Evidence map›Paper›PMID 39718700›Full record

ReviewDiscover nano2024

Utilizing nanomaterials for cancer treatment and diagnosis: an overview.

Bageesha Mukhopadhyay, Sudhakar Singh, Avtar Singh

Abstract readReview
In one paragraph

Review in Discover nano, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

3 authors.

Bageesha MukhopadhyayDepartment of Biomedical Engineering, School of Bioengineering & Biosciences, Lovely Professional University, Phagwara, Punjab, 144001, India.
Sudhakar SinghDepartment of Biomedical Engineering, School of Bioengineering & Biosciences, Lovely Professional University, Phagwara, Punjab, 144001, India.
Avtar SinghSchool of Electrical Engineering and Computing (SoEEC), Adama Science and Technology University (AS-TU), 1888, Adama, Ethiopia. avtarsingh@astu.edu.et.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a deadly disease with complex pathophysiological nature and is the leading cause of death worldwide. Traditional diagnosis methods often detect cancer at a considerably critical stage and the conventional methods of treatment like chemotherapy, radiation therapy, targeted therapy, and immunotherapy have several limitations, multidrug resistance, cytotoxicity, and lack of specificity are a few examples. These pose substantial challenge for effective and favourable cancer treatment. The advent of nanotechnology has revolutionized the face of cancer diagnosis and treatment. Nanoparticles, which have a size range of 1-100 nm, are biocompatible and have special optical, magnetic, and electrical capabilities, less toxic, more stable, exhibit permeability and retention effect, and are used for precise targeting. There are several classes of nanoparticles each having their own sets of unique properties. NPs have played an important role in the drug delivery system, overcoming the multi-drug resistance, reducing the side-effects as seen in conventional therapeutic methods and hence able to solve the limitations of conventional methods of diagnosis and treatment. This review discusses the four major classes of nanoparticles (Lipid based NPs, Carbon NPs and Metallic NPs and Polymeric NPs): their discovery and introduction in medical field, unique properties and characteristics, advantages and disadvantages, sub-categories and characteristics of these categories, major area of application in Cancer diagnosis and treatment, and latest methodologies where these are used in cancer treatment.

Indexed as

CancerCellular targetingChemotherapyEtcMultidrug resistanceNanoparticles

Identifiers

PMID39718700
PMCPMC11668726

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.