A novel AIE-based mitochondria-targeting fluorescent probe for monitoring of the fluctuation of endogenous hypochlorous acid in ferroptosis models.

Ferroptosis is a way of cell death mainly due to the imbalance between the production and degradation of lipid reactive oxygen species, which is closely associated with various diseases. Endogenous hypochlorous acid (HOCl) mainly produced in mitochondria is regarded as an important signal molecule of ferroptosis. Therefore, monitoring the fluctuation of endogenous HOCl is beneficial to better understand and treat ferroptosis-related diseases. Inspired by the promising aggregation-induced emission (AIE) properties of tetraphenylethene (TPE), herein, we rationally constructed a novel AIE-based fluorescent probe, namely QTrPEP, for HOCl with nice mitochondria-targeting ability and high sensitivity and selectivity. Probe QTrPEP consisted of phenylborate ester and the AIE fluorophore of quinoline-conjugated triphenylethylene (QTrPE). HOCl can brighten the strong fluorescence through a specific HOCl-triggered cleavage of the phenylborate ester bond and release of QTrPE, which has been demonstrated by MS, HPLC, and DLS experiments. In addition, combining QTrPE-doped test strips with a smartphone-based measurement demonstrated the excellent performance of the probe to sense HOCl. The obtained favorable optical properties and negligible cytotoxicity allowed the use of this probe for tracking of HOCl in three different cells. In particular, this work represents the first AIE-based mitochondria-targeting fluorescent probe for monitoring the fluctuation of HOCl in ferroptosis.

Wearable, Biocompatible, and Dual-Emission Ocular Multisensor Patch for Continuous Profiling of Fluoroquinolone Antibiotics in Tears.

The abuse or misuse of antibiotics in clinical and agricultural settings severely endangers human health and ecosystems, which has raised profound concerns for public health worldwide. Trace detection and reliable discrimination of commonly used fluoroquinolone (FQ) antibiotics and their analogues have consequently become urgent to guide the rational use of antibiotic medicines and deliver efficient treatments for associated diseases. Herein, we report a wearable eye patch integrated with a quadruplex nanosensor chip for noninvasive detection and discrimination of primary FQ antibiotics in tears during routine eyedrop treatment. A set of dual-mode fluorescent nanoprobes of red- or green-emitting CdTe quantum dots integrated with lanthanide ions and a sensitizer, adenosine monophosphate, were constructed to provide an enhanced fluorescence up to 45-fold and nanomolar sensitivity toward major FQs owing to the aggregation-regulated antenna effect. The aggregation-driven, CdTe-Ln(III)-based microfluidic sensor chip is highly specific to FQ antibiotics against other non-FQ counterparts or biomolecular interfering species and is able to accurately discriminate nine types of FQ or non-FQ eyedrop suspensions using linear discriminant analysis. The prototyped wearable sensing detector has proven to be biocompatible and nontoxic to human tissues, which integrates the entire optical imaging modules into a miniaturized, smartphone-based platform for field use and reduces the overall assay time to ∼5 min. The practicability of the wearable eye patch was demonstrated through accurate quantification of antibiotics in a bactericidal event and the continuous profiling of FQ residues in tears after using a typical prescription antibiotic eyedrop. This technology provides a useful supplement to the toolbox for on-site and real-time examination and regulation of inappropriate daily drug use that might potentially lead to long-term antibiotic abuse and has great implications in advancing personal healthcare techniques for the regulation of daily medication therapy.

Three in one: coordination-induced emission for inherent fluorescent Al-MOF synthesis combined with inner filter effect@aggregation-induced emission mechanisms for designing color tonality and ratiometric sensing platforms.

