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The present study aimed at identifying the acoustic pattern of vocalizations, produced by 7- to 11-month-old infants, that were interpreted by their mothers as expressing emotions or communicative functions. Participants were 6 healthy, first-born English infants, 3 boys and 3 girls, and their mothers. The acoustic analysis of the vocalizations was performed using a pattern recognition (PR) software system. A PR system not only calculates signal features, it also automatically detects patterns in the arrangement of such features. The following results were obtained: (a) the PR system distinguished vocalizations interpreted as emotions from vocalizations interpreted as communicative functions with an overall accuracy of 87.34%; (b) the classification accuracy of the PR system for vocalizations that convey emotions was 85.4% and for vocalizations that convey communicative functions was 89.5%; and (c) compared to vocalizations that express emotions, vocalizations that express communicative functions were shorter, displayed lower fundamental frequency values, and had greater overall intensity. These findings suggest that in the second half of the first year, infants possess a vocal repertoire that contributes to regulating cooperative interaction with their mothers, which is considered one of the major prerequisites for language acquisition. KEY WORDS: infant vocalizations, pattern recognition, communication, emotions, The ability of infants, before the emergence of language, to communicate different kinds of messages through nonlinguistic aspects of voice can be investigated by examining whether vocalizations that have been [...]

We used the earthquake catalogue of INGV extending from 1 January 2006 to 30 June 2009 to detect significant changes before and after the 6 April 2009 L'Aquila mainshock (Mw=6.3) in the seismicity rate, r (events/day), and in b-value. The statistical z-test and Utsu-test were applied to identify significant changes. From the beginning of 2006 up to the end of October 2008 the activity was relatively stable and remained in the state of background seismicity (r=1.14, b=1.09). From 28 October 2008 up to 26 March 2009, r increased significantly to 2.52 indicating weak foreshock sequence; the b-value did not changed significantly. The weak foreshock sequence was spatially distributed within the entire seismogenic area. In the last 10 days before the mainshock, strong foreshock signal became evident in space (dense epicenter concentration in the hanging-wall of the Paganica fault), in time (drastic increase of r to 21.70 events/day) and in size (b-value dropped significantly to 0.68). The significantly high seismicity rate and the low b-value in the entire foreshock sequence make a substantial difference from the background seismicity. Also, the b-value of the strong foreshock stage (last 10 days before mainshock) was significantly lower than that in the after-shock sequence. Our results indicate the important value of the foreshock sequences for the prediction of the mainshock. [ABSTRACT FROM AUTHOR]

We describe herein a case of sudden visual loss due to Bartonella henselae infection. Immunofluorescence methods, together with PCR and fluorescein angiography were used to identify antibodies against the pathogen, DNA of the pathogen and possible inflammation of the eye. Visual loss was verified together with the existence of an edema and of exudates at the region of the macula. Antibodies against B. henselae were detected. The patient was treated with doxycycline, ranibizumab, and cortisone. Specific therapy with systemic antibiotics and anti-angiogenesis factors is important for the treatment of neuroretinitis by B. HENSELAE. [ABSTRACT FROM AUTHOR]

Bacterial Wars (BW) is a network-based tool that applies a two-step pipeline to display information on the competition of bacterial species found in the same microbiome. It utilizes antimicrobial peptide (AMP) sequence similarities to obtain a relationship between species. The working hypothesis (putative AMP defense) is that friendly species share sequence similarity among the putative AMPs of their proteomes and are therefore immune to their AMPs. This may not happen in competing bacterial species with dissimilar putative AMPs. Similarities in the putative AMPs of bacterial proteomes may be thus used to predict predominance. The tool provides insights as to which bacterial species are more likely to 'die' in a competing environmental niche., (© The Author(s) 2023. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

