MétaCan
Menu
← Back to cohort

Peer Review #2 of "Using Peromyscus leucopus as a biomonitor to determine the impact of heavy metal exposure on the kidney and bone mineral density: results from the Tar Creek Superfund Site (v0.1)"

2022· peer-review· en· W4313315551 on OpenAlexfundno aff
P Cianciullo

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsnot available
FundersMansoura UniversityMinistry of Higher Education and Scientific ResearchCanadian Bureau for International EducationOklahoma State University
KeywordsPeromyscusEnvironmental sciencetar (computing)SuperfundEnvironmental chemistryMining engineeringGeologyChemistryEcologyBiologyHazardous waste

Abstract

fetched live from OpenAlex

Background.Human population growth and industrialization contribute to increased pollution of wildlife habitats.Heavy metal exposure from industrial and environmental sources is still a threat to public health, increasing disease susceptibility.In this study, I investigated the effects of heavy metals (cadmium (Cd), lead (Pb), and zinc (Zn)) on kidney and bone density.Objective.This study aims to determine the concentrations of Cd, Pb, and Zn in soil and compare them to the levels of the same metals in Peromyscus leucopus kidney tissue.Furthermore, the study seeks to investigate the impact of heavy metals on bone density and fragility using the fourth lumbar vertebra (L4) of P. leucopus.Methods.Cd, Pb, and Zn concentrations in soil specimens collected from Tar Creek Superfund Site (TCSFS), Beaver Creek (BC), and two reference sites (Oologah Wildlife Management Area [OWMA] and Sequoyah National Wildlife Refuge [SNWR]).Heavy metal concentrations were analyzed using inductively coupled plasma-mass spectroscopy (ICP-MS).Micro-computed tomography (µCT) was used to assess the influence of heavy metals on bone fragility and density.Results.On the one hand, soil samples revealed that Pb is the most common pollutant in the sediment at all of the investigated sites (the highest contaminated site with Pb was TSCF).Pb levels in the soil of TCSFS, BC, OWMA, and SNWR were found to be 1132±278, 6.4±1.1, and 2.3 ±0.3 mg/kg in the soil of TCSFS, BC and OWMA and SNWR, respectively.This is consistent with the fact that Pb is one of the less mobile heavy metals, causing its compounds to persist in soils and sediments and being barely influenced by microbial decomposition.On the other hand, the kidney samples revealed greater Cd levels, even higher than those found in the soil samples from the OWMA and SNWR sites.Cd concentrations in the kidney specimens were found to be 4.62±0.71,0.53±0.08,and 0.53±0.06µg/ kg, respectively.In addition, micro-CT analysis of L4 from TCSFS showed significant Pearson's correlation coefficients between Cd concentrations and trabecular bone number (-0.67, p≤ 0.05) and trabecular separation (0.72, p≤ 0.05).The results showed no correlation between bone parameters and metal concentrations at reference sites.This study is one of the few that aims to employ bone architecture as an endpoint in the field of biomonitoring.Furthermore, this study confirmed some earlier research by demonstrating substantial levels of heavy metal contamination in soil samples, kidney samples, and P. leucopus L4 trabecular bone separations from TCSFS.Moreover, this is the first study to record information regarding bone microarchitecture parameters in P. leucopus in North America.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.996
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1230.047

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 head0.054
GPT teacher head0.317
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainEvaluation
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicHeavy metals in environment→French-language works237,207→