Slowly progressive autosomal dominant Alport Syndrome due to COL4A3 splicing variant.

Alport syndrome is a rare genetic kidney disease caused by variants in the COL4A3/A4/A5 genes. It's characterised by progressive kidney failure, though therapies targeting Renin-Angiotensin System can delay its progression. Additionally, extrarenal manifestations may sometimes coexist.

Methods and Software Tools for Reliable Operation of Flying LiFi Networks in Destruction Conditions.

The analysis of utilising unmanned aerial vehicles (UAVs) to form flying networks in obstacle conditions and various algorithms for obstacle avoidance is conducted. A planning scheme for deploying a flying LiFi network based on UAVs in a production facility with obstacles is developed and described. Such networks are necessary to ensure reliable data transmission from sensors or other sources of information located in dangerous or hard-to-reach places to the crisis centre.

Temporal dynamics of coordinated online behavior: Stability, archetypes, and influence.

Large-scale online campaigns, malicious or otherwise, require a significant degree of coordination among participants, which sparked interest in the study of . State-of-the-art methods for detecting coordinated behavior perform analyses, disregarding the temporal dynamics of coordination. Here, we carry out a analysis of coordinated behavior.

Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project.

Background: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating.

The fractured lens: a controversial revision of the International Classification of Primary Care.

Background: The International Classification of Primary Care (ICPC) has represented the international standard reduction for measuring the content of primary care for over 30 years. In the process of its third revision, its authors, the Wonca International Classification Committee (WICC), delegated a major part of the technical work to a purposely formed Consortium. However, in the process of such revision, standard classification principles and rules have been inconsistently applied with the result that ICPC-3 has been published with major errors and an inconsistent structure.

Accurate prognosis for localized prostate cancer through coherent voting networks with multi-omic and clinical data.

Localized prostate cancer is a very heterogeneous disease, from both a clinical and a biological/biochemical point of view, which makes the task of producing stratifications of patients into risk classes remarkably challenging. In particular, it is important an early detection and discrimination of the indolent forms of the disease, from the aggressive ones, requiring post-surgery closer surveillance and timely treatment decisions. This work extends a recently developed supervised machine learning (ML) technique, called coherent voting networks (CVN) by incorporating a novel model-selection technique to counter the danger of model overfitting.

Hooked Up from a Distance: Charting Genome-Wide Long-Range Interaction Maps in Neural Cells Chromatin to Identify Novel Candidate Genes for Neurodevelopmental Disorders.

DNA sequence variants (single nucleotide polymorphisms or variants, SNPs/SNVs; copy number variants, CNVs) associated to neurodevelopmental disorders (NDD) and traits often map on putative transcriptional regulatory elements, including, in particular, enhancers. However, the genes controlled by these enhancers remain poorly defined. Traditionally, the activity of a given enhancer, and the effect of its possible alteration associated to the sequence variants, has been thought to influence the nearest gene promoter.

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis.

Tailored treatments for metastatic colorectal cancer (mCRC) have not yet completely evolved due to the variety in response to drugs. Therefore, artificial intelligence has been recently used to develop prognostic and predictive models of treatment response (either activity/efficacy or toxicity) to aid in clinical decision making. In this systematic review, we have examined the ability of learning methods to predict response to chemotherapy alone or combined with targeted therapy in mCRC patients by targeting specific narrative publications in Medline up to April 2022 to identify appropriate original scientific articles.

The COVID-19 scamdemic: A survey of phishing attacks and their countermeasures during COVID-19.

The COVID-19 pandemic coincided with an equally-threatening scamdemic: a global epidemic of scams and frauds. The unprecedented cybersecurity concerns emerged during the pandemic sparked a torrent of research to investigate cyber-attacks and to propose solutions and countermeasures. Within the scamdemic, phishing was by far the most frequent type of attack.

Bow-tie structures of twitter discursive communities.

Bow-tie structures were introduced to describe the World Wide Web (WWW): in the direct network in which the nodes are the websites and the edges are the hyperlinks connecting them, the greatest number of nodes takes part to a bow-tie, i.e. a Weakly Connected Component (WCC) composed of 3 main sectors: IN, OUT and SCC.

Bridging between Mouse and Human Enhancer-Promoter Long-Range Interactions in Neural Stem Cells, to Understand Enhancer Function in Neurodevelopmental Disease.

Non-coding variation in complex human disease has been well established by genome-wide association studies, and is thought to involve regulatory elements, such as enhancers, whose variation affects the expression of the gene responsible for the disease. The regulatory elements often lie far from the gene they regulate, or within introns of genes differing from the regulated gene, making it difficult to identify the gene whose function is affected by a given enhancer variation. Enhancers are connected to their target gene promoters via long-range physical interactions (loops).

Heterozygosity for neuronal ceroid lipofuscinosis predisposes to bipolar disorder.

Objective: Bipolar disorder is a heritable chronic mental disorder that causes psychosocial impairment through depressive/manic episodes. Familial transmission of bipolar disorder does not follow simple Mendelian patterns of inheritance. The aim of this study was to describe a large family with 12 members affected by bipolar disorder.

