Polymorphism of the FABP2 gene: a population frequency analysis and an association study with cardiovascular risk markers in Argentina

<p>Abstract</p> <p>Background</p> <p>The FABP2 gene encodes for the intestinal FABP (IFABP) protein, which is expressed only in intestinal enterocytes. A polymorphism at codon 54 in exon 2 of the FABP2 gene exchanges an Alanine (Ala), in the small helical region of the protein, for Threonine (Thr). Given the potential physiological role of the Ala54Thr FABP2 polymorphism, we assess in this study the local population frequency and analyze possible associations with five selected markers, i.e. glycemia, total cholesterol, body mass index (BMI), hypertension, and high Cardiovascular Risk Index (CVR index).</p> <p>Methods</p> <p>We studied 86 men and 116 women. DNA was extracted from a blood drop for genotype analysis. Allele frequencies were calculated by direct counting. Hardy Weinberg Equilibrium was evaluated using a Chi-square goodness of fit test.</p> <p>For the polymorphism association analysis, five markers were selected, i.e. blood pressure, Framingham Risk Index, total cholesterol, BMI, and glycemia.</p> <p>For each marker, the Odds Ratio (OR) was calculated by an online statistic tool.</p> <p>Results</p> <p>Our results reveal a similar population polymorphism frequency as in previous European studies, with <b>q = 0.277 </b>(95% confidence limits 0.234–0.323). No significant association was found with any of the tested markers in the context of our Argentine nutritional and cultural habits. We did, however, observe a tendency for increased Cholesterol and high BMI in Thr54 carriers.</p> <p>Conclusion</p> <p>This is the first study to look at the population frequency of the Thr54 allele in Argentina. The obtained result does not differ from previously reported frequencies in European populations. Moreover, we found no association between the Thr54 allele and any of the five selected markers. The observed tendency to increased total cholesterol and elevated BMI in Thr54 carriers, even though not significant for p < 0.1 could be worth of further investigation to establish whether the Thr54 variant should be taken into consideration in cardiovascular prevention strategies.</p

Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study

Assessing biodiversity from field-based data is difficult for a number of practical reasons: (i) establishing the total number of sampling units to be investigated and the sampling design (e.g. systematic, random, stratified) can be difficult; (ii) the choice of the sampling design can affect the results; and (iii) defining the focal population of interest can be challenging. Satellite remote sensing is one of the most cost-effective and comprehensive approaches to identify biodiversity hotspots and predict changes in species composition. This is because, in contrast to field-based methods, it allows for complete spatial coverages of the Earth's surface under study over a short period of time. Furthermore, satellite remote sensing provides repeated measures, thus making it possible to study temporal changes in biodiversity. While taxonomic diversity measures have long been established, problems arising from abundance related measures have not been yet disentangled. Moreover, little has been done to account for functional diversity besides taxonomic diversity measures. The aim of this manuscript is to propose robust measures of remotely sensed heterogeneity to perform exploratory analysis for the detection of hotspots of taxonomic and functional diversity of plant species

International Consensus Guidelines for the Definition, Detection, and Interpretation of Autophagy-Dependent Ferroptosis

Macroautophagy/autophagy is a complex degradation process with a dual role in cell death that is influenced by the cell types that are involved and the stressors they are exposed to. Ferroptosis is an iron-dependent oxidative form of cell death characterized by unrestricted lipid peroxidation in the context of heterogeneous and plastic mechanisms. Recent studies have shed light on the involvement of specific types of autophagy (e.g. ferritinophagy, lipophagy, and clockophagy) in initiating or executing ferroptotic cell death through the selective degradation of anti-injury proteins or organelles. Conversely, other forms of selective autophagy (e.g. reticulophagy and lysophagy) enhance the cellular defense against ferroptotic damage. Dysregulated autophagy-dependent ferroptosis has implications for a diverse range of pathological conditions. This review aims to present an updated definition of autophagy-dependent ferroptosis, discuss influential substrates and receptors, outline experimental methods, and propose guidelines for interpreting the results

A plot-level exploratory analysis of European forest based on the results from the BioSoil Forest Biodiversity project

