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Coronavirus Disease 2019 (COVID-19) is associated with increased incidence of neurological diseases and neuropsychiatric disorders after infection, but how it contributes to their development remains under investigation. Here, we investigate the possible relationship between COVID-19 and the development of ten neurological disorders and three neuropsychiatric disorders by exploring two pathological mechanisms: (i) dysregulation of host biological processes via virus–host protein–protein interactions (PPIs), and (ii) autoreactivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epitopes with host “self” proteins via molecular mimicry. We also identify potential genetic risk factors which in combination with SARS-CoV-2 infection might lead to disease development. Our analysis indicated that neurodegenerative diseases (NDs) have a higher number of disease-associated biological processes that can be modulated by SARS-CoV-2 via virus–host PPIs than neuropsychiatric disorders. The sequence similarity analysis indicated the presence of several matching 5-mer and/or 6-mer linear motifs between SARS-CoV-2 epitopes with autoreactive epitopes found in Alzheimer’s Disease (AD), Parkinson’s Disease (PD), Myasthenia Gravis (MG) and Multiple Sclerosis (MS). The results include autoreactive epitopes that recognize amyloid-beta precursor protein (APP), microtubule-associated protein tau (MAPT), acetylcholine receptors, glial fibrillary acidic protein (GFAP), neurofilament light polypeptide (NfL) and major myelin proteins. Altogether, our results suggest that there might be an increased risk for the development of NDs after COVID-19 both via autoreactivity and virus–host PPIs.

Fibrotic diseases constitute incurable maladies that affect a large portion of the population. Idiopathic Pulmonary Fibrosis is one of the most common, and thus studied, fibrotic diseases. Common ground among all fibrotic diseases is the uncontrollable fibrogenesis which is responsible for accumulated damage in the susceptible tissues. The plethora and complexity of the underlying mechanisms of fibrotic diseases account for the lack of regimens. Hence it is highly likely that a combination of drugs is required in order to counter every perturbation. In this study, we seek to identify common biological mechanisms and characteristics of fibrotic diseases, based on information acquired from biological databases, while we focus on Idiopathic Pulmonary Fibrosis. We also try to predict links between molecular data and their respective fibrotic phenotypes. We finally construct phenotypic and molecular networks, visualize them and apply a clustering algorithm on each network to identify fibrotic diseases that are close to Idiopathic Pulmonary Fibrosis.

The continuous rise of off-shore activities such as the development of wind farms requires a reliable operational support in order to minimize cost drawbacks and secure operations during the different stages of associated projects. One of the most important parameters for this kind of analysis is wind gustiness. The objective of the study is the development of a methodology for the surface wind gust estimation based on Numerical Weather Prediction Models and statistical post processing. The obtained method has been tested over the offshore west coastline of the United States and evaluated utilizing observational data from the NOAA' s buoy network. (C) 2017 The Authors. Published by Elsevier Ltd.

BiDaS is a web-application that can generate massive Monte Carlo simulated sequence or numerical feature data sets (e.g. dinucleotide content, composition, transition, distribution properties) based on small user-provided data sets. BiDaS server enables users to analyze their data and generate large amounts of: (i) Simulated DNA/RNA and aminoacid (AA) sequences following practically identical sequence and/or extracted feature distributions with the original data. (ii) Simulated numerical features, presenting identical distributions, while preserving the exact 2D or 3D between-feature correlations observed in the original data sets. The server can project the provided sequences to multidimensional feature spaces based on: (i) 38 DNA/RNA features describing conformational and physicochemical nucleotide sequence features from the B-DNA-VIDEO database, (ii) 122 DNA/RNA features based on conformational and thermodynamic dinucleotide properties from the DiProDB database and (iii) Pseudo-aminoacid composition of the initial sequences. To the best of our knowledge, this is the first available web-server that allows users to generate vast numbers of biological data sets with realistic characteristics, while keeping between-feature associations. These data sets can be used for a wide variety of current biological problems, such as the in-depth study of gene, transcript, peptide and protein groups/families; the creation of large data sets from just a few available members and the strengthening of machine learning classifiers. All simulations use advanced Monte Carlo sampling techniques. The BiDaS web-application is available at http://bioserver-3.bioacademy.gr/Bioserver/BiDaS/.

