Rapid Detection Research Articles

A Versatile Method to Create Antibody/Split‐Enzyme Complexes and Its Application to a Rapid, Homogeneous, and Universal Electrochemical Immunosensing System

AbstractIn this study, a versatile method is developed to create an antibody/split‐enzyme complex for use in electrochemical immunosensors. SpyCatchers are genetically fused at each terminus of flavin adenine dinucleotide‐dependent glucose dehydrogenase (FAD‐GDH) and a protease recognition sequence is inserted into a loop region to prepare a soluble protein and the split GDH. SpyTag‐fused single‐chain variable fragments (scFvs) are employed, which leads to the simple preparation of antibody‐split enzyme complexes (split AECs). The addition of pentameric C‐reactive protein (CRP), as a representative multimeric protein, restored the GDH activity of the split AECs, as the two split AEC fragments formed active GDH when in close proximity. CRP in human serum is electrochemically detected within 5 min without any washing steps with a clinically relevant CRP detection range (0.03–1 mg dL−1). The detection system is expanded to detect hemoglobin, SARS‐CoV‐2 spike protein, and inactivated SARS‐CoV‐2 by exchanging the scFvs. These results show that the convenient preparation method of the split GDH and the split AEC by the insertion of the protease recognition sequence and the use of SpyCatcher/SpyTag can realize a rapid, homogeneous, and universal electrochemical detection system that can be integrated into a commercially available electrochemical glucose sensor.

Fast Reconstruction 3D Computed Tomography Image of Stacked Cell under Faster Scanning by Dual-branch Cross-fusion Flat Bottom Network

Abstract Cone beam computed tomography (CBCT) fast scanning and reconstruction is a key step to achieve rapid detection of internal defects in batteries. In this work, we have achieved a faster CT scanning just in 5 seconds by reducing the X-ray exposure time in sparse view CT. However, the CT data is extremely incomplete by faster scanning; the existing reconstruction methods are difficult to reconstruct a high quality three-dimensional (3D) CT image of stacked cells. To address this issue, we propose a 3D CT image reconstruction network, which can reconstruct higher quality CT images from low quality 3D volume data. The input data of the reconstruction network is not 2D projection data, but 3D volume data. In this network, a high and low resolution dual-branch cross-fusion flat bottom structure is designed. The high resolution flat bottom branch aims to preserve detailed information, while the low resolution flat bottom branch focuses on capturing more semantic information. Cross-fusion between these branches mitigates the loss of semantic details. Additionally, the auxiliary loss function, the main loss function, and the 3D attention module are designed to enhance semantic accuracy and the learning performance of the network. The 3D training data is collected under a fast scanning strategy spanning 5-60 seconds. During the training phase, we use clipping block technology to cut the 3D volume data, enabling direct training on the 3D volume data. Our experimental results demonstrate that our 3D reconstruction network outperforms mainstream algorithms under this faster scanning strategy, which is able to reconstruct higher quality 3D CT images just in 15 seconds. Ablation experiments confirm the positive impact of the dual-branch cross-fusion flat bottom structure, attention module, and loss functions on improving the quality of 3D CT images.

Inkjet Printing Patterned Plasmonic SERS Platform with Surface-Optimized Paper for Label-Free Detection of Illegal Drugs in Urine.

Rapid quantitative testing of illegal drugs is urgently needed for precisely cracking down on drug crimes. Herein, an optimized paper-based surface-enhanced Raman spectroscopy (SERS) platform with patterned printing of plasmonic nanoparticles was constructed for the on-site quick testing of illegal drugs in urine. The filter paper was first coated with a layer of positive-charged chitosan, so as to reduce its roughness by filling the holes of the cellulose matrix and enhance the adhesion of negative-charged silver ink. Subsequently, hydrophobic modification was performed based on the binary silylation reaction, which could obviously improve the sensitivity of the paper-based SERS substrate by concentrating the amount of analyte. Meanwhile, SERS-active silver ink was fabricated and further printed on the surface of the above modified paper with custom-designed pattern (3 × 6). The performance of this SERS platform was assessed by using crystal violet (CV) as a model tag, and the obtained results proved it possesses excellent sensitivity and reproducibility, in which the relative standard deviation (RSD) dropped remarkably. More importantly, as a proof of concept, rapid detection of standard methylamphetamine (MAMP), one of the most widely abused drugs, was achieved with a limit of detection (LOD) of 1.43 ppb using a portable Raman spectrometer. And it also had a good capability in human urine sample detection, with a correlation index (R2) up to 0.9927. This optimized paper-based SERS platform was easily manufactured, cheap, and portable, providing a new strategy for the on-site detection of illicit drugs.

