Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples.

The collision cross-sections (CCS) measurement using ion mobility spectrometry (IMS) in combination with mass spectrometry (MS) offers a great opportunity to increase confidence in metabolite identification. However, owing to the lack of sensitivity and resolution, IMS has an analytical challenge in studying the CCS values of very low-molecular-weight metabolites (VLMs ≤ 250 Da). Here, we describe an analytical method using ultrahigh-performance liquid chromatography (UPLC) coupled to a traveling wave ion mobility-quadrupole-time-of-flight mass spectrometer optimized for the measurement of VLMs in human urine samples. The experimental CCS values, along with mass spectral properties, were reported for the 174 metabolites. The experimental data included the mass-to-charge ratio (m/z), retention time (RT), tandem MS (MS/MS) spectra, and CCS values. Among the studied metabolites, 263 traveling wave ion mobility spectrometry (TWIMS)-derived CCS values (TWCCSN2) were reported for the first time, and more than 70% of these were CCS values of VLMs. The TWCCSN2 values were highly repeatable, with inter-day variations of <1% relative standard deviation (RSD). The developed method revealed excellent TWCCSN2 accuracy with a CCS difference (ΔCCS) within ±2% of the reported drift tube IMS (DTIMS) and TWIMS CCS values. The complexity of the urine matrix did not affect the precision of the method, as evidenced by ΔCCS within ±1.92%. According to the Metabolomics Standards Initiative, 55 urinary metabolites were identified with a confidence level of 1. Among these 55 metabolites, 53 (96%) were VLMs. The larger number of confirmed compounds found in this study was a result of the addition of TWCCSN2 values, which clearly increased metabolite identification confidence.

Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion's Polarizability and Molecular Mass with Limited Data.

The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach for predicting CCS values, they rely on large data sets from various instruments, calibrants, and setups, which can introduce additional errors. In this study, we identified and validated that ion's polarizability and mass-to-charge ratio (m/z) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions. Constructed solely based on these two physicochemical properties, our CCS prediction approach demonstrated high accuracy (mean relative error of <3.0%) even when trained with limited data (15 CCS values). Given its ability to excel with limited data, our approach harbors immense potential for constructing a precisely predicted CCS database tailored to each distinct experimental setup. A Python script for CCS prediction using our approach is freely available at https://github.com/MSBSiriraj/SVR_CCSPrediction under the GNU General Public License (GPL) version 3.

Magnetic Graphene Oxide Nanocomposites for Selective miRNA Separation and Recovery.

In this study, we developed magnetic graphene oxide composites by chemically attaching Fe3O4 nanoparticles to graphene oxide nanosheets. Characterization techniques, including Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), Raman spectroscopy, thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and transmission electron microscopy (TEM), confirmed the successful synthesis of Fe3O4@GO composites with desirable properties. The resulting composites exhibited superparamagnetic behavior, solubility, and compatibility for efficient miRNA separation. Using miR-29a as a model, we demonstrated the effective binding of miR-29a to the magnetic graphene oxide (GO) composites at an optimal concentration of 1.5 mg/mL, followed by a simple separation using magnetic forces. Additionally, the addition of 5.0 M urea enhanced the miRNA recovery. These findings highlight the potential use of our magnetic graphene oxide composites for the efficient separation and recovery of miR-29a, suggesting their broad applicability in various miRNA-based studies. Further exploration can focus on investigating endogenous miRNAs with aberrant expression patterns, contributing to the advancements in precision medicine.

Enhancing protein trapping efficiency of graphene oxide-polybutylene succinate nanofiber membrane via molecular imprinting.

