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Introduction: Aging is characterized as a syndrome of deleterious, progressive, universal, and irreversible function changes affecting every structural and functional aspect of the organism and accompanied by a generalized increase in mortality. Although a substantial number of candidates for biomarkers of aging have been proposed, none has been validated or universally accepted. Human telomeres constitute hexameric repetitive DNA sequence nucleoprotein complexes that cap chromosome ends, regulating gene expression and modulating stress-related pathways. Telomere length (TL) shortening is observed both in cellular senescence and advanced age, leading to the investigation of TL as a biomarker for aging and a risk factor indicator for the development and progression of the most common age-related diseases. Objective: The present review underlines the connection between TL and the pathophysiology of the diseases associated with telomere attrition. Methods: We performed a structured search of the PubMed database for peer-reviewed research of the literature regarding leukocyte TL and cardiovascular diseases (CVD), more specifically stroke and heart disease, and focused on the relevant articles published during the last 5 years. We also applied Hill’s criteria of causation to strengthen this association. Result: We analyzed the recent literature regarding TL length, stroke, and CVD. Although approximately one-third of the available studies support the connection, the results of different studies seem to be rather conflicting as a result of different study designs, divergent methods of TL determination, small study samples, and patient population heterogeneity. After applying Hill’s criteria, we can observe that the literature conforms to them weakly, with chronology being the only Hill criterion of causality that probably cannot be contested. Conclusion: The present review attempted to examine the purported relation between leukocyte TL and age-related diseases such as CVD and more specific stroke and heart disease in view of the best established, comprehensive, medical and epidemiological criteria that have characterized the focused recent relevant research. Although several recommendations have been made that may contribute significantly to the field, a call for novel technical approaches and studies is mandatory to further elucidate the possible association.

As the rate at which scientific work is published continues to increase, so does the need to discern high-impact publications. In recent years, there have been several approaches that seek to rank publications based on their expected citation-based impact. Despite this level of attention, this research area has not been systematically studied. Past literature often fails to distinguish between short-term impact, the current popularity of an article, and long-term impact, the overall influence of an article. Moreover, the evaluation methodologies applied vary widely and are inconsistent. In this work, we aim to fill these gaps, studying impact-based ranking theoretically and experimentally. First, we provide explicit definitions for short-term and long-term impact, and introduce the associated ranking problems. Then, we identify and classify the most important ideas employed by state-of-the-art methods. After studying various evaluation methodologies of the literature, we propose a specific benchmark framework that can help us better differentiate effectiveness across impact aspects. Using this framework we investigate: (1) the practical difference between ranking by short- and long-term impact, and (2) the effectiveness and efficiency of ranking methods in different settings. To avoid reporting results that are discipline-dependent, we perform our experiments using four datasets from different scientific disciplines.

This paper summarizes the content of the 20 tutorials that have been given at The Web Conference 2022: 85% of these tutorials are lecture style, and 15% of these are hands on. Published version

Background:The Low-Density Lipoprotein (LDL) Receptor (LDL-R) is a transmembrane protein playing a crucial role in effective lipid homeostasis. Various therapeutic agents have been used in the management of dyslipidemias, however, the outcome of therapeutic target is debated.Objective:The aim of this review is to summarize and fully understand the current concept regarding LDL-R and its molecular properties, metabolic pathway, factors affecting LDL-R activity and all available pharmacological interventions. Additionally, non-lipid related properties of LDL-R are also referred.Methods:Literature from the PubMed database was extracted to identify papers between 1984 to 2017 regarding LDL-R and therapeutic agents on dyslipidemia management.Results:We analyzed basic data regarding agents associated with LDL-R (Sterol Regulating Element-Binding Proteins - SREBPs, Protein ARH, IDOL, Thyroid Hormones, Haematologic Disorders, Protein convertase subtilisin kexintype 9 - PCSK-9, ApoC-III) as well as non-lipid related properties of LDL-R, while all relevant (common and novel) pharmacological interventions (statins, fibrates, cholesterol absorption inhibitors, bile acid sequestrants and PCSK- 9) are also referred.Conclusion:LDL-R and its molecular properties are involved in lipid homeostasis, so potentially sets the therapeutic goals in cardiovascular patients, which is usually debated. Further research is needed in order to fully understand its properties, as well as to find the potential pharmacological interventions that could be beneficial in cholesterol homeostasis and various morbidities in order to reach the most appropriate therapeutic goal.