Inflammation is involved in the mechanisms of premature atherosclerosis and aortopathy of patients with repaired coarctation of aorta (RCoA). We aimed at exploring the role of positron emission tomography/computed tomography (PET/CT) imaging for evaluating aortic wall inflammation in patients with

In the last few years, mobile devices such as smartphones and tablets have become an integral part of everyday life, due to their software/hardware rapid development, as well as the increased portability they offer. Nevertheless, up to now, only few Apps have been developed in the field of bioinformatics, capable to perform fast and robust access to services. We have developed the GeneStoryTeller, a mobile application for Android platforms, where users are able to instantly retrieve information regarding any recorded human gene, derived from eight publicly available databases, as a summary story. Complementary information regarding gene–drugs interactions, functional annotation and disease associations for each selected gene is also provided in the gene story. The most challenging part during the development of the GeneStoryTeller was to keep balance between storing data locally within the app and obtaining the updated content dynamically via a network connection. This was accomplished with the implementation of an administrative site where data are curated and synchronized with the application requiring a minimum human intervention. Database URL: http://bioserver-3.bioacademy.gr/Bioserver/GeneStoryTeller/.

Historically, face-lifting consisted of elevating the skin, placing it under tension to reduce the wrinkles, resecting the skin needed to accomplish this, and then securing the resected edges. However, over time, facelift surgery evolved beyond the Dorland’s definition of “rhytidectomy” (excision of skin for the elimination of wrinkles [1]) and various different techniques and indications have been described.We report of the pre-auricular facelift approach, as described by Skoog [2] for alternative use: The excision of a giant cell tumour, utilizing this facelift technique to achieve serial excision from a two year old, male patient’s face. This has resulted in a satisfactory aesthetic outcome and scar alignment in favourable area as well as excision of a significant part of the lesion, and awaiting further serial excision for completion.

Tetrahymena thermophila is a unicellular eukaryotic model organism used for a variety of biochemical, molecular and biological studies. According to its macronucleus genome sequence, it is expected to contain more than 27,000 protein-coding genes, although only a small proportion of them have information published specifically about them. Here, we present a reference map for whole cell lysate of T. thermophila obtained using two-dimensional gel electrophoresis (2-DE) combined with mass spectrometry. Although (2-DE) is one of the most efficient techniques for resolving complex protein mixtures and revealing the relative high-abundance proteins, it has not yet been applied generally to ciliates. In order to obtain qualitative protein samples for analysis, an appropriate homogenization method is required. Optimization of the homogenization method led to the analysis of nearly 4500 protein spots, the final identification of 375 different proteins using Mascot software and an additional 258 gene products using a newly developed web service, called Peptide Finder, resulting in a total of 631 different gene products that are considered to constitute the proteomic profile of the whole cell lysate of T. thermophila.

Promoter regions of the human genome play a key role in our understanding of the regulatory mechanisms related to the physiological and disease states. The aim of this study was to investigate the sequence positional properties of experimentally verified human promoters. Consequently, we determined short sequence elements ranging from 4 to 9mers presenting position dominance close to, or away from the transcription start site (TSS). For this purpose rigid statistical criteria were used and whether position dominance was in any way related to transcription control was determined. To achieve this goal we designed and implemented a dedicated filtering method to massively detect position-dominant sequence elements embedded in the promoter set. Additionally, via a high throughput procedure, we gathered data on the majority of the publicly available transcription factor-binding sites (TFBSs) and matched them to our findings, aiming to accomplish a large-scale correlation between position-dominant sequence elements and TFBSs. In this analysis, we present unique compositional and conservational perturbations at the TSS and the core promoter region. Using our filtering method, 7,088 short sequences ranging from 4 to 9mers were found to present strong positional dominance close to or away from the TSS, while the aforementioned short sequences were matched to a large number of known TFBSs. Moreover, using probability theory, evidence is presented showing that TFBSs tend to present strong positional preferences. In addition, we demonstrate that the actual TFBS copy number is related to the transcription regulatory process. On the basis of the last argument, it is suggested that all the detected short sequences which did not match any known TFBS, have a high potential for being novel transcription control elements. Furthermore, using a well-described ;high potential cancer biomarker resource', we attempted to identify position dominant sequence elements associated with cancer, as derived by their presence in the respective promoters of cancer related proteins.