Three phenomena, namely coordination-induced emission (CIE), aggregation-induced emission (AIE), and inner filter effect (IFE), were incorporated into the design of a ratiometric and color tonality-based biosensor. Blue fluorescent Al-based metal-organic frameworks (FMIL-96) were prepared from non-emissive ligand and aluminum ions via CIE. Interestingly, the addition of tetracycline (TC) led to ratiometric detection and color tonality, as the blue emission at 380 nm was quenched (when excited at 350 nm) due to IFE, while the green-yellowish emission at 525 nm was enhanced due to AIE. Based on that, an ultra-sensitive visual-based color tonality mode with smartphone assistance was developed for detection of TC. The sensor exhibited a linear relationship within a broad range of 2.0 to 85.0 µM TC with a detection limit of 68.0 nM. TC in milk samples was quantified with high accuracy and precision. This integration of smartphone and visual fluorescence in solution is accurate, reliable, cost-effective, and time-saving, providing an alternative strategy for the semi-quantitative determination of TC on-site.

Highly Sensitive and Selective Fluorescence and Smartphone-Based Sensor for Detection of Rutin Using Boron Nitrogen Co-doped Graphene Quantum Dots.

This research explores the fluorescence properties and photostability of boron nitrogen co-doped graphene quantum dots (BN-GQDs), evaluating their effectiveness as sensors for rutin (RU). BN-GQDs are biocompatible and exhibit notable absorbance and fluorescence characteristics, making them suitable for sensing applications. The study utilized various analytical techniques to investigate the chemical composition, structure, morphology, optical attributes, elemental composition, and particle size of BN-GQDs. Techniques included X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and atomic force microscopy (AFM). The average particle size of the BN-GQDs was determined to be approximately 3.5 ± 0.3 nm. A clear correlation between the emission intensity ratio and RU concentration was identified across the range of 0.42 to 4.1 µM, featuring an impressively low detection limit (LOD) of 1.23 nM. The application of BN-GQDs as fluorescent probes has facilitated the development of a highly sensitive and selective RU detection method based on Förster resonance energy transfer (FRET) principles. This technique leverages emission at 465 nm. Density Functional Theory (DFT) analyses confirm that FRET is the primary mechanism behind fluorescence quenching, as indicated by the energy levels of the lowest unoccupied molecular orbitals (LUMOs) of BN-GQDs and RU. The method's effectiveness has been validated by measuring RU concentrations in human serum samples, showing a recovery range between 97.8% and 103.31%. Additionally, a smartphone-based detection method utilizing BN-GQDs has been successfully implemented, achieving a detection limit (LOD) of 49 nM.

Neural Network Enables High Accuracy for Hepatitis B Surface Antigen Detection with a Plasmonic Platform.

The detection of hepatitis B surface antigen (HBsAg) is critical in diagnosing hepatitis B virus (HBV) infection. However, existing clinical detection technologies inevitably cause certain inaccuracies, leading to delayed or unwarranted treatment. Here, we introduce a label-free plasmonic biosensing method based on the thickness-sensitive plasmonic coupling, combined with supervised deep learning (DL) using neural networks. The strategy of utilizing neural networks to process output data can reduce the limit of detection (LOD) of the sensor and significantly improve the accuracy (from 93.1%-97.4% to 99%-99.6%). Compared with widely used emerging clinical technologies, our platform achieves accurate decisions with higher sensitivity in a short assay time (∼30 min). The integration of DL models considerably simplifies the readout procedure, resulting in a substantial decrease in processing time. Our findings offer a promising avenue for developing high-precision molecular detection tools for point-of-care (POC) applications.

Luminol-Eu3+-Gd3+-functionalized mesoporous silica for ultrasensitive detection of tetracycline antibiotics and smartphone-assisted sensing analysis.

An organic-inorganic hybrid nanoprobe, namely LML-D-SBA@Eu3+-Gd3+, was constructed, with SBA-15 acting as the carrier material, and luminol and Eu3+ acting as fluorescence channels to achieve ratiometric signals that eliminate external interference (accurate detection). Gd3+ was used as a sensitizer to amplify the red emission of Eu3+ (ultrasensitive detection). In TCs detection, the luminol emission at 428 nm was quenched due to the photoinduced electron transfer mechanism, and the Eu3+ emission at 617 nm was sensitized due to the synergistic energy transfer from TCs and Gd3+ to Eu3+. The fluorescence intensity at 617 and 428 nm showed ratiometric changes as indicated by notable color changes from blue to red. The detection limits for TC and OTC were 0.21 and 0.08 ng/mL, respectively. To realize a facile, rapid, and cost-effective detection, we constructed a portable intelligent sensing platform based on smartphones, and it demonstrated great potential for on-site detection of TCs.