Background Influenza virus infection is associated with increased morbidity and mortality in patients with diabetes mellitus. Public health authorities recommend yearly vaccination of diabetic patients against seasonal influenza. Methods We surveyed to define the adherence to influenza vaccination and associated factors among diabetic patients in Thessaloniki, Greece. Predictors of adherence to yearly influenza vaccination were assessed with logistic regression models. Results A total of 206 patients were enrolled, with 47.1% reporting yearly vaccination against influenza (95% confidence interval, CI:40.3% to 53.9%). In univariate models, the absence of additional indications for vaccination was associated with a decreased likelihood of vaccination uptake (OR:0.29, 95% CI:0.11 to 0.68, p=0.007); older diabetic patients were more likely to receive influenza vaccination (34% increase per 10 years of age). These associations were attenuated in multivariable analysis. Conclusion Our study demonstrates a significant gap in influenza vaccination coverage rate in diabetic patients. Our data could be extrapolated to enhance the uptake of vaccines against SARS-CoV-2: emphasis should be placed on patient education.

Η διαρκής αύξηση του όγκου των επιστημονικών δημοσιεύσεων δημιουργεί προβλήματα στη διάκριση των σημαντικότερων από αυτές, επηρεάζοντας ταυτόχρονα ερευνητές, φοιτητές, υπεύθυνους ακαδημαϊκών προσλήψεων, αλλά και τις μηχανές αναζήτησης. Για το λόγο αυτό υπάρχει ανάγκη ανάπτυξης μηχανισμών κατάταξης (ή αλλιώς ιεράρχησης) των επιστημονικών δημοσιεύσεων. Παρ' ότι υπάρχει πλούσια βιβλιογραφία γύρω από την ανεξαρτήτως ερωτήματος κατάταξη (query independent ranking) επιστημονικών δημοσιεύσεων (γνωστή και ως στατική κατάταξη), στόχος της οποίας είναι η περιγραφή μεθόδων κατάταξης επιστημονικών δημοσιεύσεων, με βάση την απήχηση τους, δεν έχει πραγματοποιηθεί έως τώρα κάποια μεθοδική και συστηματική ανασκόπηση του αντικειμένου. Συγκεκριμένα, στη τρέχουσα βιβλιογραφία υφίστανται κενά στον ορισμό της απήχησης, ενώ δε γίνεται διάκριση μεταξύ μακροχρόνιας και βραχυχρόνιας επιστημονικής απήχησης. Επίσης, δεν εξετάζεται η σχέση της απήχησης των δημοσιεύσεων με άλλα χαρακτηριστικά των κειμένων, όπως η αναγνωσιμότητα. Επιπλέον, δεν έχει πραγματοποιηθεί καμία εκτενής πειραματική αξιολόγηση των επιμέρους μεθόδων που έχουν προταθεί στη βιβλιογραφία. Αντικείμενο του διδακτορικού είναι η εξέταση της κατάταξης (ιεράρχησης) δημοσιεύσεων με βάση την απήχησή τους, των μεθόδων που έχουν προταθεί στη βιβλιογραφία, της εφαρμογής τους στα πλαίσια πραγματικών μηχανών αναζήτησης επιστημονικών δημοσιεύσεων και της συσχέτισης απήχησης - αναγνωσιμότητας δημοσιεύσεων. Συνοπτικά:• Ορίζονται τυπικά η μακροχρόνια και βραχυχρόνια απήχηση και εξετάζονται και κατηγοριοποιούνται οι προσεγγίσεις που έχουν διατυπωθεί στη τρέχουσα βιβλιογραφία.• Πραγματοποιείται μια εκτενής πειραματική αξιολόγηση για τη διερεύνηση των μηχανισμών που οδηγούν στη βέλτιστη αποτελεσματικότητα για την παραγωγή κατατάξεων των δημοσιεύσεων με βάση αυτά τα δύο είδη απήχησης.• Καθώς τα αποτελέσματα της αξιολόγησης αποκαλύπτουν περιθώρια βελτίωσης στην κατάταξη με βάση τη βραχυχρόνια απήχηση, προτείνεται μια νέα μέθοδος κατάταξης, επηρεασμένη από πρόσφατες εξελίξεις της επιστήμης δικτύων (network science), ενσωματώνοντας τροποποιήσεις στη μέθοδο PageRank. Με εκτενή πειραματική αξιολόγηση αναδεικνύεται η αποτελεσματικότητα της νέας μεθόδου σε σχέση με τις άλλες τρέχουσες τεχνολογίες αιχμής.• Παρουσιάζεται, επιπλέον, η ανάπτυξη εξειδικευμένων, αλλά και γενικών ακαδημαϊκών μηχανών αναζήτησης, οι οποίες κάνουν χρήση μεθόδων κατάταξης που έχουν εξεταστεί.• Τέλος, εξετάζεται η σχέση της αναγνωσιμότητας των περιλήψεων επιστημονικών δημοσιεύσεων με την απήχησή τους.

