An innovative electrochemical immuno-platform towards ultra-sensitive monitoring of 2-arachidonoyl glycerol in samples from rats with sleep deprivation: bioanalysis of endogenous cannabinoids using biosensor technology

Kohansal, Fereshteh; Mobed, Ahmad; Ansari, Rana; Hasanzadeh, Mohammad; Ahmadalipour, Ali; Shadjou, Nasrin

doi:10.1039/d2ra00380e

Cited by 6 publications

(4 citation statements)

References 45 publications

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“…According to the results, one of the biomarker candidate metabolites for ME/CFS patients was 1-arachidonylglycerol (20:4), which is an endocannabinoid, a type of molecule involved in regulating cognitive and physiological processes in the body, including energy balance, emotion, pain sensation, and neuroinflammation ( Kohansal et al, 2022 ). The other important metabolite was Alpha-hydroxyisovalerate (AHIV).…”

Section: Discussionmentioning

confidence: 99%

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome

Yagin,

Shateri,

Nasiri

et al. 2024

PeerJ Computer Science

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Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.

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Section: Discussionmentioning

confidence: 99%

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome

Yagin,

Shateri,

Nasiri

et al. 2024

PeerJ Computer Science

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“…Kohansal et al have developed an immunosensor for 2-AG in human plasma and rat serum exploiting the conductivity changes at the modified electrode in the presence of the ferricyanide/ferrocyanide system [ 64 ]. The interrogation techniques were DPV and SWV.…”

Section: Trending Methods For Rapid Detectionmentioning

confidence: 99%

“… Schematic representation of the immunosensor proposed by Kohansal et al for the detection of 2-Ag protein conjugate. Reproduced with permission from [ 64 ]. This article is licensed under a Creative Commons Attribution 3.0 International License, which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.…”

Section: Figures Schemes and Tablesmentioning

confidence: 99%

Affinity Assays for Cannabinoids Detection: Are They Amenable to On-Site Screening?

Puiu

Bala

2022

Biosensors

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Roadside testing of illicit drugs such as tetrahydrocannabinol (THC) requires simple, rapid, and cost-effective methods. The need for non-invasive detection tools has led to the development of selective and sensitive platforms, able to detect phyto- and synthetic cannabinoids by means of their main metabolites in breath, saliva, and urine samples. One may estimate the time passed from drug exposure and the frequency of use by corroborating the detection results with pharmacokinetic data. In this review, we report on the current detection methods of cannabinoids in biofluids. Fluorescent, electrochemical, colorimetric, and magnetoresistive biosensors will be briefly overviewed, putting emphasis on the affinity formats amenable to on-site screening, with possible applications in roadside testing and anti-doping control.

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“…Biosensors measure target molecules within a certain detection interval in a biological sample and are analytical measurement devices transforming this information into a meaningful electrical signal [ 19 ]. Because of the therapeutic importance of 2-AG, as well as its rapid degradation and enzymatic sensitivity, efficient approaches to its precise detection are highly demanded [ 20 ]. Therefore, novel methods are now being developed to overcome the limitations of traditional methods.…”

Section: Introductionmentioning

confidence: 99%

An Innovative Sandwich Type Biosensor towards Sensitive and Selective Monitoring of 2-Arachidonoylglycerol in Human Plasma Samples Using P(β-CD)-AuNPs-DDT as Amplificant Agent: A New Immuno-Platform for the Recognition of Endocannabinoids in Real Samples

et al. 2022

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In this work, 2-AG was successfully detected in human plasma samples using a new sandwich-type electrochemical immune device based on poly-β-cyclodextrin P(β-CD) functionalized with AuNPs-DDT and toluidine blue. The P(β-CD) ensured the bioactivity and stability of the immobilized 2-AG antibody by providing a broad surface for the efficient immobilization of the biotinylated antibody. To complete the top section of the immunosensor (reporter), an HRP-conjugated antibody of 2-AG (secondary antibody (Ab2)) was attached to the surface of a glassy carbon electrode (GCE) modified by P(β-CD), as well as a primarily biotinylated antibody (Ab1). The biosensor fabrication process was monitored using field-emission scanning electron microscope (FE-SEM) and EDS methods. Using the differential pulse voltammetry technique, the immunosensor was utilized for detection of 2-AG in real samples. The suggested interface increased the surface area, which allowed for the immobilization of a large quantity of anti-2-AG antibody while also improving biocompatibility, stability, and electrical conductivity. Finally, the suggested immunosensor’s limit of quantitation was determined to be 0.0078 ng/L, with a linear range of 0.0078 to 1.0 ng/L. The results showed that the suggested bioassay can be utilized for diagnosis of 2-AG in clinical samples as a unique and ultrasensitive electrochemical biodevice.

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An innovative electrochemical immuno-platform towards ultra-sensitive monitoring of 2-arachidonoyl glycerol in samples from rats with sleep deprivation: bioanalysis of endogenous cannabinoids using biosensor technology

Abstract: A novel electrochemical immunosensor based gold nanoparticles for the sensitive recognition of 2-AG was introduced.

Cited by 6 publications

References 45 publications

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome

Affinity Assays for Cannabinoids Detection: Are They Amenable to On-Site Screening?

An Innovative Sandwich Type Biosensor towards Sensitive and Selective Monitoring of 2-Arachidonoylglycerol in Human Plasma Samples Using P(β-CD)-AuNPs-DDT as Amplificant Agent: A New Immuno-Platform for the Recognition of Endocannabinoids in Real Samples

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