Brane Leskošek

Uterine electrical activity as predictor of preterm birth in women with preterm contractions

OBJECTIVE To estimate the risk of preterm birth in women admitted to the tertiary maternity hospital for preterm contractions by measuring electrical uterine activity. STUDY DESIGN The study included 47 patients with contractions between the 25th and 35th week of gestation and additional risk factors for preterm delivery. Uterine electrical activity was recorded using bipolar electrodes placed on the abdominal surface. A logistic model with the electromyographic and obstetric data was built, preterm delivery before 37th week of gestation being the outcome measure. RESULTS Seventeen patients (36%) delivered before term. Logistic regression model suggested only the intensity of electrical uterine activity and womans body weight to be significant predictors of preterm delivery, with high values related to preterm birth. They predict preterm delivery with the sensitivity of 47% and specificity of 90%. CONCLUSION We propose uterine EMG as a simple, non-invasive means to estimate the risk of preterm birth in a high-risk population with multiple risk factors present.

Activity of smooth muscles in human cervix and uterus.

OBJECTIVE To find the similarities and dissimilarities between the activity of the human smooth muscles in the cervix and in the uterine corpus at the onset of induced labour. STUDY DESIGN Electromyographic activity was measured in 14 primiparous women after amniotomy. The data were sampled and stored digitally in real time. For statistical analysis, the first 20 min of recordings following amniotomy were analyzed. The ratio between the mean activity at a given time and the mean activity over the whole 20 min was used for the comparison between the cervical and uterine activity. RESULTS The analysis of correlation showed that the electromyographic activity in the cervix differed from that in the uterine corpus in the majority of the enrolled cases. CONCLUSIONS The muscular activity in the cervix is independent of that in the uterine corpus at the onset of induced labour.

Four simple recommendations to encourage best practices in research software

Scientific research relies on computer software, yet software is not always developed following practices that ensure its quality and sustainability. This manuscript does not aim to propose new software development best practices, but rather to provide simple recommendations that encourage the adoption of existing best practices. Software development best practices promote better quality software, and better quality software improves the reproducibility and reusability of research. These recommendations are designed around Open Source values, and provide practical suggestions that contribute to making research software and its source code more discoverable, reusable and transparent. This manuscript is aimed at developers, but also at organisations, projects, journals and funders that can increase the quality and sustainability of research software by encouraging the adoption of these recommendations.

Top 10 metrics for life science software good practices

Metrics for assessing adoption of good development practices are a useful way to ensure that software is sustainable, reusable and functional. Sustainability means that the software used today will be available - and continue to be improved and supported - in the future. We report here an initial set of metrics that measure good practices in software development. This initiative differs from previously developed efforts in being a community-driven grassroots approach where experts from different organisations propose good software practices that have reasonable potential to be adopted by the communities they represent. We not only focus our efforts on understanding and prioritising good practices, we assess their feasibility for implementation and publish them here.

Comparison of bibliometric measures for assessing relative importance of researchers

Quantitative evaluation of citation data to support funding decisions has become widespread. For this purpose there exist many measures (indices) and while their properties were well studied there is little comprehensive experimental comparison of the ranking lists obtained when using different methods. A further problem of the existing studies is that lack of available data about net citations prevents researchers from studying the effect of measuring scientific impact by using net citations (all citations minus self-citations). In this paper we use simulated data to study factors that could potentially influence the degree of agreement between the rankings obtained when using different indices with the emphasis given to the comparison of the number of net citations per author to other more established indices. We observe that the researchers publishing papers with a large number of co-authors are systematically ranked higher when using h-index or total citations (TC) instead of the number of citations per author (TCA), that the researchers who publish a small proportion of papers which receive many citations while the rest of their papers receive only few citations are systematically ranked higher when using TCA or TC instead of h-index, and that the authors who have lower proportion of self-citations are ranked higher when considering indices which include the number of net citations in comparison with indices considering only the total citation count. Results are verified and illustrated also by analyzing a large dataset from the field of medical science in Slovenia for the period 1986–2007.

A multiscale model of the electrohysterogram the BioModUE_PTL project

The electrohysterogram (EHG) is a promising means of monitoring pregnancy and of detecting a risk of preterm labor. To improve our understanding of the EHG as well as its relationship with the physiologic phenomena involved in uterine contractility, we plan to model these phenomena in terms of generation and propagation of uterine electrical activity. This activity can be realistically modeled by representing the principal ionic dynamics at the cell level, the propagation of electrical activity at the tissue level and then the way it is reflected on the skin surface through the intervening tissue. We present in this paper the different steps leading to the development and validation of a biophysics based multiscale model of the EHG, going from the cell to the electrical signal measured on the abdomen.

