Computational Toxicology and Risk Assessment

Fowler, Bruce A.

doi:10.1016/b978-0-12-801238-3.64225-3

Cited by 4 publications

(4 citation statements)

References 70 publications

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“…For each feature weight, the bootstrap ratio

R_{b o}

was calculated as the mean of the 1000 bootstrapped feature weights divided by their standard deviation. The bootstrap ratio is akin to a Student

t

criterion so if a ratio was large enough (a value of 2 or 3 roughly corresponds to

normalα = . 05

normalα = . 003

for a

t

test) then the corresponding feature was considered significant for the prediction (Fowler ). The statistical strength of each feature was then derived as the absolute value of the average bootstrap ratio across 10 folds (Pereira et al ).…”

Section: Methodsmentioning

confidence: 99%

Functional connectivity predicts gender: Evidence for gender differences in resting brain connectivity

Zhang

Dougherty

Baum

et al. 2018

Human Brain Mapping

196

122

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Prevalence of certain forms of psychopathology, such as autism and depression, differs between genders and understanding gender differences of the neurotypical brain may provide insights into risk and protective factors. In recent research, resting state functional magnetic resonance imaging (rfMRI) is widely used to map the inherent functional networks of the brain. Although previous studies have reported gender differences in rfMRI, the robustness of gender differences is not well characterized. In this study, we use a large data set to test whether rfMRI functional connectivity (FC) can be used to predict gender and identify FC features that are most predictive of gender. We utilized rfMRI data from 820 healthy controls from the Human Connectome Project. By applying a predefined functional template and partial least squares regression modeling, we achieved a gender prediction accuracy of 87% when multi-run rfMRI was used. Permutation tests confirmed that gender prediction was reliable ( p<.001). Effects of motion, age, handedness, blood pressure, weight, and brain volume on gender prediction are discussed. Further, we found that FC features within the default mode (DMN), fronto-parietal and sensorimotor networks contributed most to gender prediction. In the DMN, right fusiform gyrus and right ventromedial prefrontal cortex were important contributors. The above regions have been previously implicated in aspects of social functioning and this suggests potential gender differences in social cognition mediated by the DMN. Our findings demonstrate that gender can be reliably predicted using rfMRI data and highlight the importance of controlling for gender in brain imaging studies.

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“…For each feature weight, the bootstrap ratio

R_{b o}

was calculated as the mean of the 1000 bootstrapped feature weights divided by their standard deviation. The bootstrap ratio is akin to a Student

t

criterion so if a ratio was large enough (a value of 2 or 3 roughly corresponds to

normalα = . 05

normalα = . 003

for a

t

Section: Methodsmentioning

confidence: 99%

Functional connectivity predicts gender: Evidence for gender differences in resting brain connectivity

Zhang

Dougherty

Baum

et al. 2018

Human Brain Mapping

196

122

View full text Add to dashboard Cite

show abstract

“…It was shown that heterogeneity in biological measurements is less likely to skew results than heterogeneity in external exposure (8). Thus, HBM is a sound solution for addressing chemical 'events' leading to fewer uncertainties (9).…”

Section: Added Value and Advantages Of Human Biomonitoringmentioning

confidence: 99%

Added value of human biomonitoring in assessment of general population exposure to xenobiotics

Kromerová¹,

Bencko²

2019

Cent Eur J Public Health

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Human biomonitoring (HBM) has a wide range of applications and long tradition both in health care and the field of public health. Its major advantage is the integration of all exposure routes and sources. Since HBM information is an integrated exposure finding it offers the opportunity to trace and mimic a realistic exposure scenario. It reduces the number of assumptions that need to be made when estimating exposure and thus helps to reduce the uncertainties in exposure science. In spite of some challenges, such as further harmonization in the area of HBM, necessity of deriving equivalents of markers of external exposure and addressing the ethical and political aspects of its application, HBM is an efficient and cost-effective way to measure exposure levels of the human body to xenobiotics.

