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Record W4295106137 · doi:10.53350/pjmhs221661046

Biologically Synthesized Zinc Oxide Nanoparticles and Carbon Tetrachloride as an Anti Cancer Drug: A Review

2022· review· en· W4295106137 on OpenAlexaff
Muhammad Haseeb Basharat, Muhammad Tariq, Riaz Mustafa, Amar Akash, Hafiza Hira Talib, Muhammad Nouman Aziz, Anadil Noel, Adnan Zeb, Muhammad Farooq Khalid, Fakhra Soomro, Qudsia Mushtaq, Mehreen Fatima

Bibliographic record

Venuenot available
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCurcumin's Biomedical Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsZincCarbon tetrachlorideNanoparticleDrugNanotechnologyTetrachlorideMaterials scienceChemistryPharmacologyMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

Cancer is a life-threatening disease, curing it is one of the primary tasks for scientists around the world. One of the major fields that have exceptional abilities to control cancer is nanotechnology and nano medicines. Zinc oxide nanoparticles have flexible platforms for therapeutic and biomedical practice. There is a vital need to manufacture a new anti-cancerous drug. Zinc oxide nanoparticles have a great potential to act as an anti-cancerous drug. A common effect of zinc nanoparticle and carbon tetrachloride is the primary concern on the liver, biologically synthesized nanoparticles can be used for this cure purpose. This review study aims to explain the effects of synthesized nanoparticles on the rat in the presence of CCl4; Combination of toxic substance with the presence of nanoparticle can give us a better idea on the effectiveness of nanoparticle. Keywords: Zinc oxide nanoparticles, Liver cirrhosis, Carbon tetrachloride, Liver function

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.036
GPT teacher head0.347
Teacher spread0.311 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

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