Evidence map›Paper›PMID 39206392›Full record

ReviewAdvanced pharmaceutical bulletin2024

Review on Hyaluronic Acid Functionalized Sulfur and Nitrogen Co-Doped Graphene Quantum Dots Nano Conjugates for Targeting of Specific Type of Cancer.

Vinit Sudhakar Patil, Kedar Rupa Bavaskar, Dilip Omprakash Morani, Ashish Suresh Jain

Abstract readReview
In one paragraph

Review in Advanced pharmaceutical bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Vinit Sudhakar PatilShri D.D. Vispute College of Pharmacy and Research Center, Devad-Vichumbe, New Panvel, India-410206.
Kedar Rupa BavaskarDepartment of Pharmaceutics, Shri D.D. Vispute College of Pharmacy and Research Center, Devad-Vichumbe, New Panvel, India-410206.ORCID https://orcid.org/0009-0001-5575-3435
Dilip Omprakash MoraniDepartment of Pharmaceutics, Bombay Institute of Pharmacy and Research, Dombivali India-421204.
Ashish Suresh JainDepartment of Pharmacognosy, Shri D.D. Vispute College of Pharmacy and Research Center, Devad-Vichumbe, New Panvel, India-410206.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many people lose their lives to cancer each year. The prevalence of illnesses, metabolic disorders, high-risk infections, and other conditions has been greatly slowed down by expanding scientific research. Chemotherapy and radiation are still the initial lines of treatment for cancer patients, along with surgical removal of tumors. Modifications have been made in chemotherapy since medicines frequently have substantial systemic toxicity and poor pharmacokinetics and still do not reach the tumor site at effective concentrations. Chemotherapy may now be administered more safely and effectively thanks to nanotechnology. Nanotechnology-based graphene quantum dots (GQDs) are very applicable in breast cancer detection, as a drug delivery system, and in the treatment of breast cancer because of their physical and chemical properties, lower toxicity, small size, fluorescence, and effective drug delivery. This paper analyzes the GQDs as cutting-edge platforms for biotechnology and nanomedicine also its application in drug delivery in cancer. It shows that GQDs can be effectively conjugated with hyaluronic acid (HA) to achieve efficient and target-specific delivery.

Indexed as

CancerDrug deliveryFluorescenceGraphene quantum dotsHyaluronic acidNanoparticlesNanotechnologyTumor

Identifiers

PMID39206392
PMCPMC11347733

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.