Human Blood Plasma Samples Research Articles

Electrochemical Analysis of Amyloid Plaques and ApoE4 with Chitosan-Coated Gold Nanostars for Alzheimer's Detection.

Monitoring the progression of Alzheimer's disease (AD) is crucial for mitigating dementia symptoms, alleviating pain, and improving mobility. Traditionally, AD biomarkers like amyloid plaques are predominantly identified in cerebrospinal fluid (CSF) due to their concentrated presence. However, detecting these markers in blood is hindered by the blood-brain barrier (BBB), resulting in lower concentrations. To address this challenge and identify pertinent AD biomarkers-specifically amyloid plaques and apolipoprotein E4 (ApoE4)-in blood plasma, we propose an innovative approach. This involves enhancing a screen-printed carbon electrode (SPCE) with an immobilization matrix comprising gold nanostars (AuNSs) coated with chitosan. Morphological and electrical analyses confirmed superior dispersion and conductivity with 0.5% chitosan, supported by UV-Vis spectroscopy, cyclic voltammetry, and Nyquist plots. Subsequent clinical assays measured electrical responses to quantify amyloid-β 42 (Aβ42) (15.63-1000 pg/mL) and APoE4 levels (0.41 to 40 ng/mL) in human blood plasma samples. Differential pulse voltammetry (DPV) responses exhibited peak currents proportional to biomarker concentrations, demonstrating high linear correlations (0.985 for Aβ42 and 0.919 for APoE4) with minimal error bars. Cross-reactivity tests with mixed solutions of amyloid-β 40 (Aβ40), Aβ42, and ApoE4 indicated minimal interference between biomarkers (<3% variation), further confirming the high specificity of the developed sensor. Validation studies demonstrated a strong concurrence with the gold-standard enzyme-linked immunosorbent assay (ELISA), while interference tests indicated a minimal variation in peak currents. This improved device presents promising potential as a point-of-care system, offering a less invasive, cost-effective, and simplified approach to detecting and tracking the progression of AD. The substantial surface binding area further supports the efficacy of our method, offering a promising avenue for advancing AD diagnostics.

Fusion of Raman and FTIR Spectroscopy Data Uncovers Physiological Changes Associated with Lung Cancer.

Due to the high mortality rate, more effective non-invasive diagnostic methods are still needed for lung cancer, the most common cause of cancer-related death worldwide. In this study, the integration of Raman and Fourier-transform infrared spectroscopy with advanced data-fusion techniques is investigated to improve the detection of lung cancer from human blood plasma samples. A high statistical significance was found for important protein-related oscillations, which are crucial for differentiating between lung cancer patients and healthy controls. The use of low-level data fusion and feature selection significantly improved model accuracy and emphasizes the importance of structural protein changes in cancer detection. Although other biomolecules such as carbohydrates and nucleic acids also contributed, proteins proved to be the decisive markers found using this technique. This research highlights the power of these combined spectroscopic methods to develop a non-invasive diagnostic tool for discriminating lung cancer from healthy state, with the potential to extend such studies to a variety of other diseases.

An effective procedure used metal–organic framework for determination of cadmium ions in real tap water and human blood plasma samples

A newly developed 2H5MA-MOF sensor by covalently linking NH2-MIL-53(Al) with 2′-Hydroxy-5′-methylacetophenon, designed for highly sensitive and selective detection of Cd2+ ions using fluorometric methods. Detailed structural and morphological analyses confirmed the sensor’s unique properties. It demonstrated an impressive linear detection range from 0 to 2 ppm, with an exceptionally low detection limit of 5.77 × 10−2 ppm and a quantification limit of 1.75 × 10−1 ppm, indicating its high sensitivity (R2 = 0.9996). The sensor also responded quickly, detecting Cd2+ within just 30 s at pH 4. We successfully tested it on real samples of tap water and human blood plasma, achieving recovery rates between 96 % and 104 %. The accuracy of these findings was further validated by comparison with ICP-OES. Overall, the 2H5MA-MOF sensor shows great potential for fast, ultra-sensitive, and reliable detection of Cd2+ ions, making it a promising tool for environmental and biomedical applications.