Background and objectives: The circadian pattern seems to play a crucial role in cardiovascular events and arrhythmias. Diabetes mellitus is a complex metabolic disorder associated with autonomic nervous system alterations and increased risk of microvascular and macrovascular disease. We sought to determine whether acute myocardial infarction (AMI) and atrial fibrillation (AF) follow a circadian pattern in diabetic patients in a Mediterranean country. Materials and Methods: This retrospective study included 178 diabetic patients (mean age: 67.7) with AMI or AF who were admitted to the coronary care unit. The circadian pattern of AMI and AF was identified in the 24-h period (divided in 3-h and 1-h intervals). Patients were also divided in 3 groups according to age, 40&ndash, 65 years, 66&ndash, 79 years and patients older than 80 years. A chi-square goodness-of-fit test was used for the statistical analysis. Results: AMI seems to occur more often in the midnight hours (21:00&ndash, 23:59) (p &lt, 0.001). Regarding age distribution, patients between 40 and 65 years were more likely to experience an AMI compared to other age groups (p &lt, 0.001). Autonomic alterations, working habits, and social reasons might contribute to this phenomenon. AF in diabetic patients occurs more frequently at noon (12:00&ndash, 14:59) (p = 0.019). Conclusions: Diabetic patients with AMI and AF seem to follow a specific circadian pattern in a Mediterranean country, with AMI occurring most often at midnight hours and AF mostly at noon. Autonomic dysfunction, glycemic fluctuations, intense anti-diabetic treatment before lunch, and patterns of insulin secretion and resistance may explain this pattern. More studies are needed to elucidate the circadian pattern of AMI and AF in diabetic patients to contribute to the development of new therapeutic approaches in this setting.

Background: Diabetes mellitus (DM) incidence is ever-increasing and along with its microvascular and macrovascular complications is associated with a high morbidity and mortality burden globally. Major components of diabetes pathophysiology include glucotoxicity, lipotoxicity and insulin resistance, disturbing the vascular wall integrity and leading to endothelial dysfunction and platelet hyperaggregation. Objective: This review aims to identify and summarize the effect of novel anti-diabetic agents (glucagon-like peptide-1 receptor agonists, dipeptidyl peptidase-4 inhibitors, sodium-glucose co-transporter -2 inhibitors) on endothelial (EF) and platelet function (PF) and evaluate the consistency with the results of cardiovascular outcomes studies. Methods: We performed a structured search of the PubMed database for peer-reviewed research of the literature between 1981 and 2020 regarding the effect of DM and novel anti-diabetic agents on EF and PF. Results: We analyzed data regarding the effect of novel anti-diabetic agents on EF and PF as well as the pathophysiological interplay between DM, PF, and EF. The available studies use different methods to evaluate these outcomes and the results of different studies are rather conflicting as a result of different study designs, combinations of drugs tested, small study samples and patient population heterogeneity. Conclusion: The currently available data do not unequivocally support a consistent effect of novel antidiabetic agents on EF and PF. Further study is required ideally with validation of the results with clinical outcomes.