Filtration of biological liquids has been widely employed in biological, medical, and environmental investigations due to its convenience; many could be performed without energy and on-site, particularly protein separation. However, most available membranes are universal protein absorption or sub-fractionation due to molecule sizes or properties. SPMA, or syringe-push membrane absorption, is a quick and easy way to prepare biofluids for protein evaluation. The idea of initiating SPMA was to filter proteins from human urine for subsequent proteomic analysis. In our previous study, we developed nanofiber membranes made from polybutylene succinate (PBS) composed of graphene oxide (GO) for SPMA. In this study, we combined molecular imprinting with our developed PBS fiber membranes mixed with graphene oxide to improve protein capture selectivity in a lock-and-key fashion and thereby increase the efficacy of protein capture. As a model, we selected albumin from human serum (ABH), a clinically significant urine biomarker, for proteomic application. The nanofibrous membrane was generated utilizing the electrospinning technique with PBS/GO composite. The PBS/GO solution mixed with ABH was injected from a syringe and transformed into nanofibers by an electric voltage, which led the fibers to a rotating collector spinning for fiber collection. The imprinting process was carried out by removing the albumin protein template from the membrane through immersion of the membrane in a 60% acetonitrile solution for 4 h to generate a molecular imprint on the membrane. Protein trapping ability, high surface area, the potential for producing affinity with proteins, and molecular-level memory were all evaluated using the fabricated membrane morphology, protein binding capacity, and quantitative protein measurement. This study revealed that GO is a controlling factor, increasing electrical conductivity and reducing fiber sizes and membrane pore areas in PBS-GO-composites. On the other hand, the molecular imprinting did not influence membrane shape, nanofiber size, or density. Human albumin imprinted membrane could increase the PBS-GO membrane's ABH binding capacity from 50 to 83%. It can be indicated that applying the imprinting technique in combination with the graphene oxide composite technique resulted in enhanced ABH binding capabilities than using either technique individually in membrane fabrication. The suitable protein elution solution is at 60% acetonitrile with an immersion time of 4 h. Our approach has resulted in the possibility of improving filter membranes for protein enrichment and storage in a variety of biological fluids.

Ultrasensitive Detection of MicroRNA in Human Saliva via Rolling Circle Amplification Using a DNA-Decorated Graphene Oxide Sensor.

MicroRNAs (miRNAs) are a family of conserved small noncoding RNAs whose expression is associated with many diseases, including cancer. Salivary miRNAs are gaining popularity as noninvasive diagnostic biomarkers for cancer and other systemic disorders, but their use is limited by their low abundance and complicated detection procedure. Herein, we present a novel self-assembly approach based on rolling circle amplification (RCA) and graphene oxide (GO) for the ultrasensitive detection of miRNA21 and miRNA16 (miRNA oral cancer biomarkers in human saliva). First, target miRNA hybridizes with the RCA template. In the presence of DNA polymerase, the RCA reaction is induced and sequences matching the template are generated. Then, a nicking enzyme cuts the long ssDNA product into tiny pieces to obtain the amplified products. The DNA-decorated GO sensor was fabricated by preabsorbing the ssDNA fluorescence-labeled probe on the GO surface, resulting in fluorescence quenching. The DNA-decorated GO sensor could detect the amplified product via the self-assembly of dsDNA, leading to the desorption and recovery of the fluorescence-labeled probe. Under optimal conditions, the proposed system exhibited ultrasensitive detection; the detection limits of miRNA16 and miRNA21 were 8.81 and 3.85 fM, respectively. It showed a wide range of detection between 10 fM and 100 pM for miRNA16 and between 10 fM and 1 nM for miRNA16. It demonstrated high selectivity, distinguishing between 1- and 3-mismatch nucleotides in target miRNA. Overall, our proposed DNA-decorated GO sensor can accurately detect the salivary miRNAs and may potentially be used for the diagnosis and screening of early-stage oral cancer.

GC × GC-TOFMS metabolomics analysis identifies elevated levels of plasma sugars and sugar alcohols in diabetic mellitus patients with kidney failure.

Two dimensional GC (GC × GC)-time-of-flight mass spectrometry (TOFMS) has been used to improve accurate metabolite identification in the chemical industry, but this method has not been applied as readily in biomedical research. Here, we evaluated and validated the performance of high resolution GC × GC-TOFMS against that of GC-TOFMS for metabolomics analysis of two different plasma matrices, from healthy controls (CON) and diabetes mellitus (DM) patients with kidney failure (DM with KF). We found GC × GC-TOFMS outperformed traditional GC-TOFMS in terms of separation performance and metabolite coverage. Several metabolites from both the CON and DM with KF matrices, such as carbohydrates and carbohydrate-conjugate metabolites, were exclusively detected using GC × GC-TOFMS. Additionally, we applied this method to characterize significant metabolites in the DM with KF group, with focused analysis of four metabolite groups: sugars, sugar alcohols, amino acids, and free fatty acids. Our plasma metabolomics results revealed 35 significant metabolites (12 unique and 23 concentration-dependent metabolites) in the DM with KF group, as compared with those in the CON and DM groups (N = 20 for each group). Interestingly, we determined 17 of the 35 (14/17 verified with reference standards) significant metabolites identified from both the analyses were metabolites from the sugar and sugar alcohol groups, with significantly higher concentrations in the DM with KF group than in the CON and DM groups. Enrichment analysis of these 14 metabolites also revealed that alterations in galactose metabolism and the polyol pathway are related to DM with KF. Overall, our application of GC × GC-TOFMS identified key metabolites in complex plasma matrices.

