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Enregistrement W2047199250 · doi:10.1890/1540-9295-7.4.228

Toxins and toddlers

2009· review· en· W2047199250 sur OpenAlexaboutno aff
Katherine Ellison

Notice bibliographique

RevueFrontiers in Ecology and the Environment · 2009
Typereview
Langueen
DomaineMedicine
ThématiquePoisoning and overdose treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésQuarter (Canadian coin)PsychologySchizophrenia (object-oriented programming)Inheritance (genetic algorithm)Mental healthAttention deficit hyperactivity disorderPsychiatryMedicineDevelopmental psychologyHistoryGeneticsGeneBiology

Résumé

récupéré en direct d'OpenAlex

We hear the same story so often these days: a child is diagnosed with a learning disorder, and later the parent turns out to have it, too. Genes, after all, play a key role in many diagnoses du jour. Attention deficit/hyperactivity disorder (ADHD), which affects more than one in 15 US children, is more likely to be inherited than schizophrenia, and is only slightly less genetically determined than height. It is tempting to think there's a simple explanation for behaviors that often seem mystifying. I felt free to start blaming my own genes for my occasional rash judgment after discovering that my great-grandfather gambled away a family inheritance in Monte Carlo. Still, hand-me-down genes only tell a small part of the story regarding this era's rapidly expanding numbers of mental health diagnoses. Some genes get passed on but never turn on. Nuture –including what we eat, drink, and inhale – often outweighs nature. Scientists' concern about potential environmental contributions to learning disabilities dates back several years. In 2000, the National Academy of Sciences estimated that a quarter of known neurological deficits in children are likely due to some interaction between toxins in the environment and genes. Six years later, a report from the Harvard School of Public Health warned of a “silent pandemic” of behavioral and developmental disorders caused by chemicals that damage and destroy brain cells. It has long been known that many widely used toxic substances are capable of interfering with developing life. These include the billions of pounds of pesticides released annually in the US alone, in addition to some solvents and polychlorinated biphenyls (better known by their acronym, PCBs), banned for commercial use, but still present in our air and water. Recent lab tests by the Environmental Working Group have uncovered an average of 200 industrial chemicals in the umbilical cord blood of newborn humans. Virginia Rauh, deputy director of Columbia University's Center for Children's Environmental Health, has been studying chemical exposure in 700 children since 1998, and has found “significant” correlations between prenatal exposure to the common insecticide chlorpyrifos (now banned for household use in the US) and later ADHD-type symptoms. Joel T Nigg, a National Institutes of Health-funded research scientist at Michigan State University who specializes in ADHD research, calls this type of risk “both vast and unstudied”. Indeed, research on learning disorders has focused far more on genetics than on environmental factors, for understandable reasons. Environmental causes are technically more difficult to study, and also more controversial. Yet, as the number of diagnoses has increased –to the point where a startling one in six US children are now believed to have some form of learning disability – a new constituency of parents is pressing both scientists and policy makers for better answers, and increasing pressure on Washington to overhaul federal regulatory laws. This spring sees the launch of an ambitious research project, the National Children's Study. Led by the National Institute of Environmental Health Sciences, the Centers for Disease Control and Prevention, and the US Environmental Protection Agency, the study will investigate environmental influences on the health and development of more than 100 000 children – from before birth until age 21 – across the US. The newly organized parents' groups – along with other activists – aren't willing to wait for the final word from government scientists, however. They argue that enough is known about some ubiquitous toxins to initiate more effective regulation immediately. This would begin with an overhaul of the US Toxic Substances Control Act, now more than 30 years old, never amended, and widely regarded as the weakest piece of US environmental legislation. The Act included a “grandfather” clause that applied to 62 000 chemicals in wide use at the time, despite the lack of scientific data on their safety. Reformists say we need tougher rules, some of which are outlined in a bill first proposed in Congress last year – the Kid-Safe Chemicals Act – that would require the chemical industry to provide unequivocal evidence that products are safe for children. Energizing the calls for US reform is the European Union's recent upgrade of its toxic substances oversight, through a policy known as the Registration, Evaluation, Authorisation, and Restriction of Chemicals, or REACH. REACH requires all manufacturers – including US companies – that sell products in Europe to provide public data on the chemical hazards associated with those products. With a new administration in Washington that seems considerably more willing than the last one to wield regulatory power, it may not be much longer before Americans stop blaming their genes for their disorders and focus more on the chemical dangers to their children.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Synthèse · Signal consensuel: aucune
Score de désaccord entre enseignants0,063
Score d'incertitude au seuil0,125

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0060,002
Communication savante0,0040,002
Science ouverte0,0010,005
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0290,009

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,253
Écart entre enseignants0,240 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2009
Routes d'admission1
Résumé présentoui

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