Chemiluminescence data modeling using parallel factor analysis for the simple and sensitive determination of diphenoxylate in human plasma and tablets

AbstractIn this study, a chemiluminescence (CL) method was developed to determine diphenoxylate in tablets and human plasma. This is the first CL method proposed to determine diphenoxylate. Creating three‐dimensional data caused the parallel factor analysis algorithm (PARAFAC) to be used for the first time in CL methods. The method is based on the fact that diphenoxylate enhances the weak CL produced in the reaction of Ru(phen)32+ and acidic Ce(IV), and the concentration of Ce(IV) solution has a different effect on the CL response of diphenoxylate and the blank plasma. The calibration curve was linear from 4.0 × 10−8 to 1.6 × 10−6 mol L−1 (R2 = 0.9954), and the detection limit was 1.3 × 10−8 mol L−1 (S/N = 3). The sampling rate was about 30 samples per hour, and the % RSD for 10 repeated measurements of 4 × 10−7 mol L−1 diphenoxylate was 5.4%. The interference effects of some ions, amino acids, and common additives were also investigated. The CL method was successfully used to determine diphenoxylate in tablets, and the results were statistically confirmed by the reference method. The proposed CL method and the PARAFAC algorithm were successfully used to determine the concentration of diphenoxylate in human blood plasma samples.

One-drop micro-array towards accelerated optical quantification of dopamine in human biofluids using triangular silver nanoparticles: Smartphone-assisted biomedical analysis by colorimetric sensing and Lab-on-paper technology

Trace-level detection of Dopamine (DA) in human body fluids is crucial for diagnosing neurological disorders, understanding mental health, and advancing drug discovery, but found challenging with rapid and low-cost detection technologies. Herein, an innovative paper-based photochemical method has been developed for the detection of DA using triangular silver nanoprism (AgNPrs), as an optical nanoprobe, in human blood plasma and urine samples. The redox reaction between DA and AgNPrs was evaluated through a color change at two pHs (5.35and 6.14), which can be analyzed by UV–Vis spectrophotometry and microfluidic paper-based colorimetric device (µPCD) with low limit of quantification of 0.01 µM. This study presents pioneering work with the potential to inspire the development of simple and effective on-site semi quantifying recognition devices for other neurotransmitters, requiring only a lightweight piece of paper and a single drop of the necessary reagent.

Power of Light: Raman Spectroscopy and Machine Learning for the Detection of Lung Cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide, emphasizing the urgent need for reliable and efficient diagnostic methods. Conventional approaches often involve invasive procedures and can be time-consuming and costly, thereby delaying the effective treatment. The current study explores the potential of Raman spectroscopy, as a promising noninvasive technique, by analyzing human blood plasma samples from lung cancer patients and healthy controls. In a benchmark study, 16 machine learning models were evaluated by employing four strategies: the combination of dimensionality reduction with classifiers; application of feature selection prior to classification; stand-alone classifiers; and a unified predictive model. The models showed different performances due to the inherent complexity of the data, achieving accuracies from 0.77 to 0.85 and areas under the curve for receiver operating characteristics from 0.85 to 0.94. Hybrid methods incorporating dimensionality reduction and feature selection algorithms present the highest figures of merit. Nevertheless, all machine learning models deliver creditable scores and demonstrate that Raman spectroscopy represents a powerful method for future in vitro diagnostics of lung cancer.

Lysine-functionalized graphene oxide on cost-effective microporous support: A hydrophilic and fouling resistant membrane for safe lead filtration

The presence of heavy metals in freshwater is a severe problem humanity faces. Remedies with high removal efficiency of heavy metals from contaminated water are crucial. However, existing studies often neglect effluent quality per World Health Organization (WHO) standards. Also, the reported conditions are either unrealistic to the actual contamination levels or unsuitable for large-scale applications. Here, we report the fabrication of zwitterionic graphene oxide (GO) by incorporating a pH-responsive group (i.e., Lysine) using N, N′-diisopropylcarbodiimide (DIC) as a coupling agent. The modified GO-Lys was then coated on a commercially available 0.45-μm Nylon membrane and was tested for selective removal of toxic heavy metals from synthetic water and human blood plasma samples while allowing essential metal ions. Consequently, lead was the most retained toxic metal (i.e., 99.99% retention with effluent quality meeting WHO standards) among nickel, arsenic, cadmium, and mercury (i.e., between 50 to 80% retention). These composite membranes also displayed excellent fouling resistance and inhibited bacterial adhesion onto the membrane surface, while maintaining stable performance over a long time and critical transmembrane pressure conditions. This research marks a significant advancement in environmental technologies, providing an effective solution for selectively removing heavy metal pollutants, with a particular focus on lead detoxification applications.

