Emerging Signatures of Hematological Malignancies from Gene Expression and Transcription Factor-Gene Regulations.

Hematological malignancies are a diverse group of cancers developing in the peripheral blood, the bone marrow or the lymphatic system. Due to their heterogeneity, the identification of novel and advanced molecular signatures is essential for enhancing their characterization and facilitate its translation to new pharmaceutical solutions and eventually to clinical applications. In this study, we collected publicly available microarray data for more than five thousand subjects, across thirteen hematological malignancies.

Transposable element exonization generates a reservoir of evolving and functional protein isoforms.

Alternative splicing enhances protein diversity in different ways, including through exonization of transposable elements (TEs). Recent transcriptomic analyses identified thousands of unannotated spliced transcripts with exonizing TEs, but their contribution to the proteome and biological relevance remains unclear. Here, we use transcriptome assembly, ribosome profiling, and proteomics to describe a population of 1,227 unannotated TE exonizing isoforms generated by mRNA splicing and recurrent in human populations.

External beam radiotherapy followed by image-guided adaptive brachytherapy in locally advanced cervical cancer: a multicenter retrospective analysis.

Purpose: To evaluate oncological outcomes and toxicities in patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy followed by image-guided adaptive brachytherapy at two Italian centres.

Material And Methods: A retrospective analysis was conducted on 122 patients with LACC treated between 2010 and 2022. Primary endpoints were local control (LC), pelvic control (PC), and nodal control (NC).

Time-series sewage metagenomics distinguishes seasonal, human-derived and environmental microbial communities potentially allowing source-attributed surveillance.

Sewage metagenomics has risen to prominence in urban population surveillance of pathogens and antimicrobial resistance (AMR). Unknown species with similarity to known genomes cause database bias in reference-based metagenomics. To improve surveillance, we seek to recover sewage genomes and develop a quantification and correlation workflow for these genomes and AMR over time.