Predicting treatment response and clinicopathological findings in lupus nephritis with urine epidermal growth factor, monocyte chemoattractant protein-1 or their ratios.

INTRODUCTION: There is a need for sensitive and specific biomarkers to predict kidney damage and therapeutic response in lupus nephritis (LN). Monocyte chemoattractant protein-1 (MCP-1) and epidermal growth factor (EGF) are cytokines with divergent roles. EGF or EGF/MCP1 ratio have been shown to correlate with prognosis in primary glomerulonephritis, but there is limited information in lupus nephritis (LN). This study evaluated the roles of MCP-1, EGF or their ratio as biomarkers of histopathology and response to treatment in LN. METHODS: This was a cross-sectional and observational study. Baseline urine MCP-1 and EGF levels in systemic lupus erythematosus (SLE) patients and controls (total n = 101) were compared, and levels were correlated with clinicopathological findings and subsequent response to treatment. RESULTS: MCP-1 was higher in active LN (n = 69) compared to other SLE groups and controls, whereas EGF was not different. MCP-1 correlated with disease activity (proteinuria, renal SLEDAI, classes III/IV/V, and high activity index.) By contrast, EGF correlated with eGFR, but not with proteinuria, activity index, or class III/IV/V. MCP-1 was higher, and EGF was lower in high chronicity index. EGF/MCP-1 decreased with greater clinicopathological severity. In a subgroup with proliferative LN who completed six months of induction therapy (n = 41), EGF at baseline was lower in non-responders compared to responders, whereas MCP-1 was similar. By multivariable analysis, baseline EGF was independently associated with subsequent treatment response. Area under the curve for EGF to predict response was 0.80 (0.66-0.95). EGF ≥ 65.6 ng/ mgCr demonstrated 85% sensitivity and 71% specificity for response. EGF/MCP-1 did not improve the prediction for response compared to EGF alone. CONCLUSION: MCP-1 increased with disease activity, whereas EGF decreased with low GFR and chronic damage. Urine EGF may be a promising biomarker to predict therapeutic response in LN. EGF/MCP-1 did not improve the prediction of response.

Down-regulation of the transcriptional repressor ZNF802 (JAZF1) reactivates fetal hemoglobin in ß0-thalassemia/HbE.

Reactivating of fetal hemoglobin (HbF; α2γ2) can ameliorate the severity of ß-thalassemia disease by compensating for adult hemoglobin deficiency in patients. Previously, microarray analysis revealed that zinc finger protein (ZNF)802 (also known as Juxta-posed with another zinc finger gene-1 (JAZF1)) was upregulated in human erythroblasts derived from adult peripheral blood compared with fetal liver-derived cells, implying a potential role as a HbF repressor. However, deficiency in ZNF802 induced by lentiviral shRNA in ß0-thalassemia/hemoglobinE erythroblasts had no effect on erythroblast proliferation and differentiation. Remarkably, the induction of HBG expression was observed at the transcriptional and translational levels resulting in an increase of HbF to 35.0 ± 3.5%. Interestingly, the embryonic globin transcripts were also upregulated but the translation of embryonic globin was not detected. These results suggest ZNF802 might be a transcriptional repressor of the γ-globin gene in adult erythroid cells.

Global research alliance in infectious disease: a collaborative effort to combat infectious diseases through dissemination of portable sequencing.

