A Chemical Structure and Machine Learning Approach to Assess the Potential Bioactivity of Endogenous Metabolites and Their Association with Early Childhood Systemic Inflammation.

Metabolomics has gained much attention due to its potential to reveal molecular disease mechanisms and present viable biomarkers. This work uses a panel of untargeted serum metabolomes from 602 children from the COPSAC2010 mother-child cohort. The annotated part of the metabolome consists of 517 chemical compounds curated using automated procedures. We created a filtering method for the quantified metabolites using predicted quantitative structure-bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines. The metabolites measured in the children's serums are predicted to affect specific targeted models, known for their significance in inflammation, immune function, and health outcomes. The targets from Tox21 have been used as targets with quantitative structure-activity relationships (QSARs). They were trained for ~7000 structures, saved as models, and then applied to the annotated metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation.

A chemical structure and machine learning approach to assess the potential bioactivity of endogenous metabolites and their association with early-childhood hs-CRP levels.

Metabolomics has gained much attraction due to its potential to reveal molecular disease mechanisms and present viable biomarkers. In this work we used a panel of untargeted serum metabolomes in 602 childhood patients of the COPSAC2010 mother-child cohort. The annotated part of the metabolome consists of 493 chemical compounds curated using automated procedures. Using predicted quantitative-structure-bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines, we created a filtering method for the vast number of quantified metabolites. The metabolites measured in children's serums used here have predicted potential against the chosen target modelled targets. The targets from Tox21 have been used with quantitative structure-activity relationships (QSARs) and were trained for ~7000 structures, saved as models, and then applied to 493 metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation. The significant metabolites were reported.

Linking infant size and early growth with maternal lifestyle and breastfeeding - the first year of life in the CRIBS cohort.

BACKGROUND: Every third child in Croatia is classed as overweight or obese. Infant growth can represent early warning signs for obesity. AIM: To detect early risk factors for obesity by investigating infant size and early growth trajectories and their association with maternal lifestyle and breastfeeding. SUBJECTS AND METHODS: Ninety-eight mother-child pairs from the Croatian Islands' Birth Cohort Study (CRIBS) cohort were included in the study. Data were collected from questionnaires and medical records. Growth data were converted to Z-scores using World Health Organisation (WHO) standards and used as the primary outcome. RESULTS: Z-score trajectories in the first year of life were in line with WHO standards. A direct link between infant size and maternal socioeconomic status (SES) or breastfeeding was not detected. However, child weight gain in the first 6 months was associated with maternal body mass index (BMI) before pregnancy (p < 0.01). A positive association was also established between breastfeeding and maternal SES and mothers that report an unhealthy diet have heavier children (p < 0.05, respectively). CONCLUSION: Infant size and early growth in Croatia is in line with WHO standards and risk factors for obesity development were detectable in the first year of life, but not highly pronounced. However, more effective BMI monitoring and promotion of a healthy diet and lifestyle of women before and during pregnancy is needed.

The Impact of Long-Term Clinoptilolite Administration on the Concentration Profile of Metals in Rodent Organisms.

Heavy metals are dangerous systemic toxicants that can induce multiple organ damage, primarily by inducing oxidative stress and mitochondrial damage. Clinoptilolite is a highly porous natural mineral with a magnificent capacity to eliminate metals from living organisms, mainly by ion-exchange and adsorption, thus providing detoxifying, antioxidant and anti-inflammatory medicinal effects. The in vivo efficiency and safety of the oral administration of clinoptilolite in its activated forms, tribomechanically activated zeolite (TMAZ) and Panaceo-Micro-Activated (PMA) zeolite, as well as the impact on the metallic biodistribution, was examined in healthy female rats. Concentration profiles of Al, As, Cd, Co, Pb, Ni and Sr were measured in rat blood, serum, femur, liver, kidney, small and large intestine, and brain using inductively coupled plasma mass spectrometry (ICP-MS) after a 12-week administration period. Our results point to a beneficial effect of clinoptilolite materials on the concentration profile of metals in female rats supplemented with the corresponding natural clinoptilolite materials, TMAZ and PMA zeolite. The observed decrease of measured toxicants in the kidney, femur, and small and large intestine after three months of oral intake occurred concomitantly with their most likely transient release into the bloodstream (serum) indicative of a detoxification process.

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia.

In this paper, the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown. Daily samples of PM1, PM2.5 and PM10 fractions were measured at an urban background sampling site in Zagreb, Croatia from 2009 to late 2020. For the purpose of meteorological normalization, the mass concentrations were fed alongside meteorological and temporal data to Random Forest (RF) and LightGBM (LGB) models tuned by Bayesian optimization. The models' predictions were subsequently de-weathered by meteorological normalization using repeated random resampling of all predictive variables except the trend variable. Three pollution periods in 2020 were examined in detail: January and February, as pre-lockdown, the month of April as the lockdown period, as well as June and July as the "new normal". An evaluation using normalized mass concentrations of particulate matter and Analysis of variance (ANOVA) was conducted. The results showed that no significant differences were observed for PM1, PM2.5 and PM10 in April 2020-compared to the same period in 2018 and 2019. No significant changes were observed for the "new normal" as well. The results thus indicate that a reduction in mobility during COVID-19 lockdown in Zagreb, Croatia, did not significantly affect particulate matter concentration in the long-term..

A Generation Shift in Mediterranean Diet Adherence and Its Association with Biological Markers and Health in Dalmatia, Croatia.

Previous studies have confirmed the beneficial effect of a Mediterranean diet in mitigating health issues related to cardiovascular disease, diabetes and obesity. However, rapid changes in the traditional way of life and the "westernization" of the diet in Mediterranean populations, especially in younger generations, has led to progressive abandonment of healthy dietary patterns. In order to investigate the generation shift in dietary patterns and lifestyle habits in the Mediterranean part of Croatia, we compared two cohorts of 610 women (266 pregnant and 344 non-pregnant) from the same region, but from different age groups. The MDSS score was derived from food frequency questionnaires. The results showed that the young, reproductively active generation (pregnant women) in Dalmatia, Croatia, although having a higher education and socioeconomic status, exhibits a more adverse eating behaviour (lower adherence to the Mediterranean diet) and lifestyle (excessive smoking in pregnancy) than the older population from the same region. Lower MDSS scores across aggregated age groups in both cohorts showed significant association with higher blood lipid levels and higher smoking frequency. In conclusion, Mediterranean diet adherence is associated with biological markers (age, lipid profile) and lifestyle (smoking) in our study, with a more adverse trend observed in the younger generation.