Dataset Information

Paper-based LRET sensor for the detection of total heavy rare-earth ions.

ABSTRACT: Based on the mechanism of luminescence resonance energy transfer (LRET) and using a special single strand DNA as the recognition element, a portable paper-based sensor for the accurate detection of total heavy rare-earth ions (mainly Gd³⁺, Tb³⁺ and Dy³⁺) concentration was proposed. The RNA cleaving-DNAzyme should recognize rare-earth ions to cleave RNA on DNA duplexes linking UCNPs and AuNPs, causing UCNPs and AuNPs to approach each other, inducing LRET, which attenuated the green upconversion luminescence (UCL) triggered by the 980 nm laser. UCL was captured by a charge-coupled device (CCD) image sensor and processed with the red-green-blue (RGB) image to quantitatively analyze heavy rare-earth ions in the samples. In the range of 5-50 μmol·L-1, the sensor has good sensitivity, with the limit of detection of 1.26 μmol L^-1.

SUBMITTER: Chen Q

PROVIDER: S-EPMC9577015 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Paper-based LRET sensor for the detection of total heavy rare-earth ions.

Chen Qiang Q Tang Keren K Luo Dengwang D Han Luodan L Yu ChunXiao C Shen Yiping Y Lin Qi Q Chen Yiting Y Li Chunyan C Chen Jinghua J Lan Jianming J

Frontiers in chemistry 20221004

Based on the mechanism of luminescence resonance energy transfer (LRET) and using a special single strand DNA as the recognition element, a portable paper-based sensor for the accurate detection of total heavy rare-earth ions (mainly Gd3+, Tb3+ and Dy3+) concentration was proposed. The RNA cleaving-DNAzyme should recognize rare-earth ions to cleave RNA on DNA duplexes linking UCNPs and AuNPs, causing UCNPs and AuNPs to approach each other, inducing LRET, which at ...[more]

PMID: 36267653

Similar Datasets

Project description:Purpose: The goals of this study is to compare the transcriptome (RNA-seq) modulations in Saccharomyces cerevisiae exposed to two rare earth elements. Lanthanum and ytterbium were used as representative of light and heavy rare earth elements, respectively. Methods: mRNA were sequenced from Saccharomyces cerevisiae exposed to two different rare earth elements. Lanthanum and ytterbium were used as representative of light and heavy rare earth elements respectively. The transcriptome of S. cerevisiae was analysed after being exposed for one hour to the EC10 (Effective concentration 10 %) and the EC50 (Effective concentration 50 %) of lanthanum (50 and 160 µM) and ytterbium (6 and 8 µM). The sequence reads were trimmed using Trimmomativ v0.36.1 and FastQC v0.67 used for quality check. Reads passing the quality check were mapped on the reference genome (S288C R64-2-1 of 2015-01-31 from https://www.yeastgenome.org/) of S. cerevisiae using TopHat v2.1.1. Reads that were mapped on the reference genome were quantified using HTSeq-count v0.6.1p1. Finally, differential gene expression analysis between treatments was carried out using DESeq2 v1.14.1. Differentially expressed genes between conditions were obtained and expressed as log2-fold change with adjusted p-values calculated via a Benjamini-Hochberg test. A cut-off adjusted p-value of < 0.01 was applied. Results: The transcription of genes related to several crucial pathways was modulated in response to both REEs, such as oxidative-reduction processes, DNA replication, and carbohydrate metabolism. REE-specific responses involving the cell wall and the pheromone signalling pathways were highlighted, while these were not reported for other metals. REE exposure also modified the expression and abundance of several ion transport systems, for which strong discrepancies were observed between the two contrasted REEs. Conclusions: Our results demonstrate the discrepancies in yeast response to different rare earth elements (light vs heavy rare earth elements). This results are valuable to prioritize key genes and proteins involved in REE detoxification mechanisms that would deserve further characterisation to better understand the REE toxicity on the environment and human health.

Dataset Information

Paper-based LRET sensor for the detection of total heavy rare-earth ions.

Publications

Paper-based LRET sensor for the detection of total heavy rare-earth ions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets