MiRNome Profiling of Circulating Extracellular Vesicles in Patients With Chronic Hepatitis D Undergoing Pegylated Interferon Alpha Treatment.

Micro-RNAs (miRNAs) are involved in the modulation of viral replication and host immune antiviral response. Using next-generation sequencing, we investigated the miRNome profile of circulating extracellular vesicles in 20 patients with chronic hepatitis D virus (HDV) infection undergoing pegylated interferon alpha (Peg-IFNα) treatment. Circulating miRNAs' expression was analysed according to virologic response (i.

MUSE-XAE: MUtational Signature Extraction with eXplainable AutoEncoder enhances tumour types classification.

Motivation: Mutational signatures are a critical component in deciphering the genetic alterations that underlie cancer development and have become a valuable resource to understand the genomic changes during tumorigenesis. Therefore, it is essential to employ precise and accurate methods for their extraction to ensure that the underlying patterns are reliably identified and can be effectively utilized in new strategies for diagnosis, prognosis, and treatment of cancer patients.

Results: We present MUSE-XAE, a novel method for mutational signature extraction from cancer genomes using an explainable autoencoder.

Functional characterization of archaic-specific variants in mitonuclear genes: insights from comparative analysis in S. cerevisiae.

Neanderthal and Denisovan hybridisation with modern humans has generated a non-random genomic distribution of introgressed regions, the result of drift and selection dynamics. Cross-species genomic incompatibility and more efficient removal of slightly deleterious archaic variants have been proposed as selection-based processes involved in the post-hybridisation purge of archaic introgressed regions. Both scenarios require the presence of functionally different alleles across Homo species onto which selection operated differently according to which populations hosted them, but only a few of these variants have been pinpointed so far.

SYNDSURV: A simple framework for survival analysis with data distributed across multiple institutions.

Data sharing among different institutions represents one of the major challenges in developing distributed machine learning approaches, especially when data is sensitive, such as in medical applications. Federated learning is a possible solution, but requires fast communications and flawless security. Here, we propose SYNDSURV (SYNthetic Distributed SURVival), an alternative approach that simplifies the current state-of-the-art paradigm by allowing different centres to generate local simulated instances from real data and then gather them into a centralised hub, where an Artificial Intelligence (AI) model can learn in a standard way.

Influence of Model Structures on Predictors of Protein Stability Changes from Single-Point Mutations.

Missense variation in genomes can affect protein structure stability and, in turn, the cell physiology behavior. Predicting the impact of those variations is relevant, and the best-performing computational tools exploit the protein structure information. However, most of the current protein sequence variants are unresolved, and comparative or ab initio tools can provide a structure.

Variability of transient elastography-based spleen stiffness performed at 100 Hz.

Background: Spleen stiffness measurement (SSM) performed by transient elastography at 100 Hz is a novel technology for the evaluation of portal hypertension in advanced chronic liver disease, but technical aspects are lacking. We aimed to evaluate the intraexamination variability of SSM and to determine the best transient elastography protocol for obtaining robust measurements to be used in clinical practice.

Methods: We analyzed 253 SSM exams with up to 20 scans for each examination, performed between April 2021 and June 2022.

Small non-coding RNA profiling in patients with gastrointestinal cancer.

Background: Small non-coding (snc)RNAs, including microRNAs and P-element induced wimpy testis (PIWI)-interacting-RNAs (piRNAs), crucially regulate gene expression in both physiological and pathological conditions. In particular, some muscle-specific microRNAs (myomiRs) have been involved in the pathogenesis of cancer-induced muscle wasting. The aims of the present study were (i) to profile sncRNAs in both skeletal muscle and plasma of gastrointestinal cancer patients and (ii) to investigate the association among differentially expressed sncRNAs and the level of muscularity at body composition analysis.

Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics.

Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers.

Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review.

Background: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterised by the progressive loss of motor neurons in the brain and spinal cord. The fact that ALS's disease course is highly heterogeneous, and its determinants not fully known, combined with ALS's relatively low prevalence, renders the successful application of artificial intelligence (AI) techniques particularly arduous.

Objective: This systematic review aims at identifying areas of agreement and unanswered questions regarding two notable applications of AI in ALS, namely the automatic, data-driven stratification of patients according to their phenotype, and the prediction of ALS progression.

Impact of PNPLA3 rs738409 Polymorphism on the Development of Liver-Related Events in Patients With Nonalcoholic Fatty Liver Disease.

Background And Aims: Nonalcoholic fatty liver disease (NAFLD) is a complex disease, resulting from the interplay between environmental determinants and genetic variations. Single nucleotide polymorphism rs738409 C>G in the PNPLA3 gene is associated with hepatic fibrosis and with higher risk of developing hepatocellular carcinoma. Here, we analyzed a longitudinal cohort of biopsy-proven NAFLD subjects with the aim to identify individuals in whom genetics may have a stronger impact on disease progression.

Unravelling the instability of mutational signatures extraction archetypal analysis.

The high cosine similarity between some single-base substitution mutational signatures and their characteristic flat profiles could suggest the presence of overfitting and mathematical artefacts. The newest version (v3.3) of the signature database available in the Catalogue Of Somatic Mutations In (COSMIC) provides a collection of 79 mutational signatures, which has more than doubled with respect to previous version (30 profiles available in COSMIC signatures v2), making more critical the associations between signatures and specific mutagenic processes.

Challenges in predicting stabilizing variations: An exploration.

