Metabonomics Analysis of Plasma Reveals the Lactate to Cholesterol Ratio as an Independent Prognostic Factor of Short-Term Mortality in Acute Heart Failure

Objective

Mortality in heart failure (AHF) remains high, especially during the first days of hospitalization. New prognostic biomarkers may help to optimize treatment. The aim of the study was to determine metabolites that have a high prognostic value.

Methods

We conducted a prospective study on a training cohort of AHF patients (n = 126) admitted in the cardiac intensive care unit and assessed survival at 30 days. Venous plasmas collected at admission were used for ¹H NMR – based metabonomics analysis. Differences between plasma metabolite profiles allow determination of discriminating metabolites. A cohort of AHF patients was subsequently constituted (n = 74) to validate the findings.

Results

Lactate and cholesterol were the major discriminating metabolites predicting 30-day mortality. Mortality was increased in patients with high lactate and low total cholesterol concentrations at admission. Accuracies of lactate, cholesterol concentration and lactate to cholesterol (Lact/Chol) ratio to predict 30-day mortality were evaluated using ROC analysis. The Lact/Chol ratio provided the best accuracy with an AUC of 0.82 (P < 0.0001). The acute physiology and chronic health evaluation (APACHE) II scoring system provided an AUC of 0.76 for predicting 30-day mortality. APACHE II score, Cardiogenic shock (CS) state and Lact/Chol ratio ≥ 0.4 (cutoff value with 82% sensitivity and 64% specificity) were significant independent predictors of 30-day mortality with hazard ratios (HR) of 1.11, 4.77 and 3.59, respectively. In CS patients, the HR of 30-day mortality risk for plasma Lact/Chol ratio ≥ 0.4 was 3.26 compared to a Lact/Chol ratio of < 0.4 (P  =  0.018). The predictive power of the Lact/Chol ratio for 30-day mortality outcome was confirmed with the independent validation cohort.

Conclusion

This study identifies the plasma Lact/Chol ratio as a useful objective and simple parameter to evaluate short term prognostic and could be integrated into quantitative guidance for decision making in heart failure care.     

Omega 3 Fatty Acids Promote Macrophage Reverse Cholesterol Transport in Hamster Fed High Fat Diet

The aim of this study was to investigate macrophage reverse cholesterol transport (RCT) in hamster, a CETP-expressing species, fed omega 3 fatty acids (ω3PUFA) supplemented high fat diet (HFD). Three groups of hamsters (n = 6/group) were studied for 20 weeks: 1) control diet: Control, 2) HFD group: HF and 3) HFD group supplemented with ω3PUFA (EPA and DHA): HFω3. In vivo macrophage-to-feces RCT was assessed after an intraperitoneal injection of ³H-cholesterol-labelled hamster primary macrophages.Compared to Control, HF presented significant (p<0.05) increase in body weight, plasma TG (p<0.01) and cholesterol (p<0.001) with an increase in VLDL TG and in VLDL and LDL cholesterol (p<0.001).Compared to HF, HFω3 presented significant decrease in body weight. HFω3 showed less plasma TG (p<0.001) and cholesterol (p<0.001) related to a decrease in VLDL TG and HDL cholesterol respectively and higher LCAT activity (p<0.05) compared to HF. HFω3 showed a higher fecal bile acid excretion (p<0.05) compared to Control and HF groups and higher fecal cholesterol excretion (p<0.05) compared to HF. This increase was related to higher gene expression of ABCG5, ABCA1 and SR-B1 in HFω3 compared to Control and HF groups (<0.05) and in ABCG1 and CYP7A1 compared to HF group (p<0.05). A higher plasma efflux capacity was also measured in HFω3 using ³H- cholesterol labeled Fu5AH cells.In conclusion, EPA and DHA supplementation improved macrophage to feces reverse cholesterol transport in hamster fed HFD. This change was related to the higher cholesterol and fecal bile acids excretion and to the activation of major genes involved in RCT.     

Child Centred Approach to Climate Change and Health Adaptation through Schools in Bangladesh: A Cluster Randomised Intervention Trial

Background

Bangladesh is one of the most vulnerable countries to climate change. People are getting educated at different levels on how to deal with potential impacts. One such educational mode was the preparation of a school manual, for high school students on climate change and health protection endorsed by the National Curriculum and Textbook Board, which is based on a 2008 World Health Organization manual. The objective of this study was to test the effectiveness of the manual in increasing the knowledge level of the school children about climate change and health adaptation.

Methods

This cluster randomized intervention trial involved 60 schools throughout Bangladesh, with 3293 secondary school students participating. School upazilas (sub-districts) were randomised into intervention and control groups, and two schools from each upazila were randomly selected. All year seven students from both groups of schools sat for a pre-test of 30 short questions of binary response. A total of 1515 students from 30 intervention schools received the intervention through classroom training based on the school manual and 1778 students of the 30 control schools did not get the manual but a leaflet on climate change and health issues. Six months later, a post-intervention test of the same questionnaire used in the pre-test was performed at both intervention and control schools. The pre and post test scores were analysed along with the demographic data by using random effects model.

