Besides time, our approach could be applied using other surrogate measures of phenotype similarity, thus providing a versatile method of general interest to the phenotypic profiling community.

Source code is provided in https//github.com/bayer-science-for-a-better-life/plant-triplet-net.

Supplementary data are available at Bioinformatics online.

Supplementary data are available at Bioinformatics online.

Previous studies have indicated that Behçet’s disease (BD) has a genetic component, however population-level familial risk estimates are unavailable. We quantified the familial incidence and risk of BD in first-degree relatives (FDR) according to age, sex and type of family relationship.

Using the Korean National Health Insurance database, which has full population coverage and confirmed FDR information, we constructed a cohort of 21940795 individuals comprising 12 million families, which were followed for a familial occurrence of BD from 2002 to 2017. Age- and sex-adjusted incidence risk ratios for BD were calculated in individuals with affected FDR compared with those without affected FDR.

Among the total study population, 53687 individuals had affected FDR, of whom 284 familial cases developed BD with an incidence of 3.57/104 person-years. The familial risk (incidence) for BD was increased to 13.1-fold (2.71/104 person-years) in individuals with an affected father, 13.9-fold (3.11/104 person-years) with affected mother, 15.2-fold (4.9/104 person-years) with an affected sibling and the highest risk was 165-fold (46/104 person-years) with an affected twin. Familial risks showed age dependence, being higher in younger age groups. The sex-specific familial risk was similar in males and females.

This study provides quantified estimates of familial incidence and risk in FDR of BD patients in an entire population. Familial risks were higher within generation (sibling-sibling) vs between generations (parent-offspring). This implicates complex interactions between genetic factors and shared childhood environmental exposures in the pathogenesis of BD.

This study provides quantified estimates of familial incidence and risk in FDR of BD patients in an entire population. Familial risks were higher within generation (sibling-sibling) vs between generations (parent-offspring). Mitoquinone This implicates complex interactions between genetic factors and shared childhood environmental exposures in the pathogenesis of BD.

Uraemic cardiac remodelling is associated with vitamin D and Klotho deficiency, elevated fibroblast growth factor 23 (FGF23) and activation of the renin-angiotensin system (RAS). The cardioprotective properties of active vitamin D analogues in this setting are unclear.

In rats with 5/6 nephrectomy (5/6Nx) treated with calcitriol, the cardiac phenotype and local RAS activation were investigated compared with controls. A nested case-control study was performed within the Cardiovascular Comorbidity in Children with Chronic Kidney Disease (4C) study, including children with chronic kidney disease (CKD) Stages 3-5 [estimated glomerular filtration rate (eGFR) 25 mL/min/1.73 m2] treated with and without active vitamin D. Echocardiograms, plasma FGF23 and soluble Klotho (sKlotho) were assessed at baseline and after 9 months.

In rats with 5/6Nx, left ventricular (LV) hypertrophy, LV fibrosis and upregulated cardiac RAS were dose-dependently attenuated by calcitriol. Calcitriol further stimulated FGF23 synthesis o and higher serum phosphate in vitamin D-treated patients.

Pre-pregnancy counselling in women with systemic lupus erythematosus (SLE) is important in order to improve knowledge on the risks of pregnancy and to optimize pregnancy outcomes. Knowledge on the preferences of women with SLE regarding pre-pregnancy counselling have not yet been studied. In a closely monitored cohort of women with SLE we enquired about the present status of their wish to have children, and wish for and experiences with pre-pregnancy counselling.

A questionnaire developed by physicians in collaboration with two women with SLE was sent to all (n = 177) women participating in the Amsterdam SLE cohort. The questionnaire comprised 32 items, of which 15 focused on the above-mentioned three themes.

A total of 124 women (70%) returned the questionnaire. The median disease duration was 13 years (interquartile range 9-19). Childlessness occurred in 51 women and 31% declared this was due to SLE [conscious decision (21%), stringent medical advice (6%), infertility due to medication (4%)]. Half of g by healthcare providers on fertility, risks and pregnancy outcomes in women with SLE.

Large observational clinical datasets are becoming increasingly available for mining associations between various disease traits and administered therapy. These datasets can be considered as representations of the landscape of all possible disease conditions, in which a concrete disease state develops through stereotypical routes, characterized by “points of no return” and “final states” (such as lethal or recovery states). Extracting this information directly from the data remains challenging, especially in the case of synchronic (with a short-term follow-up) observations.

Here we suggest a semi-supervised methodology for the analysis of large clinical datasets, characterized by mixed data types and missing values, through modeling the geometrical data structure as a bouquet of bifurcating clinical trajectories. The methodology is based on application of elastic principal graphs, which can address simultaneously the tasks of dimensionality reduction, data visualization, clustering, feature selection, andl data.

Drug mass spectrometry imaging (MSI) data contain knowledge about drug and several other molecular ions present in a biological sample. However, a proper approach to fully explore the potential of such type of data is still missing. Therefore, a computational pipeline that combines different spatial and non-spatial methods is proposed to link the observed drug distribution profile with tumor heterogeneity in solid tumor. Our data analysis steps include pre-processing of MSI data, cluster analysis, drug local indicators of spatial association (LISA) map, and ions selection.

The number of clusters identified from different tumor tissues. The spatial homogeneity of the individual cluster was measured using a modified version of our drug homogeneity method. The clustered image and drug LISA map were simultaneously analyzed to link identified clusters with observed drug distribution profile. Finally, ions selection was performed using the spatially aware method.

In this paper, we have shown an approach to correlate the drug distribution with spatial heterogeneity in untargeted MSI data.