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Smart carbon-based sensors for the detection of non-coding RNAs associated with exposure to micro(nano)plastics: an artificial intelligence perspective

  • Review Article
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Abstract

Micro(nano)plastics (MNPs) are pervasive environmental pollutants that individuals eventually consume. Despite this, little is known about MNP’s impact on public health. In this article, we assess the evidence for potentially harmful consequences of MNPs in the human body, concentrating on molecular toxicity and exposure routes. Since MNPs are present in various consumer products, foodstuffs, and the air we breathe, exposure can occur through ingestion, inhalation, and skin contact. MNPs exposure can cause mitochondrial oxidative stress, inflammatory lesions, and epigenetic modifications, releasing specific non-coding RNAs in circulation, which can be detected to diagnose non-communicable diseases. This article examines the most fascinating smart carbon-based nanobiosensors for detecting circulating non-coding RNAs (lncRNAs and microRNAs). Carbon-based smart nanomaterials offer many advantages over traditional methods, such as ease of use, sensitivity, specificity, and efficiency, for capturing non-coding RNAs. In particular, the synthetic methods, conjugation chemistries, doping, and in silico approach for the characterization of synthesized carbon nanodots and their adaptability to identify and measure non-coding RNAs associated with MNPs exposure is discussed. Furthermore, the article provides insights into the use of artificial intelligence tools for designing smart carbon nanomaterials.

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Abbreviations

3D:

Three-dimensional

AIs:

Artificial intelligence

ANN:

Artificial neural network

ATP:

Adenosine triphosphate

BBP :

Benzyl butyl phthalate

BPA:

Bisphenol A

C-dots:

Carbon dots

CGenFF:

CHARMM general force field

CNAs:

Circulating nucleic acids

CNDs:

Carbon Nanodots

CPS:

Cyber-physical systems

CSTR:

Continuous stirred-tank reactor

CVD:

Chemical vapor deposition

DBP :

Dibutyl phthalate

DEHP:

Di (2-ethylhexyl) phthalate

DFT:

Density functional theory

DLP:

Digital light process

DMLS:

Direct metal laser sintering

DNA:

Deoxyribonucleic acid

DTW:

Dynamic time warping

EBM:

Electron beam melting

ECL:

Electrochemiluminescence

EMR:

Electronic medical records

ESR1:

Estrogen receptor 1

f-CQD:

Functionalized carbon quantum dots

FDM:

Fused deposition modeling

FF:

Force-Field

GAFF:

General AMBER Force Field

Hpcal1:

Hippocalcin-like 1

INSL3:

Insulin-like hormone 3 expression

IoMT:

Internet of medical things

IoT:

Internet of things

LAMP3:

Lysosomal-associated membrane protein 3

LDA:

Linear discriminant analysis

LR:

Logistic Regression

MAPK:

Mitogen-activated protein kinase signaling

MBP :

Monobutyl phthalate

MD:

Molecular dynamics

MEHP :

Mono-2-ethylhexyl phthalate

MiRNAs:

MicroRNAs

MJF:

Multi jet fusion

ML:

Machine learning

MNPs:

Micro/Nanoplastics

MPs:

Microplastics

N-CNDs:

Nitrogen-containing carbon Nanodots

NLRP3:

Nucleotide-binding domain (NOD)-like receptor protein 3

NNs:

Neural networks

NPs:

Nanoplastics

Nrf2:

Nuclear factor erythroid 2-related factor2

Nsbp1:

Nucleosome binding protein-1

PCA:

Principal component analysis

PLGA:

Poly lactic-co-glycolic acid

PS:

Polystyrene

PVC:

Polyvinyl chloride

QM:

Quantum mechanics

QY:

Quantum yield

RCDs:

Red carbon dots

RNA:

Ribonucleic acid

ROS:

Reactive oxygen species

SEMO:

Semi-empirical

SiO2 :

Silicon dioxide

SLA:

Stereolithography

SLS:

Selective laser sintering

SVM:

Support vector machine

SVN:

Support vector network

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  1. Pooja Ratre and Nazim Nazeer contributed equally.

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  1. Department of Environmental Biotechnology, Genetics & Molecular Biology, ICMR-National Institute for Research in Environmental Health, Bhopal, India

    Pooja Ratre, Nazim Nazeer, Nikita Soni, Prasan Kaur, Rajnarayan Tiwari & Pradyumna Kumar Mishra

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Pradyumna Kumar Mishra: conceptualization, supervision, project administration, funding acquisition, resources, writing—original draft preparation. Pooja Ratre: writing—original draft preparation, formal analysis. Nazim Nazeer: writing—original draft preparation, visualization, formal analysis. Nikita Soni: visualization, formal analysis. Prasan Kaur: visualization, formal analysis. Rajnarayan Tiwari: formal analysis. All authors read and approved the manuscript.

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Ratre, P., Nazeer, N., Soni, N. et al. Smart carbon-based sensors for the detection of non-coding RNAs associated with exposure to micro(nano)plastics: an artificial intelligence perspective. Environ Sci Pollut Res 31, 8429–8452 (2024). https://doi.org/10.1007/s11356-023-31779-9

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