OBJECTIVE: To disseminate the portable sequencer MinION in developing countries for the main purpose of battling infectious diseases, we found a consortium called Global Research Alliance in Infectious Diseases (GRAID). By holding and inviting researchers both from developed and developing countries, we aim to train the participants with MinION's operations and foster a collaboration in infectious diseases researches. As a real-life example in which resources are limited, we describe here a result from a training course, a metagenomics analysis from two blood samples collected from a routine cattle surveillance in Kulan Progo District, Yogyakarta Province, Indonesia in 2019. RESULTS: One of the samples was successfully sequenced with enough sequencing yield for further analysis. After depleting the reads mapped to host DNA, the remaining reads were shown to map to Theileria orientalis using BLAST and OneCodex. Although the reads were also mapped to Clostridium botulinum, those were found to be artifacts derived from the cow genome. An effort to construct a consensus sequence was successful using a reference-based approach with Pomoxis. Hence, we concluded that the asymptomatic cow might be infected with T. orientalis and showed the usefulness of sequencing technology, specifically the MinION platform, in a developing country.

CRISP: a deep learning architecture for GC × GC-TOFMS contour ROI identification, simulation and analysis in imaging metabolomics.

Two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) provides a large amount of molecular information from biological samples. However, the lack of a comprehensive compound library or customizable bioinformatics tool is currently a challenge in GC × GC-TOFMS data analysis. We present an open-source deep learning (DL) software called contour regions of interest (ROI) identification, simulation and untargeted metabolomics profiler (CRISP). CRISP integrates multiple customizable deep neural network architectures for assisting the semi-automated identification of ROIs, contour synthesis, resolution enhancement and classification of GC × GC-TOFMS-based contour images. The approach includes the novel aggregate feature representative contour (AFRC) construction and stacked ROIs. This generates an unbiased contour image dataset that enhances the contrasting characteristics between different test groups and can be suitable for small sample sizes. The utility of the generative models and the accuracy and efficacy of the platform were demonstrated using a dataset of GC × GC-TOFMS contour images from patients with late-stage diabetic nephropathy and healthy control groups. CRISP successfully constructed AFRC images and identified over five ROIs to create a deepstacked dataset. The high fidelity, 512 × 512-pixels generative model was trained as a generator with a Fréchet inception distance of <47.00. The trained classifier achieved an AUROC of >0.96 and a classification accuracy of >95.00% for datasets with and without column bleed. Overall, CRISP demonstrates good potential as a DL-based approach for the rapid analysis of 4-D GC × GC-TOFMS untargeted metabolite profiles by directly implementing contour images. CRISP is available at https://github.com/vivekmathema/GCxGC-CRISP.

Predicting lupus membranous nephritis using reduced picolinic acid to tryptophan ratio as a urinary biomarker.

The current gold standard for classifying lupus nephritis (LN) progression is a renal biopsy, which is an invasive procedure. Undergoing a series of biopsies for monitoring disease progression and treatments is unlikely suitable for patients with LN. Thus, there is an urgent need for non-invasive alternative biomarkers that can facilitate LN class diagnosis. Such biomarkers will be very useful in guiding intervention strategies to mitigate or treat patients with LN. Urine samples were collected from two independent cohorts. Patients with LN were classified into proliferative (class III/IV) and membranous (class V) by kidney histopathology. Metabolomics was performed to identify potential metabolites, which could be specific for the classification of membranous LN. The ratio of picolinic acid (Pic) to tryptophan (Trp) ([Pic/Trp] ratio) was found to be a promising candidate for LN diagnostic and membranous classification. It has high potential as an alternative biomarker for the non-invasive diagnosis of LN.

Pilot study to investigate differences in middle molecules, oxidative stress and markers of peripheral vascular disease in patients treated by high flux haemodialysis and haemodiafiltration.

