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Record W4410312074 · doi:10.47852/bonviewjopr52025045

Sustainable Nanoparticle Synthesis Using <i>Tinospora cordifolia</i> (Giloy) Leaves Extracts: Evaluation of Antimicrobial Efficacy Against MultiDrug Resistant Bacteria and Optical Features

2025· article· en· W4410312074 on OpenAlexaff
Jyoti Jaglan, Anshu Jaglan, Harsh Jaglan, Preeti Jaglan, Savita Jaglan

Bibliographic record

VenueJournal of Optics and Photonics Research · 2025
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsTinospora cordifoliaAntimicrobialMultiple drug resistanceTraditional medicineChemistryBacteriaMicrobiologyAntibioticsBiologyMedicineBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Sustainable synthesis, also known as environmentally benign synthesis, of nanoparticles, presents an energy and resource-efficient approach for the development of nanoparticles to advanced materials with considerable biomedical potential. This study focuses on the synthesis of zinc oxide (ZnO) nanoparticles using Tinospora cordifolia (Giloy) leaves, aqueous extract as a natural strengthening and stabilizing and natural reducing agent. The bioactive compounds present in the leaves extract facilitated the reduction of zinc ions (Zn2+) to ZnO nanoparticles under optimized reaction conditions. For the characterization of nanoparticles, analytical tools were used like UV-Vis spectroscopy and X-ray diffraction (XRD) to determine the size of nanoparticles, their morphology, and crystalline structure. Green-synthesized ZnO nanoparticle's optical properties and their energy band gap were evaluated, which revealed an energy band gap of approximately 3.12 eV, which suggests their efficiency for photocatalytic and biomedical applications. The antimicrobial potential of the green-synthesized ZnO nanoparticles was assessed against a pathogen associated with waterborne infections which is Aeromonas hydrophila, showcasing multidrug-resistant (MDR) activity. The nanoparticles exhibited significant biocidal activity, with a zone of inhibition that is directly correlated to the size of nanoparticles and their concentration. The effectiveness of antimicrobial activity is attributed to the unique physicochemical properties of the ZnO nanoparticles, including a high surface area and size-dependent reactivity, which increases their interaction with bacterial cell membranes. This study brings to light the potential of Tinospora cordifolia-mediated green synthesis of ZnO which is a renewable and competent method for producing biofunctional ZnO nanoparticles. The encouraging antimicrobial activity, coupled with their tunable optical properties, positions these nanoparticles as valuable agents in combating multidrug-resistant bacteria, with further applications in nanomedicine, biosensing, and environmental remediation technologies. Received: 20 December 2024 | Revised: 26 March 2025 | Accepted: 16 April 2025 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Jyoti Jaglan: Conceptualization, Methodology, Writing – review & editing, Supervision. Anshu Jaglan: Methodology, Validation, Investigation, Writing – review & editing, Project administration. Bajinder Singh: Formal analysis, Resources. Harsh Jaglan: Software, Formal analysis, Resources, Data curation, Visualization. Preeti Jaglan: Validation, Investigation. Savita Jaglan: Investigation, Writing – original draft. Monika Barala: Conceptualization, Writing – original draft, Visualization, Project administration.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.049
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.375
Teacher spread0.323 · 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.

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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