Evidence map›Paper›PMID 39400023›Full record

ReviewCurrent pharmaceutical design2025

Emerging Promise of Green Synthesized Metallic Nanoparticles for the Management of Neurological Disorders.

Zahra Esmaeili Moghaddam, Samin Hamidi, Maryam Azarfarin, Sara Salatin

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current pharmaceutical design, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Zahra Esmaeili MoghaddamStudent Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
Samin HamidiResearch Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.
Maryam AzarfarinNeurosciences Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Sara SalatinNeurosciences Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.ORCID 0000-0002-4779-7868

Funding

National Institute for Medical Research Development 4021341Tabriz University of Medical Sciences 73400
6 · The paper itself

Abstract

The management of neurological disorders is very challenging due to the presence of the bloodbrain barrier (BBB) that prevents the entry of drugs into the central nervous system (CNS). The advancement of metallic nanoparticles (NPs) provides a novel direction for the treatment of neurological disorders. However, there is a significant concern regarding the toxic effects of metal NPs on biological tissues like the brain. The green synthesis strategy offers a superior alternative to the traditional methods for the development of metallic NPs. Notable metal and metal oxide NPs can be produced using various bio-reductants derived from natural sources such as plant tissues, fungi, bacteria, yeast, and alga. These biological agents play double roles as they expedite the reduction process and act as capping and stabilizing agents. In this paper, we discuss the major neurological disorders and the physical barriers limiting the transport of therapeutics to the CNS. Moreover, a special focus is given to the unique features of green synthesized metallic NPs for therapeutic purposes in various neurological disorders. The insights provided will guide future research toward better outcomes and facilitate the development of innovative treatments for neurological disorders.

Indexed as

Green Chemistry TechnologyMetal NanoparticlesNervous System DiseasesAnimalsBlood-Brain BarrierHumansbrainCentral nervous system (CNS)green synthesismetal and metal oxide nanoparticlesneurological disordersstabilizing agents.

Identifiers

What OpenQuestion holds

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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.