Integration of Myrica rubra-based N-doped carbon dots with Fe3S4 as excellent peroxidase mimics for colorimetric assay and smartphone-based intelligent sensing of p-aminophenol in waters.

To realize the reutilization of waste Myrica rubra in the analytical field, we synthesized Myrica rubra-based N-doped carbon dots (MN-CDs) and further anchored them onto the surface of Fe3S4 to fabricate Fe3S4@MN-CD nanocomposites. The as-fabricated nanocomposites possessed higher peroxidase-mimetic activity than its two precursors, resulting from the synergistic effect between them, and could catalyze colorless 3,3',5,5'-tetramethylbenzidine (TMB) into deep blue oxTMB with a strong 652-nm absorption. Under optimized conditions (initial solution pH, 3.5; incubation temperature, 35 ℃; Fe3S4@MN-CD concentration, 50 µg mL-1, and 652-nm absorption), Fe3S4@MN-CDs were employed for colorimetric assay of p-aminophenol (p-AP) with wide linear range (LR, 2.9-100 µM), low detection limit (LOD, 0.87 µM), and satisfactory recoveries (86.3-105%) in environmental waters. Encouragingly, this colorimetric assay provided the relative accuracy of 97.0-99.4% as compared with  conventional HPLC-UV detection. A portable smartphone-based colorimetric application was developed by combining the Fe3S4@MN-CD-based visually chromogenic reaction with a "Thing Identify" APP software. Besides, we engineered an image-capturing device feasible for field use, in which the internal-compact sealing prevented external light source from entering photography chamber, thereby reducing light interference, and also the bottom light source enhanced the intensity of blue imaging. This colorimetric platform exhibited satisfactory LR (1-500 µM), low LOD (0.3 µM), and fortification recoveries (86.6-99.6%). In the chromogenic reaction catalyzed by Fe3S4@MN-CDs, ·O2- played a key role in concomitant with the participation of •OH and h+. Both the colorimetric assay and smartphone-based intelligent sensing show great promising in on-site monitoring of p-AP under field conditions.

Evidence for Bidirectional, Cross-Lagged Associations Between Alliance and Psychological Distress in an Unguided Mobile-Health Intervention.

Bidirectional associations between changes in symptoms and alliance are established for in-person psychotherapy. Alliance may play an important role in promoting engagement and effectiveness within unguided mobile health (mHealth) interventions. Using models disaggregating alliance and psychological distress into within- and between-person components (random intercept cross-lagged panel model), we report bidirectional associations between alliance and distress over the course of a 4-week smartphone-based meditation intervention (n=302, 80.0% elevated depression/anxiety). Associations were stable across time with effect sizes similar to those observed for psychotherapy (ßs=-.13 to -.14 and -.09 to -.10, for distress to alliance and alliance to distress, respectively). Alliance may be worth measuring to improve the acceptability and effectiveness of mHealth tools. Further empirical and theoretical work characterizing the role and meaning of alliance in unguided mHealth is warranted.

Investigating the efficacy of digital cognitive behavioural therapy in comparison to a sleep-monitoring application via integrated diary and actigraphy: A randomised-controlled trial.

Dissemination of digital cognitive behavioural therapy is a promising approach for treating insomnia in the broad population. Current evidence supports the effectiveness of the digital format, but clinical findings are often limited by the choice of control group and lack of in-depth therapeutic measures. This study was designed to investigate the specific effects of digital cognitive behavioural therapy in comparison to a self-monitoring application. Participants meeting criteria for insomnia were randomly allocated (1:1) to 8 weeks of digital cognitive behavioural therapy or 8 weeks of digital sleep monitoring (control application). The primary outcome, insomnia severity, was assessed at baseline, 8- and 16-weeks post-randomisation. Secondary outcomes included the assessment of sleep via application-integrated sleep diaries and actigraphy. Linear-mixed models were fitted to assess between-group differences. Fifty-six participants (48 females, mean age: M = 45.55 ± 13.70 years) were randomised to either digital cognitive behavioural therapy (n = 29) or digital sleep monitoring (n = 27). At 8- and 16-weeks post-randomisation, large treatment effects (d = 0.87-1.08) indicated robust reductions (-3.70 and -2.97, respectively; p ≤ 0.003) in insomnia severity in the digital cognitive behavioural therapy arm, relative to digital sleep monitoring. Treatment effects in favour of digital cognitive behavioural therapy were also found for self-reported and actigraphy-derived sleep continuity variables, indicating that sleep improved throughout the 8-week intervention period. Our study reinforces the role of digital cognitive behavioural therapy in achieving clinical improvements for patients with insomnia, affirming previous findings and supporting the specific effects of cognitive behavioural therapy.

Urine multi-index intelligent detection based on polymer/paper hybrid microfluidic biochip for hyperuricemia monitoring.

Hyperuricemia (HUA) has gradually become a public health burden as an independent risk factor for a variety of chronic diseases. Herein, a user-friendly point-of-care (POC) detection system (namely "Smart-HUA-Monitor") based on smartphone-assisted paper-based microfluidic is proposed for colorimetric quantification of HUA urinary markers, including uric acid (UA), creatinine (CR) and pH. The detection limits of UA and CR were 0.0178 and 0.5983 mM, respectively, and the sensitivity of pH were 0.1. The method was successfully validated in artificial urine samples and 100 clinical samples. Bland-Altman plots showed a high consistency between µPAD and the testing instruments (HITACHI 7600 Automatic Analyzer, URIT-500B Urine Analyzer and AU5800B automatic biochemical analyzer) in hospital. Smart-HUA-Monitor provides an accurate quantitative, rapid, low-cost and reliable tool for the monitoring and early diagnosis of HUA urine indicators.

Central composite design-assisted visual and non-invasive detection of sertraline by sweet lemon waste-derived core-shell AuNPs@CDs.

This study reports a fast and visual detection method of antidepressant sertraline (SRT) drug by the core-shell AuNPs@CDs as the nanoprobes. The CDs has been eco-friendly synthesized from sweet lemon wastes to directly reduce Au+ to AuNPs without any external photoirradiation process or additional reductants. Optimizing key variables that impact the sensing process has been done using the central composite design (CCD) approach to simulate the assay condition before the analysis. Adding SRT with different concentrations to the nanoprobes under mildly acidic conditions presents an absorbance peak at 560 nm with purple color tonalities that differ from the behavior of alone nanoprobes (530 nm, pink color). The obtained absorption change is linearly proportional to the increase of SRT concentration from 1 µM to 35 µM with a limit of detection (LOD) value of 100 nM. The color changes with a vivid tonality from pink and purple to violet as the colorful fingerprint patterns are readily traceable by the naked eye, allowing the visual assay of SRT. The greenness of the developed approach is well evaluated by some international indexes including the complimentary green analytical procedure (ComplexGAPI) and also, the analytical greenness (AGREE) indexes. The proposed waste-derived nanoprobes based on the eco-friendly procedure not only conduct quantitative and qualitative non-invasive analysis of SRT by the naked eye but also, may widen for other applications in various fields.

Remote and unsupervised digital memory assessments can reliably detect cognitive impairment in Alzheimer's disease.