Common viral respiratory infections in children with cancer during the COVID-19 pandemic: a multicenter study from Türkiye

Background. Microbiologic confirmation of respiratory tract infections gained importance during the coronavirus disease 2019 (COVID-19) pandemic. This study retrospectively evaluated seasonal distribution, clinical presentation, and complications of respiratory viral infections (RVIs) other than COVID-19 in children with cancer during and after the pandemic lockdown. Methods. Two hundred and sixty-five inpatient and outpatient RVI episodes in 219 pediatric cancer patients confirmed by multiplex reverse transcriptase polymerase chain reaction (RT-PCR) panels from 13 centers were enrolled. Results. Eighty-six (32.5%) of the total 265 episodes occurred in 16 months corresponding to the lockdowns in Türkiye, and the remaining 67.5% in 10 months thereafter. Human rhinovirus/enterovirus (hRE) (48.3%) was the most common agent detected during and after lockdown. Parainfluenza virus (PIV) (23.0%), influenza virus (9.8%), and respiratory syncytial virus (RSV) (9.1%) were the other common agents. The 28.7% of episodes were lower respiratory tract infections (LRTIs), and complications and mortality were higher than upper respiratory tract infections (URTIs) (25.0% vs 5.3%). Bacteremia was identified in 11.5% of culture-drawn episodes. Treatment delay in one-third and death within four weeks after RVI in 4.9% of episodes were observed. Conclusion. During the pandemic, fewer episodes of RVIs occurred during the lockdown period. Respiratory viruses may cause complications, delays in treatment, and even death in children with cancer. Therefore, increased awareness of RVIs and rapid detection of respiratory viruses will benefit the prevention and, in some cases, abrupt supportive and some antiviral treatment of RVI in children with cancer.

Rapid detection of mouse spermatogenic defects by testicular cellular composition analysis via enhanced deep learning model.

Histological analysis of the testicular sections is paramount in infertility research but tedious and often requires months of training and practice. Establish an expeditious histopathological analysis of mutant mice testicular sections stained with commonly available hematoxylin and eosin (H&E) via enhanced deep learning model MATERIALS AND METHODS: Automated segmentation and cellular composition analysis on the testes of six mouse reproductive mutants of key reproductive gene family, DAZ and PUMILIO gene family via H&E-stained mouse testicular sections. We improved the deep learning model with human interaction to achieve better pixel accuracy and reduced annotation time for histologists; revealed distinctive cell composition features consistent with previously published phenotypes for four mutants and novel spermatogenic defects in two newly generated mutants; established a fast spermatogenic defect detection protocol for quantitative and qualitative assessment of testicular defects within 2.5-3h, requiring as few as 8 H&E-stained testis sections; uncovered novel defects in AcDKO and a meiotic arrest defect in HDBKO, supporting the synergistic interaction of Sertoli Pum1 and Pum2 as well as redundant meiotic function of Dazl and Boule. Our testicular compositional analysis not only could reveal spermatogenic defects from staged seminiferous tubules but also from unstaged seminiferous tubule sections. Our SCSD-Net model offers a rapid protocol for detecting reproductive defects from H&E-stained testicular sections in as few as 3h, providing both quantitative and qualitative assessments of spermatogenic defects. Our analysis uncovered evidence supporting the synergistic interaction of Sertoli PUM1 and PUM2 in maintaining average testis size, and redundant roles of DAZ family proteins DAZL and BOULE in meiosis.

Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplification and flow cytometry

The detection of cancer-associated nucleic acids and mutations through liquid biopsy has emerged as a highly promising non-invasive approach for early cancer detection and monitoring. In this study, we report the development of primer exchange reaction (PER) based signal amplification strategy that enables the rapid, sensitive and specific detection of nucleic acids bearing cancer specific single nucleotide mutations using flow cytometry. Using micrometer size beads as support for immobilizing oligonucleotides and programmable PER assembly for target oligonucleotide recognition and fluorescence signal amplification, we demonstrated the versatile detection of target nucleic acids including KRAS oligonucleotide, fragmented mRNAs, and miR-21. Moreover, our detection system can discriminate single base mutations frequently occurred in cancer-associated genes including KRAS, PIK3CA and P53 from cell extracts and circulating tumor DNAs (ctDNAs). The detection is highly sensitive, with a limit of detection down to 27 fM without pre-amplification. In view of a clinical application, we demonstrate the detection of single mutations after extraction and pre-amplification of ctDNAs from the plasma of breast cancer patients. Importantly, our detection strategy enabled the detection of single KRAS mutation even in the presence of 1000-fold excess of wild type (WT) DNA using multi-color flow cytometry detection approach. Overall, our strategy holds immense potential for clinical applications, offering significant improvements for early cancer detection and monitoring.

Co-freezing localized CRISPR-Cas12a system enables rapid and sensitive nucleic acid analysis

Rapid and sensitive nucleic acid detection is vital in disease diagnosis and therapeutic assessment. Herein, we propose a co-freezing localized CRISPR-Cas12a (CL-Cas12a) strategy for sensitive nucleic acid detection. The CL-Cas12a was obtained through a 15-minute co-freezing process, allowing the Cas12a/crRNA complex and hairpin reporter confined on the AuNPs surface with high load efficiency, for rapid sensing of nucleic acid with superior performance to other localized Cas12a strategies. This CL-Cas12a based platform could quantitatively detect targets down to 98 aM in 30 min with excellent specificity. Furthermore, the CL-Cas12a successful applied to detect human papillomavirus infection and human lung cancer-associated single-nucleotide mutations. We also achieved powerful signal amplification for imaging Survivin mRNA in living cells. These findings highlight the potential of CL-Cas12a as an effective tool for nucleic acid diagnostics and disease monitoring.Graphical abstract

Development of a Triplex qPCR Assay Based on the TaqMan Probe for the Detection of Haemophilus parasuis, Streptococcus suis Serotype 2 and Pasteurella multocida

Porcine respiratory disease is a significant economic problem for the global swine industry. Haemophilus parasuis (H. parasuis), Streptococcus suis (S. suis), and Pasteurella multocida (P. multocida) are three important pathogenic bacteria of the swine respiratory tract. Notably, the three pathogens not only frequently manifest as mixed infections, but their striking clinical similarities also present difficulties for pig populations in terms of disease prevention and treatment. Thus, we developed a triplex real-time quantitative polymerase chain reaction (qPCR) assay based on a TaqMan probe for the detection of H. parasuis, S. suis serotype 2, and P. multocida. Primers and probes were designed to target the conserved regions of the H. parasuis OmpP2 gene, the S. suis serotype 2 gdh gene, and the P. multocida Kmt1 gene. By optimizing the reaction system and conditions, a triplex qPCR method for simultaneous detection of H. parasuis, S. suis serotype 2, and P. multocida was successfully established. The amplification efficiencies of the standard curves for all three pathogens were found to be highly similar, with values of 102.105% for H. parasuis, 105.297% for S. suis serotype 2, and 104.829% for P. multocida, and all R2 values achieving 0.999. The specificity analysis results showed that the triplex qPCR method had a strong specificity. The sensitivity test results indicated that the limit of detection can reach 50 copies/μL for all three pathogens. Both intra- and inter-assay coefficients of variation for repeatability were below 1%. This triplex qPCR method was shown to have good specificity, sensitivity, and reproducibility. Finally, the triplex qPCR method established in this study was compared with the nested PCR as recommended by the Chinese national standard (GB/T34750-2017) for H. parasuis, the PCR as recommended by the Chinese national standard (GB/T 19915.9-2005) for S. suis serotype 2, and the PCR as recommended by the Chinese agricultural industry standard (NY/T 564-2016) for P. multocida by detecting the same clinical samples. Both methods are reasonably consistent, while the triplex qPCR assay was more sensitive. In summary, triplex qPCR serves not only as a rapid and accurate detection and early prevention method for these pathogens but also constitutes a robust tool for microbial quality control in specific pathogen-free pigs.

Detection of pathogenic gram-negative bacteria using an antimicrobial peptides-modified bipolar electrode-electrochemiluminescence platform.

