ReviewEuropean journal of medical research2025
Nanobiosensors for revolutionizing parasitic infections diagnosis: a critical review to improve global health with an update on future challenges prospect.
Review in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Peptide-Enabled Nanoplatforms for Malaria and Leishmaniasis: From Intracellular Targeting to Translational Diagnostic Perspectives.ChemMedChem · 2026Review
- Evaluation of a commercial real-time PCR assay targeting Leishmania spp. with microscopically positive skin biopsies obtained from Nigerian patients.European journal of microbiology & immunology · 2026Article
- Decoding Leukocyte Dynamics: Functional Biomarkers and Precision Diagnostics in Parasitic Infections.Acta parasitologica · 2026Review
- Recent advances in clinical and laboratory diagnosis of hydatid cyst: from imaging to recombinant and nanobiosensor-based approaches.Infection · 2026Review
- Postoperative Prophylaxis of Cystic Echinococcosis with Albendazole and Praziquantel: A Retrospective Cohort Study.Biomedicines · 2026Article
- Integrative multi-omics and machine learning reveal glycolysis-related biomarkers driving vascular remodeling in pulmonary arterial hypertension.Molecular and cellular biochemistry · 2026Article
- In Vitro Evaluation of Antileishmanial Activity of Commiphora myrrha Essential Oil Nanoliposome.Veterinary medicine and science · 2026Article
- Epidemiological study and risk factors of equine (Parasite epidemiology and control · 2026Article
- Strongyloidiasis Beyond the Tropics: Updated Epidemiological Evidence from a Historically Endemic Region in Spain.Tropical medicine and infectious disease · 2026Article
- Enhancing hydatid cysts diagnosis utilizing cell-free DNA as a sensitive biomarker forHelminthologia · 2026Article
- Revisiting visceral leishmaniasis in immunocompromised patients: Ongoing gaps and advances in diagnostics, therapies, and preventive measures.Current research in parasitology & vector-borne diseases · 2026Review
- mRNA based vaccines and therapeutics for parasitic infections: a comprehensive review.Journal of nanobiotechnology · 2025Review
- Nanobiosensors for Single-Molecule Diagnostics: Toward Integration with Super-Resolution Imaging.Biosensors · 2025Review
- Advances in Microbial Diagnostics: Machine Learning and Nanotechnology for Zoonotic Disease Control.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parasitic infections remain a serious public health issue globally, requiring prompt and precise diagnosis. Traditional diagnostic techniques, such as microscopic examinations, immunological methods, such as enzyme-linked immunosorbent assay (ELISA), and molecular tests, such as polymerase chain reaction (PCR), are standard tools for parasite identification. However, traditional methods are time-consuming and have less sensitivity and specificity than nanobiosensors. Hence, the current review aims to analyze the nanobiosensors in detecting globally important human parasites, i.e., Plasmodium, Leishmania, Echinococcus, Schistosoma, and Taenia, emphasizing their significance in the early detection and analyzing their future challenges. Nanobiosensors provide efficient, sensitive, and rapid diagnosis of parasites' antigens or genetic material using nanomaterials, such as nanowires, quantum dots (QDs), metallic nanoparticles, and carbon nanotubes, as well as identification of biomarkers, including excretory-secretory products and microRNAs. Nanobiosensors can utilize diverse nanomaterials such as gold nanoparticles (AuNPs) for the detection of Plasmodium falciparum histidine-rich protein 2 (PfHRP2) in Plasmodium, carbon nanotubes (CNTs) functionalized with anti-EgAgB antibodies for Echinococcus, and QDs labeled with DNA probes for the detection of Leishmania kDNA. Regarding Schistosoma, graphene oxide (GO)-based nanobiosensors with a soluble egg antigen (SEA) binding, and for Taenia, metallic nanobiosensors can detect parasites' biomarkers even at low concentrations. Challenges for using nanobiosensors in parasitic infection diagnosis include limitations in mass production, biological matrix interference, and the need for standardization. Development of multiplex nanobiosensors using polymer nanofibers or hybrid nanoparticles for simultaneous detection of multiple pathogens, along with integration of lab-on-a-chip technology for point-of-care (PoC) platforms, is an important future prospect that needs to be worked on. In conclusion, considering the rapidly ongoing advancement of nanobiosensors, it is expected that they will aid the detection, treatment, and management of parasitic infections by providing new avenues for early detection, improved treatment, and improved disease management in the future.
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.