INTRODUCTION: Remote unsupervised cognitive assessments have the potential to complement and facilitate cognitive assessment in clinical and research settings. METHODS: Here, we evaluate the usability, validity, and reliability of unsupervised remote memory assessments via mobile devices in individuals without dementia from the Swedish BioFINDER-2 study and explore their prognostic utility regarding future cognitive decline. RESULTS: Usability was rated positively; remote memory assessments showed good construct validity with traditional neuropsychological assessments and were significantly associated with tau-positron emission tomography and downstream magnetic resonance imaging measures. Memory performance at baseline was associated with future cognitive decline and prediction of future cognitive decline was further improved by combining remote digital memory assessments with plasma p-tau217. Finally, retest reliability was moderate for a single assessment and good for an aggregate of two sessions. DISCUSSION: Our results demonstrate that unsupervised digital memory assessments might be used for diagnosis and prognosis in Alzheimer's disease, potentially in combination with plasma biomarkers. HIGHLIGHTS: Remote and unsupervised digital memory assessments are feasible in older adults and individuals in early stages of Alzheimer's disease. Digital memory assessments are associated with neuropsychological in-clinic assessments, tau-positron emission tomography and magnetic resonance imaging measures. Combination of digital memory assessments with plasma p-tau217 holds promise for prognosis of future cognitive decline. Future validation in further independent, larger, and more diverse cohorts is needed to inform clinical implementation.

Portable electrochemical sensor for adrenaline detection using CoNi-MOF-based CS-PAM hydrogel.

The development of a portable smartphone-based electrochemical sensor for analyzing adrenaline levels in real samples can make a great contribution to the research community worldwide. In order to achieve this goal, the key challenge is to build sensing interfaces with excellent electrocatalytic properties. In this work, microspherical bimetallic metal-organic frameworks (CoNi-MOF) consisting of nanoclusters were first synthesized using a hydrothermal method. On this basis, the catalytic activity of pure chitosan-polyacrylamide hydrogel (CS-PAM) was modulated by adding different amounts of CoNi-MOF during the in-situ synthesis of CS-PAM. Finally, a portable electrochemical detection system based on CS-PAM was established for the detection of adrenaline. A series of resulting composite hydrogels with a large specific surface area, abundant active sites, and unique network structure facilitate the enrichment and catalysis of adrenaline molecules. Under optimal conditions, the analytical platform constructed by using CoNi-MOF-based CS-PAM has the advantages of a wide detection range (0.5-10 and 10-2500 µM), a low detection limit (0.167 µM), and high sensitivity (0.182 and 0.133 µA·µM·cm-2). In addition, the sensor maintains selective detection of the target in the presence of many different types of interferences, and the current response is not significantly reduced even after 60 cycles of testing. We strongly believe that the designed smart portable sensing can realize the accurate determination of adrenaline in complex systems, and this study can provide new ideas for the research of MOFs-based hydrogels in electrochemical analysis.

3D-printed portable device for illicit drug identification based on smartphone-imaging and artificial neural networks.

In this manuscript, a 3D-printed analytical device has been successfully developed to classify illicit drugs using smartphone-based colorimetry. Representative compounds of different families, including cocaine, 3,4-methylenedioxy-methamphetamine (MDMA), amphetamine and cathinone derivatives, pyrrolidine cathinones, and 3,4-methylenedioxy cathinones, have been analyzed and classified after appropriate reaction with Marquis, gallic acid, sulfuric acid, Simon and Scott reagents. A picture of the colored products was acquired using a smartphone, and the corrected RGB values were used as input data in the chemometric treatment. ANN using two active layers of nodes (6 nodes in layer 1 and 2 nodes in layer 2) with a sigmoidal transfer function and a minimum strict threshold of 0.50 identified illicit drug samples with a sensitivity higher than 83.4 % and a specificity of 100 % with limits of detection in the microgram range. The 3D printed device can operate connected to a rechargeable lithium-ion cell portable battery, is inexpensive, and requires minimal training. The analytical device has been able to discriminate the analyzed psychoactive substances from cutting and mixing agents, being a useful tool for law enforcement agents to use as a screening method.

A Step Forward Understanding Directional Limitations in Markerless Smartphone-Based Gait Analysis: A Pilot Study.

