Tesori

This article focuses on the demands/suggestions made in 2009 by Kanak women upon the return of the Hadfield\u2019s collection of objects, in particular pandanus mats and bags. This contribution aims to engage in the dialogue be- tween heritage processes in Oceania and the Italian debate on the same themes. Fieldwork conducted in Lifou (Kanaky, New Caledonia) allows the author to realize the interest of the elderly to recall the stories related to the mats, thick objects that continue to bring out memories of the past and trigger intense emotions because they do not cease to represent a women \u301s richesse , a treasure linked to the knowledge and practices of female ancestors. The rediscovered mats arouse a strong sense of connection with the women \u301s cultural past and set in motion narra- tives in which they want to be protagonists, giving shape to an informal heritage community

The acoustics of public square/places: a comparison between results from a computer simulation program and measurements in situ

http://www.odeon.dk/pdf/InterNoise2004.pd

Perubahan Kadar Senyawa Bioaktif dan Aktivitas Antioksidan Beras Organik Hitam Varietas Jawa dengan Pengemas Polipropilen Selama Enam Bulan Penyimpanan

The importance of health awareness has increased so the consumption of organic products has increased. Java varieties black organic rice is one of the local organic rice grown in Indonesia. Pigmented rice contains bioactive compounds that can act as antioxidants. Rice needs to be packaged to minimize damage and facilitate the storage using polypropylene (PP) packaging. The results showed an increase in the yield, bioactive compounds, and antioxidant activities during storage. The highest yield of black rice (12.08 ± 0.03% dry basis) was at the 4th month. Total phenol of black rice (10.55 ± 0.29 mg Gallic Acid Equivalent/g dry basis) and total anthocyanins (0.04 ± 0.00 mg Cyanidin-3-Glucoside Equivalent/g dry basis) was the highest at 3rd month, total flavonoids (2.10 ± 0.11 mg Catechin Equivalent/g dry basis) at 6th month, the free radical DPPH scavenging (1.53 ± 0.03 mg GAE/g dry basis) activity at 3rd month, and the iron reducing power (31.31 ± 2.05 mg GAE/g dry basis) at 4th month

Practical use of the Virtual Cell Based Assay: Simulation of repeated exposure experiments in liver cell lines

AbstractThe Virtual Cell Based Assay (VCBA) was applied to simulate the long-term (repeat dose) toxic effects of chemicals, including substances in cosmetics and personal care products. The presented model is an extension of the original VCBA for simulation of single exposure and is implemented in a KNIME workflow. This work illustrates the steps taken to simulate the repeated dose effects of two reference compounds, caffeine and amiodarone. Using caffeine, in vitro experimental viability data in single exposure from two human liver cell lines, HepG2 and HepaRG, were measured and used to optimize the VCBA, subsequently repeated exposure simulations were run. Amiodarone was then tested and simulations were performed under repeated exposure conditions in HepaRG. The results show that the VCBA can adequately predict repeated exposure experiments in liver cell lines. The refined VCBA model can be used not only to support the design of long term in vitro experiments but also practical applications in risk assessment. Our model is a step towards the development of in silico predictive approaches to replace, refine, and reduce the in vivo repeated dose systemic toxicity studies in the assessment of human safety

Practical use of the Virtual Cell Based Assay: Simulation of repeated exposure experiments in liver cell lines

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In vitro-to-in vivo correlation of the skin penetration, liver clearance and hepatotoxicity of caffeine

Abstract This work illustrates the use of Physiologically-Based Toxicokinetic (PBTK) modelling for the healthy Caucasian population in in vitro -to- in vivo correlation of kinetic measures of caffeine skin penetration and liver clearance (based on literature experiments), as well as dose metrics of caffeine-induced measured HepaRG toxicity. We applied a simple correlation factor to quantify the in vitro and in vivo differences in the amount of caffeine permeated through the skin and concentration-time profiles of caffeine in the liver. We developed a multi-scale computational approach by linking the PBTK model with a Virtual Cell-Based Assay to relate an external oral and dermal dose with the measured in vitro HepaRG cell viability. The results revealed higher in vivo skin permeation profiles than those determined in vitro using identical exposure conditions. Liver clearance of caffeine derived from in vitro metabolism rates was found to be much slower than the optimised in vivo clearance with respect to caffeine plasma concentrations. Finally, HepaRG cell viability was shown to remain almost unchanged for external caffeine doses of 5–400 mg for both oral and dermal absorption routes. We modelled single exposure to caffeine only

Automated workflows for modelling chemical fate, kinetics and toxicity.

Automation is universal in today's society, from operating equipment such as machinery, in factory processes, to self-parking automobile systems. While these examples show the efficiency and effectiveness of automated mechanical processes, automated procedures that support the chemical risk assessment process are still in their infancy. Future human safety assessments will rely increasingly on the use of automated models, such as physiologically based kinetic (PBK) and dynamic models and the virtual cell based assay (VCBA). These biologically-based models will be coupled with chemistry-based prediction models that also automate the generation of key input parameters such as physicochemical properties. The development of automated software tools is an important step in harmonising and expediting the chemical safety assessment process. In this study, we illustrate how the KNIME Analytics Platform can be used to provide a user-friendly graphical interface for these biokinetic models, such as PBK models and VCBA, which simulates the fate of chemicals in vivo within the body and in vitro test systems respectively

Physiologically based kinetic (PBK) modelling and human biomonitoring data for mixture risk assessment

Human biomonitoring (HBM) data can provide insight into co-exposure patterns resulting from exposure to multiple chemicals from various sources and over time. Therefore, such data are particularly valuable for assessing potential risks from combined exposure to multiple chemicals. One way to interpret HBM data is establishing safe levels in blood or urine, called Biomonitoring Equivalents (BE) or HBM health based guidance values (HBM-HBGV). These can be derived by converting established external reference values, such as tolerable daily intake (TDI) values. HBM-HBGV or BE values are so far agreed only for a very limited number of chemicals. These values can be established using physiologically based kinetic (PBK) modelling, usually requiring substance specific models and the collection of many input parameters which are often not available or difficult to find in the literature. The aim of this study was to investigate the suitability and limitations of generic PBK models in deriving BE values for several compounds with a view to facilitating the use of HBM data in the assessment of chemical mixtures at a screening level. The focus was on testing the methodology with two generic models, the IndusChemFate tool and High-Throughput Toxicokinetics package, for two different classes of compounds, phenols and phthalates. HBM data on Danish children and on Norwegian mothers and children were used to evaluate the quality of the predictions and to illustrate, by means of a case study, the overall approach of applying PBK models to chemical classes with HBM data in the context of chemical mixture risk assessment. Application of PBK models provides a better understanding and interpretation of HBM data. However, the study shows that establishing safety threshold levels in urine is a difficult and complex task. The approach might be more straightforward for more persistent chemicals that are analysed as parent compounds in blood but high uncertainties have to be considered around simulated metabolite concentrations in urine. Refining the models may reduce these uncertainties and improve predictions. Based on the experience gained with this study, the performance of the models for other chemicals could be investigated, to improve the accuracy of the simulations