We draw from the assumption that similarities between pathogens at both pathogen protein and host protein level, may provide the appropriate framework to identify and rank candidate drugs to be used against a specific pathogen. Vir2Drug is a drug repurposing tool that uses network-based approaches to identify and rank candidate drugs for a specific pathogen, combining information obtained from: (a) ranked pathogen-to-pathogen networks based on protein similarities between pathogens, (b) taxonomy distance between pathogens and (c) drugs targeting specific pathogen's and host proteins. The underlying pathogen networks are used to screen drugs by means of specific methodologies that account for either the host or pathogen's protein targets. Vir2Drug is a useful and yet informative tool for drug repurposing against known or unknown pathogens especially in periods where the emergence for repurposed drugs plays significant role in handling viral outbreaks, until reaching a vaccine. The web tool is available at: https://bioinformatics.cing.ac.cy/vir2drug, https://vir2drug.cing-big.hpcf.cyi.ac.cy., (© The Author(s) 2022. Published by Oxford University Press.)

PathIN is a web-service that provides an easy and flexible way for rapidly creating pathway-based networks at several functional biological levels: genes, compounds and reactions. The tool is supported by a database repository of reference pathway networks across a large set of species, developed through the freely available information included in the KEGG, Reactome and Wiki Pathways database repositories. PathIN provides networks by means of five diverse methodologies: (a) direct connections between pathways of interest, (b) direct connections as well as the first neighbours of the given pathways, (c) direct connections, the first neighbours and the connections in between them, and (d) two additional methodologies for creating complementary pathway-to-pathway networks that involve additional (missing) pathways that interfere in-between pathways of interest. PathIN is expected to be used as a simple yet informative reference tool for understanding networks of molecular mechanisms related to specific diseases., Competing Interests: The authors have declared no Conflict of Interest., (© 2022 Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is undeniably the most severe global health emergency since the 1918 Influenza outbreak. Depending on its evolutionary trajectory, the virus is expected to establish itself as an endemic infectious respiratory disease exhibiting seasonal flare-ups. Therefore, despite the unprecedented rally to reach a vaccine that can offer widespread immunization, it is equally important to reach effective prevention and treatment regimens for coronavirus disease 2019 (COVID-19). Contributing to this effort, we have curated and analyzed multi-source and multi-omics publicly available data from patients, cell lines and databases in order to fuel a multiplex computational drug repurposing approach. We devised a network-based integration of multi-omic data to prioritize the most important genes related to COVID-19 and subsequently re-rank the identified candidate drugs. Our approach resulted in a highly informed integrated drug shortlist by combining structural diversity filtering along with experts' curation and drug-target mapping on the depicted molecular pathways. In addition to the recently proposed drugs that are already generating promising results such as dexamethasone and remdesivir, our list includes inhibitors of Src tyrosine kinase (bosutinib, dasatinib, cytarabine and saracatinib), which appear to be involved in multiple COVID-19 pathophysiological mechanisms. In addition, we highlight specific immunomodulators and anti-inflammatory drugs like dactolisib and methotrexate and inhibitors of histone deacetylase like hydroquinone and vorinostat with potential beneficial effects in their mechanisms of action. Overall, this multiplex drug repurposing approach, developed and utilized herein specifically for SARS-CoV-2, can offer a rapid mapping and drug prioritization against any pathogen-related disease., (© The Author(s) 2021. Published by Oxford University Press.)

A fundamental issue related to the understanding of the molecular mechanisms, is the way in which common pathways act across different biological experiments related to complex diseases. Using network-based approaches, this work aims to provide a numeric characterization of pathways across different biological experiments, in the prospect to create unique footprints that may characterise a specific disease under study at a pathway network level. In this line we propose PathExNET, a web service that allows the creation of pathway-to-pathway expression networks that hold the over- and under expression information obtained from differential gene expression analyses. The unique numeric characterization of pathway expression status related to a specific biological experiment (or disease), as well as the creation of diverse combination of pathway networks generated by PathExNET, is expected to provide a concrete contribution towards the individualization of disease, and further lead to a more precise personalised medicine and management of treatment. PathExNET is available at: https://bioinformatics.cing.ac.cy/PathExNET and at https://pathexnet.cing-big.hpcf.cyi.ac.cy/., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

