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Record W4388041847 · doi:10.3390/molecules28217365

Exposure Assessment of Essential and Potentially Toxic Metals in Wheat-Based Sweets for Human Consumption: Multivariate Analysis and Risk Evaluation Studies

2023· article· en· W4388041847 on OpenAlexaff
Mahmood Ahmed, Syed Salman Shafqat, Amna Javed, Mudassar Sanaullah, Abdul Shakoor, Muhammad Imtiaz Shafiq, Syeda Kiran Shahzadi, Tanveer A. Wani, Seema Zargar

Bibliographic record

VenueMolecules · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsMcGill University Health Centre
FundersKing Saud University
KeywordsMultivariate analysisConsumption (sociology)Risk assessmentEnvironmental healthMultivariate statisticsToxicologyRisk analysis (engineering)ChemistryFood scienceEnvironmental chemistryBiotechnologyMedicineBiologyComputer scienceMathematicsStatisticsInternal medicineComputer security

Abstract

fetched live from OpenAlex

In recent years, there has been a growing concern about the negative impact of unforeseen contaminants such as metals in commonly consumed food items, which pose a threat to human well-being. Therefore, it is of utmost importance to evaluate the levels of these contaminants to guarantee the safe consumption of these food items. The goal of the current research is to determine the levels of essential (EMs: Mg, Ca, Mn, Fe, Co, Cu, and Zn) and potentially toxic metals (PTMs: Al, Cr, Ni, As, Cd, and Pb) in various brands of wheat-based sweets. One hundred samples were collected and analysed via flame atomic absorption spectrometry (FAAS) and inductively coupled plasma-optical emission spectrometry (ICP-OES). Also, the current study was to investigate the distribution, correlation, and multivariate analysis of 13 metals (Mg, Ca, Mn, Fe, Co, Cu, Zn, Al, Cr, Ni, As, Cd, and Pb). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to interpret the metals' association. The concentration (mg/kg) ranges of EMs were, in order, Mg (12.70-65.67), Ca (24.02-209.12), Mn (1.32-9.61), Fe (4.55-111.23), Co (0.32-8.94), Cu (2.12-8.61), and Zn (2.60-19.36), while the concentration (mg/kg) ranges of PTMs were, in order, Al (0.32-0.87), Cr (0.17-5.74), Ni (0.36-1.54), Cd (0.16-0.56), and Pb (0.14-0.92), and As was not detected in any sample under investigation. The HCA data revealed that Co, Al, and Ni form clusters with other metals. Sweets are prepared at high temperatures, and the elevated temperatures can increase the likelihood of Ni and Al leaching from stainless steel. Tolerable dietary intake (TDI) values for Ni were higher than the values established by the European Food Safety Authority (EFSA). The CR value found for the Ni and Cr was at the threshold level of cancer risk, if an amount of 25 g were to be used over a lifetime. In a nutshell, this study highlights the monitoring of EM and PTM levels in wheat-based sweets, and from a food safety perspective, the study is important for consumers of wheat-based sweets.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.371
Teacher spread0.328 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations31
Published2023
Admission routes1
Has abstractyes

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