Endocrine disruptors: from endocrine to metabolic disruption.

Synthetic chemicals currently used in a variety of industrial and agricultural applications are leading to widespread contamination of the environment. Even though the intended uses of pesticides, plasticizers, antimicrobials, and flame retardants are beneficial, effects on human health are a global concern. These so-called endocrine-disrupting chemicals (EDCs) can disrupt hormonal balance and result in developmental and reproductive abnormalities. New in vitro, in vivo, and epidemiological studies link human EDC exposure with obesity, metabolic syndrome, and type 2 diabetes. Here we review the main chemical compounds that may contribute to metabolic disruption. We then present their demonstrated or suggested mechanisms of action with respect to nuclear receptor signaling. Finally, we discuss the difficulties of fairly assessing the risks linked to EDC exposure, including developmental exposure, problems of high- and low-dose exposure, and the complexity of current chemical environments.

PPAR-mediated activity of phthalates: A link to the obesity epidemic?

The endocrine disruption hypothesis asserts that exposure to small amounts of some chemicals in the environment may interfere with the endocrine system and lead to harmful effects in wildlife and humans. Many of these chemicals may interact with members of the nuclear receptor superfamily. Peroxisome proliferator-activated receptors (PPARs) are such candidate members, which interact with many different endogenous and exogenous lipophilic compounds. More particularly, the roles of PPARs in lipid and carbohydrate metabolism raise the question of their activation by a sub-class of pollutants, tentatively named "metabolic disrupters". Phthalates are abundant environmental micro-pollutants in Europe and North America and may belong to this class. Mono-ethyl-hexyl-phthalate (MEHP), a metabolite of the widespread plasticizer di-ethyl-hexyl-phthalate (DEHP), has been found in exposed organisms and interacts with all three PPARs. A thorough analysis of its interactions with PPARgamma identified MEHP as a selective PPARgamma modulator, and thus a possible contributor to the obesity epidemic.

The endocrine disruptor monoethyl-hexyl-phthalate is a selective peroxisome proliferator-activated receptor gamma modulator that promotes adipogenesis.

The ability of pollutants to affect human health is a major concern, justified by the wide demonstration that reproductive functions are altered by endocrine disrupting chemicals. The definition of endocrine disruption is today extended to broader endocrine regulations, and includes activation of metabolic sensors, such as the peroxisome proliferator-activated receptors (PPARs). Toxicology approaches have demonstrated that phthalate plasticizers can directly influence PPAR activity. What is now missing is a detailed molecular understanding of the fundamental basis of endocrine disrupting chemical interference with PPAR signaling. We thus performed structural and functional analyses that demonstrate how monoethyl-hexyl-phthalate (MEHP) directly activates PPARgamma and promotes adipogenesis, albeit to a lower extent than the full agonist rosiglitazone. Importantly, we demonstrate that MEHP induces a selective activation of different PPARgamma target genes. Chromatin immunoprecipitation and fluorescence microscopy in living cells reveal that this selective activity correlates with the recruitment of a specific subset of PPARgamma coregulators that includes Med1 and PGC-1alpha, but not p300 and SRC-1. These results highlight some key mechanisms in metabolic disruption but are also instrumental in the context of selective PPAR modulation, a promising field for new therapeutic development based on PPAR modulation.

Patterns of Subject Mix in Higher Education Institutions : A First Empirical Analysis Using the AQUAMETH Database

Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions.

Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Simultaneous determination of Pu and Am radioisotopes in environmental samples: a tool for determining origin and release date

A radiochemical procedure was developed for the sequential determination of Pu and Am radioisotopes in environmental samples. The radioisotope activities were then used to assess the origin and release date of the environmental plutonium. The radioanalytical procedure is based on the separation of Pu and Am on selective extraction chromatographic resins (Eichrom TEVA and DGA). Alpha sources were prepared by electrodeposition on stainless steel discs, and the alpha emitting radionuclides (238Pu, 239,240Pu and 241Am) were measured by alpha spectrometry. For the determination of the beta emitting 241Pu, the Pu alpha source was leached in hot concentrated nitric acid and the Pu fraction further purified by extraction chromatography on a small column of TEVA resin (100 μg of resin in a pipette tip). 241Pu is then measured by ultra low level liquid scintillation counting. Due to the lack of reference material for 241Pu, the proposed radiochemical method was nevertheless validated using four IAEA reference sediments with information values of 241Pu. The proposed method was then used to determine the 238Pu, 239,240Pu, 241Pu and 241Am activity concentrations in alpine soils of France and Switzerland. The soil is the primary receptor of the atmospheric radioactive fallout and, because of the strong binding interaction with soils particles, the isotopes are little fractionated. Therefore, the activity ratios 241Pu/239+240Pu and 238Pu/239,240Pu in soil samples were used to determine the origin (source) and date of the Pu contamination in the investigated alpine sites. The 241Pu/239,240Pu and 238Pu/239,240Pu activity ratios confirmed that the main origin of Pu in the alpine soils was the global fallout from the nuclear bomb tests (NBT) in the fifties and sixties. Furthermore, the 241Pu/241Am activity ratios were used to determine the age of the Pu contamination, which is also an important data for distinguishing the Pu sources. The estimation of the date of the contamination, by the 241Pu/241Am age-dating method, further confirmed the NBT as the Pu source. However, the 241Pu/241Am dating method was limited to samples where Pu-Am fractionation was insignificant. If any, the contribution of the Chernobyl accident in the studied sites is negligible.