This study aims to highlight SARS-COV-2 mutations which are associated with increased or decreased viral virulence. We utilize genetic data from all strains available from GISAID and countries' regional information, such as deaths and cases per million, as well as COVID-19-related public health austerity measure response times. Initial indications of selective advantage of specific mutations can be obtained from calculating their frequencies across viral strains. By applying modelling approaches, we provide additional information that is not evident from standard statistics or mutation frequencies alone. We therefore, propose a more precise way of selecting informative mutations. We highlight two interesting mutations found in genes N (P13L) and ORF3a (Q57H). The former appears to be significantly associated with decreased deaths and cases per million according to our models, while the latter shows an opposing association with decreased deaths and increased cases per million. Moreover, protein structure prediction tools show that the mutations infer conformational changes to the protein that significantly alter its structure when compared to the reference protein., Competing Interests: The authors have declared that no competing interests exist.

Signal transduction tasks as well as other complex biological processes involve many different changes in groups of genes, proteins, and metabolites linked together in chains or networks called pathways or networks of pathways. In a classical functional analysis, the biomolecules found to play a role in the biological status under investigation are members of a group of pathways that are not necessarily interconnected. However, interconnectivity is a critical factor for functionality. Thus, it is necessary to be able to construct "connected functional stories" to understand better the complex biological processes. PathwayConnector is a recently introduced web-tool that facilitates the construction of complementary pathway-to-pathway networks, bringing to our attention missing pathways that are crucial links towards the understanding of the molecular mechanisms related to complex diseases. Current version of the web-tool draws from an expanded pathway reference network and provides information deriving from 19 different organisms and 2 different pathway repositories: the KEGG and the REACTOME. Novel genes, proteins, and pathways derived from any experimental/computational method either in large-scale (omics) or even in smaller scale (specific laboratory experiments) can potentially be projected and analyzed through PathwayConnector. This chapter describes in details the pipeline and methodologies used for the latest updated version of PathwayConnector, providing an easy way for rapidly relating human or other organism's pathways together. Recent studies have shown that pathway networks and subnetworks, generated by PathwayConnector, are an integral part towards the individualization of disease, leading to a more precise and personalized management of the treatment.

Significant seismicity anomalies preceded the 25 October 2018 mainshock (M w = 6.8), NW Hellenic Arc: a transient intermediate-term (~2 yrs) swarm and a short-term (last 6 months) cluster with typical time-size-space foreshock patterns: activity increase, b-value drop, foreshocks move towards mainshock epicenter. The anomalies were identified with both a standard earthquake catalogue and a catalogue relocated with the Non-Linear Location (NLLoc) algorithm. Teleseismic P-waveforms inversion showed oblique-slip rupture with strike 10°, dip 24°, length ~70 km, faulting depth ~24 km, velocity 3.2 km/s, duration 18 s, slip 1.8 m within the asperity, seismic moment 2.0 × 10 26 dyne*cm. The two largest imminent foreshocks (M w = 4.1, M w = 4.8) occurred very close to the mainshock hypocenter. The asperity bounded up-dip by the foreshocks area and at the north by the foreshocks/swarm area. The accelerated foreshocks very likely promoted slip accumulation contributing to unlocking the asperity and breaking with the mainshock. The rupture initially propagated northwards, but after 6 s stopped at the north bound and turned southwards. Most early aftershocks concentrated in the foreshocks/swarm area. This distribution was controlled not only by stress transfer from the mainshock but also by pre-existing stress. In the frame of a program for regular monitoring and near real-time identification of seismicity anomalies, foreshock patterns would be detectable at least three months prior the mainshock, thus demonstrating the significant predictive value of foreshocks., Competing Interests: (A1)