Real-time, label-free detection of gram-negative bacteria with high selectivity and sensitivity is demonstrated using a bipolar electrode-electrochemiluminescence (BPE-ECL) platform. This platform utilizes anode luminescence and cathode modification of antimicrobial peptides (AMPs) to effectively capture bacteria. Magainin I, basic AMP from Xenopus skin, boasting an α-helix structure, exhibits a preferential affinity for the surface of gram-negative pathogens. The covalent attachment of the peptide's C-terminal carboxylic acid to the free amines of a previously thiolated linker ensures its secure immobilization onto the surface of theinterdigitated gold-plated cathode of BPE. The AMP-modified BPE sensor, when exposed to varying concentrations of gram-negative bacteria, produces reproducible ECL intensities, allowing for the detection of peptide-bacteria interactions within the range 1 to 104CFUmL-1. Furthermore, this AMP-modified BPE sensor demonstrates a selective capacity to detect Escherichia coli O157:H7 amidst other gram-negative strains, even at a concentration of 1-CFU mL-1. This study underscores the high selectivity of Magainin I in bacterial detection, and the AMP-modified BPE-ECL system holds significant promise for rapid detection of gram-negative bacteria in various applications. The AMP-modified BPE sensor generated reproducible ECL intensity that detected peptide-bacteria interactions in the range 1 to 104CFUmL-1. The AMP-modified BPE sensor also selectively detected E. coli O157:H7 from other gram-negative strains at a concentration of 1-CFU mL-1. In this paper, AMP demonstrated high selectivity in bacterial detection. The AMP-modified BPE-ECL system prepared has a great potential for application in the field of rapid detection of gram-negative bacteria.

Rapid screening of prednisolone acetate adulterants in health foods using colloidal gold immunochromatographic assay

In this study, a rapid detection method utilizing colloidal gold immunochromatography (CG-ICA) was developed for the detection of illegally added prednisone acetate in health foods. Initially, the preparation conditions of colloidal gold solution were optimized. The optimal potassium carbonate dosage, antibody diluent type, antibody dosage, probe labeling time, blocking time and BSA dosage were determined. Technical analysis was performed to ensure that the established CG-ICA exhibited satisfactory color development and inhibition rates. Under optimized conditions, the cut-off value of CG-ICA was 250 μg/kg. The assay demonstrated a sensitivity of 100 %, a false positive rate of 8 %, and a false negative rate of 0, indicating high specificity for prednisone acetate. The results obtained from testing actual samples were consistent with those obtained using LC-MS/MS, thereby verifying the reliability of the developed method. This method offers robust support for the rapid detection of illegally added prednisone acetate in health foods.

Electrochemical immunosensor based on gold nanoparticles for the detection of creatine kinase as a cardiac marker

This study presents the development of an electrochemical immunosensor utilizing gold nanoparticles for the detection of creatine kinase (CK), a crucial cardiac marker. Gold nanoparticles with an average diameter of 18.3 ± 2.1 nm were synthesized and characterized, exhibiting a characteristic surface plasmon resonance peak at 520 nm. The construction of the immunosensor was observed through cyclic voltammetry and electrochemical impedance spectroscopy, showing notable alterations in electron transfer rates during each step of the assembly process. Optimal performance was achieved at pH 7.4, with an antibody concentration of 100 μg/mL and an incubation time of 45 minutes. The sensor demonstrated a sensitivity of 152.6 Ω/(ng/mL) and maintained its response in the presence of common interfering substances, with maximum signal deviation of 7.2 %. Testing with spiked human serum samples yielded recovery rates between 96.5 % and 103.8 %. Comparison with ELISA using clinical samples further validated the sensor's accuracy. This AuNP-based immunosensor offers a promising platform for rapid and sensitive CK detection in cardiac health assessment.

RAA-CRISPR/Cas12a-Mediated Rapid, Sensitive, and Onsite Detection of Newcastle Disease in Pigeons

RAA-CRISPR/Cas12a-Mediated Rapid, Sensitive, and Onsite Detection of Newcastle Disease in Pigeons

Construction of dual-signal output sensing platform for different scene of rapid and sensitive ochratoxin A detection in corn