An open challenge of computational and experimental biology is understanding the impact of non-synonymous DNA variations on protein function and, subsequently, human health. The effects of these variants on protein stability can be measured as the difference in the free energy of unfolding (ΔΔ) between the mutated structure of the protein and its wild-type form. Throughout the years, bioinformaticians have developed a wide variety of tools and approaches to predict the ΔΔ.

Serum Extracellular Vesicle-Derived microRNAs as Potential Biomarkers for Pleural Mesothelioma in a European Prospective Study.

Malignant pleural mesothelioma (MPM) is an aggressive cancer with a dismal prognosis. Early therapeutic interventions could improve patient outcomes. We aimed to identify a pattern of microRNAs (miRNAs) as potential early non-invasive markers of MPM.

The 8q24 region hosts miRNAs altered in biospecimens of colorectal and bladder cancer patients.

Background: The 8q24 locus is enriched in cancer-associated polymorphisms and, despite containing relatively few protein-coding genes, it hosts the MYC oncogene and other genetic elements connected to tumorigenesis, including microRNAs (miRNAs). Research on miRNAs may provide insights into the transcriptomic regulation of this multiple cancer-associated region.

Material And Methods: We profiled all miRNAs located in the 8q24 region in 120 colorectal cancer (CRC) patients and 80 controls.

Deep learning methods to predict amyotrophic lateral sclerosis disease progression.

Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target the patient's treatment. Predictive models for disease progression are thus of great interest.

The genomic landscape of canine diffuse large B-cell lymphoma identifies distinct subtypes with clinical and therapeutic implications.

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid neoplasm in dogs and in humans. It is characterized by a remarkable degree of clinical heterogeneity that is not completely elucidated by molecular data. This poses a major barrier to understanding the disease and its response to therapy, or when treating dogs with DLBCL within clinical trials.

DDGun: an untrained predictor of protein stability changes upon amino acid variants.

Estimating the functional effect of single amino acid variants in proteins is fundamental for predicting the change in the thermodynamic stability, measured as the difference in the Gibbs free energy of unfolding, between the wild-type and the variant protein (ΔΔG). Here, we present the web-server of the DDGun method, which was previously developed for the ΔΔG prediction upon amino acid variants. DDGun is an untrained method based on basic features derived from evolutionary information.

Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer.

Background: Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine.

Methods: Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs).

BamToCov: an efficient toolkit for sequence coverage calculations.

Motivation: Many genomics applications require the computation of nucleotide coverage of a reference genome or the ability to determine how many reads map to a reference region.

Results: BamToCov is a toolkit for rapid and flexible coverage computation that relies on the most memory efficient algorithm and is designed for integration in pipelines, given its ability to read alignment files from streams. The tools in the suite can process sorted BAM or CRAM files, allowing the user to extract coverage information via different filtering approaches and to save the output in different formats (BED, Wig or counts).

Long-Term Hepatocellular Carcinoma Development and Predictive Ability of Non-Invasive Scoring Systems in Patients with HCV-Related Cirrhosis Treated with Direct-Acting Antivirals.

Patients with hepatitis C virus (HCV)-related cirrhosis treated with direct-acting antivirals (DAA) are still at risk of developing hepatocellular carcinoma (HCC). We investigated the accuracy of non-invasive scoring systems (NSS) for the prediction of de novo HCC development in patients treated with DAA on long-term follow-up (FU). We analyzed data from 575 consecutive patients with cirrhosis and no history of HCC who achieved a sustained virologic response (SVR) to DAA therapy.

Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset.

Predicting the difference in thermodynamic stability between protein variants is crucial for protein design and understanding the genotype-phenotype relationships. So far, several computational tools have been created to address this task. Nevertheless, most of them have been trained or optimized on the same and 'all' available data, making a fair comparison unfeasible.

Extracellular vesicles derived from tumour cells as a trigger of energy crisis in the skeletal muscle.

Background: Cachexia, a syndrome frequently occurring in cancer patients, is characterized by muscle wasting, altered energy and protein metabolism and impaired myogenesis. Tumour-derived microvesicles (TMVs) containing proteins, messenger RNAs (mRNAs), and non-coding RNAs could contribute to cancer-induced muscle wasting.

Methods: Differential ultracentrifugation was used to isolate TMVs from the conditioned medium of Lewis lung carcinoma and C26 colon carcinoma cell cultures.

Genetic and Epigenetic Characterization of a Discordant -Rearranged Infant Monozygotic Twin Pair.

The rearrangement is associated with an unfavorable prognosis in infant acute lymphocytic leukemia (ALL). Discordant ALL in monozygotic twins is uncommon and represents an attractive resource to evaluate intrauterine environment-genetic interplay in ALL. Mutational and epigenetic profiles were characterized for a discordant -rearranged infant monozygotic twin pair and their parents, and they were compared to three independent /-positive ALL infants, in which the DNA methylation and gene expression profiles were investigated.

Usefulness of a Hepatitis B Surface Antigen-Based Model for the Prediction of Functional Cure in Patients with Chronic Hepatitis B Virus Infection Treated with Nucleos(t)ide Analogues: A Real-World Study.

In patients with chronic hepatitis B (CHB) under long-term treatment with nucleso(t)ide analogues (NAs), the loss of hepatitis B surface antigen (HBsAg) is a rare event. A growing body of evidence supports the use of quantitative HBsAg for the prediction of functional cure, although these results are mainly derived from studies performed on Asian patients with hepatitis B e antigen (HBeAg)-positive CHB. Here, we investigated the clinical role of quantitative HBsAg in a real-life cohort of CHB patients under treatment with NAs in a tertiary care center from North-West Italy.