BACKGROUND: Dialysis patients have an increased risk of mortality. Recently treatment with haemodiafiltration (HDF) has been reported to reduce mortality, particularly cardiovascular mortality, compared to standard high-flux haemodialysis (HD). However, why HDF may offer a survival advantage remains to be determined. So, we conducted a pilot study to explore differences in middle-molecules, inflammation and markers of vascular disease in patients treated by HD and HDF. METHODS: Observational cross-sectional study measuring serum ß2-microglobulin (ß2M), Advanced Glycosylation End Products (AGEs) by skin autofluorescence (SAF), oxidative stress with ischaemia modified albumin ratio (IMAR) and peripheral vascular disease assessment using Ankle-Brachial Index (ABI), and arterial stiffness using Cardio-Ankle Vascular Index (CAVI). RESULTS: We studied 196 patients, mean age 69.1 ± 12.4 years, 172 (87.8%) treated by HD and 24 (12.2%) by HDF. Age, body mass index, co-morbidity and dialysis vintage were not different between HD and HDF groups. Middle molecules; ß2M (31±9.9 vs 31.2±10 ug/mL) and SAF (2.99±0.72 vs 3.0±0.84 AU), ABI (1.06±0.05 vs 1.07±0.10) and CAVI (9.34±1.55 vs 9.35±1.23) were not different, but IMAR was higher in the HD patients (38.4±14.8 vs 31.3 ± 17.4, P = 0.035). CONCLUSIONS: In this pilot observational study, we found patients treated by HDF had lower oxidative stress as measured by IMAR, with no differences in middle molecules. Lower oxidative stress would be expected to have diverse protective effects on the cardiovascular system Although we found no differences in ABI and CAVI, future studies are required to determine whether reduced oxidative stress translates into clinically relevant differences over time.

Electrospun Fibers of Polybutylene Succinate/Graphene Oxide Composite for Syringe-Push Protein Absorption Membrane.

The adsorption of proteins on membranes has been used for simple, low-cost, and minimal sample handling of large volume, low protein abundance liquid samples. Syringe-push membrane absorption (SPMA) is an innovative way to process bio-fluid samples by combining a medical syringe and protein-absorbable membrane, which makes SPMA a simple, rapid protein and proteomic analysis method. However, the membrane used for SPMA is only limited to commercially available protein-absorbable membrane options. To raise the method's efficiency, higher protein binding capacity with a lower back pressure membrane is needed. In this research, we fabricated electrospun polybutylene succinate (PBS) membrane and compared it to electrospun polyvinylidene fluoride (PVDF). Rolling electrospinning (RE) and non-rolling electrospinning (NRE) were employed to synthesize polymer fibers, resulting in the different characteristics of mechanical and morphological properties. Adding graphene oxide (GO) composite does not affect their mechanical properties; however, electrospun PBS membrane can be applied as a filter membrane and has a higher pore area than electrospun PVDF membrane. Albumin solution filtration was performed using all the electrospun filter membranes by the SPMA technique to measure the protein capture efficiency and staining of the protein on the membranes, and these membranes were compared to the commercial filter membranes-PVDF, nitrocellulose, and Whatman no. 1. A combination of rolling electrospinning with graphene oxide composite and PBS resulted in two times more captured protein when compared to commercial membrane filtration and more than sixfold protein binding than non-composite polymer. The protein staining results further confirmed the enhancement of the protein binding property, showing more intense stained color in compositing polymer with GO.

Dual sensitive and rapid detection of glycated human serum albumin using a versatile lead/graphene nanocomposite probe as a fluorescence-electrochemical aptasensor.

Monitoring of glycated human serum albumin (GHSA) as a glycemic marker for screening and monitoring of diabetes mellitus is widely practiced for patients with conditions that affect red blood cells. In this study, a complex comprising Pb ions adsorbed on graphene oxide (GO-Pb) was fabricated and utilized as a versatile probe in a fluorescence-electrochemical aptasensor for GHSA quantification. To simplify the aptasensor, the GO-Pb complex probe was prepared via an ion adsorption process. After modification with a fluorophore-labeled aptamer, the GO-Pb complex served as an excellent energy acceptor in fluorescence-based analysis, as well as generating a high current in the electrochemical transducer. Additionally, the proposed platform can detect GHSA via the dual technique from a single sample, allowing for precise and accurate results. Under optimal conditions, the fluorescence-electrochemical aptasensor exhibited a linear relationship with GHSA concentrations from 0.001 to 80 µg mL-1 and from 0.005 to 10 µg mL-1 for fluorescence and electrochemical detection, respectively. The corresponding detection limits were 8.80 ng mL-1 and 0.77 ng mL-1, respectively. The proposed aptasensor additionally displayed good selectivity and excellent stability. Moreover, its successful application in the analysis of clinical samples further demonstrated its utility. Therefore, the proposed platform has significant potential as a novel, facile, highly responsive, and low-cost monitoring method for the development of diabetes mellitus diagnostic devices intended for a clinical setting.

Immobilization-Free Electrochemical Sensor Coupled with a Graphene-Oxide-Based Aptasensor for Glycated Albumin Detection.