Preparation of nickel foam modified by multiwalled hollow spheres of NiCo2O4 as a promising non-enzymatic glucose sensor.

Nickel foam modified by hollow sphere NiCo2O4 particles was successfully prepared via a hydrothermal method using nanosphere SiO2 particles as the hard template for the hollow structure. Characterisation using SEM-EDX and TEM confirmed the structure as multiwalled hollow spheres with an average size of 270 nm, while characterisation using SEM, XRD, and XPS confirmed that the NiCo2O4 particles were attached on the surface of the nickel foam. BET analysis showed that the surface area of the synthesized NiCo2O4@Ni foam was nearly three times higher compared to that of the unmodified Ni foam. Investigation of the NiCo2O4-modified nickel foam as an electrode for the detection of glucose in sodium hydroxide solution showed high linearity of the anodic currents (R2 = 0.99) in the concentration range of 0-2.5 μM with sensitivity of 0.060 mA μM-1 and an estimated limit of detection of 0.060 μM. Excellent stability of the current response was also obtained with a relative standard deviation of 1.51% (n = 10). Furthermore, the developed sensor demonstrates strong applicability for glucose detection in real samples of human blood plasma, making it highly suitable for practical use. The results indicate that the material is promising for the further development of nickel-based sensors.

Inner-filter effect of nitrogen-doped carbon quantum dots-MnO2 nanotubes for smartphone-integrated dual-mode sensing of glutathione and captopril.

Nitrogen-doped carbon quantum dots (N-CQDs) exhibit unique fluorescence properties and are considered one of the best candidates for the development of fluorescence-based sensors for the detection of many analytes. In this work, a smartphone-assisted fluorescent sensor has been developed using N-CQDs and MnO2 nanotubes (MnO2 NTs) for the detection of glutathione (GSH) and captopril (CAP). N-CQDs were facilely synthesized via the solvothermal method, where o-phenylenediamine (o-PD) and urea were used as nitrogen precursors. Likewise, MnO2 NTs were synthesized using the hydrothermal method. Relying on the excellent fluorescence quenching ability of MnO2 NTs, a nanocomposite of N-CQDs and MnO2 NTs is prepared, wherein the fluorescence intensity of N-CQDs was effectively quenched in the presence of MnO2 NTs via the inner-filter effect (IFE). The addition of thiolated compounds (GSH and CAP) helped in the recovery of the fluorescence of N-CQDs by triggering the redox reaction and decomposing the MnO2 NTs. An investigation of fluorescence along with smartphone-based studies by evaluating the gray measurement using Image J software showed a great response towards GSH and CAP providing LODs of 4.70 μM and 5.22 μM (fluorometrically) and 5.76 μM and 2.81 μM (smartphone-based), respectively. The practical applicability of the sensing system has been verified using human blood plasma samples.

Identification of taurine biomarker in human biofluids using plasmonic patterns of silver nanostructure.

Taurine is now widely used as a new biomarker for cardiovascular and neurodegenerative diseases. This study discusses the importance of accurately determining taurine biomarker levels in various tissues and fluids for the early diagnosis of important pathologies and diseases. Current methods for taurine analysis face challenges such as low sensitivity, lack of selectivity, and complex procedures. Therefore, an efficient analytical method/technique is urgently needed by clinicians. A new paper-based photochemical method using triangular silver nanoparticles (TA-AgNPs) as optical nanoprobes was developed to detect taurine in human blood plasma and urine samples. This method involves a chemical reaction between taurine and TA-AgNPs, leading to a color change at pH 4.8, which is detected using a paper-based colorimetry (PCD) assay. The reaction is further confirmed by UV-visible spectrophotometry as the interaction between taurine and TA-AgNPs causes a significant change in the absorption spectrum, enabling the rapid and reliable measurement of this important biomarker with a detection limit of less than 0.2 μM to 20 mM. The method has been successfully applied to bioanalyzing taurine in human body fluids. Additionally, it requires optimized single-drop paper/parafilm-based colorimetric devices (OD-PCDs) for in situ and on-demand taurine analysis. This study represents the first use of TA-AgNPs for the specific and sensitive detection of taurine in real samples. The sensor design allows for the direct quantification of biomarkers in biological samples without the need for derivatization procedures or sample preparation. The simplicity and portability of OD-PCDs make them promising for tracking and monitoring. This method is expected to contribute to improving environmental health and occupational safety and represents a significant advancement in colorimetric analysis for the sensitive and selective detection of taurine, potentially providing a platform for the identification of taurine and other biomarkers.