The lack of multi-dimensional data is one of the major gaps which limit the knowledge and the assessment possibilities of European forests. Nowadays, the most extensive and complete data on the European forest statuses are given by National Forest Inventories (NFIs) which provide information about the extent of forest's resources and their composition and structure. Traditionally, NFIs collect data related to trees, with a limited consideration of other habitat components, such as ground vegetation. This information which goes beyond the mere arboreal component is instead essential for a more complete forest biodiversity assessment. This paper is aimed at introducing the ICP Forests LI-BioDiv database which resulted from BioSoil Forest Biodiversity, a large collaborative European project. This database is organized as a multi-dimensional forest geodatabase that contains forest structure and vegetation records collected in 19 European countries in the period of 2005-2008. The data were acquired from 3311 geocoded plots where several different types of data were gathered: stand-level general information, tree-level data, deadwood, canopy closure and floristic composition. This paper is structured in order to: (1) give a clear overview of the raw data available in the database and to (2) present an elaboration of raw data to calculate simple plot-level forest variables (biomass, deadwood volume, alpha diversity). On the basis of the results we achieved, the LI-BioDiv database appears useful mainly for research purposes aimed at studying cross-relationships between multiple forest variables and not for an operative use for monitoring and assessing European forest. In particular, we hope that this contribution can stimulate scientists to carry out cross-analysis of the database for defining future forest biodiversity indicators that could be introduced into the field protocols of the NFIs in Europe

Valutazione delle foreste europee attraverso il Li-BioDiv database all’interno della rete ICP Forest

Il Li-BioDiv database (ICP Forests) che deriva dal progetto BioSoil-Biodiversity, rappresenta un database multidimensionale riguardo alle foreste con dati provenienti da 19 paesi europei, investigati tra il 2005 e il 2008. Tale database contiene informazioni riguardo agli alberi vivi, legno morto e dati riguardo allo strato erbaceo. Il progetto BioSoil-Biodiversity rappresenta l’unica iniziativa di monitoraggio standardizzato multidimesionale della diversità forestale a livello europeo, tuttavia, il Li-BioDiv database risulta essere sottoutilizzato dal mondo scientifico a causa di passate restrizioni di tipo amministrativo-politico e fino ad oggi non sono state effettuate analisi esplorative profonde. Pianificazioni ambientali e forestali efficienti richiedono una valutazione e una gestione attenta della struttura e dell’incertezza legata a grandi moli di dati. Basandoci sui dati grezzi: (i) abbiamo confrontato informazioni derivate dagli alberi vivi e dal legno morto, con i rispettivi dati derivanti dagli inventari nazionali. Inoltre; (ii) abbiamo cercato di caratterizzare l’incertezza relativa ai dati dello strato erbaceo; (iii) abbiamo calcolato indici classici di diversità forestale e analizzato le loro relazioni e i loro trend spaziali nei diversi tipi forestali e in diverse condizioni ambientali. I risultati saranno utili per comprendere con maggiore accuratezza le stime della biodiversità forestale europea, per interpretarle correttamente e per facilitare l’uso dei dati.Forest ecosystems are the most biodiverse and complex habitats. For this reason, it is very important to monitor them specifically. The importance of forest monitoring is recognized from several years, and the most extensive and complete data on the European forest status are given by National Forest Inventories (NFIs). This information concerns trees but usually it marginally considers other ecosystem components such as ground vegetation. The LI-BioDiv (ICP Forests) database, derived from the BioSoil-Biodiversity project, is a multi-dimensional forest database that contains records collected in 19 European countries in the period 2005-2008. The database includes information on living trees, deadwood and a ground vegetation survey. The BioSoil-Biodiversity project represents an unique pan-European effort for a standardized multi-dimensional forest diversity monitoring survey, however the LI-BioDiv database is still under-utilized by scientists due to policy restrictions and no depth exploratory analysis of the dataset was carried out until now. Efficient environmental and forest planning require careful assessment and management of big data structure and uncertainty. On the basis of row data: (i) we compared information of standing living trees and deadwood with results of NFIs. Furthermore; (ii) we characterized uncertainty related on ground vegetation data; (iii) we calculated several forest biodiversity indicators analyzing therefore their inter-relationship and their trend over the space and over different forest types and environmental conditions. The results will be useful for achieving satisfactory accuracy of European forest biodiversity estimates, for correctly interpretating the estimates, and for facilitating comparable use of the data