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Effect of Pesticide Residues on Health and Different Enzyme Levels in the Milk of Women from Karachi-Pakistan

2012· article· en· W2312375091 on OpenAlexvenueno aff
Uzma Mehboob, Mohammad Ahmed Azmi, Mohammad Arshad Azmi, Syed Naeem ul Hasan Naqvi

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Exposure and Toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsDeltamethrinMalathionCypermethrinToxicologyPesticideMedicineBiologyPesticide residueVeterinary medicineAnimal scienceAgronomy

Abstract

fetched live from OpenAlex

The aim of this study was to investigate the presence of pesticide residues in human milk and their effects on the enzyme levels (cholinesterase and lactate dehydrogenase) as well as the health status of the pesticide exposed women. Total 135 milk samples from 45 women were collected from nine different divisions of Karachi, Pakistan. In addition ten milk samples were also collected from normal subjects. The milk samples were taken at day 1, day 15 and day 30 from the same women and from the same divisions. The data indicated that only cypermethrin, deltamethrin, malathion and match were identified. The highest concentration 34.86 µg/10 µl of deltamethrin and the lowest concentration 0.336 µg/10 µl of cypermethrin was found in the milk sample. It may be concluded that exposed women showed significant increased and decreased enzyme levels at different division and also complained about the disturbance in the normal functioning of different organ system and possibly produced various ailments and clinically suffered with skin diseases, backache, disturbance in micturition, difficulty in breathing, asthma and hepatitis.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.027
GPT teacher head0.281
Teacher spread0.254 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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