Spastic ataxia (SA) is a group of rare neurodegenerative diseases, characterized by mixed features of generalized ataxia and spasticity. The pathogenetic mechanisms that drive the development of the majority of these diseases remain unclear, although a number of studies have highlighted the involvement of mitochondrial and lipid metabolism, as well as calcium signaling. Our group has previously published the GBA2 c.1780G > C (p.Asp594His) missense variant as the cause of spastic ataxia in a Cypriot consanguineous family, and more recently the biochemical characterization of this variant in patients' lymphoblastoid cell lines. GBA2 is a crucial enzyme of sphingolipid metabolism. However, it is unknown if GBA2 has additional functions and therefore additional pathways may be involved in the disease development. The current study introduces bioinformatics approaches to better understand the pathogenetic mechanisms of the disease. We analyzed publicly available human gene expression datasets of diseases presented with 'ataxia' or 'spasticity' in their clinical phenotype and we performed pathway analysis in order to: (a) search for candidate perturbed pathways of SA; and (b) evaluate the role of sphingolipid signaling pathway and sphingolipid metabolism in the disease development, through the identification of differentially expressed genes in patients compared to controls. Our results demonstrate consistent differential expression of genes that participate in the sphingolipid pathways and highlight alterations in the pathway level that might be associated with the disease phenotype. Through enrichment analysis, we discuss additional pathways that are connected to sphingolipid pathways, such as PI3K-Akt signaling, MAPK signaling, calcium signaling, and lipid and carbohydrate metabolism as the most enriched for ataxia and spasticity phenotypes.

Motivation: Understanding the underlying biological mechanisms and respective interactions of a disease remains an elusive, time consuming and costly task. Computational methodologies that propose pathway/mechanism communities and reveal respective relationships can be of great value as they can help expedite the process of identifying how perturbations in a single pathway can affect other pathways., Results: We present a random-walks-based methodology called PathWalks, where a walker crosses a pathway-to-pathway network under the guidance of a disease-related map. The latter is a gene network that we construct by integrating multi-source information regarding a specific disease. The most frequent trajectories highlight communities of pathways that are expected to be strongly related to the disease under study.We apply the PathWalks methodology on Alzheimer's disease and idiopathic pulmonary fibrosis and establish that it can highlight pathways that are also identified by other pathway analysis tools as well as are backed through bibliographic references. More importantly, PathWalks produces additional new pathways that are functionally connected with those already established, giving insight for further experimentation., Availability and Implementation: https://github.com/vagkaratzas/PathWalks., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2020. Published by Oxford University Press.)

ProTExA is a web-tool that provides a post-processing workflow for the analysis of protein and gene expression datasets. Using network-based bioinformatics approaches, ProTExA facilitates differential expression analysis and co-expression network analysis as well as pathway and post-pathway analysis. Specifically, for a given set of protein-gene expression data across samples, ProTExA: (1) performs statistical analysis and filtering to highlight the differentially expressed proteins-genes, (2) performs enrichment analysis to identify top-scored pathways, (3) generates pathway-to-pathway and pathway-to-gene networks (4) generates protein and gene co-expression networks using a variety of methodologies, and (5) applies clustering methodologies to identify sub-networks of co-expressed proteins-genes. The proposed web-tool is a simple yet informative tool, towards understanding and exploitation of protein and gene expression datasets, especially for those that do not have the expertise and local resources to replicate specific analyses in the context of collaborative and scientific data exchanging., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 The Author(s).)

Drug repurposing techniques allow existing drugs to be tested against diseases outside their initial spectrum, resulting in reduced cost and eliminating the long time-frames of new drug development. In silico drug repurposing further speeds up the process either by proposing drugs suitable to invert the transcriptomic profile of a disease or by indicating drugs based on their common targets or structural similarity with other drugs with similar mode of action. Such methods usually return a number of potential repurposed drugs that need to be tested against the disease in in vitro, pre-clinical and clinical studies. Thus, it is crucial to have a more sophisticated candidate drug ranking in order to start testing from the most promising chemical substances. As a means to enhance the above decision process, we present CoDReS (Composite Drug Reranking Scoring), a drug (re-)ranking web-based tool, which combines an initial drug ranking (i.e. repurposing score or hypothesis/potentiality score) with a functional score of each drug considered in conjunction with the disease under study as well as with a structural score derived from potential drugability violations. Furthermore, a structural similarity clustering is applied on the considered drugs and a handful of structural exemplars are suggested for further in vitro and in vivo validation. The user is able to filter the results further, through structural similarity examination of the candidate drugs with drugs that have failed against the queried disease where related clinical trials have been carried out. CoDReS is publicly available online at http://bioinformatics.cing.ac.cy/codres.

Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine., (© The Author 2017. Published by Oxford University Press.)

Variants of unknown/uncertain significance (VUS) pose a huge dilemma in current genetic variation screening methods and genetic counselling. Driven by methods of next generation sequencing (NGS) such as whole exome sequencing (WES), a plethora of VUS are being detected in research laboratories as well as in the health sector. Motivated by this overabundance of VUS, we propose a novel computational methodology, termed VariantClassifier (VarClass), which utilizes gene-association networks and polygenic risk prediction models to shed light into this grey area of genetic variation in association with disease. VarClass has been evaluated using numerous validation steps and proves to be very successful in assigning significance to VUS in association with specific diseases of interest. Notably, using VUS that are deemed significant by VarClass, we improved risk prediction accuracy in four large case-studies involving disease-control cohorts from GWAS as well as WES, when compared to traditional odds ratio analysis. Biological interpretation of selected high scoring VUS revealed interesting biological themes relevant to the diseases under investigation. VarClass is available as a standalone tool for large-scale data analyses, as well as a web-server with additional functionalities through a user-friendly graphical interface.

Summary: PathwayConnector is a web-tool that facilitates the construction of complementary pathway-to-pathway networks and subnetworks of them, based on a reference pathway network derived from the rich information available either in KEGG or Reactome database for pathway mapping. Specifically, for a given set of pathways, PathwayConnector (i) finds all the direct connections between them, (ii) adds a minimum set of complementary pathways required to achieve connectivity between the pathways, leading to informative fully connected networks and (ii) provides a series of clustering methods for the further grouping of pathways in to sub-clusters. The proposed web-tool is a simple yet informative tool towards identifying connected groups of pathways that are significantly related to specific diseases., Availability and Implementation: http://bioinformatics.cing.ac.cy/PathwayConnector., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2018. Published by Oxford University Press.)

Extracellular matrix (ECM)-related adhesion proteins are important in metastasis. Ras suppressor-1 (RSU-1), a suppressor of Ras -transformation, is localized to cell⁻ECM adhesions where it interacts with the Particularly Interesting New Cysteine-Histidine rich protein (PINCH-1), being connected to Integrin Linked Kinase (ILK) and alpha-parvin (PARVA), a direct actin-binding protein. RSU-1 was also found upregulated in metastatic breast cancer (BC) samples and was recently demonstrated to have metastasis-promoting properties. In the present study, we transiently silenced RSU-1 in BC cells, MCF-7 and MDA-MB-231. We found that RSU-1 silencing leads to downregulation of Growth Differentiation Factor-15 ( GDF-15 ), which has been associated with both actin cytoskeleton reorganization and metastasis. RSU-1 silencing also reduced the mRNA expression of PINCH-1 and cell division control protein-42 ( Cdc42 ), while increasing that of ILK and Rac regardless of the presence of GDF-15. However, the downregulation of actin-modulating genes PARVA , RhoA , Rho associated kinase-1 ( ROCK-1 ), and Fascin-1 following RSU-1 depletion was completely reversed by GDF-15 treatment in both cell lines. Moreover, complete rescue of the inhibitory effect of RSU-1 silencing on cell invasion was achieved by GDF-15 treatment, which also correlated with matrix metalloproteinase-2 expression. Finally, using a graph clustering approach, we corroborated our findings. This is the first study providing evidence of a functional association between RSU-1 and GDF-15 with regard to cancer cell invasion.