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“…mRNA, proteíny a malé molekuly. Keď sa tieto dátové toky rozdelia do ciest a sietí, každá sieť môže zahŕňať veľké množstvo interakcií z génov, proteínov a metabolitov (50). Uľahčenie vysvetlenia a pochopenia týchto interakcií podporuje rozvoj počítačovej toxikológie.…”

Section: Počítačová Toxikológiaunclassified

Current Trends in the Process of Risk Assessment of Exposure to Xenobiotics Including Dietary Intake

Kromerová¹,

Bencko²

2017

Hygiena

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54HYGIENA § § 62(2) § 54-61 PŘEHLEDOVÉ PRÁCE SÚHRNNové tendencie v oblasti hodnotenia rizika z expozície cudzorodým látkam vrátane tej z potravín sú reakciou na zrýchľujúci sa pokrok v oblasti vedy, metodiky hodnotenia rizika, generovania a prístupu k obrovskému množstvu dát o rôznych faktoroch a parametroch, zmenám v regulačnom prostredí. Na druhej strane samé osebe vytvárajú ďalšie výzvy. Možno konštatovať, že je jednoznačná tendencia k integrovanému prístupu v hodnotení rizika expozície cudzorodým látkam vrátane expozície z potravinového reťazca na viacerých úrovniach. Cieľom uplatňovania týchto prístupov je, že výsledok procesu hodnotenia rizika, jeho kvalifikovaný odhad zakotvený legislatívne, sa bude v najväčšej možnej miere blížiť reálnej situácii. Takto poskytne spoľahlivý podklad pre efektívne riadenie únosnosti miery rizika pre zdravie ľudí za účelom jeho minimalizácie pri rešpektovaní princípu predbežnej opatrnosti.Kľúčové slová: hodnotenie zdravotných rizík (HRA), xenobiotika, ťažké kovy, dietárna expozícia, potraviny SUMMARYNew trends in risk assessment of exposure to xenobiotics (including via food) respond to rapid advances in science, risk assessment methodologies, the generation of and access to a huge volume of data on various factors and parameters and changes in the regulatory environment. On the other hand, as such they constitute additional challenges. There is a clear tendency for an integrated approach to risk assessment of exposure to xenobiotics including those in the food chain on several levels. The aim of these approaches is to ensure that the result of the risk assessment process by its qualified estimation as established by law reflects as closely as possible the real situation. In this way a reliable basis for effective management of acceptable levels of the health risk is provided in the interests of minimizing risk and respecting the precautionary principle. Množstvo chemických látok antropogénneho a prí-rodného pôvodu vstupuje do krmív pre zvieratá, potravín a vody buď ako nežiadúce kontaminanty alebo ako súčasť zložiek stravy (1). Xenobiotiká sú kontaminanty v biosfére, aj keď nie všetky kontaminanty sú xenobiotiká. Syntetické xenobiotiká tvoria zvyčajne chemické látky, ako sú napr. produkty petrochémie, pesticídy a plasty. Stále rastúci podiel populácie ľudí je cestou potravinového reťazca a pitnou vodou vystavených pôso-beniu širokého spektra rôznych xenobiotík (2). Legislatíva Európskej únie definuje kontaminanty ako látky, ktoré neboli zámerne pridané do potraviny a ktoré sú v potravine prítomné ako dôsledok produkcie (vrátane operácií uskutočnených v rámci pestovania a zberu plodín, chovu dobytka a veterinárneho lekárstva), výroby, spracovania, úpravy, ošetrenia, zabalenia, obalu, dopravy a skladovania alebo ako dôsledok kontaminácie životné-ho prostredia. Cudzie predmety ako napr. časti hmyzu, živočíšna srsť, atď., nespadajú pod túto definíciu kontaminantov (3).V prípade niektorých chemických látok bolo dokáza-né, že expozícia z potravín tvorí viac ako 90 % celkovej humá...

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Computational Toxicology and Risk Assessment

Cited by 4 publications

References 70 publications

Functional connectivity predicts gender: Evidence for gender differences in resting brain connectivity

Functional connectivity predicts gender: Evidence for gender differences in resting brain connectivity

Added value of human biomonitoring in assessment of general population exposure to xenobiotics

Current Trends in the Process of Risk Assessment of Exposure to Xenobiotics Including Dietary Intake

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