Sustainable and effective reconditioning of SPR gold chips functionalized with molecularly imprinted polynorepinephrine.

Surface Plasmon Resonance (SPR) technology has revolutionized the study of affinity-based biomolecular interactions, offering label-free and real-time analysis capabilities. However, traditional SPR gold chips have been viewed as disposable due to challenges in post-use reconditioning, leading to significant resource wastage and increased costs. To address this issue, we propose a novel approach utilizing polynorepinephrine-based (PNE) Molecularly Imprinted Bio-Polymers (MIBPs) as alternative receptors to conventional antibodies. Self-adhesive MIBPs do not require covalent immobilization. This enables efficient and rapid chip functionalization and post-use removal, facilitating multiple reuses of the plasmon source without compromising analytical performance. We conducted a thorough characterization and data analysis, confirming the robustness and repeatability of a single MIBP-functionalized chip for human IgG detection. 10 cycles of reconditioning and reuse, assayed by 60 kinetic calibrations, were performed. Our findings demonstrate the potential indefinite reuse of SPR chips facilitated by PNE MIBPs, with implications for streamlining test development and routine implementation in SPR biosensing applications. Therefore, they represent a sustainable solution to the longstanding challenge of disposable SPR gold chips also by reducing the reliance on animal-derived Abs for bioanalytic testing. Being also extremely low-cost and green, PNE-based MIBPs minimize the ecological footprint associated with traditional SPR assays. Overall, our work represents a significant advancement towards the development of reusable SPR biosensors. It promises a more sustainable and cost-effective future for biomedical research and diagnostic applications, with application on other transducers and bioanalytical platforms.

The Tunable Parameters of Graphene-Based Biosensors.

Graphene-based surface plasmon resonance (SPR) biosensors have emerged as a promising technology for the highly sensitive and accurate detection of biomolecules. This study presents a comprehensive theoretical analysis of graphene-based SPR biosensors, focusing on configurations with single and bimetallic metallic layers. In this study, we investigated the impact of various metallic substrates, including gold and silver, and the number of graphene layers on key performance metrics: sensitivity of detection, detection accuracy, and quality factor. Our findings reveal that configurations with graphene first supported on gold exhibit superior performance, with sensitivity of detection enhancements up to 30% for ten graphene layers. In contrast, silver-supported configurations, while demonstrating high sensitivity, face challenges in maintaining detection accuracy. Additionally, reducing the thickness of metallic layers by 30% optimizes light coupling and enhances sensor performance. These insights highlight the significant potential of graphene-based SPR biosensors in achieving high sensitivity of detection and reliability, paving the way for their application in diverse biosensing technologies. Our findings pretend to motivate future research focusing on optimizing metallic layer thickness, improving the stability of silver-supported configurations, and experimentally validating the theoretical findings to further advance the development of high-performance SPR biosensors.

Au Nanoshell-Based Lateral Flow Immunoassay for Colorimetric and Photothermal Dual-Mode Detection of Interleukin-6.

Interleukin-6 (IL-6) detection and monitoring are of great significance for evaluating the progression of many diseases and their therapeutic efficacy. Lateral flow immunoassay (LFIA) is one of the most promising point-of-care testing (POCT) methods, yet suffers from low sensitivity and poor quantitative ability, which greatly limits its application in IL-6 detection. Hence, in this work, we integrated Aushell nanoparticles (NPs) as new LFIA reporters and achieved the colorimetric and photothermal dual-mode detection of IL-6. Aushell NPs were conveniently prepared using a galvanic exchange process. By controlling the shell thickness, their localized surface plasmon resonance (LSPR) peak was easily tuned to near-infrared (NIR) range, which matched well with the NIR irradiation light. Thus, the Aushell NPs were endowed with good photothermal effect. Aushell NPs were then modified with IL-6 detection antibody to construct Aushell probes. In the LFIA detection, the Aushell probes were combined with IL-6, which were further captured by the capture IL-6 antibody on the test line of the strip, forming a colored band. By observation with naked eyes, the colorimetric qualitative detection of IL-6 was achieved with limit of 5 ng/mL. By measuring the temperature rise of the test line with a portable infrared thermal camera, the photothermal quantitative detection of IL-6 was performed from 1~1000 ng/mL. The photothermal detection limit reached 0.3 ng/mL, which was reduced by nearly 20 times compared with naked-eye detection. Therefore, this Aushell-based LFIA efficiently improved the sensitivity and quantitative ability of commercial colloidal gold LFIA. Furthermore, this method showed good specificity, and kept the advantages of convenience, speed, cost-effectiveness, and portability. Therefore, this Aushell-based LFIA exhibits practical application potential in IL-6 POCT detection.

Ultrasensitive optical fiber SPR sensor enhanced by Au-NPs-film modified with functionalized CQDs for label-free detecting cobalt (II) ion.

BACKGROUND: Cobalt, an essential trace element, is vital for maintaining human nervous system function, aiding in DNA synthesis, and contributing to red blood cell production. It is helpful for disease diagnosis and treatment plan evaluation by precisely monitoring its concentration changes in the human body. Despite extensive efforts made, due to its ultra-low concentration, the current limit of detection (LOD) as reported is still inadequate and cannot be satisfied with the precise clinical applications. Therefore, it is crucial to develop novel label-free sensors with high sensitivity and excellent selectivity for detecting trace amounts of Co2+. RESULTS: Here, an ultrasensitive optical fiber SPR sensor was designed and fabricated for label-free detection of Co2+ with ultra-low concentration. It is achieved by modifying the carboxyl-functionalized CQDs on the AuNPs/Au film-coated hetero-core fiber, which can specifically capture the Co2+, leading to changes in the fiber's surface refractive index (RI) and subsequent SPR wavelength shifts in the transmission spectrum. Both the Au film and AuNPs on the fiber are modified with CQDs, leveraging their large surface area to enhance the number of active sites and probes. The sensor exhibits an ultra-high sensitivity of approximately 6.67 × 1019 nm/M, and the LOD is obtained as low as 5.36 × 10-20 M which is several orders of magnitude lower compared to other conventional methods. It is also experimentally demonstrated that the sensor possesses excellent specificity, stability, and repeatability, which may be adapted for detecting real clinical samples. SIGNIFICANCE: The CQDs-functionalized optical fiber SPR sensor exhibits substantial potential for precisely detecting Co2+ of trace amounts, which is especially vital for scarce clinical samples. Additionally, the sensing platform with sample sensor fabrication and measurement configuration introduces a novel, highly sensitive approach to biochemical analysis, particularly adapting for applications involving the detection of trace targets, which could also be employed to detect various biochemical targets by facile modification of CQDs with specific groups or biomolecules.

Noninvasive Prenatal Genetic Screening of Cell-Free Fetal DNA for Early Prediction of ß-Thalassemia Using Fiber Optic Nanogold-Linked Sorbent Assay.

ß-Thalassemia is a prevalent type of severe inherited chronic anemia, primarily identified in developing countries. The identification of single nucleotide polymorphisms (SNPs) plays a vital role in the early diagnosis of genetic diseases. Here, we reported the development of an amplification-free fiber optic nanogold-linked sorbent assay method using a fiber optic particle plasmon resonance (FOPPR) biosensor for rapid and ultrasensitive detection of SNPs. Herein, MutS protein was selected as the biorecognition capture probe and immobilized on the sensing region to capture the target mutant DNA, which was hybridized with a single-base mismatched single-stranded DNA labeled by a gold nanoparticle (AuNP). The AuNP acts as a signaling agent to be detected by the FOPPR biosensor when it is bound on the fiber core surface. The method effectively differentiates mismatched double-stranded DNA by MutS protein from perfectly matched/complementary dsDNA. It exhibits an impressively low detection limit for the detection of SNPs at approximately 10-16 M using low-cost sensor chips and devices. By determination of the ratio of mutant DNA to normal DNA in cell-free genomic DNA from blood samples, this method is promising for diagnosing ß-thalassemia in fetuses without invasive testing techniques.

Modulating Weak Protein-Protein Cross-Interactions by the Addition of Free Amino Acids at Millimolar Concentrations.