Photoelectrochemical (PEC) is a highly sensitive and fast analytical method that can be used at low concentrations, while photoelectrochromic is a simple and low-cost method primarily utilized for high concentration detection. Therefore, we have developed a dual-signal output sensing platform based on both PEC and photoelectrochromism for rapid and sensitive OTA detection. The sensing platform is divided into signal generation (SG) region and signal output (SO) region, which modified with WO3/BiVO4 photoactive nanocomposites and polyaniline (PANI), respectively. By irradiating the SG region, photogenerated electrons are generated and injected into the SO region through the conductive pathway, resulting in a decrease in surface blue polyaniline and a change to green. The smart device can accurately measure the RGB-Green values, enabling the construction of a photochromic visual sensing platform. After immobilizing the OTA aptamer in the SG region, a linear correlation was observed between the concentration of OTA and the RGB-Green value within the range of 20 ng/L ∼250 μg/L. The detection limit was determined to be 8.33 ng/L (S/N = 3). Furthermore, for a more sensitive OTA detection, a PEC sensing platform was developed utilizing the SG region as a photoanode, exhibiting a linear correlation in the range of 2 pg/L∼300 μg/L with a detection limit of 0.8 pg/L (S/N = 3). The detection of these two modes under the requirement of the international standard for the maximum limit realizes the sensitive OTA detection. The RGB-Green is verified to PEC signal, which improves the detection accuracy. The sensing platform has several advantages and is suitable for various application scenarios.

Advancements in Rapid Detection Technologies for Club Drugs in Beverages

Advancements in Rapid Detection Technologies for Club Drugs in Beverages

Research on Rapid Detection of Underwater Targets Based on Global Differential Model Compression

Research on Rapid Detection of Underwater Targets Based on Global Differential Model Compression

Comparative analysis of the results of live anthrax vaccine identification by immunofluorescence and immunochromatography

INTRODUCTION. The quality evaluation of live anthrax vaccines will benefit from the implementation of alternative testing methods that are capable of specific identification of the Bacillus anthracis spore antigen using the appropriate diagnostic products that are authorised in the Russian Federation for the detection of B. anthracis spores.AIM. This study aimed to investigate the applicability of immunofluorescence analysis to the identification of live anthrax vaccines and compare this method with immunochromatography.MATERIALS AND METHODS. The study used commercial batches of a live anthrax vaccine and Russian diagnostic products, including diagnostic dry adsorbed fluorescent anti-anthrax spore immunoglobulins and an immunochromatographic assay (ICA) reagent kit for rapid detection and identification of B. anthracis spores (ICA system for B. anthracis). For smears and ICA system reactions, the authors prepared working solutions of bacterial suspensions at spore concentrations typical of the B. anthracis STI-1 vaccine strain. The spore concentrations were achieved using the pharmacopoeial reference standard (RS) for the opacity of bacterial suspensions of 10 international units (IU). Identification reactions involved the registration of immune complex formation.RESULTS. Immunofluorescence tests of the live anthrax vaccine demonstrated bright greenish-yellow envelope fluorescence with an intensity score of 3+ to 4+ for smears stained with diagnostic immunoglobulins at 1:32 and 1:64 dilutions. Immunochromatographic tests of the live anthrax vaccine detected the spore antigen at vaccine concentrations of 109 and 108 spores/mL, with the test strips showing two distinct dark-pink lines indicative of immunoprecipitation. According to the results obtained using the selected methods, the tested microbial culture was confirmed as B. anthracis.CONCLUSIONS. Immunochromatography and immunofluorescence tests with appropriate diagnostic preparations are convenient and reliable tools for the species-specific detection of B. anthracis STI-1 spores in the live anthrax vaccine. The results obtained in the anthrax vaccine identification tests provide a basis for recommending the above methods as supplementary alternatives to Ziehl–Neelsen bacteriological staining, which is currently prescribed by the State Pharmacopoeia of the Russian Federation.

Development of a mobile application for rapid detection of meat freshness using deep learning

The freshness or spoilage of meat is critical in terms of meat color and quality criteria. Detecting the condition of the meat is important not only for consumers but also for the processing of the meat itself. Meat quality is influenced by various pre-slaughter factors including housing conditions, diet, age, genetic background, environmental temperature, and stress factors. Additionally, spoilage can occur due to the slaughtering process, though post-slaughter spoilage is more frequent and has a stronger correlation with postslaughter factors. The primary indicator of meat quality is the pH value, which can be high or low. Variations in pH values can lead to adverse effects in the final product such as color defects, microbial issues, short shelf life, reduced quality, and consumer complaints. Many of these characteristics are visible components of quality. This study aimed to develop a mobile application using deep learning-based image processing techniques for the rapid detection of freshness. The attributes of the source and the targeted predictions were found satisfactory, indicating that further advancements could be made in developing future versions of the application.

