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Reproductive Toxicity of Nanoparticles: A Comprehensive Review

2023· review· en· W4385827625 on OpenAlexaff
Elaheh Mohammadi, Behzad Behnam, Ahad Mokhtarzadeh, Ramin Rezaee, Ardavan Abiri, Mohammad Ramezani, John P. Giesy, Amirhossein Sahebkar

Bibliographic record

VenueCurrent Medicinal Chemistry · 2023
Typereview
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of Saskatchewan
FundersKerman University of Medical Sciences
KeywordsReproductive toxicityNanotechnologyNanotoxicologyToxicityNanoparticleSpermMale reproductive systemNanomaterialsChemistryBiologyMedicineMaterials scienceInternal medicine

Abstract

fetched live from OpenAlex

The unique characteristics of nanoparticles (NPs) have captivated scientists in various fields of research. However, their safety profile has not been fully scrutinized. In this regard, the effects of NPs on the reproductive system of animals and humankind have been a matter of concern. In this article, we will review the potential reproductive toxicity of various types of NPs, including carbon nanomaterials, dendrimers, quantum dots, silica, gold, and magnetic nanoparticles, reported in the literature. We also mention some notable cases where NPs have elicited beneficial effects on the reproductive system. This review provides extensive insight into the effects of various NPs on sperm and ovum and the outcomes of their passage through blood-testis and placental barriers and accumulation in the reproductive organs.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.146
GPT teacher head0.402
Teacher spread0.256 · 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.

Study designNot applicable
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

Citations7
Published2023
Admission routes1
Has abstractyes

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