In this paper, we quantify weak protein-protein interactions in solution using cross-interaction chromatography (CIC) and surface plasmon resonance (SPR) and demonstrate that they can be modulated by the addition of millimolar concentrations of free amino acids. With CIC, we determined the second osmotic virial cross-interaction coefficient (B23) as a proxy for the interaction strength between two different proteins. We perform SPR experiments to establish the binding affinity between the same proteins. With CIC, we show that the amino acids proline, glutamine, and arginine render the protein cross-interactions more repulsive or equivalently less attractive. Specifically, we measured B23 between lysozyme (Lys) and bovine serum albumin (BSA) and between Lys and protein isolates (whey and canola). We find that B23 increases when amino acids are added to the solution even at millimolar concentrations, corresponding to protein/ligand stoichiometric ratios as low as 1:1. With SPR, we show that the binding affinity between proteins can change by 1 order of magnitude when 10 mM glutamine is added. In the case of Lys and one whey protein isolate (WPI), it changes from the mM to the M range, thus by 3 orders of magnitude. Interestingly, this efficient modulation of the protein cross-interactions does not alter the protein's secondary structure. The capacity of amino acids to modulate protein cross-interactions at mM concentrations is remarkable and may have an impact across fields in particular for specific applications in the food or pharmaceutical industries.

Artificial Intelligence-Powered Molecular Docking and Steered Molecular Dynamics for Accurate scFv Selection of Anti-CD30 Chimeric Antigen Receptors.

Chimeric antigen receptor (CAR) T cells represent a revolutionary immunotherapy that allows specific tumor recognition by a unique single-chain fragment variable (scFv) derived from monoclonal antibodies (mAbs). scFv selection is consequently a fundamental step for CAR construction, to ensure accurate and effective CAR signaling toward tumor antigen binding. However, conventional in vitro and in vivo biological approaches to compare different scFv-derived CARs are expensive and labor-intensive. With the aim to predict the finest scFv binding before CAR-T cell engineering, we performed artificial intelligence (AI)-guided molecular docking and steered molecular dynamics analysis of different anti-CD30 mAb clones. Virtual computational scFv screening showed comparable results to surface plasmon resonance (SPR) and functional CAR-T cell in vitro and in vivo assays, respectively, in terms of binding capacity and anti-tumor efficacy. The proposed fast and low-cost in silico analysis has the potential to advance the development of novel CAR constructs, with a substantial impact on reducing time, costs, and the need for laboratory animal use.

In-line fiber optical sensor for detection of IgG aggregates in affinity chromatography.

Therapeutic monoclonal antibodies (mAbs) are critical for treatment of a wide range of diseases. Immunoglobulin G (IgG) is the most predominant form of mAb but is prone to aggregation during production. Detection and removal of IgG aggregates are time-consuming and laborious. Chromatography is central for purification of biopharmaceuticals in general and essential in the production of mAbs. Protein purification systems are usually equipped with detectors for monitoring pH, UV absorbance, and conductivity, to facilitate optimization and control of the purification process. However, specific in-line detection of the target products and contaminating species, such as aggregates, is currently not possible using convectional techniques. Here we show a novel fiber optical in-line sensor, based on localized surface plasmon resonance (LSPR), for specific detection of IgG and IgG aggregates during affinity chromatography. A flow cell with a Protein A sensor chip was connected to the outlet of the affinity column connected to three different chromatography systems operating at lab scale to pilot scale. Samples containing various IgG concentrations and aggregate contents were analyzed in-line during purification on a Protein A column using both pH gradient and isocratic elution. Because of avidity effects, IgG aggregates showed slower dissociation kinetics than monomers after binding to the sensor chips. Possibilities to detect aggregate concentrations below 1 % and difference in aggregate content smaller than 0.3 % between samples were demonstrated. In-line detection of aggregates can circumvent time-consuming off-line analysis and facilitate automation and process intensification.

Early determination of potential critical quality attributes of therapeutic antibodies in developability studies through surface plasmon resonance-based relative binding activity assessment.

