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Record W2809568600 · doi:10.1093/annweh/wxy048

A Systematic Review of the Routes and Forms of Exposure to Engineered Nanomaterials

2018· review· en· W2809568600 on OpenAlexfundno aff
Ioannis Basinas, Araceli Sánchez Jiménez, Karen S. Galea, Martie van Tongeren, Fintan Hurley

Bibliographic record

VenueAnnals of Work Exposures and Health · 2018
Typereview
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsnot available
FundersUniversité de MontréalWorld Health Organization
KeywordsRisk analysis (engineering)Medicine

Abstract

fetched live from OpenAlex

Background: Establishing the routes of exposure is a fundamental component of the risk assessment process for every dangerous substance. The present study systematically reviews the available literature to assess the relevance of the different routes and forms of exposure that are of concern for the protection of workers during the manufacture, handling, or end-use of engineered nanomaterials (ENMs). Methods: A systematic review of the peer-reviewed literature published between 2000 and 2015 was completed. Only studies including measurements of inhalation or dermal exposure were selected and used to identify the exposure situations for which the measurements were collected. The identified exposure situations were grouped based on the type of ENM (i.e. carbon nanotubes and fibres, silicon-based, titanium dioxide, other metal oxides, pure elemental metals, and other ENMs) and activity involved. The grouped exposure situations were assessed to provide a conclusion regarding the likelihood, form, and route of exposure. Assessment of the likelihood of exposure was based on well-defined criteria using a previously established decision logic for inhalation exposure and the outputs from measurements and/or conceptual models for dermal/ingestion exposure. For each combination of nano-activity and type of ENM, the aggregated likelihood across all relevant individual assessments was used to draw conclusions about the relevance of both the inhalation and dermal/ingestion routes. Based on the quality of the data, the strength of the evidence was also evaluated. Results: One hundred and seven studies were identified during the review process, reporting 424 individual exposure assessments. Measurement data were limited for dermal/ingestion exposure and for inhalation exposure for downstream use and end-of-life. However, the data provided high-quality evidence that in occupational settings all three routes can be of relevance for exposure to ENMs. In general, whenever inhalation exposure occurs then dermal and inadvertent ingestion exposure may occur due to surface deposition and transfer due to the ENMs release. However, for some forms of exposure (e.g. suspension/liquids), dermal exposure can occur even when inhalation exposure is unlikely. An increased likelihood of exposure was observed for manual activities such as cleaning and maintenance, collection/harvesting, spraying, and finishing as well as those involving feeding into a process and handling of powders outside enclosures. The likelihood of exposure was affected by the presence of risk management measures and the scale of the production involved. Conclusion: This literature review provides evidence that for ENMs, as found for other materials, the likelihood of the exposure depends largely on the physical form of the substance as well as the applied process and operational conditions. These results can be used to provide first indications of the likelihood of exposure and guidance for exposure controls in workplaces. However, there is a clear lack of high-quality exposure data, in particular for downstream use and end-of-life scenarios and in low- and medium-income countries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.087
GPT teacher head0.368
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations42
Published2018
Admission routes1
Has abstractyes

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