The progress in markerless technologies is providing clinicians with tools to shorten the time of assessment rapidly, but raises questions about the potential trade-off in accuracy compared to traditional marker-based systems. This study evaluated the OpenCap system against a traditional marker-based system-Vicon. Our focus was on its performance in capturing walking both toward and away from two iPhone cameras in the same setting, which allowed capturing the Timed Up and Go (TUG) test. The performance of the OpenCap system was compared to that of a standard marker-based system by comparing spatial-temporal and kinematic parameters in 10 participants. The study focused on identifying potential discrepancies in accuracy and comparing results using correlation analysis. Case examples further explored our results. The OpenCap system demonstrated good accuracy in spatial-temporal parameters but faced challenges in accurately capturing kinematic parameters, especially in the walking direction facing away from the cameras. Notably, the two walking directions observed significant differences in pelvic obliquity, hip abduction, and ankle flexion. Our findings suggest areas for improvement in markerless technologies, highlighting their potential in clinical settings.

Development of a sustainable procedure for smartphone-based colorimetric determination of benzalkonium chloride in pharmaceutical preparations.

A sustainable procedure offering green, simple, and rapid analysis was developed to determine benzalkonium chloride (BKC) in pharmaceutical preparations. The determination using smartphones was based on the ion pair colorimetric reaction with bromothymol blue (BTB), which produces a yellow color. The intensity of the product color, which is proportional to the concentration of BKC, was detected and evaluated using a smartphone camera and an image processing application. The procedure was performed in a microliter and was rapidly detected within 1 min after incubation. This offered high throughput at 28 samples per well plate in duplicate. Linear calibration, which was a plot of BKC concentrations and relative red intensities, was in the range of 2.0-24.0 µg/mL with an R2 of 0.997. The limits of detection (LOD) and quantitation (LOQ) were 1.0 and 3.2 µg/mL, respectively. This work was successful in applying it to pharmaceutical materials, disinfectant products, and pharmaceutical products containing BKC. It was discovered that the concentrations of BKC as an active ingredient in pharmaceutical materials were 82% w/v, whereas those in disinfectant products ranged from 0.4 to 2.1% w/v. In pharmaceutical products, ophthalmic drops and nasal sprays contain BKC as preservatives in the 0.01-0.02, and the 0.02% w/v, respectively. The results obtained by the proposed procedure compared with a reference titration method showed no significant differences at a 95% confidence level with 1.2-3.4% RSDs. This promotes the efficiency of pharmaceutical preparations regarding infection prevention and control by ensuring that available disinfectants contain a sufficient concentration of BKC. Additionally, this improves the efficiency of pharmaceutical preparations for quality control of pharmaceutical products by ensuring that the available preservatives maintain a sufficient concentration throughout the lifespan of the products.

Disposable graphene-oxide screen-printed electrode integrated with portable device for detection of SARS-CoV-2 in clinical samples.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis is the need of the hour, as cases are persistently increasing, and new variants are constantly emerging. The ever-changing nature of the virus leading to multiple variants, has brought an imminent need for early, accurate and rapid detection methods. Herein, we have reported the design and fabrication of Screen-Printed Electrodes (SPEs) with graphene oxide (GO) as working electrode and modified with specific antibodies for SARS-CoV-2 Receptor Binding Domain (RBD). Flexibility of design, and portable nature has made SPEs the superior choice for electrochemical analysis. The developed immunosensor can detect RBD as low as 0.83 fM with long-term storage capacity. The fabricated SPEs immunosensor was tested using a miniaturized portable device and potentiostat on 100 patient nasopharyngeal samples and corroborated with RT-PCR data, displayed 94 % sensitivity. Additionally, the in-house developed polyclonal antibodies detected RBD antigen of the mutated Omicron variant of SARS-CoV-2 successfully. We have not observed any cross-reactivity/binding of the fabricated immunosensor with MERS (cross-reactive antigen) and Influenza A H1N1 (antigen sharing common symptoms). Hence, the developed SPEs sensor may be applied for bedside point-of-care diagnosis of SARS-CoV-2 using miniaturized portable device, in clinical samples.

A smartphone-based diagnostic analyzer for point-of-care milk somatic cell counting.