Precise measurement of the binding activity changes of therapeutic antibodies is important to determine the potential critical quality attributes (CQAs) in developability assessment at the early stage of antibody development. Here, we report a surface plasmon resonance (SPR)-based relative binding activity method, which incorporates both binding affinity and binding response and allows us to determine relative binding activity of antibodies with high accuracy and precision. We applied the SPR-based relative binding activity method in multiple forced degradation studies of antibody developability assessment. The current developability assessment strategy provided comprehensive, precise characterization of antibody binding activity in the stability studies, enabling us to perform correlation analysis and establish the structure-function relationship between relative binding activity and quality attributes. The impact of a given quality attribute on binding activity could be confidently determined without isolating antibody variants. We identified several potential CQAs, including Asp isomerization, Asn deamidation, and fragmentation. Some potential CQAs affected binding affinity of antibody and resulted in a reduction of binding activity. Certain potential CQAs impaired antibody binding to antigen and led to a loss of binding activity. A few potential CQAs could influence both binding affinity and binding response and cause a substantial decrease in antibody binding activity. Specifically, we identified low abundance Asn33 deamidation in the light chain complementarity-determining region as a potential CQA, in which all the stressed antibody samples showed Asn33 deamidation abundances ranging from 4.2% to 27.5% and a mild binding affinity change from 1.76 nM to 2.16 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.

Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction.

Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predicting the radioresistance that is the main reason for treatment failure. Herein, the molecular profiles of patient plasma from NPC with radiotherapy sensitivity and resistance groups as well as healthy group, respectively, were explored by label-free surface enhanced Raman spectroscopy (SERS) based on surface plasmon resonance for the first time. Especially, the components with different molecular weight sizes were analyzed via the separation process, helping to avoid the possible missing of diagnostic information due to the competitive adsorption. Following that, robust machine learning algorithm based on principal component analysis and linear discriminant analysis (PCA-LDA) was employed to extract the feature of blood-SERS data and establish an effective predictive model with the accuracy of 96.7% for identifying the radiotherapy resistance subjects from sensitivity ones, and 100% for identifying the NPC subjects from healthy ones. This work demonstrates the potential of molecular separation-assisted label-free SERS combined with machine learning for NPC screening and treatment strategy guidance in clinical scenario.

Application and Method of Surface Plasmon Resonance Technology in the Preparation and Characterization of Biomedical Nanoparticle Materials.

Surface Plasmon Resonance (SPR) technology, as a powerful analytical tool, plays a crucial role in the preparation, performance evaluation, and biomedical applications of nanoparticles due to its real-time, label-free, and highly sensitive detection capabilities. In the nanoparticle preparation process, SPR technology can monitor synthesis reactions and surface modifications in real-time, optimizing preparation techniques and conditions. SPR enables precise measurement of interactions between nanoparticles and biomolecules, including binding affinities and kinetic parameters, thereby assessing nanoparticle performance. In biomedical applications, SPR technology is extensively used in the study of drug delivery systems, biomarker detection for disease diagnosis, and nanoparticle-biomolecule interactions. This paper reviews the latest advancements in SPR technology for nanoparticle preparation, performance evaluation, and biomedical applications, discussing its advantages and challenges in biomedical applications, and forecasting future development directions.

Quantitative Hydrogen-Deuterium Exchange Mass Spectrometry for Simultaneous Structural Characterization and Affinity Indexing of Single Target Drug Candidate Libraries.

Hydrogen-deuterium eXchange mass spectrometry (HDX-MS) is increasingly used in drug development to locate binding sites and to identify allosteric effects in drug/target interactions. However, the potential of this technique to quantitatively analyze drug candidate libraries remains largely unexplored. Here, a collection of 13 WDR5-targeting small molecules with surface plasmon resonance (SPR) dissociation coefficients (KD) ranging from 20 nM to ∼116 µM were characterized using differential HDX-MS (ΔHDX-MS). Conventional qualitative analysis of the ΔHDX-MS data set revealed the binding interfaces for all compounds and allosteric effects where present. We then demonstrated that ΔHDX-MS signal-to-noise (S/N) not only can rank library-relative affinity but also can accurately predict KD from a calibration curve constructed from high-quality SPR data. Three methods for S/N calculation are explored, each suitable for libraries with different characteristics. Our results demonstrate the potential for ΔHDX-MS use in drug candidate library affinity validation and/or determination while simultaneously characterizing structure.

Role of Graphene in Surface Plasmon Resonance-Based Biosensors.

