ARHL. Long-term caffeine intake was reported to have anti-aging effects in many diseases.

Useful blunders: Can automated speech recognition errors improve downstream dementia classification?

Objectives: We aimed to investigate how errors from automatic speech recognition (ASR) systems affect dementia classification accuracy, specifically in the "Cookie Theft" picture description task. We aimed to assess whether imperfect ASR-generated transcripts could provide valuable information for distinguishing between language samples from cognitively healthy individuals and those with Alzheimer's disease (AD).

Methods: We conducted experiments using various ASR models, refining their transcripts with post-editing techniques.

TRESTLE: Toolkit for Reproducible Execution of Speech, Text and Language Experiments.

The evidence is growing that machine and deep learning methods can learn the subtle differences between the language produced by people with various forms of cognitive impairment such as dementia and cognitively healthy individuals. Valuable public data repositories such as TalkBank have made it possible for researchers in the computational community to join forces and learn from each other to make significant advances in this area. However, due to variability in approaches and data selection strategies used by various researchers, results obtained by different groups have been difficult to compare directly.

GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Models.

Deep learning (DL) techniques involving fine-tuning large numbers of model parameters have delivered impressive performance on the task of discriminating between language produced by cognitively healthy individuals, and those with Alzheimer's disease (AD). However, questions remain about their ability to generalize beyond the small reference sets that are publicly available for research. As an alternative to fitting model parameters directly, we propose a novel method by which a Transformer DL model (GPT-2) pre-trained on general English text is paired with an artificially degraded version of itself (GPT-D), to compute the ratio between these two models' on language from cognitively healthy and impaired individuals.

Crosstalk of mRNA, miRNA, lncRNA, and circRNA and Their Regulatory Pattern in Pulmonary Fibrosis.

Noncoding RNAs (ncRNAs), such as microRNA (miRNA), long ncRNA (lncRNA), and circular RNA (circRNA), are regulators of important biological functions. Therefore, understanding their crosstalk and regulatory patterns can provide treatment for diseases. In this study, differentially expressed RNA transcripts were obtained by RNA sequencing in bleomycin-induced pulmonary fibrosis in mice.