An immobilization-free electrochemical sensor coupled with a graphene oxide (GO)-based aptasensor was developed for glycated human serum albumin (GHSA) detection. The concentration of GHSA was monitored by measuring the electrochemical response of free GO and aptamer-bound GO in the presence of glycated albumin; their currents served as the analytical signals. The electrochemical aptasensor exhibited good performance with a base-10 logarithmic scale. The calibration curve was achieved in the range of 0.01-50 µg/mL. The limit of detection (LOD) was 8.70 ng/mL. The developed method was considered a one-drop measurement process because a fabrication step and the probe-immobilization process were not required. This simple sensor offers a cost-effective, rapid, and sensitive detection method, and could be an alternative approach for determination of GHSA levels.

Albuminuria detection using graphene oxide-mediated fluorescence quenching aptasensor.

A simple and sensitive graphene oxide-mediated fluorescence quenching aptasensor is developed to quantify albuminuria in urine samples. The developed aptasensor used the specific target binding property of aptamer and fluorescence quenching property of graphene oxide to determine the concentration of human serum albumin in urine. The limit of detection of the developed platform is 0.05 µg.mL-1 and the detection range is 0.1-600 µg.mL-1, which covers the albuminuria concentration range present in normal human urine and the urine of the patient with chronic kidney disease. This approach can be modified to measure albuminuria using a high-throughput quantification platform and portable point of care testing. In addition, the production cost for one reaction is cheaper than those for the standard automated method. Therefore, this aptasensor has significant potential for commercialization and public use.•Our protocol is customized by using the fluorescence quenching property of graphene oxide and specific binding property of human serum albumin aptamer to detect human serum albumin in urine sample•The limit of detection of our developed platform is 0.05 µg.mL-1•The detection range of our aptasensor is 0.1-600 µg.mL-1.

Roles of kininogen-1, basement membrane specific heparan sulfate proteoglycan core protein, and roundabout homolog 4 as potential urinary protein biomarkers in diabetic nephropathy.

Diabetic nephropathy, a major complication of diabetes mellitus (DM), is increasing worldwide and the large majority of patients have type 2 DM. Microalbuminuria has been used as a diagnostic marker of diabetic nephropathy. But owing to its insufficient sensitivity and specificity, other biomarkers are being sought. In addition, the pathophysiology of diabetic nephropathy is not fully understood and declines in renal function occur even without microalbuminuria. In this study, we investigated urinary proteins from three study groups (controls, and type 2 diabetic subjects with or without microalbuminuria). Non-targeted label-free Nano-LC QTOF analysis was conducted to discover underlying mechanisms and protein networks, and targeted label-free Nano-LC QTOF with SWATH was performed to qualify discovered protein candidates. Twenty-eight proteins were identified as candidates and functionally analyzed via String DB, gene ontology and pathway analysis. Four predictive mechanisms were analyzed: i) response to stimulus, ii) platelet activation, signaling and aggregation, iii) ECM-receptor interaction, and iv) angiogenesis. These mechanisms can provoke kidney dysfunction in type 2 diabetic patients via endothelial cell damage and glomerulus structural alteration. Based on these analyses, three proteins (kininogen-1, basement membrane-specific heparan sulfate proteoglycan core protein, and roundabout homolog 4) were proposed for further study as potential biomarkers. Our findings provide insights that may improve methods for both prevention and diagnosis of diabetic nephropathy.

Sensitive detection of albuminuria by graphene oxide-mediated fluorescence quenching aptasensor.

Albuminuria is a pathological condition wherein the human serum albumin (HSA) protein is present in abnormally excess amounts in the urine. A simple and sensitive graphene oxide-mediated fluorescence quenching aptasensor is developed to quantify albumin in urine samples and HSA in serum samples. The aptamer-bound HSA used in this aptasensor has hairpin structures, which are characteristic of the aptamer binding site. The limit of detection of the developed platform is 0.05 µg·mL-1 and the detection range is 0.1-14.0 µg·mL-1, which covers the albuminuria concentration range present in normal human urine and the urine of the patient with kidney diseases. This approach can be modified to measure HSA using a high-throughput quantification platform and portable point of care testing. In addition, the production cost for one reaction is cheaper than those for other standard automated methods. Therefore, this aptasensor has significant potential for commercialization and wide-scale public use.