Monitoring Retinoblastoma by Machine Learning of Aqueous Humor Metabolic Fingerprinting (Small Methods 1/2022)

High‐Throughput Screening of Metabolic Biomarkers and Wearable Biosensors for the Quantification of Metabolites

“…[72][73][74][75] As a common intraocular pediatric malignancy, retinoblastoma (RB) that arises in the retina, accounts for almost 10% of cancer in children. [1] Humor biosamples were harvested from retinoblastoma patients and microarrayed with matrix for enhanced MALDI metabolic fingerprinting, and subsequent metabolic biomarkers could be identified via MS values (Figure 2a). [1] The MALDI metal fingerprinting were performed on inorganic nanoparticles as the matrix with SEM characterizations (Figure 2b) and high-angle annular dark-field (HAADF) photograph and elemental mapping with O in purple and Fe in green (Figure 2c) validated the morphology and composition of inorganic nanoparticles.…”

“…[1] Humor biosamples were harvested from retinoblastoma patients and microarrayed with matrix for enhanced MALDI metabolic fingerprinting, and subsequent metabolic biomarkers could be identified via MS values (Figure 2a). [1] The MALDI metal fingerprinting were performed on inorganic nanoparticles as the matrix with SEM characterizations (Figure 2b) and high-angle annular dark-field (HAADF) photograph and elemental mapping with O in purple and Fe in green (Figure 2c) validated the morphology and composition of inorganic nanoparticles. Via the metabolic analysis, normalized intensity of seven metabolites (Nor, Ace, Asp, Lev, Lac, Val, and Prc) were screened and demonstrated pronounced differences between the early and advanced retinoblastoma, which could sever as the potential biomarkers for diagnosis of RB (Figure 2d).…”

“…Meanwhile, screening/quantification of metabolic biomarkers holds the promises to precisely monitor even regulate biological/pathogenic processes. [1,2] Coincidentally, partial metabolic biomarkers could be noninvasively induced from human biospecimens (e.g., sweat and tears, etc. ), which may afford a noninvasive biosample for wearable biosensors.…”

“…[39] Briefly, for the noninvasive quantification of metabolites, the main challenges are the low detection limit, specificity, and bio-interfacial adaptation (skinaffinity, biosafety, mechanical compliance, and signal fidelity). [3] Remarkably, integrating micro/nanomaterials with detection techniques has been proved beneficial for clinical diagnosis in the following aspects: i) tunable dimensional effect of micro/nanomaterials allows them to combine with detection platform easily; [1,[40][41][42] ii) attractive characteristics, such as electrochemical properties, large surface ratio, and easy functionalization; [43][44][45] iii) They can sever as capturing/recognizing components, signal reporter/amplifier, electron-transfer mediator, which facilitate the bioanalytical reaction, resulting in enhanced sensitivity. [46,47] In short, the rational design of micro/nanomaterials may open a new avenue for screening and quantification of metabolic biomarkers, by facilitating metabolic analysis platform with improved performances.…”

“…The integration of MS and wearable biosensor techniques may open a novel avenue for screening and quantification of metabolic biomarkers, embracing the future development of wearable device platforms toward personalized, intelligent, and precise home-healthcare in large-scale. [1] Copyright 2022, Wiley-VCH GmbH; b) MXene, Reproduced with permission. [48] Copyright 2021, Wiley-VCH GmbH; c) Hydrogel, Reproduced with permission.…”