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Record W2796147648 · doi:10.1186/s11671-018-2497-2

A Comparative In Vivo Scrutiny of Biosynthesized Copper and Zinc Oxide Nanoparticles by Intraperitoneal and Intravenous Administration Routes in Rats

2018· article· en· W2796147648 on OpenAlexaff
C. Ashajyothi, Harish K. Handral, Chandrakanth Kelmani R

Bibliographic record

VenueNanoscale Research Letters · 2018
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity Health Network
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsIn vivoPharmacologyToxicityIntraperitoneal injectionZincChemistryIC50MedicineToxicologyBiologyBiochemistryIn vitroInternal medicineBiotechnology

Abstract

fetched live from OpenAlex

During the present time, anti-microbial features of copper (Cu) and zinc oxide (ZnO) nanoparticles (NPs) are extensively used to combat the growth of pathogenic microbes. CuNPs and ZnONPs are recurrently used in cosmetics, medicine and food additives, and their potential for toxic impacts on human and ecosystem is of high concern. In this study, the fate and toxicity of 16- to 96-nm-ranged biosynthesized copper (Bio-CuNPs) and zinc oxide (Bio-ZnONPs) was assessed in male Wistar rats. In vivo exposures of the two nanoparticles are achieved through two different administration routes namely, intraperitoneal (i/p) and intravenous (i/v) injections. The three different concentrations, no observable adverse effect concentration (NOAEC), inhibitory concentration (IC 50 ) and total lethal concentration (TLC), were appraised at the dose range of 6.1 to 19.82 μg/kg and 11.14 to 30.3 μg/kg for Bio-CuNPs and Bio-ZnONPs respectively, for both i/p and i/v routes on 14th and 28th day of observation. These dose ranges are considered based on the previous study of antibacterial dose on multidrug-resistant pathogenic bacteria. In this study, we investigated the toxic effect of Bio-CuNPs and Bio-ZnONPs on animal behaviour, animal mass, haematologic indices, organ indices and histopathology of liver, spleen, kidney and brain organs. We found that i/v and i/p administration of Bio-ZnONPs in three different doses did not cause mortality and body weight was slightly reduced up to second week of administration compared with the vehicle control group. At the dose ranges of 11–16 μg/kg (i/v) and 24–30 μg/kg (i/p), no significant changes were observed in the serum creatinine level as well as serum ALT, serum AST level and ALP level which were 40.7 mg/dl, 37.9 IU/L and 82.4 IU/L normal as compared to vehicle control on 14th and 28th day of observation. These findings are confirmed in liver, kidney and spleen indices and histopathology studies. Furthermore, liver and kidney injury occurred when the concentrations of Bio-CuNPs were at 9.5 μg/kg (IC 50 ) and 11.7 μg/kg (TLC) for i/v route of administration. Similarly, increase in serum ALT (67.7 mg/dl), AST level (70 IU/L) and ALP (128 IU/L) was also observed. And the body weight was significantly lower than in the control group after 14th day, and there were statistically significant differences observed by this route; interestingly, the toxicity of Bio-CuNPs in serum is prolonged (up to 28th day). Effect of Bio-CuNPs through i/p route was considerably low as compare to the control. Results of the present study revealed that Bio-ZnONPs have no effect on kidney and liver function biomarkers (both i/v and i/p) as compared to Bio-CuNPs. As shown in graphical abstract (Fig. 1), our aim is to assess the toxicity of Bio-CuNPs and Bio-ZnONPs through in vivo protocol. According to Kahru and Dubourguier reviews, AgNPs, CuNPs and ZnONPs have been historically used as biocides, for preventing the growth of microorganisms and algae (Kahru and Dubourguier 2010). Therefore, as like pesticides, nanomaterials should be monitored for their toxic response toward non-target species, including humans and animals. To gain a better understanding whether the accidental release of metal-containing NPs may pose a threat to non-target species, assessing of toxic effect is indispensable.The ‘non-target organism’ is an organism which will be exposed to NPs after their incidental release into the environment.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.038
GPT teacher head0.331
Teacher spread0.293 · 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 designBench or experimental
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".

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Citations21
Published2018
Admission routes1
Has abstractyes

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