Evidence map›Paper›PMID 39021196›Full record

ReviewCurrent pharmaceutical design2024

Nanotechnological Advances in the Diagnosis of Gynecological Cancers and Nanotheranostics.

Vahideh Keyvani, Samaneh Mollazadeh, Espanta Riahi, Reihaneh Alsadat Mahmoudian, Kazem Anvari, Amir Avan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current pharmaceutical design, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Vahideh KeyvaniDepartment of Medical Genetics and Molecular Medicine, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Samaneh MollazadehNatural Products and Medicinal Plants Research Center, North Khorasan University of Medical Sciences, Bojnurd, Iran.
Espanta RiahiBlood Borne Infections Research Center, Academic Center for Education, Culture and Research (ACECR), Mashhad, Iran.
Reihaneh Alsadat MahmoudianMetabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Kazem AnvariCancer Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Amir AvanMetabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.

Funding

Mashhad University of Medical Sciences
6 · The paper itself

Abstract

Gynecological cancers are one of the main causes of female mortality worldwide. Despite the various strategies to reduce mortality and improve quality of life, there are still many deficiencies in the diagnosis and treatment of gynecological cancers. One of the important steps to ensure optimal cancer treatment is the early detection of cancer cells and the use of drugs to reduce toxicity. Due to the increase in systemic toxicity and resistance to traditional and conventional diagnostic methods, new strategies, including nanotechnology, are being used to improve diagnosis and reduce the severity of the disease. Nanoparticles (NPs) provide exciting opportunities to improve Gynecological Cancers (GCs) diagnosis, particularly in the initial stages. In biomedical investigations and clinical settings, NPs can be used to increase the sensitivity and specificity of recognition and/or imaging of GCs with the help of their molecular and cellular processes. To design more efficient diagnostic NPs for gynecological cancer cells or tissues, determining the specific biomarkers is of great importance. NP-based imaging agents are another solution to trace cancer cells. This review highlights the potential of some NP-based diagnostic techniques in GC detection, which could be translated to clinical settings to improve patient care.

Indexed as

Genital Neoplasms, FemaleNanoparticlesNanotechnologyAnimalsFemaleHumansTheranostic Nanomedicinecancer cells.cervical cancergynecological cancer diagnosisnanotechnological platformsNP-based diagnosticsovarian cancer

Identifiers

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.