BACKGROUND: Mastitis, a pervasive and detrimental disease in dairy farming, poses a significant challenge to the global dairy industry. Monitoring the milk somatic cell count (SCC) is vital for assessing the incidence of mastitis and the quality of raw cow's milk. However, existing SCC detection methods typically require large-scale instruments and specialized operators, limiting their application in resource-constrained settings such as dairy farms and small-scale labs. To address these limitations, this study introduces a novel, smartphone-based, on-site SCC testing method that leverages smartphone capabilities for milk somatic cell identification and enumeration, offering a portable and user-friendly testing platform. RESULTS: The central findings of our study demonstrate the effectiveness of the proposed method for counting milk somatic cells. Its on-site applicability, facilitated by the microfluidic chip, optical system, and smartphone integration, heralds a paradigm shift in point-of-care testing (POCT) for dairy farms and smaller laboratories. This approach bypasses complex processing and presents a user-friendly solution for real-time SCC monitoring in resource-limited settings. This device boasts several unique features: small size, low cost (<$1,000 total manufacturing cost and <$1 per test), and high accuracy. Remarkably, it delivers test results within just 2 min. Actual-sample testing confirmed its consistency with results from the commercial Bentley FTS/FCM cytometer, affirming the reliability of the proposed method. Overall, these results underscore the potential for transformative change in dairy farm management and laboratory testing practices. SIGNIFICANCE: In summary, this study concludes that the proposed smartphone-based method significantly contributes to the accessibility and ease of SCC testing in resource-limited environments. By fostering the use of POCT technology in food safety control, particularly in the dairy industry, this innovative approach has the potential to revolutionize the monitoring and management of mastitis, ultimately benefiting the global dairy sector.

Innovative detection mechanism for deltamethrin based on a dual-emitting Fluoroprobe and its application in a smartphone-based photoelectric conversion device.

Pyrethroids are widely used insecticides worldwide, while their on-site and rapid detection still faces technological challenges. Herein, an innovative detection mechanism was designed for deltamethrin, a typical kind of type II pyrethroids, based on a dual-emitting fluoroprobe consisting of NH2-SiQDs and Eu3+. Deltamethrin can rapidly hydrolyze into 3-phenoxybenzaldehyde (3-PBD) and react specifically with fluoroprobe, causing fluorescence quenching of SiQDs while maintaining the fluorescent stability of Eu3+. Building upon the above fluorescence-responsive principle, SiQDs@Eu3+ provided satisfactorily dual-emitting signals, realizing the highly-selective and sensitive detection of deltamethrin. Correlation between the surface structure of SiQDs and their absorption spectra was in-depth unraveled by TD-DFT calculation and FT-IR analysis. As for the analytical performance, the recovery and LOD of deltamethrin in lettuce, provided by SiQDs@Eu3+, were comparable or even superior over conventional chromatographic analysis. Meanwhile, an innovative smartphone-based optical device was developed, which greatly decreased errors caused by the previously reported smartphone-based fluorescence detection.

Development of a smartphone-integrated microfluidic paper-based optosensing platform coupled with molecular imprinting technique for in-situ determination of histamine in canned tuna.

We reported the development of a smartphone-integrated microfluidic paper-based optosensing platform for in-situ detection and quantification of histamine in canned tuna. Molecularly imprinted polymers were synthesized via precipitation polymerization and utilized as dispersive solid phase extraction sorbent to selectively extract histamine from canned tuna. Carbon quantum dots functioning as a fluorescent probe were synthesized and introduced onto the microzones of the microfluidic paper device. This facilitated a noticeable fluorescence color change from dark red to vivid blue upon the addition of histamine. The change in fluorescence on the paper device was converted into specific RGB values using a portable UV light box combined with a smartphone. This assay achieved the limit of detection of 14.04 mg/kg with the linear range from 20 to 100 mg/kg of histamine in canned tuna. The entire molecular imprinting-microfluidic optosensing test could be completed in 45 min including sample preparation.