Easy and Rapid Approach to Obtaining the Binding Affinity of Biomolecular Interactions Based on the Deep Learning Boost.

Recently, the deep learning (DL) dimension of artificial intelligence has received much attention from biochemical researchers and thus has gradually become the key approach adopted in the area of biosensing applications. Studies have shown that the use of DL techniques for sensing can not only shorten the time of data analysis but also significantly increase the accuracy of data analysis and prediction, resulting in the performance improvement of biosensing systems in comparison to conventional methods. However, obtaining reliable equilibrium and rate constants of biomolecular interactions during the detection process remains difficult and time-consuming to date. In this study, we propose a transformed model based on the deep transfer learning and sequence-to-sequence autoencoder that can successfully transfer the SPR sensorgram to the protein-binding constants, that is, the association rate constant (ka) and dissociation rate constant (kd), which provide crucial information to understand the mechanisms of drug action and the functional structures of biomolecules. Experimentally, we first trained and tested the pre-trained model using the Langmuir model which generated ideal SPR sensorgrams and then we fine-tuned the pre-trained model through the augmented SPR sensorgrams which were synthesized by using the synthesized minority oversampling technique (SMOTE) through the moderate-scale experiment. Next, the fine-tuned model was inputted with a short experimental SPR sensorgram that only needs 110 s, and the sensorgram was directly transformed into a reconstructed ideal sensorgram. Finally, the binding kinetic constants, that is, ka and kd, as outputs, were obtained through fitting the reconstructed ideal sensorgram. The results showed that the prediction errors of ka and kd obtained by our model were less than 12 and 24%, respectively. Based on the convenience, accuracy, and reliability of the proposed DL approach, we believe our strategy significantly boosts the feasibility to monitor the binding affinity of antibodies online during production.

Amplification-free Detection of Cytomegalovirus miRNA Using a Modification-free Surface Plasmon Resonance Biosensor.

Cytomegalovirus (CMV) is the most frequent cause of congenital infection worldwide; congenital CMV may lead to significant mortality, morbidity, or long-term sequelae, such as sensorineural hearing loss. The current study presents a newly designed surface plasmon resonance (SPR) biosensor for CMV-specific microRNAs that does not involve extra care for receptor immobilization or treatment to prevent fouling on bare gold surfaces. The modification-free approach, which utilizes a poly-adenine [poly(A)]-Au interaction, exhibited a high affinity that was comparable to that of the gold-sulfur (Au-S) interaction. In addition, magnetic nanoparticles (MNPs) were used to separate the analyte from complex sample matrixes that significantly reduced nonspecific adsorption. Moreover, the MNPs also played an important role in SPR signal amplification due to the binding-induced change in the refractive index. Our SPR biosensing platform was used successfully for the multi-detection of the microRNAs, UL22A-5p, and UL112-3p, which were associated with CMV. Our SPR biosensor offered the detection limits of 108 fM and 24 fM for UL22A-5p and UL112-3p, respectively, with an R2 of 0.9661 and 0.9985, respectively. The precision of this biosensor has an acceptable CV (coefficient of variation) value of <10%. In addition, our sensor is capable of discriminating between serum samples collected from healthy and CMV-infected newborns. Taken together, we believe that our newly developed SPR biosensing platform is a promising alternative for the diagnosis of CMV-specific microRNA in clinical settings, and its application for the detection of other miRNAs may be extended further.

Targeting triple-negative breast cancer with an aptamer-functionalized nanoformulation: a synergistic treatment that combines photodynamic and bioreductive therapies.

BACKGROUND: Areas of hypoxia are often found in triple-negative breast cancer (TNBC), it is thus more difficult to treat than other types of breast cancer, and may require combination therapies. A new strategy that combined bioreductive therapy with photodynamic therapy (PDT) was developed herein to improve the efficacy of cancer treatment. Our design utilized the characteristics of protoporphyrin IX (PpIX) molecules that reacted and consumed O2 at the tumor site, which led to the production of cytotoxic reactive oxygen species (ROS). The low microenvironmental oxygen levels enabled activation of a bioreductive prodrug, tirapazamine (TPZ), to become a toxic radical. The TPZ radical not only eradicated hypoxic tumor cells, but it also promoted therapeutic efficacy of PDT. RESULTS: To achieve the co-delivery of PpIX and TPZ for advanced breast cancer therapy, thin-shell hollow mesoporous Ia3d silica nanoparticles, designated as MMT-2, was employed herein. This nanocarrier designed to target the human breast cancer cell MDA-MB-231 was functionalized with PpIX and DNA aptamer (LXL-1), and loaded with TPZ, resulting in the formation of TPZ@LXL-1-PpIX-MMT-2 nanoVector. A series of studies confirmed that our nanoVectors (TPZ@LXL-1-PpIX-MMT-2) facilitated in vitro and in vivo targeting, and significantly reduced tumor volume in a xenograft mouse model. Histological analysis also revealed that this nanoVector killed tumor cells in hypoxic regions efficiently. CONCLUSIONS: Taken together, the synergism and efficacy of this new therapeutic design was confirmed. Therefore, we concluded that this new therapeutic strategy, which exploited a complementary combination of PpIX and TPZ, functioned well in both normoxia and hypoxia, and is a promising medical procedure for effective treatment of TNBC.

