Genome sequencing reveals the impact of non-canonical exon inclusions in rare genetic disease.

Introduction: Advancements in sequencing technologies have significantly improved clinical genetic testing, yet the diagnostic yield remains around 30-40%. Emerging sequencing technologies are now being deployed in the clinical setting to address the remaining diagnostic gap.

Methods: We tested whether short-read genome sequencing could increase diagnostic yield in individuals enrolled into the UCI-GREGoR research study, who had suspected Mendelian conditions and prior inconclusive clinical genetic testing.

Burnout, Engagement, and Resilience During the COVID-19 Lockdown: Keys to a Model for Teachers' Self-Efficacy.

Background: Social isolation measures by the COVID-19 pandemic have impacted teaching work. In an "Emergency Remote Teaching" (ERT) context, it is relevant to investigate the factors that affect teachers' self-efficacy.

Methods: A total of 289 teachers from schools in southern Spain have participated in this study.

Homologous Recombination Abnormalities Associated With Mutations as Predicted by Machine Learning of Targeted Next-Generation Sequencing Data.

Background: Homologous recombination deficiency (HRD) is the hallmark of breast cancer gene 1/2 ()-mutated tumors and the unique biomarker for predicting response to double-strand break (DSB)-inducing drugs. The demonstration of HRD in tumors with mutations in genes other than is considered the best biomarker of potential response to these DSB-inducer drugs.

Objectives: We explored the potential of developing a practical approach to predict in any tumor the presence of HRD that is similar to that seen in tumors with mutations using next-generation sequencing (NGS) along with machine learning (ML).

Differential Diagnosis of Hematologic and Solid Tumors Using Targeted Transcriptome and Artificial Intelligence.

Diagnosis and classification of tumors is increasingly dependent on biomarkers. RNA expression profiling using next-generation sequencing provides reliable and reproducible information on the biology of cancer. This study investigated targeted transcriptome and artificial intelligence for differential diagnosis of hematologic and solid tumors.