One of the most common cancer types among women is breast cancer. Regular mammographic examinations increase the possibility for early diagnosis and treatment and significantly improve the chance of survival for patients with breast cancer. Keeping an informed and complete patient record is of great importance as the doctor needs this information for every patient examination. The proposed implementation is a patient record system that includes 'smart' algorithms in order to automatically use data from the patient's record to calculate well established epidemiological breast cancer models. A computer-aided diagnosis system is also used in order to analyze each mammogram and obtain a certain risk percentage concerning whether the patient has to undergo biopsy or not. The aforementioned system has been implemented to support a large set of patient data (1,178 patients) which included detailed personal patient data, medical history and examination details per date and is used in the daily clinical practice of a breast cancer diagnostic center facilitating patient record retrieval, storage and supporting the doctor's decisions.

We address here the problem of the noise deterioration of the quality of the reconstructed images when employing the maximum likelihood expectation maximization (MLEM) algorithm for iterative image reconstruction in positron emission tomography (PET). It is observed that despite the fact the cost function (log-likelihood) is monotonically increasing, the image quality deteriorates after reaching a certain “optimum” point during the iterative process. The principal aim of the work is the discovery of a rule that would directly link the quality of the reconstructed images at each iteration with the log-likelihood. We assume that the true image corresponds to a log-likelihood value in correlation with the data acquired, which, when achieved, makes no sense looking for higher log-likelihood levels. We study here the hypothesis that there is a direct correlation of the log-likelihood of the true image (a quantity that is not known a priori in real PET scans) and acquired data, with certain properties of the pixel updating coefficients (PUC) in the MLEM algorithm. For the validation of this hypothesis we have employed Monte Carlo experiments using known phantoms. We show here that the minimum value of the PUC for the non-zero pixels might be one parameter that could be used to verify the above mentioned hypothesis.

Mammography is accepted as the most effective method to detect breast cancer. However, interpreting a mammogram is not easy for not experienced radiologists. The aim of computer aided detection techniques in breast cancer is to improve the chance that a malignant region is detected and appropriately evaluated. Breast microcalcifications have been considered as a very useful index of malignancy, which helps in the early detection of breast cancer. A system of computer aided diagnosis has been developed that is based on detailed analysis and evaluation of related features of individual microcalcifications and of formed clusters helping the doctor to make risk estimation for each microcalcification cluster as well as for isolated microcalcifications. This information is considered to be very useful to radiologists, giving them extra input before making their estimation of each case. The aforementioned system has been thoroughly tested using a number of real life cases provided from collaborating doctors. Each case, apart from the mammograms, was accompanied by a biopsy test result, the patient's demographic data and medical history. A total of 200 cases (147 benign and 53 malignant) have been examined and the results are presented as the Receiver Operating Characteristic (ROC) performance and are quantified using the ROC curve. The system is showing high levels of sensitivity identifying correctly all malignant cases.

Tissue expansion is in widespread use for the reconstruction of congenital and acquired defects. Complications of tissue expansion are well documented, the most common being infection or extrusion of the expander. Although the complications associated with scalp tissue expansion are similar to those experienced elsewhere in the body, site-specific complications can occur. These include bone thinning and erosion of the cranial vault. In this study, we report an unusual case of multiple osteophyte formation beneath a scalp tissue expander, resulting in its rupture and necessitating removal.