Results

None of the various school level and student level variables were significantly different between the control and intervention group. However, the intervention group had a 17.42% (95% CI: 14.45 to 20.38, P = <0.001) higher score in the post-test after adjusting for pre-test score and other covariates in a multi-level linear regression model.

Conclusions

These results suggest that school-based intervention for climate change and health adaptation is effective for increasing the knowledge level of school children on this topic.     

Identification of marker genes in Alzheimer's disease using a machine-learning model

Alzheimer''s Disease (AD) is one of the most common causes of dementia, mostly affecting the elderly population. Currently, there is no proper diagnostic tool or method available for the detection of AD. The present study used two distinct data sets of AD genes, which could be potential biomarkers in the diagnosis. The differentially expressed genes (DEGs) curated from both datasets were used for machine learning classification, tissue expression annotation and co-expression analysis. Further, CNPY3, GPR84, HIST1H2AB, HIST1H2AE, IFNAR1, LMO3, MYO18A, N4BP2L1, PML, SLC4A4, ST8SIA4, TLE1 and N4BP2L1 were identified as highly significant DEGs and exhibited co-expression with other query genes. Moreover, a tissue expression study found that these genes are also expressed in the brain tissue. In addition to the earlier studies for marker gene identification, we have considered a different set of machine learning classifiers to improve the accuracy rate from the analysis. Amongst all the six classification algorithms, J48 emerged as the best classifier, which could be used for differentiating healthy and diseased samples. SMO/SVM and Logit Boost further followed J48 to achieve the classification accuracy.     

Conservation value of alternative land-use systems for dung beetles in Amazon: valuing traditional farming practices

Land-use systems (LUS), placed in originally forested areas, represent different degrees of opportunity for species conservation. In this study, we examined the dung beetle communities in order to identify the conservation value of different LUS: primary forest, old secondary forest, young secondary forest, agroforestry, agriculture and pasture in Western Amazon. The LUS were sampled in two campaigns during the highest precipitation period and dryest period. The primary forest has a high number of total and exclusive species. Large beetles show a continuous decreasing in richness and abundance from primary forest to pastures, while small ones are not sensible to intermediate systems (secondary forest to agriculture) in terms of species richness and exhibit a increase in abundance at agroforest and agriculture when contrasted to secondary forest and pasture The beetle community composition was not sensible to secondary forest recovering time. Secondary forests and agroforestry stood out as harboring many species shared with primary forests. Cloud-point dispersion (average dissimilarity) increased from primary forest towards LUS’s submitted to more intense use. The higher sampling points similarity observed in primary forest might be the result of the relative stability of this system, given that environmental impacts might increase variability in community structure and beta diversity. Increase in beta diversity as expressed by greater dispersion of sites in multivariate space suggests that these areas are dependent on nearby species pools, possibly primary forests, and harbor a higher spatial heterogeneity in species composition. This high variability can overestimate the importance of occasional species, thus biasing the actual value of alternative LUS for biodiversity conservation.     

Seasonal physiological responses of Argania spinosa tree from Mediterranean to semi-arid climate

Argania spinosa (the argan tree) is a slow-growing tree endemic of Morocco, growing on semi-arid areas where no other tree species can live. With the aim of predicting temporal changes in A. spinosa woodlands under a probable increase in aridity, we set off to investigate these questions: how do A. spinosa physiological attributes respond to variations in climatic conditions and seasonality, and which is the set of attributes that most affects tree response to environmental conditions? In three study sites, Beni Snassen (North), High-Atlas (Mountain) and Admine Forest in Agadir (Coastal), gas exchange measurements, photochemical efficiency, leaf water potential and different leaf attributes were monitored in February, July and November of 2006. The Mountain site presents the most continental climate. Trees in this site were the most stressed in summer, having the lowest midday leaf water potential values, photochemical efficiency and assimilation rates. We found a Ψ_md threshold around -4 MPa, below which stomatal conductance responds linearly to Ψ_md. Plants from the North area never reached this threshold during the study period. Although leaf pigments presented a clear seasonal pattern, leaves from Coastal trees exhibit the highest content for each season. The three study sites were separated by two discriminate functions obtained by canonical discriminant analysis. In summer, the Mountain population is separated from the other sites mainly by assimilation rate and F_v/F_m, while in winter transpiration rates and chlorophyll content are the main discriminant variables. Our study shows that A. spinosa trees adjust their physiological status and leaf attributes to environmental conditions allowing plants to thrive under a dry climate. Under a scenario of global change, the distribution of the argan tree likely shifts to milder areas.