Contemporary Comprehensive Review on Arsenic-Induced Male Reproductive Toxicity and Mechanisms of Phytonutrient Intervention
Bibliographic record
Abstract
Arsenic (As) is a poisonous metalloid that is toxic to both humans and animals. Drinking water contamination has been linked to the development of cancer (skin, lung, urinary bladder, and liver), as well as other disorders such as diabetes and cardiovascular, gastrointestinal, neurological, and developmental damage. According to epidemiological studies, As contributes to male infertility, sexual dysfunction, poor sperm quality, and developmental consequences such as low birth weight, spontaneous abortion, and small for gestational age (SGA). Arsenic exposure negatively affected male reproductive systems by lowering testicular and accessory organ weights, and sperm counts, increasing sperm abnormalities and causing apoptotic cell death in Leydig and Sertoli cells, which resulted in decreased testosterone synthesis. Furthermore, during male reproductive toxicity, several molecular signalling pathways, such as apoptosis, inflammation, and autophagy are involved. Phytonutrient intervention in arsenic-induced male reproductive toxicity in various species has received a lot of attention over the years. The current review provides an in-depth summary of the available literature on arsenic-induced male toxicity, as well as therapeutic approaches and future directions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".