Dose-response relationship between arsenic exposure and the serum enzymes for liver function tests in the individuals exposed to arsenic: a cross sectional study in Bangladesh

<p>Abstract</p> <p>Background</p> <p>Chronic arsenic exposure has been shown to cause liver damage. However, serum hepatic enzyme activity as recognized on liver function tests (LFTs) showing a dose-response relationship with arsenic exposure has not yet been clearly documented. The aim of our study was to investigate the dose-response relationship between arsenic exposure and major serum enzyme marker activity associated with LFTs in the population living in arsenic-endemic areas in Bangladesh.</p> <p>Methods</p> <p>A total of 200 residents living in arsenic-endemic areas in Bangladesh were selected as study subjects. Arsenic concentrations in the drinking water, hair and nails were measured by Inductively Coupled Plasma Mass Spectroscopy (ICP-MS). The study subjects were stratified into quartile groups as follows, based on concentrations of arsenic in the drinking water, as well as in subjects' hair and nails: lowest, low, medium and high. The serum hepatic enzyme activities of alkaline phosphatase (ALP), aspartate transaminase (AST) and alanine transaminase (ALT) were then assayed.</p> <p>Results</p> <p>Arsenic concentrations in the subjects' hair and nails were positively correlated with arsenic levels in the drinking water. As regards the exposure-response relationship with arsenic in the drinking water, the respective activities of ALP, AST and ALT were found to be significantly increased in the high-exposure groups compared to the lowest-exposure groups before and after adjustments were made for different covariates. With internal exposure markers (arsenic in hair and nails), the ALP, AST and ALT activity profiles assumed a similar shape of dose-response relationship, with very few differences seen in the higher groups compared to the lowest group, most likely due to the temporalities of exposure metrics.</p> <p>Conclusions</p> <p>The present study demonstrated that arsenic concentrations in the drinking water were strongly correlated with arsenic concentrations in the subjects' hair and nails. Further, this study revealed a novel exposure- and dose- response relationship between arsenic exposure metrics and serum hepatic enzyme activity. Elevated serum hepatic enzyme activities in the higher exposure gradients provided new insights into arsenic-induced liver toxicity that might be helpful for the early prognosis of arsenic-induced liver diseases.</p

Freie Fettsäuren und Kohlenwasserstoffe im Liquor cerebrospinalis

Peer Reviewe

Environmental enrichment reveals effects of genotype on hippocampal spine morphologies in the mouse model of Fragile X Syndrome.

Fragile X Syndrome (FXS) and the Fmr1 knockout (KO) mouse model of this disorder exhibit abnormal dendritic spines in neocortex, but the degree of spine disturbances in hippocampus is not clear. The present studies tested if the mutation influences dendritic branching and spine measures for CA1 pyramidal cells in Fmr1 KO and wild-type (WT) mice provided standard or enriched environment (EE) housing. Automated measures from 3D reconstructions of green fluorescent protein (GFP)-labeled cells showed that spine head volumes were ∼ 40% lower in KOs when compared with WTs in both housing conditions. With standard housing, average spine length was greater in KOs versus WTs but there was no genotype difference in dendritic branching, numbers of spines, or spine length distribution. However, with EE rearing, significant effects of genotype emerged including greater dendritic branching in WTs, greater spine density in KOs, and greater numbers of short thin spines in KOs when compared with WTs. Thus, EE rearing revealed greater effects of the Fmr1 mutation on hippocampal pyramidal cell morphology than was evident with standard housing, suggesting that environmental enrichment allows for fuller appreciation of the impact of the mutation and better representation of abnormalities likely to be present in human FXS

Environmental enrichment reveals effects of genotype on hippocampal spine morphologies in the mouse model of Fragile X Syndrome.

Fragile X Syndrome (FXS) and the Fmr1 knockout (KO) mouse model of this disorder exhibit abnormal dendritic spines in neocortex, but the degree of spine disturbances in hippocampus is not clear. The present studies tested if the mutation influences dendritic branching and spine measures for CA1 pyramidal cells in Fmr1 KO and wild-type (WT) mice provided standard or enriched environment (EE) housing. Automated measures from 3D reconstructions of green fluorescent protein (GFP)-labeled cells showed that spine head volumes were ∼ 40% lower in KOs when compared with WTs in both housing conditions. With standard housing, average spine length was greater in KOs versus WTs but there was no genotype difference in dendritic branching, numbers of spines, or spine length distribution. However, with EE rearing, significant effects of genotype emerged including greater dendritic branching in WTs, greater spine density in KOs, and greater numbers of short thin spines in KOs when compared with WTs. Thus, EE rearing revealed greater effects of the Fmr1 mutation on hippocampal pyramidal cell morphology than was evident with standard housing, suggesting that environmental enrichment allows for fuller appreciation of the impact of the mutation and better representation of abnormalities likely to be present in human FXS

Deep Learning-Based Metasurface Design for Smart Cooling of Spacecraft

A reconfigurable metasurface constitutes an important block of future adaptive and smart nanophotonic applications, such as adaptive cooling in spacecraft. In this paper, we introduce a new modeling approach for the fast design of tunable and reconfigurable metasurface structures using a convolutional deep learning network. The metasurface structure is modeled as a multilayer image tensor to model material properties as image maps. We avoid the dimensionality mismatch problem using the operating wavelength as an input to the network. As a case study, we model the response of a reconfigurable absorber that employs the phase transition of vanadium dioxide in the mid-infrared spectrum. The feed-forward model is used as a surrogate model and is subsequently employed within a pattern search optimization process to design a passive adaptive cooling surface leveraging the phase transition of vanadium dioxide. The results indicate that our model delivers an accurate prediction of the metasurface response using a relatively small training dataset. The proposed patterned vanadium dioxide metasurface achieved a 28% saving in coating thickness compared to the literature while maintaining reasonable emissivity contrast at 0.43. Moreover, our design approach was able to overcome the non-uniqueness problem by generating multiple patterns that satisfy the design objectives. The proposed adaptive metasurface can potentially serve as a core block for passive spacecraft cooling applications. We also believe that our design approach can be extended to cover a wider range of applications