Selective and sensitive colorimetric detection of endocrine disrupter fungicide carbendazim through secnidazole capped silver nanoparticles

Pesticides and fungicides are extremely useful to hinder the attacks of pests and fungi to secure crops, vegetables, fruits and other plants but due to their endocrine disrupting and carcinogenic risks in humans and animals through their continued addition in water resources they are extremely important to monitor carefully. In this investigation we synthesized silver nanoparticles (AgNPs) via the reducing action of sodium borohydride in the presence of secnidazole (SEC) as capping agent under various optimized parameters such as the concentration of NaBH4, silver nitrate (AgNO3), SEC and pH. These SEC-AgNPs were characterized through various techniques including ultra-violet visible (UV–Vis) spectroscopy, Fourier transform infra-red (FTIR) spectroscopy, field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), dynamic light scattering (DLS) and zeta-potential analysis (ZPA) in order to investigate their diverse properties. As prepared SEC-AgNPs were proved as extremely sensitive for trace level sensing of fungicide carbendazim (CARB) in the range of 0.5–22 µM with limit of detection (LOD) equal to 0.021 µM and R2 value of 0.9964. SEC-AgNPs were tested for CARB sensing under the presence of several pesticides with negligible interference thus verifying its exclusive selectivity for the targeted analyte. This SEC-AgNPs was further applied to find out the concentration of CARB in real samples of tap water and human blood plasma with reference to standard addition method.

Fluorescence sensing of NADH using silica-zinc nitride nanocomposite for monitoring diabetes

Quantitative detection of NADH in blood plasma acts as a biomarker for diagnosing diabetes at an early stage. However, detection of NADH in cells/tissue is difficult due to their limitation in autofluorescence signal intensity. Thus, a suitable material is needed to enhance the signal without affecting the molecular structure of NADH. Herein, we report on facile, rapid and cost effective APTES functionalized sustainable silica (SiO2) composited with zinc nitride (Zn3N2) for the sensing of NADH by fluorescence method. The composite exhibits excellent sensitivity with the limit of detection 4.73 μM. The proposed sensing method also validated in human blood plasma samples, showing the LOD of 0.78 μM. The sensing results were exhibit that the sustainable composite material would be a suitable material in clinical application towards diagnosing diabetes at an earlier stage.

Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis.

Aging clocks, built from comprehensive molecular data, have emerged as promising tools in medicine, forensics, and ecological research. However, few studies have compared the suitability of different molecular data types to predict age in the same cohort and whether combining them would improve predictions. Here, we explored this at the level of proteins and small RNAs in 103 human blood plasma samples. First, we used a two-step mass spectrometry approach measuring 612 proteins to select and quantify 21 proteins that changed in abundance with age. Notably, proteins increasing with age were enriched for components of the complement system. Next, we used small RNA sequencing to select and quantify a set of 315 small RNAs that changed in abundance with age. Most of these were microRNAs (miRNAs), downregulated with age, and predicted to target genes related to growth, cancer, and senescence. Finally, we used the collected data to build age-predictive models. Among the different types of molecules, proteins yielded the most accurate model (R² = 0.59 ± 0.02), followed by miRNAs as the best-performing class of small RNAs (R² = 0.54 ± 0.02). Interestingly, the use of protein and miRNA data together improved predictions (R2 = 0.70 ± 0.01). Future work using larger sample sizes and a validation dataset will be necessary to confirm these results. Nevertheless, our study suggests that combining proteomic and miRNA data yields superior age predictions, possibly by capturing a broader range of age-related physiological changes. It will be interesting to determine if combining different molecular data types works as a general strategy to improve future aging clocks.

