Evidence map›Paper›PMID 40371018›Full record

ArticleIndian journal of microbiology2025

Multifunctional Nanomaterials: Recent Advancements in Cancer Therapeutics and Vaccines.

Saurabh Gupta, Rasanpreet Kaur, Alok Bhardwaj, Deepak Parashar

Abstract read
In one paragraph

Article in Indian journal of microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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.

Saurabh Gupta *Department of Biotechnology, GLA University, Mathura, Uttar Pradesh 281406 India.
Rasanpreet Kaur *Department of Biotechnology, GLA University, Mathura, Uttar Pradesh 281406 India.
Alok BhardwajDepartment of Biotechnology, GLA University, Mathura, Uttar Pradesh 281406 India.
Deepak ParasharDivision of Hematology and Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI 53226 United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanotechnology has revolutionized cancer detection and treatment, overcoming limitations of conventional methods. Imaging, targeting, and therapy moieties can all be combined in multifunctional nanoparticle systems to deliver the imaging or treatment modalities to the tumor in a targeted manner. These nanostructures can be engineered to create smart drug delivery systems for effective distribution and combinatorial therapy. Nanostructures made of biomolecules are naturally multifunctional and have a variety of biological functions that can be investigated for use in cancer nanomedicine. The supramolecular characteristics of biomolecules can be carefully engineered to create smart drug delivery systems that enable effective drug distribution to specific areas of the body as well as combinatorial therapy in a single design. Nanotechnology has also increased the efficiency of cancer vaccines, highlighting the future of tumor immunotherapy. Nanomaterials are often used as anti-cancer drugs or anti-inflammatory drugs due to their biosafety potential and enhanced bioavailability. By delivering targeted antigens and adjuvants, nanomaterials can improve vaccination efficacy and safety, preventing rapid degradation and prolonging antigen retention in lymphoid and tumor cells. We examine both organic and inorganic multifunctional nanomaterials in this review, emphasizing particular multifunctional properties in the context of cancer targeting, therapy, and vaccinations.

Indexed as

Drug deliveryImmunotherapyNanomaterialsTumorVaccine

Identifiers

PMID40371018
PMCPMC12069785

What OpenQuestion holds

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Registered trials

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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.