This work explores the transformative role of graphene in enhancing the performance of surface plasmon resonance (SPR)-based biosensors. The motivation for this review stems from the growing interest in the unique properties of graphene, such as high surface area, excellent electrical conductivity, and versatile functionalization capabilities, which offer significant potential to improve the sensitivity, specificity, and stability of SPR biosensors. This review systematically analyzes studies published between 2010 and 2023, covering key metrics of biosensor performance. The findings reveal that the integration of graphene consistently enhances sensitivity. Specificity, although less frequently reported numerically, showed promising results, with high specificity achieved at sub-nanomolar concentrations. Stability enhancements are also significant, attributed to the protective properties of graphene and improved biomolecule adsorption. Future research should focus on mechanistic insights, optimization of integration techniques, practical application testing, scalable fabrication methods, and comprehensive comparative studies. Our findings provide a foundation for future research, aiming to further optimize and harness the unique physical properties of graphene to meet the demands of sensitive, specific, stable, and rapid biosensing in various practical applications.

Biparatopic anti-PCSK9 antibody enhances the LDL-uptake in HepG2 cells.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) has emerged as a promising therapeutic target to reduce lipids. In 2020, we reported a chimeric camelid-human heavy chain antibody VHH-B11-Fc targeting PCSK9. Recently, it was verified that VHH-B11 binds one linear epitope in the PCSK9 hinge region. To enhance its druggability, we have developed a novel biparatopic B11-H2-Fc Ab herein. Thereinto, surface plasmon resonance (SPR) confirmed the epitope differences in binding-PCSK9 among VHH-B11, VHH-H2 and the approved Repatha. Additionally, SPR revealed the B11-H2-Fc exhibits an avidity of approximately 0.036 nM for PCSK9, representing a considerable increase compared to VHH-B11-Fc (~ 0.69 nM). Moreover, we found the Repatha and B11-H2-Fc exhibited > 95% PCSK9 inhibition efficiency compared to approximately 48% for the VHH-Fc at 7.4 nM (P < 0.0005). Further, we verified its biological activity using the human hepatoma cells G2 model, where the B11-H2-Fc exhibited almost 100% efficiency in PCSK9 inhibition at only 0.75 µM. The immunoblotting results of low-density lipoprotein cholesterol (LDL-c) uptake assay also demonstrated the excellent performance of B11-H2-Fc on recovering the LDL-c receptor (LDLR), as strong as the Repatha (P > 0.05). These findings provide the first evidence of the efficacy of a novel Ab targeting PCSK9 in the field of lipid-lowering drugs.

Bowtie Nanoantenna LSPR Biosensor for Early Prediction of Preeclampsia.

OBJECTIVE: The concentration of the placental circulating factor in early pregnancy is often extremely low, and the traditional prediction method cannot meet the clinical demand for early detection preeclampsia in high-risk gravida. It is of prime importance to seek an ultra-sensitive early prediction method. METHODS: In this study, finite-different time-domain (FDTD) and Discrete Dipole Approximation (DDA) simulation, and electron beam lithography (EBL) methods were used to develop a bowtie nanoantenna (BNA) with the best field enhancement and maximum coupling efficiency. Bio-modification of the placental circulating factor (sFlt-1, PLGF) to the noble nanoparticles based on the amino coupling method were explored. A BNA LSPR biosensor which can specifically identify the placental circulating factor in preeclampsia was constructed. RESULTS: The BNA LSPR biosensor can detect serum placental circulating factors without toxic labeling. Serum sFlt-1 extinction signal (Δλmax) in the preeclampsia group was higher than that in the normal pregnancy group (14.37 ± 2.56 nm vs. 4.21 ± 1.36 nm), p = 0.008, while the serum PLGF extinction signal in the preeclampsia group was lower than that in the normal pregnancy group (5.36 ± 3.15 nm vs. 11.47 ± 4.92 nm), p = 0.013. The LSPR biosensor detection results were linearly consistent with the ELISA kit. CONCLUSIONS: LSPR biosensor based on BNA can identify the serum placental circulating factor of preeclampsia with high sensitivity, without toxic labeling and with simple operation, and it is expected to be an early detection method for preeclampsia.

Terahertz Fingerprint Metasurface Sensor Based on Temperature Variation for Trace Molecules.

Terahertz (THz) spectroscopy has demonstrated significant potential for substance detection due to its low destructiveness and due to the abundance of molecular fingerprint absorption signatures that it contains. However, there is limited research on the fingerprint detection of substances at different temperatures. Here, we propose a THz metamaterial slit array sensor that exploits localized surface plasmons to enhance the electric field within the slit. The transmission peak frequency can be modulated via temperature adjustments. This method enables the detection of molecular absorption characteristics at multiple spectral frequency points, thereby achieving a specific and highly sensitive detection of characteristic analyte fingerprint spectra. Additionally, the sensor supports the detection of substances at multiple temperatures and sensitively identifies changes in their absorption properties as a function of temperature. Our research has employed temperature variation to achieve a highly sensitive and specific detection of trace analytes, offering a new solution for THz molecular detection.