Truncated M13 phage for smart detection of E. coli under dark field

BackgroundThe urgent need for affordable and rapid detection methodologies for foodborne pathogens, particularly Escherichia coli (E. coli), highlights the importance of developing efficient and widely accessible diagnostic systems. Dark field microscopy, although effective, requires specific isolation of the target bacteria which can be hindered by the high cost of producing specialized antibodies. Alternatively, M13 bacteriophage, which naturally targets E. coli, offers a cost-efficient option with well-established techniques for its display and modification. Nevertheless, its filamentous structure with a large length-diameter ratio contributes to nonspecific binding and low separation efficiency, posing significant challenges. Consequently, refining M13 phage methodologies and their integration with advanced microscopy techniques stands as a critical pathway to improve detection specificity and efficiency in food safety diagnostics.MethodsWe employed a dual-plasmid strategy to generate a truncated M13 phage (tM13). This engineered tM13 incorporates two key genetic modifications: a partial mutation at the N-terminus of pIII and biotinylation at the hydrophobic end of pVIII. These alterations enable efficient attachment of tM13 to diverse E. coli strains, facilitating rapid magnetic separation. For detection, we additionally implemented a convolutional neural network (CNN)-based algorithm for precise identification and quantification of bacterial cells using dark field microscopy.ResultsThe results obtained from spike-in and clinical sample analyses demonstrated the accuracy, high sensitivity (with a detection limit of 10 CFU/μL), and time-saving nature (30 min) of our tM13-based immunomagnetic enrichment approach combined with AI-enabled analytics, thereby supporting its potential to facilitate the identification of diverse E. coli strains in complex samples.ConclusionThe study established a rapid and accurate detection strategy for E. coli utilizing truncated M13 phages as capture probes, along with a dark field microscopy detection platform that integrates an image processing model and convolutional neural network.Graphical

Bridge modal identification method based on adaptive VMD-HT algorithm

ABSTRACT Bridge engineering structures play a crucial role in transportation. Traditional methods of road and bridge closures for inspection and evaluation, while effective, increase bridge inspection costs and disrupt normal traffic flow. Therefore, a rapid detection and evaluation method for bridge structural modal parameters in the operational state is more suitable for practical engineering applications. However, under real operating conditions, bridge vibration signals typically contain a large amount of noise and interference, and modal identification must overcome issues of non-stationarity and non-linearity in the vibration signals caused by vehicle loads and environmental changes to ensure the accuracy of the identification. This study replaces the traditional Empirical Mode Decomposition algorithm in the Hilbert-Huang Transform with the Variational Mode Decomposition algorithm. It proposes a new method that combines the VMD algorithm with the Hilbert Transform, referred to as the Variational Mode Decomposition-Hilbert Transform method. Compared to the EMD algorithm, it offers significant improvements in suppressing mode mixing and endpoint effects. A vehicle-bridge coupling model was constructed, and the bridge’s natural modal information was successfully extracted from the vibration response signals. The research results indicate that the improved algorithm offers higher accuracy and faster computational speed compared to traditional identification algorithms.

Fast, sensitive, and sustainable colorimetric detection of chlorogenic acid in artichoke waste material

Caffeoylquinic acids (CQAs) are nutraceutical polyphenols highly represented in natural sources, including artichoke waste (AW). In this study a colorimetric method for rapid and sustainable detection of a 5-CQA isomer (Chlorogenic acid) in AW extract was developed by using alkaline Tris buffer (10 mmol L−1, pH 9) to generate a yellow color associated with 5- to 3-CQA isomerization reaction, as suggested by NMR and MS analyses. The strong absorbance at 360 nm was followed by standard UV–Vis methodology. The colorimetric assay was exploited for detection of 5-CQA into leaf extract from artichoke, obtaining a value of 15.2 ± 0.3 μg/mg of dry extract, in agreement with HPLC analysis (14.3 ± 0.7 μg/mg, 106 ± 2 % recovery) used as validation technique, with excellent linear correlation and precision (R2 = 0.9996, avRSD% = 3.2 %). The method is fast and selective, offering a valuable tool for nutraceuticals identification and food waste valorization.