Evidence map›Paper›PMID 33686548›Full record

ArticleMikrochimica acta2021

Protein-templated copper nanoclusters for fluorimetric determination of human serum albumin.

Mariagrazia Lettieri, Pasquale Palladino, Simona Scarano, Maria Minunni

Open access · hybridAbstract read
In one paragraph

Article in Mikrochimica acta, 2021. 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
1.2field-weighted citation impact, top 24% of its field
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, 22 citations in OpenAlex.

  1. Review
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 at 1 institution in 1 country.

Mariagrazia LettieriDepartment of Chemistry "Ugo Schiff", University of Florence, 50019, Sesto Fiorentino, FI, Italy.
Pasquale PalladinoDepartment of Chemistry "Ugo Schiff", University of Florence, 50019, Sesto Fiorentino, FI, Italy.
Simona ScaranoDepartment of Chemistry "Ugo Schiff", University of Florence, 50019, Sesto Fiorentino, FI, Italy. simona.scarano@unifi.it.ORCID 0000-0002-8050-1715
Maria MinunniDepartment of Chemistry "Ugo Schiff", University of Florence, 50019, Sesto Fiorentino, FI, Italy.
University of Florence · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Copper nanoclusters (CuNCs) are attractive for their unique optical properties, providing sensitive fluorescent detection of several kinds of targets even in complex matrices. Their ability in growing on suitable protein and nucleic acid templates make CuNCs efficient optical reporters to be exploited in bioanalysis. In this work, we report the specific and sensitive determination of human serum albumin (HSA) in human serum (HS) and urine via CuNCs fluorescence. HSA is the most abundant protein in plasma, and plays a key role in the early diagnosis of serious pathological conditions such as albuminuria and albuminemia. Recently, HSA has become clinically central also as a biomarker to assess severity, progression, and prognosis of various cancers. We report the controlled and reproducible growth of CuNCs directly on the target analyte, HSA, which results in a fine dose-dependent fluorescent emission at 405 nm. The protocol is optimized in water, and then applied to serum and urine specimens, without matrix pretreatment. The method linearly responds within the whole concentration of clinical interest, with a sensitivity of 1.8 ± 0.1 × 10

Indexed as

BiomarkersCopperFluorescent DyesHumansLimit of DetectionMaleMetal NanoparticlesReproducibility of ResultsSerum Albumin, HumanSpectrometry, FluorescenceBiomarkersCopperFluorescent DyesSerum Albumin, HumanCopper nanoclustersFluorescenceHuman serum albuminLabel-free assay

Identifiers

PMID33686548
PMCPMC7940276
OpenAlexW3135305766

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Registered trials

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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.