Synthesis of molecularly imprinted polymer as a nanosorbent for dispersive magnetic micro solid-phase extraction and determination of valsartan in biological samples by UV–Vis Spectrophotometry: Isotherm, kinetics, and thermodynamic studies

A magnetic molecularly imprinted polymer (MIP) was synthesized by precipitation polymerization utilizing Fe3O4@SiO2-MPS as a magnetic core, itaconic acid as a functional monomer, azobisisobutyronitrile as an initiator, and ethylene glycol dimethacrylate as a cross linker. It was then applied as a nanosorbent for dispersive magnetic micro solid phase extraction (DM-µ-SPE) and determination of valsartan in biological fluids. The morphology and structure of magnetic MIP were characterized by Fourier-transform infrared spectroscopy, Field Emission Scanning electron microscopy, Vibrating sample magnetometer, Energy dispersive x-ray analysis, and Thermogravimetric analysis. The influence of operation conditions on sorption, such as pH (4–10), contact time (10–25 min), initial concentration (1–30 mg L−1), and temperature (25–40 °C) was investigated. After the extraction step, the valsartan concentration was determined by UV–Vis spectrophotometer at 253 nm. The isotherm and kinetic of valsartan sorption were best fitted by the Langmuir model (R2 = 0.987) and the Pseudo second-order kinetic model (R2 = 0.971), respectively. The maximum monolayer sorption capacity for magnetic MIP was obtained to be 4.56 mg g−1. The analytical approach demonstrated favorable figures of merit, with a linear dynamic range of 10–100 µg L−1, a low detection limit of 0.56 µg L−1, and an acceptable preconcentration factor of 5 acquired in optimum conditions. The recoveries of the suggested technique at three spiked levels of analysis were in the range of 101 %–102 %. Valsartan was extracted from various real samples (urine and human blood plasma samples) utilizing the proposed magnetic nanosorbent, and the results exhibited that magnetic MIP was favorable for extraction and measurement of trace amounts of valsartan in biological samples.

Optimization of Diffusion-Ordered NMR Spectroscopy Experiments for High-Throughput Automation in Human Metabolic Phenotyping.

The diffusion-ordered nuclear magnetic resonance spectroscopy (DOSY) experiment allows the calculation of diffusion coefficient values of metabolites in complex mixtures. However, this experiment has not yet been broadly used for metabolic profiling due to lack of a standardized protocol. Here we propose a pipeline for the DOSY experimental setup and data processing in metabolic phenotyping studies. Due to the complexity of biological samples, three experiments (a standard DOSY, a relaxation-edited DOSY, and a diffusion-edited DOSY) have been optimized to provide DOSY metabolic profiles with peak-picked diffusion coefficients for over 90% of signals visible in the one-dimensional 1H general biofluid profile in as little as 3 min 36 s. The developed parameter sets and tools are straightforward to implement and can facilitate the use of DOSY for metabolic profiling of human blood plasma and urine samples.

Biogenic carbon dot-based fluorescence-mediated immunosensor for the detection of disease biomarker

The dynamic interplay of nanotechnology and immunoassay has unlocked an arena for developing next-generation techniques to contribute to detecting disease biomarkers. Herein, the work establishes the strategic fabrication of an immunosensor by sandwich technique based on the fluorescence phenomenon of carbon dots for the detection of the disease biomarker VEGF (Vascular Endothelial Growth Factor). VEGF, a biomarker for angiogenesis, is considered cancerous if found in elevated levels in the blood, and so is paramount for early detection of disease. Carbon dots derived from a biogenic source were synthesized employing a green microwave-assisted method followed by conjugating with a detection antibody, human immunoglobulin G (IgG), via EDC-NHS amidation reaction. On the other hand, the VEGF biomarker was immobilized onto the capture antibody. The detection antibody tagged with the fluorescent probe is employed as a bridge to connect with the VEGF biomarkers bound to the capture antibody. The response to different concentrations of VEGF biomarkers was recorded in terms of the fluorescence intensity of the carbon dots. The fluorescence immunosensor could exhibit a wide linear range of 0.1 fg/mL to 10 pg/mL with a low detection limit of 5.65 pg/mL towards VEGF. The potentiality of this designed immunosensor was qualitatively assessed with human blood plasma samples, showing promising results, thereby upholding the applicability of carbon dots as fluorescent labels in immunoassay techniques.

