ReviewBioMed research international2019
Nanoenabled Bioseparations: Current Developments and Future Prospects.
Review in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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, 30 citations in OpenAlex.
- Surface complexation and multilayer formation in the adsorption of NADA and phosphate on magnetic iron oxide nanoparticles: implications for bioseparation.Nanoscale advances · 2026Article
- Therapeutic potential of betaine and its derivatives in cancer treatment: a comprehensive review.RSC advances · 2025Review
- Increasing the Particle Size and Magnetic Property of Iron Oxide Nanoparticles through a Segregated Nucleation and Growth Process.Nanomaterials (Basel, Switzerland) · 2024Article
- PLGA/PEG Nanoparticles Loaded with Cyclodextrin-Pharmaceutics · 2022Article
- Aspects of high-performance and bio-acceptable magnetic nanoparticles for biomedical application.Asian journal of pharmaceutical sciences · 2021Review
- Chitosan-Coated PLGA Nanoparticles Loaded withNanomaterials (Basel, Switzerland) · 2021Article
- Liposome Photosensitizer Formulations for Effective Cancer Photodynamic Therapy.Pharmaceutics · 2021Review
- Betaine host-guest complexation with a calixarene receptor: enhancedRSC advances · 2021Article
- Magnetic Nanoparticle Composites: Synergistic Effects and Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Review
- Green Synthesis of Platinum and Palladium Nanoparticles UsingNanomaterials (Basel, Switzerland) · 2021Article
- Core-Shell Imidazoline-Functionalized Mesoporous Silica Superparamagnetic Hybrid Nanoparticles as a Potential Theranostic Agent for Controlled Delivery of Platinum(II) Compound.International journal of nanomedicine · 2020Article
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 at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of nanomaterials in bioseparations has been recently introduced to overcome the drawbacks of the conventional methods. Different forms of nanomaterials, particularly magnetic nanoparticles (MNPs), carbon nanotubes (CNTs), casted nanoporous membranes, and electrospun nanofiber membranes were utilized in biological separation for the aim of production of different biomolecules such as proteins, amino acids, nucleic acids, and enzymes. This paper critically reviews the state-of-the-art efforts undertaken in this regard, with emphasis on the synthesis and performance evaluation of each nanoform. Challenges and future prospects in developing nanoenabled bioseparations are also discussed, for the purpose of highlighting potential advances in the synthesis and fabrication of novel nanomaterials as well as in the design of efficient nanoenabled processes for separating a wide spectrum of biomolecules.
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.