Evidence map›Paper›PMID 22956869›Full record

ReviewInternational journal of nanomedicine2012

Nanotheranostics--a review of recent publications.

Li-Sheng Wang, Min-Chieh Chuang, Ja-An Annie Ho

Abstract readReview
In one paragraph

Review in International journal of nanomedicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
–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

43 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Recent nanotheranostic approaches in cancer research.Clinical and experimental medicine · 2024
    Review
  7. Review
  8. α-FeChemistryOpen · 2023
    Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Synthesis of Graphene Oxide-FeInternational journal of molecular sciences · 2019
    Article
  19. Article
  20. Article
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.

Li-Sheng WangDepartment of Biochemical Science and Technology, National Taiwan University, Taipei, Taiwan.
Min-Chieh Chuang
Ja-An Annie Ho

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Theranostics is referred to as a treatment strategy that combines therapeutics with diagnostics, aiming to monitor the response to treatment and increase drug efficacy and safety, which would be a key part of personalized medicine and require considerable advances in predictive medicine. Theranostics associates with both a diagnosis that tests patients for possible reactions to taking new medication and targeted drug delivery based on the test results. Emerging nanotechnology provides a great deal of opportunity to design and develop such combination agents, permitting the delivery of therapeutics and concurrently allowing the detection modality to be used not only before or after but also throughout the entire treatment regimen. The introduction of nanotheranostics into routine health care has still a long way to go, since evaluations on cytotoxicity, genotoxicity, and immunotoxicity of prospective nanotheranostics, demonstration of cost-effectiveness, and availability of appropriate accessible testing systems are still required. An extensive review, from a chemistry point of view, of the recent development of nanotheranostics and its in vitro and in vivo applications are herein presented.

Indexed as

Contrast MediaMolecular ImagingNanomedicineNanostructuresContrast Mediadiagnosticsnanomaterialtheranosticstherapeutics

Identifiers

PMID22956869
PMCPMC3431969

What OpenQuestion holds

Textmetadata
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.