HbA1c is a biomarker with a central role in the diagnosis and follow-up of patients with diabetes, although not a perfect one. Common comorbidities encountered in patients with diabetes mellitus, such as renal insufficiency, high output states (iron deficiency anaemia, haemolytic anaemia, haemoglobinopathies and pregnancy) and intake of specific drugs could compromise the sensitivity and specificity of the biomarker. COVID-19 pandemic poses a pressing challenge for the diabetic population, since maintaining optimal blood glucose control is key to reduce morbidity and mortality rates. Alternative methods for diabetes management, such as fructosamine, glycosylated albumin and device-based continuous glucose monitoring, are discussed.

Since the beginning of the coronavirus pandemic, a large number of relevant articles have been published or become available in preprint servers. These articles, along with earlier related literature, compose a valuable knowledge base affecting contemporary research studies or even government actions to limit the spread of the disease, and directing treatment decisions taken by physicians. However, the number of such articles is increasing at an intense rate, making the exploration of the relevant literature and the identification of useful knowledge challenging. In this work, we describe BIP4COVID19, an open data set that offers a variety of impact measures for coronavirus-related scientific articles. These measures can be exploited for the creation or extension of added-value services aiming to facilitate the exploration of the respective literature, alleviating the aforementioned issue. In the same context, as a use case, we provide a publicly accessible keyword-based search interface for COVID-19-related articles, which leverages our data to rank search results according to the calculated impact indicators.

As the number of published scientific papers continuously increases, the need to assess paper impact becomes more valuable than ever. In this work, we focus on citation-based measures that try to estimate the popularity (current impact) of an article. State-of-the-art methods in this category calculate estimates of popularity based on paper citation data. However, with respect to recent publications, only limited data of this type are available, rendering these measures prone to inaccuracies. In this work, we present ArtSim, an approach that exploits paper similarity, calculated using scholarly knowledge graphs, to better estimate paper popularity for recently published papers. Our approach is designed to be applied on top of existing popularity measures, to improve their accuracy. We apply ArtSim on top of four well-known popularity measures and demonstrate through experiments its potential in improving their popularity estimates.

Some data suggest that nocturnal dosing of antihypertensive agents may reduce cardiovascular outcomes more than daytime dosing. This trial was designed to evaluate whether ambulatory blood pressure monitoring levels differ by timing of drug dosing. Patients aged 18 to 80 years with reasonably controlled hypertension (≤150/≤90 mm Hg) on stable therapy of ≥1 antihypertensive agent were recruited from 2 centers in London and Thessaloniki. Patients were randomized to receive usual therapy either in the morning (6 am –11 am ) or evening (6 pm –11 pm ) for 12 weeks when participants crossed over to the alternative timing for a further 12 weeks. Clinic blood pressures and a 24-hour recording were taken at baseline, 12, and 24 weeks and routine blood tests were taken at baseline. The study had 80% power to detect 3 mm Hg difference in mean 24-hour systolic blood pressure (α=0.05) by time of dosing. A 2-level hierarchical regression model adjusted for center, period, and sequence was used. Of 103 recruited patients (mean age, 62; 44% female), 95 patients (92%) completed all three 24-hour recordings. Mean 24-hour systolic and diastolic blood pressures did not differ between daytime and evening dosing. Similarly, morning and evening dosing had no differential impact on mean daytime (7 am –10 pm ) and nighttime (10 pm –7 am ) blood pressure levels nor on clinic levels. Stratification by age (≤65/≥65 years) or sex did not affect results. In summary, among hypertensive patients with reasonably well-controlled blood pressure, the timing of antihypertensive drug administration (morning or evening) did not affect mean 24-hour or clinic blood pressure levels. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT01669928.

DIANA-TarBase v8 (http://www.microrna.gr/tarbase) is a reference database devoted to the indexing of experimentally supported microRNA (miRNA) targets. Its eighth version is the first database indexing >1 million entries, corresponding to ∼670 000 unique miRNA-target pairs. The interactions are supported by >33 experimental methodologies, applied to ∼600 cell types/tissues under ∼451 experimental conditions. It integrates information on cell-type specific miRNA–gene regulation, while hundreds of thousands of miRNA-binding locations are reported. TarBase is coming of age, with more than a decade of continuous support in the non-coding RNA field. A new module has been implemented that enables the browsing of interactions through different filtering combinations. It permits easy retrieval of positive and negative miRNA targets per species, methodology, cell type and tissue. An incorporated ranking system is utilized for the display of interactions based on the robustness of their supporting methodologies. Statistics, pie-charts and interactive bar-plots depicting the database content are available through a dedicated result page. An intuitive interface is introduced, providing a user-friendly application with flexible options to different queries.