Diagnosing the RGS11 Lung Cancer Biomarker: The Integration of Competitive Immunoassay and Isothermal Nucleic Acid Exponential Amplification Reaction.

Lung cancer is the primary cause of cancer-associated mortality worldwide, which makes the identification of reliable lung cancer biomarkers a pressing need for early diagnosis and prognosis. RGS11, which is a regulator of G-protein signaling and also a lung cancer biomarker, plays an important role in cancer-related metastasis. However, trace levels of RGS11 (in the range of pg/mL) in serum samples make it difficult to quantify using currently available enzyme-linked immunosorbent assay (ELISA) kits and, therefore, this hinders progress in the discovery of new approaches for treating lung cancer. The aim of this study is to develop a rapid, sensitive, and reliable platform for the detection of RGS11 lung cancer biomarker based on a suspension immunoassay coupled with an isothermal exponential amplification strategy. Our study was initiated by the functionalization of magnetic beads with anti-RGS11 antibodies (Ab-MB) by EDC (1-ethyl-3-(3-(dimethylamino)propyl)-carbodiimide)/NHS ( N-hydroxysulfosuccinimide) activation. Ab-MB served as a sensing probe for the competitive immunorecognitions between known concentrations of His-tag RGS11 and unknown concentrations of target RGS11 in serum. The reporter anti-His antibodies, which were modified with primers that induced an isothermal exponential amplification reaction, were subsequently introduced to the reaction mixture that resulted in the formation of immunosandwich complexes. The exponentially amplified DNA duplex that was intercalated with SYBR Green was designated as a signal reporter for the assessment of RGS11 in an inversely proportional relationship. The sensing platform was excellent for the determination of RGS11 with an exceptional detection limit of 148 fg/mL and a linear dynamic range of 0.1-10 pg/mL using a minimal sample volume (20 µL) and with a reaction time of 1.5 h. In addition, we challenged the sensing platform with RGS11-spiked samples (in 2× diluted serum), and an acceptable recovery rate (>90%) was observed. Finally, 24 clinical samples acquired from patients with advanced lung cancer (C), inflammation (I), and heart failure (H) were analyzed by this newly developed sensing platform and a commercial ELISA kit for validation. This sensing platform has potential in biomedical applications for clinically diagnosing liquid biopsy samples for patients with lung cancer. Moreover, the universal design of our proposed system is easily adapted to detect any other protein if a His-tag recombinant protein is available.

Simple Strategy for Rapid and Sensitive Detection of Avian Influenza A H7N9 Virus Based on Intensity-Modulated SPR Biosensor and New Generated Antibody.

In 2013 a new reassortant avian influenza A H7N9 virus emerged in China, causing human infection with high mortality. An accurate and timely diagnosis is crucial for controlling the outbreaks of the disease. We therefore propose a simple strategy for rapidly and sensitively detecting the H7N9 virus using an intensity-modulated surface plasmon resonance (IM-SPR) biosensor integrated with a new generated monoclonal antibody. The novel antibody exhibits significant specificity to recognize H7N9 virus compared with other clinical human influenza isolates (p < 0.01). Experimentally, the detection limit of the proposed approach for H7N9 virus detection is estimated to be 144 copies/mL, which is a 20-fold increase in sensitivity compared with homemade target-captured ELISA using the identical antibody. For the measurement of mimic clinical specimens containing the H7N9 virus mixed with nasal mucosa from flu-like syndrome patients, the detection limit is calculated to be 402 copies/mL, which is better than conventional influenza detection assays; quantitative reverse transcription polymerase chain reaction (qRT-PCR) and rapid influenza diagnostic test (RIDT). Most importantly, the assay time took less than 10 min. Combined, the results of this study indicate that the proposed simple strategy demonstrates high sensitivity and time-saving in H7N9 virus detection. By incorporating a high specific recognizer, the proposed technique has the potential to be used in applications and development of other emerging or re-emerging microbe detection platforms.

Rapid and highly sensitive method for influenza A (H1N1) virus detection.

