Evidence map›Paper›PMID 42366317›Full record

ReviewDiscover nano2026

Nanotechnological applications of marine algae derived neurotoxins spanning harmful algal blooms and therapeutic innovations.

Morteza Golbashirzadeh

Abstract readReview
In one paragraph

Review in Discover nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Morteza GolbashirzadehMarine Medicinal Plants Research Center, Chabahar University of Medical Science, Chabahar, Iran. m.golbashir@gmail.com.ORCID http://orcid.org/0000-0002-1611-9175

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Marine algae-derived neurotoxins, commonly associated with harmful algal blooms (HABs), represent a paradox in marine and biomedical sciences. While traditionally studied for their ecological disruptions and health hazards, these bioactive compounds possess unique biochemical properties with promising therapeutic and technological applications. By summarizing current knowledge and identifying gaps in research, this review systematically examines the biological significance of marine algae, elucidates the mechanisms underlying neurotoxin production, and assesses their biomedical relevance. Furthermore, it explores nanotechnology as a transformative approach for harnessing neurotoxins in drug delivery, biosensing, and theranostics. Particular emphasis is placed on nano-biosensors for precise neurotoxin detection, nanomaterial-based mitigation strategies for HABs, and the use of neurotoxin-loaded nanocarriers in targeted pharmacological interventions. Ethical and environmental considerations surrounding neurotoxin utilization are critically analyzed to ensure sustainable applications. By synthesizing current knowledge and identifying gaps in research, this review hypothesizes that marine algae-derived neurotoxins, when incorporated into nanosystems, can serve as multifunctional agents in precision medicine, neuropharmacology, and diagnostic imaging. Through an interdisciplinary perspective bridging marine biology, toxicology, and nanoscience, this work aims to provide a structured framework for future research, fostering innovation at the intersection of marine biotechnology and nanomedicine.

Indexed as

Harmful algal blooms (HABs)Marine algae-derived neurotoxinsNanotechnology for algae toxinsNeurotoxin biosynthesisNeurotoxin effects

Identifiers

PMID42366317
PMCPMC13310870

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.