Advancements in long-read genome sequencing technologies and algorithms.

The recent advent of long read sequencing technologies, such as Pacific Biosciences (PacBio) and Oxford Nanopore technology (ONT), have led to substantial improvements in accuracy and computational cost in sequencing genomes. However, de novo whole-genome assembly still presents significant challenges related to the quality of the results. Pursuing de novo whole-genome assembly remains a formidable challenge, underscored by intricate considerations surrounding computational demands and result quality.

Comparing assembly strategies for third-generation sequencing technologies across different genomes.

The recent advent of long-read sequencing technologies, such as Pacific Biosciences (PacBio) and Oxford Nanopore technology (ONT), has led to substantial accuracy and computational cost improvements. However, de novo whole-genome assembly still presents significant challenges related to the computational cost and the quality of the results. Accordingly, sequencing accuracy and throughput continue to improve, and many tools are constantly emerging.

A bench-to-bedside study about trigger asynchronies induced by the introduction of external gas into the non-invasive mechanical ventilation circuit.

Treatments that require the introduction of external gas into the non-invasive ventilation (NIV) circuit, such as aerosol and oxygen therapy, may influence the performance of the ventilator trigger system. The aim of the study was to determine the presence and type of asynchronies induced by external gas in the NIV circuit in a bench model and in a group of patients undergoing chronic NIV. Bench study: Four ventilators (one with two different trigger design types) and three gas sources (continuous flow at 4 and 9 l/min and pulsatile flow at 9 l/min) were selected in an active simulator model.

Expression-based, consistent biomarkers for prognosis and diagnosis in lung cancer.

Overview: Lung cancer is one of the deadliest cancers in the world. Its histological classification depends on early diagnosis and successful treatment. Therefore, having specific biomarkers for a quick sorting widens the successful output of lung cancer treatment.

Biomarker potential of repetitive-element transcriptome in lung cancer.

Since repetitive elements (REs) account for nearly 53% of the human genome, profiling its transcription after an oncogenic change might help in the search for new biomarkers. Lung cancer was selected as target since it is the most frequent cause of cancer death. A bioinformatic workflow based on well-established bioinformatic tools (such as , , , and ) has been developed to identify differentially expressed RNAs from REs.