Due to the rapidly increasing number of scientific articles, finding valuable work for further research has become tedious and time consuming. To alleviate this issue, search engines have used citation-based article impact ranking. However, most engines rely on very simplistic impact measures (usually the citation count) and make the problematic assumption that there is a one-size-fits-all impact measure. To address these problems, we present BIP! Finder, a search engine that facilitates the identification of valuable articles by exploiting two different impact measures, each capturing a different aspect of the article impact. In addition, BIP! Finder provides many useful features (article comparison, intuitive visualisations, article bookmarking mechanism, etc.) making it a powerful addition to the researcher's toolbox.

Monitoring trends in scientific disciplines is a common task forresearchers and other professionals in the broad research and academiccommunity, like research and innovation policy makers and research fundmanagers. We demonstrate SciTo, a powerful tool that assists in the monitoring oftrends in scientific disciplines. SciTo supports keyword-based search for the identification of scientific topics of interest and comparison ofinteresting topics to each other in terms of their popularity inside the academic community. Full author list: SerafeimChatzopoulos, PanagiotisDeligiannis, ThanasisVergoulis, IliasKanellos, ChristosTryfonopoulos, TheodoreDalamagas

Several works have used traditional readability measures to investigate the readability of scientific texts and its association with scientific impact . However, these works are limited in terms of dataset size, range of domains, and examined readability and impact measures. Our study addresses these limitations, investigating the readability of paper abstracts on a very large multidisciplinary corpus, the association of expert judgments on abstract readability with traditional readability measures, and the association of abstract readability with the scientific impact of the corresponding publication.

Introduction Recently there was a debate concerning the etiology behind attempts and completed suicides. The aim of the current study was to search for possible correlations between the rates of attempted and completed suicide and climate variables and regional unemployment per year in the county of Thessaloniki, Macedonia, northern Greece, for the years 2000–12. Material and methods The regional rates of suicide and attempted suicide as well as regional unemployment were available from previous publications of the authors. The climate variables were calculated from the daily E-OBS gridded dataset which is based on observational data Results Only the male suicide rates correlate significantly with high mean annual temperature but not with unemployment. The multiple linear regression analysis results suggest that temperature is the only variable that determines male suicides and explains 51% of their variance. Unemployment fails to contribute significantly to the model. There seems to be a seasonal distribution for attempts with mean rates being higher for the period from May to October and the rates clearly correlate with temperature. The highest mean rates were observed during May and August and the lowest during December and February. Multiple linear regression analysis suggests that temperature also determines the female attempts rate although the explained variable is significant but very low (3–5%) Conclusion Climate variables and specifically high temperature correlate both with suicide and attempted suicide rates but with a different way between males and females. The climate effect was stronger than the effect of unemployment.

Bone lymphomas can be classified as primary (PBL), or secondary (SBL). PBL is a rare entity, accounting for approximately 7% of malignant bone tumors, 5% of extra nodal lymphomas and

microRNAs (miRNAs) are small non-coding RNAs that actively fine-tune gene expression. The accurate characterization of the mechanisms underlying miRNA transcription regulation will further expand our knowledge regarding their implication in homeostatic and pathobiological networks. Aim of DIANA-miRGen v3.0 (http://www.microrna.gr/mirgen) is to provide for the first time accurate cell-line-specific miRNA gene transcription start sites (TSSs), coupled with genome-wide maps of transcription factor (TF) binding sites in order to unveil the mechanisms of miRNA transcription regulation. To this end, more than 7.3 billion RNA-, ChIP- and DNase-Seq next generation sequencing reads were analyzed/assembled and combined with state-of-the-art miRNA TSS prediction and TF binding site identification algorithms. The new database schema and web interface facilitates user interaction, provides advanced queries and innate connection with other DIANA resources for miRNA target identification and pathway analysis. The database currently supports 276 miRNA TSSs that correspond to 428 precursors and >19M binding sites of 202 TFs on a genome-wide scale in nine cell-lines and six tissues of Homo sapiens and Mus musculus.