A research information system (RIS) for breast cancer genetics

In healthcare great quantities of patient’s data are collected for healthcare and administrative/financial purposes. Some of these data would be very useful for potential research, however, for any serious research, uniform and standardised data are needed which are normally scattered among many different electronic and also paper based information data sources. We had a similar problem in our breast cancer genetics study, so a decision was made to develop a simple and lightweight web based research information system (RIS) which would allow user friendly data input, search, edit and export with low maintenance costs. For development our in-house system for automatic application generation (AAGIP) was used. Developed research information system is secure (all data between server and clients are encrypted by using 256-bit SSL protocol and database on server is periodically backuped), highly compatible (it was tested with number of popular browsers like Mozilla/Firefox, IE, Opera, Chrome, Safari...), fast (doesn’t use any high demanding graphical gadgets), userfriendly and allows (international) users simple data input (in local languages by using Unicode UTF-8 standard) and data usage/export for different simple or advanced analyses.

Consumption of antihypertensives in Slovenia and comparison with Norway

Background: Prescribing antihypertensives is increasing in Slovenia and worldwide. This article is aimed to analyze changes in prescribing antihypertensives in Slovenia in the years 2002–2008, as well as to find out to what extent the prescribing followed the Slovenian guidelines. Furthermore, the consumption of antihypertensives in Slovenia was compared with the consumption in the same period in Norway. Methods: We acquired statistical data on the number of primary care prescriptions of antihypertensives and defined daily doses (DDD) per 1000 inhabitants per day from the publications Primary Care Prescribing of Drugs in Slovenia, based on Anatomical-Therapeutic-Chemical Classification (ATC), published by the National Institute of Public Health for each year from 2002 to 2008. We calculated the number of prescriptions of each active ingredient, registered in Slovenia, of antihypertensive subgroups C02, C03, C07, C08 and C09 as well as for whole subgroups. Data on the consumption of antihypertensives in Norway were acquired from the website of the Norwegian Institute of Public Health. Results: In Slovenia, the number of prescriptions for antihypertensives per 1000 inhabitants increased by 57 % during the period 2002–2008. The increase in prescribing antihypertensives was highest between 2002 and 2003. Each year, the most widely prescribed drugs in Slovenia were agents acting on the renin-angiotensin system and the most widely prescribed active ingredient from this subgroup was enalapril. During the studied period, the relative consumption of beta blocking agents increased the most. In Slovenia, relatively more antihypertensives from the C02 subgroup and agents acting on the renin-angiotensin system (C09), but less diuretics (C03), beta blocking agents (C07) and calcium channel blockers (C08) were used, compared to Norway. Conclusions: Consumption of antihypertensives in Slovenia increased by more than a half in the period 2002–2008. The association between the increasing number of prescriptions for antihypertensives and the quality of arterial hypertension control in Slovenia has not been evaluated yet. Compared to Norway, Slovenia is more oriented to prescribing agents acting on the renin-angiotensin system.

Predicting potential drug-drug interactions on topological and semantic similarity features using statistical learning

Drug-drug interaction (DDI) is a change in the effect of a drug when patient takes another drug. Characterizing DDIs is extremely important to avoid potential adverse drug reactions. We represent DDIs as a complex network in which nodes refer to drugs and links refer to their potential interactions. Recently, the problem of link prediction has attracted much consideration in scientific community. We represent the process of link prediction as a binary classification task on networks of potential DDIs. We use link prediction techniques for predicting unknown interactions between drugs in five arbitrary chosen large-scale DDI databases, namely DrugBank, KEGG, NDF-RT, SemMedDB, and Twosides. We estimated the performance of link prediction using a series of experiments on DDI networks. We performed link prediction using unsupervised and supervised approach including classification tree, k-nearest neighbors, support vector machine, random forest, and gradient boosting machine classifiers based on topological and semantic similarity features. Supervised approach clearly outperforms unsupervised approach. The Twosides network gained the best prediction performance regarding the area under the precision-recall curve (0.93 for both random forests and gradient boosting machine). The applied methodology can be used as a tool to help researchers to identify potential DDIs. The supervised link prediction approach proved to be promising for potential DDIs prediction and may facilitate the identification of potential DDIs in clinical research.

Ten steps to get started in Genome Assembly and Annotation

As a part of the ELIXIR-EXCELERATE efforts in capacity building, we present here 10 steps to facilitate researchers getting started in genome assembly and genome annotation. The guidelines given are broadly applicable, intended to be stable over time, and cover all aspects from start to finish of a general assembly and annotation project. Intrinsic properties of genomes are discussed, as is the importance of using high quality DNA. Different sequencing technologies and generally applicable workflows for genome assembly are also detailed. We cover structural and functional annotation and encourage readers to also annotate transposable elements, something that is often omitted from annotation workflows. The importance of data management is stressed, and we give advice on where to submit data and how to make your results Findable, Accessible, Interoperable, and Reusable (FAIR).