ReviewBiomolecules2022
Methods for Radiolabelling Nanoparticles: SPECT Use (Part 1).
Review in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods for Radiolabeling Nanoparticles (Part 3): Therapeutic Use.Biomolecules · 2023Pooled it
- The Application of Radiolabeled Mesoporous Silica Nanoparticles in Molecular Imaging.Molecules (Basel, Switzerland) · 2026Review
- Radiolabelling and bioequivalence of modified Tamoxifen solid lipid nanoparticles as a targeted chemotherapeutic drug.Drug delivery and translational research · 2026Article
- Nanoparticle Detection in Biology and Medicine: A Review.Biosensors · 2025Review
- Luteinizing Hormone-Releasing Hormone (LHRH)-Targeted Treatment in Ovarian Cancer.International journal of molecular sciences · 2025Review
- Radiolabeled LHRH and FSH Analogues as Cancer Theranostic Agents: A Systematic Review.Journal of clinical medicine · 2025Review
- Advances in multimodal imaging techniques in nanomedicine: enhancing drug delivery precision.RSC advances · 2025Review
- Expanding horizons in theragnostics: from oncology to multidisciplinary applications.La Radiologia medica · 2025Review
- Magnetic Resonance Imaging-Based Monitoring of the Accumulation of Polyethylene Terephthalate Nanoplastics.Molecules (Basel, Switzerland) · 2024Article
- Developments in radionanotheranostic strategies for precision diagnosis and treatment of prostate cancer.EJNMMI radiopharmacy and chemistry · 2024Review
- Three-Dimensional In Vitro Tumor Spheroid Models for Evaluation of Anticancer Therapy: Recent Updates.Cancers · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of nanoparticles (NPs) is rapidly increasing in nuclear medicine (NM) for diagnostic and therapeutic purposes. Their wide use is due to their chemical-physical characteristics and possibility to deliver several molecules. NPs can be synthetised by organic and/or inorganic materials and they can have different size, shape, chemical composition, and charge. These factors influence their biodistribution, clearance, and targeting ability in vivo. NPs can be designed to encapsulate inside the core or bind to the surface several molecules, including radionuclides, for different clinical applications. Either diagnostic or therapeutic radioactive NPs can be synthetised, making a so-called theragnostic tool. To date, there are several methods for radiolabelling NPs that vary depending on both the physical and chemical properties of the NPs and on the isotope used. In this review, we analysed and compared different methods for radiolabelling NPs for single-photon emission computed tomography (SPECT) use.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.