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The complexes [(HgCl2)(2)((ch)(2)30S(4)O(6))] (1), [HgCl,(mn21S(2)O(5))] (2), [HgCl2(ch18S(2)O(4))] (3) and [HgI(meb12S(2)O(2))](2)[Hg2I6] (4) have been synthesized, characterized and their crystal structures were determined. In [(HgCl2)(2)((ch)(2)3OS(4)O(6))] two HgCl2 units are discretely bonded within the ligand cavity of the 30-membered dichinoxaline-tetrathia-30-crown-10 ((ch)(2)30S(4)O(6)) forming a binuclear complex. HgCl2 forms I : I "in-cavity" complexes with the 21-membered maleonitrile-dithia-21-crown-7(mn21S(2)O(5)) ligand and the 18-membered chinoxaline- dithia-18-crown-6 (ch18S(2)O(4)) ligand, respectively. The 12-membered 4-methyl-benzo-dithia-12-crown-4 (meb12S(2)O(2)) ligand gave with two equivalents HgI2 the compound [HgI(meb12S(2)O(2))](2)[Hg2I6]. In the cation [HgI(meb12S(2)O(2))](+) meb12S(2)O(2) forms with the cation HgI+ a half-sandwich complex
Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
Arsenic-containing hydrocarbons (AsHCs), a subgroup of arsenolipids (AsLs) occurring in fish and edible algae, possess a substantial neurotoxic potential in fully differentiated human brain cells. Previous in vivo studies indicating that AsHCs cross the blood–brain barrier of the fruit fly Drosophila melanogaster raised the question whether AsLs could also cross the vertebrate blood–brain barrier (BBB). In the present study, we investigated the impact of several representatives of AsLs (AsHC 332, AsHC 360, AsHC 444, and two arsenic-containing fatty acids, AsFA 362 and AsFA 388) as well as of their metabolites (thio/oxo-dimethylpropionic acid, dimethylarsinic acid) on porcine brain capillary endothelial cells (PBCECs, in vitro model for the blood–brain barrier). AsHCs exerted the strongest cytotoxic effects of all investigated arsenicals as they were up to fivefold more potent than the toxic reference species arsenite (iAsIII). In our in vitro BBB-model, we observed a slight transfer of AsHC 332 across the BBB after 6 h at concentrations that do not affect the barrier integrity. Furthermore, incubation with AsHCs for 72 h led to a disruption of the barrier at sub-cytotoxic concentrations. The subsequent immunocytochemical staining of three tight junction proteins revealed a significant impact on the cell membrane. Because AsHCs enhance the permeability of the in vitro blood–brain barrier, a similar behavior in an in vivo system cannot be excluded. Consequently, AsHCs might facilitate the transfer of accompanying foodborne toxicants into the brain.
Two common data representations are mostly used in intelligent data analysis, namely the vectorial and the pairwise representation. Pairwise data which satisfy the restrictive conditions of Euclidean spaces can be faithfully translated into a Euclidean vectorial representation by embedding. Non-metric pairwise data with violations of symmetry, reflexivity or triangle inequality pose a substantial conceptual problem for pattern recognition since the amount of predictive structural information beyond what can be measured by embeddings is unclear. We show by systematic modeling of non-Euclidean pairwise data that there exists metric violations which can carry valuable problem specific information. Furthermore, Euclidean and non-metric data can be unified on the level of structural information contained in the data. Stable component analysis selects linear subspaces which are particularly insensitive to data fluctuations. Experimental results from different domains support our pattern recognition strategy.
Inhalt: 1 Entwicklung der Fragestellung 2. Erscheinungsformen betrieblicher Modernisierung – Kompetenzentwicklung als interessiertes Handeln 3. Die Managementperspektive auf Kompetenzentwicklung – ‚Entwickeln’ als steuern und trainieren 4. Die Subjektperspektive auf Kompetenzentwicklung – ‚Entwickeln’ als sich verständigen, sich entfalten - Die lerntheoretische Rahmung der Subjektperspektive - ‚Fallarbeit’ als empirischer und verstehender Zugang zu subjektiven Selbstverständigungsprozessen (1) Fallerzählung und Nachfragen (2) Spuren suchen und Kernthemen finden (3) Kernthemen bearbeiten
Lipid-soluble arsenicals, so-called arsenolipids, have gained a lot of attention in the last few years because of their presence in many seafoods and reports showing substantial cytotoxicity emanating from arsenic-containing hydrocarbons (AsHCs), a prominent subgroup of the arsenolipids. More recent in vivo and in vitro studies indicate that some arsenolipids might have adverse effects on brain health. In the present study, we focused on the effects of selected arsenolipids and three representative metabolites on the blood-cerebrospinal fluid barrier (B-CSF-B), a brain-regulating interface. For this purpose, we incubated an in vitro model of the B-CSF-B composed of porcine choroid plexus epithelial cells (PCPECs) with three AsHCs, two arsenic-containing fatty acids (AsFAs) and three representative arsenolipid metabolites (dimethylarsinic acid, thio/oxo-dimethylpropanoic acid) to examine their cytotoxic potential and impact on barrier integrity. The toxic arsenic species arsenite was also tested in this way and served as a reference substance. While AsFAs and the metabolites showed no cytotoxic effects in the conducted assays, AsHCs showed a strong cytotoxicity, being up to 1.5-fold more cytotoxic than arsenite. Analysis of the in vitro B-CSF-B integrity showed a concentration dependent disruption of the barrier within 72 h. The correlation with the decreased plasma membrane surface area (measured as capacitance) indicates cytotoxic effects. These findings suggest exposure to elevated levels of certain arsenolipids may have detrimental consequences for the central nervous system.
Hydrogel systems based on hydroxyethyl starch-polyethylene glycol methacrylate (HES-P(EG)(6)MA) or hydroxyethyl starch methacrylate (HES-MA) were used to assess the protein release behavior. Here, we analyzed the in vitro release of FITC-anti-human antibodies incorporated in either HES-P(EG)(6)MA or HES-MA hydrogel delivery systems in PBS or human serum. In addition, hydrogel disks and microparticles prepared from the two polymers were subcutaneously implanted in BALB/c mice. The in vivo release of FITC-IgG was non-invasively monitored by an in vivo imaging system (IVIS 200) over a time period of up to 3 months. The imaging system allowed to asses individual animals over time, therefore only a small number of animals was required to obtain high quality data. The reduction in fluorescence intensity at the site of administration was compared to in vitro release profiles. These investigations demonstrated a sustained release from HES-MA hydrogel disks compared to rapidly degrading HES-P(EG)(6)MA disks and microparticles. The sustained release from HES-MA disks could be further optimized by using increased polymer concentrations. Human serum as in vitro release medium reflected better the in vivo release from HES-P(EG)(6)MA systems than PBS, suggesting that the presence of organic substances like proteins or lipids may play a significant role for the release kinetics.