A Biologically Compatible Colorimetric Sensor for the Selective Recognition of Cu2+ Ions in Biological Matrices

AbstractHeavy metal ions pollution is posing a major danger to human health across the planet. We present a phenylhydrazone‐based colorimetric sensor for detecting Cu2+ ions in tap water and human blood plasma. The phenylhydrazone‐based sensor (Sensor 1) is extremely selective for recognizing Cu2+ ions over other similar metal ions by producing a colorimetric response. Upon interaction with Cu2+, the colorless sensor 1 changes to dark yellow within a minute producing a bathochromic shift in the absorption spectrum. The AFM, Zetasizer and FTIR spectroscopic techniques were used for Cu2+ detection and selectivity of sensor 1. The average size of sensor 1 is around 293.9 nm which changes to 2275 nm upon complexation with Cu2+. Sensor 1 was highly selective towards Cu2+ as no interference was recorded by various metals ions. The detection limit was found to be 0.1 μM with R2 equal to 0.9821. Furthermore, cytotoxic experiments showed that sensor 1 is nontoxic to various cell lines, which revealed that it could detect Cu2+ ions in the biological system. Moreover, sensor 1 gives satisfactory results for detecting Cu2+ ions in human blood plasma and real water samples.

A Polyaniline‐Supported, Chromium‐Based Metal‐Organic Framework for Electrochemical Sensing of Cadmium(II)

AbstractIn this work a conducting electrochemical sensing probe, Cr‐BDC‐NH2@PANI composite material (BDC=1,4‐benzenedicarboxylate), was successfully synthesized by polymerization of conducting polyaniline (PANI) around the Cr‐BDC‐NH2 material. The synthesized composite material was characterized by various analytical techniques. The Cr‐BDC‐NH2@PANI composite was successfully dropped cast on the surface of an inexpensive pencil graphite electrode (PGE) to detect the cadmium ions at trace level. The selectivity of proposed sensor observed towards cadmium ion is due to chelation mechanism operating between cadmium ions and amine groups. Under optimized condition, the proposed sensor is capable of measuring cadmium ions in aqueous as well as in human blood serum, plasma, and various water samples within the range of 0.50‐32.5 μg L−1 with the limit of detection (LOD) of 0.20 μg L−1. The Cr‐BDC‐NH2@PANI composite material modified sensor shows high affinity and no interference with real samples.

Analytical Validation of Surface-Enhanced Raman Scattering Paper Lateral Flow Assays for Detection of Traumatic Brain Injury Biomarker

Traumatic brain injury (TBI) can cause brain function loss injury-related deaths. Early TBI management is significant, but requires a timely, accurate, and sensitive assessment solution. However, current radiation- or imaging-based TBI diagnostic technologies are either less effective or time-consuming and expensive. Here, a surface-enhanced Raman scattering paper-based lateral flow strip (SERS-PLFS) is developed for rapid detection of neuron-specific enolase (NSE), a TBI biomarker in clinical blood plasma samples. The SERS-PLFS device is validated analytically with clinical human blood plasma samples. The performance metrics including accuracy, precision, reportable range, lower limit of quantification and upper limit of quantification, recovery, uncertainty, selectivity, robustness, are assessed using statistical methods. The validation results show that the SERS-PLFS is reliable in measuring the NSE levels in TBI patients.

Human Heart Anoxia and Reperfusion Tissue (HEART) Model for the Rapid Study of Exosome Bound miRNA Expression As Biomarkers for Myocardial Infarction.

Current biomarkers for myocardial infarction (MI) diagnosis are typically late markers released upon cell death, incapable of distinguishing between ischemic and reperfusion injury and can be symptoms of other pathologies. Circulating microRNAs (miRNAs) have recently been proposed as alternative biomarkers for MI diagnosis; however, detecting the changes in the human cardiac miRNA profile during MI is extremely difficult. Here, to study the changes in miRNA levels during acute MI, a heart-on-chip model with a cardiac channel, containing human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes in human heart decellularized matrix and collagen, and a vascular channel, containing hiPSC-derived endothelial cells, is developed. This model is exposed to anoxia followed by normoxia to mimic ischemia and reperfusion, respectively. Using a highly sensitive miRNA biosensor that the authors developed, the exact same increase in miR-1, miR-208b, and miR-499 levels in the MI-on-chip and the time-matched human blood plasma samples collected before and after ischemia and reperfusion, is shown. That the surface marker profile of exosomes in the engineered model changes in response to ischemic and reperfusion injury, which can be used as biomarkers to detect MI, is also shown. Hence, the MI-on-chip model developed here can be used in biomarker discovery.