Risk assessment of selected pharmaceuticals on wildlife with nanomaterials based aptasensors

Satish, Swathi; Dey, Aayush; Tharmavaram, Maithri; Khatri, Nitasha; Rawtani, Deepak

doi:10.1016/j.scitotenv.2022.155622

Cited by 7 publications

(2 citation statements)

References 84 publications

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“…Aptamer-based biosensors have been widely used in various fields, such as environmental monitoring [ 1 ], food quality and safety [ 2 ], and medical diagnostics and therapy [ 3 ], due to the physical and chemical features of aptamers for detection and small binding substances [ 4 ]. Moreover, the advancement in nanostructured materials has attracted much attention in recent years due to their potential applications and unique properties, including high reactivity, high functionalization, large surface-area-to-volume ratio, and small size [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

et al. 2022

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Nanomaterial-based aptasensors are useful devices capable of detecting small biological species. Determining suitable signal processing methods can improve the identification and quantification of target analytes detected by the biosensor and consequently improve the biosensor’s performance. In this work, we propose a data augmentation method to overcome the insufficient amount of available original data and long short-term memory (LSTM) to automatically predict the analyte concentration from part of a signal registered by three electrochemical aptasensors, with differences in bioreceptors, analytes, and the signals’ lengths for specific concentrations. To find the optimal network, we altered the following variables: the LSTM layer structure (unidirectional LSTM (LSTM) and bidirectional LSTM (BLSTM)), optimizers (Adam, RMSPROP, SGDM), number of hidden units, and amount of augmented data. Then, the evaluation of the networks revealed that the highest original data accuracy increased from 50% to 92% by exploiting the data augmentation method. In addition, the SGDM optimizer showed a lower performance prediction than that of the ADAM and RMSPROP algorithms, and the number of hidden units was ineffective in improving the networks’ performances. Moreover, the BLSTM nets showed more accurate predictions than those of the ULSTM nets on lengthier signals. These results demonstrate that this method can automatically detect the analyte concentration from the sensor signals.

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Section: Introductionmentioning

confidence: 99%

Predicting Analyte Concentrations from Electrochemical Aptasensor Signals Using LSTM Recurrent Networks

et al. 2022

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“…The need is for specific, optimized methods which are precise yet following strict quality procedures to generate relevant data. The solution for such trace‐level detection is aptasensors which are biological sensors developed using aptamers (Satish et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Aptasensors in environmental forensics: Tracking the silent killers

Dube

Satish

Rawtani

2023

WIREs Forensic Science

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Since its inception, environmental forensics has observed expansion of its horizons across several threats to life forms, be it pertaining to wildlife trafficking or tracking the release of effluents containing pharmaceutical drugs, toxins, pesticides, heavy metals, pathogenic microbes, and microplastics. With the substantial growth of pharmaceutical industry over the past few decades, especially with respect to therapeutic personal care products and over the counter drugs, a new threat to environment has emerged from pharmaceutical toxicity.Due to the recalcitrant nature and poor wastewater treatment practices related to these pollutants, they leach into different strata of ecosystem like aquatic, terrestrial, and atmospheric systems. These drugs pose a threat to several life forms even at trace concentrations. This article aims at providing a profound perspective by exhaustively reviewing several classes of pharmaceutical drugs that are silently threatening the wildlife and environment. The sensitive, specific, and rapid detection of such drugs menacing the environment and wildlife is pertinent and can be achieved through aptamer-based biosensors known as aptasensors. These are a rising class of biosensors with vast application potential in numerous fields including environmental and wildlife forensics. This article also highlights the gap in research in the availability of rapid sensors for trace detection of drugs in environment hence encouraging researchers to explore the under-explored potential of aptasensors in environmental forensics. Highly sensitive and selective detection of such drugs is crucial in narrowing down the origin of such pollutants so as to aid the regulatory authorities in enforcing control over their release into environment.

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