Efeitos da exposição ao arsênio, chumbo, mercúrio e cádmio no metabolismo lipídico e glicêmico
Bibliographic record
Abstract
Contamination by toxic elements, including arsenic (As), lead (Pb), mercury (Hg) and cadmium (Cd), represents a global problem associated with harmful effects on human health, which can cause metabolic changes. However, understanding the impact of exposure to toxic elements on glycemic and lipid profiles remains incomplete. This dissertation consists of two studies: the first is a systematic review and meta-analysis of observational studies (Study 1), and the second, a narrative review (Study 2). Study 1 aimed to answer the following question: “Is exposure to As, Pb, Hg and Cd associated with changes in lipid and glycemic profiles in humans?” The review is registered with PROSPERO (CRD42023393681) and was developed based on the Preferred Reporting Items for Systematic Review and Metaanalysis (PRISMA). Studies involving individuals over 10 years of age were included, containing an exposed group and a group not exposed (or with low exposure) to As, Pb, Hg and Cd, published until March 2024. Fasting blood glucose and lipoprotein low density (LDL-c) were defined as the primary outcomes. Secondary outcomes include glycated hemoglobin (HbA1c), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), and triglycerides (TG). The search, selection, extraction and quality analysis process were carried out independently, by two reviewers. The searches were conducted in the MEDLINE (PubMed), EMBASE, Web of Science, LILACS and Google Scholar databases and analyzes of risk of bias and methodological quality of the included studies were carried out using the modified Newcastle–Ottawa (NOS) and JBI tools. Critical Appraisal Tool. Stata statistical software (Stata Corp., College Station, TX, USA) was used to conduct the meta-analysis. Continuous variables were represented as standardized mean difference (SMD) with 95% confidence intervals (CIs). Heterogeneity between studies was verified by the I² test. The search strategy resulted in 6,020 reported articles, remaining at the end of the selection, 17 studies for narrative synthesis (systematic review) 11 for meta-analysis. Studies report adverse effects on fasting blood glucose concentration, HbA1c, HDL-C and LDL-c in individuals exposed to As. Individuals exposed to Hg showed an increase in TG and TC concentrations. Exposure to Pb was associated with changes in glycemic metabolism and increased concentrations of LDL-c, TC and TG. Finally, exposure to Cd led to an increase in the concentrations of HbA1c, TC, LDL-c and TG, in addition to a reduction in the concentration of HDL-c. Two other studies did not report changes in the components of the glycemic profile in relation to exposure to Cd and Pb. In the meta-analysis, subgroup analysis showed that exposure to As and Cd, as well as concomitant exposure to Pb and Cd, increased concentrations of fasting blood glucose. Exposure to Hg and synergy between Cd and Pb were associated with increased LDL-c and TC. Exposure to Hg was also related to reduced HDL-c concentrations and increased TG. In Study 2, the narrative review aimed to investigate the metabolic aspects of As and mechanisms of action associated with glycemic changes. The search resulted in 466 articles of which only 50 were included in the review. It was observed that the relationship between exposure to As and glycemic changes in humans may be associated with factors such as sex, smoking, body mass index, age, occupation, and genetic factors.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".