An Efficient Bio-Receptor Layer Combined with a Plasmonic Plastic Optical Fiber Probe for Cortisol Detection in Saliva.

Cortisol is a clinically validated stress biomarker that takes part in many physiological and psychological functions related to the body's response to stress factors. In particular, it has emerged as a pivotal tool for understanding stress levels and overall well-being. Usually, in clinics, cortisol levels are monitored in blood or urine, but significant changes are also registered in sweat and saliva. In this work, a surface plasmon resonance probe based on a D-shaped plastic optical fiber was functionalized with a glucocorticoid receptor exploited as a highly efficient bioreceptor specific to cortisol. The developed plastic optical fiber biosensor was tested for cortisol detection in buffer and artificial saliva. The biosensor response showed very good selectivity towards other hormones and a detection limit of about 59 fM and 96 fM in phosphate saline buffer and artificial saliva, respectively. The obtained detection limit, with a rapid detection time (about 5 min) and a low-cost sensor system, paved the way for determining the cortisol concentration in saliva samples without any extraction process or sample pretreatment via a point-of-care test.

Thiram Determination in Milk Samples by Surface Plasmon Resonance Based on Molecularly Imprinted Polymers and Sulphur-Doped Titanium Dioxide.

In this work, a new surface plasmon resonance (SPR) sensor based on sulphur-doped titanium dioxide (S-TiO2) nanostructures and molecularly imprinted polymer (MIP) was presented for thiram (THI) determination in milk samples. Firstly, the S-TiO2 nanomaterial with a high product yield was prepared by using a facile sol-gel hydrolysis technique with a high product yield. After that, UV polymerization was carried out for the preparation of the THI-imprinted SPR chip based on S-TiO2 using a mixture including ethylene glycol dimethacrylate (EGDMA) as the cross-linker, N,N'-azobisisobutyronitrile (AIBN) as the initiator, and methacryloylamidoglutamicacid (MAGA) as the monomer. The reliability of the sensor preparation procedure has been successfully proven by characterization studies of the prepared nanomaterials and SPR chip surfaces through spectroscopic, microscopic, and electrochemical methods. As a result, the prepared SPR sensor showed linearity in the range of 1.0 × 10-9-1.0 × 10-7 M with a detection limit (LOD) of 3.3 × 10-10 M in the real samples, and a sensor technique for THI determination with high sensitivity, repeatability, and selectivity can be included in the literature.

Synergy of Target-Induced Magnetic Network and Single-Drop Chromogenic System for Ultrasensitive "All-in-Tube" Detection of miRNA in Whole Blood.

The development of liquid biopsy methods for the accurate and reliable detection of miRNAs in whole blood is critical for the early diagnosis and monitoring of diseases. However, accurate quantification of miRNA expression levels remains challenging due to the complex matrix and low abundance of miRNAs in blood samples. Herein, we report a contactless signal output strategy with low background interference that ensures "zero-contact" between the reaction system and the colorimetry system. The designed target-induced magnetic ZnS/ZIF-90/ZnS network can serve as a unique signal amplifier and transducer. It releases hydrogen sulfide (H2S) gas in an acidic solution which can be concentrated in a droplet of only a few microliters in volume, etching the silver layer of Au@Ag nanostars (NSTs) in the droplet. This will lead to changes in the localized surface plasmon resonance signals of the NSTs. Finally, quantitative detection of let-7a is realized by measuring the offset value of the UV-vis absorption peak. Therefore, by virtue of the synergistic action of quadruple signal amplification methods, including catalytic hairpin assembly, ZnS/ZIF-90/ZnS, magnetic separation, and microextraction, the "All-in-Tube" ultrasensitive detection of low-abundance let-7a in whole blood is achieved with a detection limit as low as the aM level. In addition, the "zero-contact" signal output mode effectively solves the problem of complex matrix interference, demonstrating the great potential of this method for miRNA quantification in complex samples, such as whole blood.