Toward a Detailed Evaluation of Wireless Industrial Data Distribution Approaches.

Data distribution is a cornerstone of efficient automation for intelligent machines in Industry 4.0. Although in the recent literature there have been several comparisons of relevant methods, we identify that most of those comparisons are either theoretical or based on abstract simulation tools, unable to uncover the specific, detailed impacts of the methods to the underlying networking infrastructure.

Drug repositioning by merging active subnetworks validated in cancer and COVID-19.

Computational drug repositioning aims at ranking and selecting existing drugs for novel diseases or novel use in old diseases. In silico drug screening has the potential for speeding up considerably the shortlisting of promising candidates in response to outbreaks of diseases such as COVID-19 for which no satisfactory cure has yet been found. We describe DrugMerge as a methodology for preclinical computational drug repositioning based on merging multiple drug rankings obtained with an ensemble of disease active subnetworks.

Correction to: Flow of online misinformation during the peak of the COVID-19 pandemic in Italy.

[This corrects the article DOI: 10.1140/s13688-021-00289-4.].

Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling.

For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is hard, due to the heterogeneous nature of the disease. We devised a methodology for predicting 5-years survival based on the new machine learning paradigm of coherent voting networks, with improved accuracy over state-of-the-art prediction methods.

Flow of online misinformation during the peak of the COVID-19 pandemic in Italy.

Unlabelled: The COVID-19 pandemic has impacted on every human activity and, because of the urgency of finding the proper responses to such an unprecedented emergency, it generated a diffused societal debate. The online version of this discussion was not exempted by the presence of misinformation campaigns, but, differently from what already witnessed in other debates, the COVID-19 -intentional or not- flow of false information put at severe risk the public health, possibly reducing the efficacy of government countermeasures. In this manuscript, we study the impact of misinformation in the Italian societal debate on Twitter during the pandemic, focusing on the various discursive communities.

Protocol to analyze circulating small non-coding RNAs by high-throughput RNA sequencing from human plasma samples.

The identification and validation of circulating small non-coding RNA (sncRNA) as biomarkers for disease diagnosis, staging, and response to novel therapies is still a compelling challenge. Pre-analytical variables, such as storage temperature or blood hemolysis, and different analytical approaches affect sncRNA stability, detection, and expression, resulting in discrepancies among studies. Here, we report a systematic standardized protocol to reproducibly analyze circulating sncRNAs, employing high-throughput sncRNA sequencing and qRT-PCR validation, from 200 μL of human plasma samples.

ContextLabeler dataset: Physical and virtual sensors data collected from smartphone usage in-the-wild.

This paper describes a data collection campaign and the resulting dataset derived from smartphone sensors characterizing the daily life activities of 3 volunteers in a period of two weeks. The dataset is released as a collection of CSV files containing more than 45K data samples, where each sample is composed by 1332 features related to a heterogeneous set of physical and virtual sensors, including motion sensors, running applications, devices in proximity, and weather conditions. Moreover, each data sample is associated with a ground truth label that describes the user activity and the situation in which she was involved during the sensing experiment (e.

High-Throughput Identification of miRNA-Target Interactions in Melanoma Using miR-CATCHv2.0.

MicroRNAs (miRNAs) can regulate the expression of potentially every transcript in the cell, and the definition of miRNA-target interactions is crucial to understand their role in all biological processes. However, the identification of the miRNAs that target a specific mRNA remains a challenge. Here, we describe an innovative method called miR-CATCHv2.

Misinformation, manipulation, and abuse on social media in the era of COVID-19.

The COVID-19 pandemic represented an unprecedented setting for the spread of online misinformation, manipulation, and abuse, with the potential to cause dramatic real-world consequences. The aim of this special issue was to collect contributions investigating issues such as the emergence of infodemics, misinformation, conspiracy theories, automation, and online harassment on the onset of the coronavirus outbreak. Articles in this collection adopt a diverse range of methods and techniques, and focus on the study of the narratives that fueled conspiracy theories, on the diffusion patterns of COVID-19 misinformation, on the global news sentiment, on hate speech and social bot interference, and on multimodal Chinese propaganda.

Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method.

Genes are organized in functional modules (or pathways), thus their action and their dysregulation in diseases may be better understood by the identification of the modules most affected by the disease (aka disease modules, or active subnetworks). We describe how an algorithm based on the Core&Peel method is used to detect disease modules in co-expression networks of genes. We first validate Core&Peel for the general task of functional module detection by comparison with 42 methods participating in the Disease Module Identification DREAM challenge.

MicroRNA Expression in the Aqueous Humor of Patients with Diabetic Macular Edema.

We identified and compared secreted microRNA (miRNA) expression in aqueous humor (AH) and plasma samples among patients with: type 2 diabetes mellitus (T2D) complicated by non-proliferative diabetic retinopathy (DR) associated with diabetic macular edema (DME) (DME group: 12 patients); T2D patients without DR (D group: 8 patients); and non-diabetic patients (CTR group: 10 patients). Individual patient AH samples from five subjects in each group were profiled on TaqMan Low Density MicroRNA Array Cards. Differentially expressed miRNAs identified from profiling were then validated in single assay for all subjects.