In this study, we applied the developed paired surface plasma waves biosensor (PSPWB) in a dual-channel biosensor for rapid and sensitive detection of swine-origin influenza A (H1N1) virus (S-OIV). In conjunction with the amplitude ratio of the signal and the reference channel, the stability of the PSPWB system is significantly improved experimentally. The theoretical limit of detection (LOD) of the dual-channel PSPWB for S-OIV is 30 PFU/mL (PFU, plaque-forming unit), which was calculated from the fitting curve of the surface plasmon resonance signal with a S-OIV clinical isolate concentration in phosphate-buffered saline (PBS) over a range of 18-1.8 × 10(6) PFU/mL. The LOD is 2 orders of magnitude more sensitive than the commercial rapid influenza diagnostic test at worst and an order of magnitude less sensitive than real-time quantitative polymerase chain reaction (PCR) whose LOD for S-OIV in PBS was determined to be 3.5 PFU/mL in this experiment. Furthermore, under in vivo conditions, this experiment demonstrates that the assay successfully measured S-OIV at a concentration of 1.8 × 10(2) PFU/mL in mimic solution, which contained PBS-diluted normal human nasal mucosa. Most importantly, the assay time took less than 20 min. From the results, the dual-channel PSPWB potentially offers great opportunity in developing an alternative PCR-free diagnostic method for rapid, sensitive, and accurate detection of viral pathogens with epidemiological relevance in clinical samples by using an appropriate pathogen-specific antibody.

Bi2O2Se-Based True Random Number Generator for Security Applications.

The fast development of the Internet of things (IoT) promises to deliver convenience to human life. However, a huge amount of the data is constantly generated, transmitted, processed, and stored, posing significant security challenges. The currently available security protocols and encryption techniques are mostly based on software algorithms and pseudorandom number generators that are vulnerable to attacks. A true random number generator (TRNG) based on devices using stochastically physical phenomena has been proposed for auditory data encryption and trusted communication. In the current study, a Bi2O2Se-based memristive TRNG is demonstrated for security applications. Compared with traditional metal-insulator-metal based memristors, or other two-dimensional material-based memristors, the Bi2O2Se layer as electrode with non-van der Waals interface, high carrier mobility, air stability, extreme low thermal conductivity, as well as vertical surface resistive switching shows intrinsic stochasticity and complexity in a memristive true analogue/digital random number generation. Moreover, those analogue/digital random number generation processes are proved to be resilient for machine learning prediction.

Binding kinetics of biomolecule interaction at ultralow concentrations based on gold nanoparticle enhancement.

Measuring the kinetic constants of protein-protein interactions at ultralow concentrations becomes critical in characterizing biospecific affinity, and exploring the feasibility of clinical diagnosis with respect to detection sensitivity, efficiency and accuracy. In this study, we propose a method that can calculate the binding constants of protein-protein interactions in sandwich assays at ultralow concentrations at the pg/mL level, using a localized surface plasmon coupled fluorescence fiber-optic biosensor (LSPCF-FOB). We discuss a two-compartment model to achieve reaction-limited kinetics under the stagnant conditions of the reaction chamber. The association rate constant, dissociation rate constant, and the equilibrium dissociation constant, that is, k(a), k(d), K(D), respectively, of the kinetics of binding between total prostate-specific antigen (t-PSA) and anti-t-PSA at concentrations from 0.1 pg/mL to 1 ng/mL, were measured either in PBS or in human serum. This is the first time that k(a), k(d), and K(D) have been measured at such a low concentration range in a complex sample such as human serum.

Discrimination of breast cancer by measuring prostate-specific antigen levels in women's serum.

Prostate-specific antigen (PSA) has been reported to be a potential biomarker of breast cancer. Serum PSA of normal women is around 1 pg/mL, which is usually undetectable by current assay methods; thus an ultrasensitive measurement of PSA expression in women's serum is necessary to distinguish normal from malignant breast diseases. To enhance the sensitivity of conventional immunoassay technology for the detection of PSA in sera, we adopted a localized surface plasmon coupled fluorescence fiber-optic biosensor, which combines a sandwich immunoassay with the localized surface plasmon technique. The concentration of total PSA (t-PSA) (from 0.1 to 1000 pg/mL) in phosphate-buffered saline solution and the normalized fluorescence signal exhibit a linear relationship where the correlation coefficient is 0.9574. In addition, the concentration of additional t-PSA in 10-fold-diluted healthly women's serum across a similar range was measured. The correlation coefficient for this measurement is 0.9142. In clinical serum samples, moreover, the experimental results of t-PSA detection show that both the mean value and median of normalized fluorescence signals in the breast cancer group (155.2 and 145.7, respectively) are higher than those in the noncancer group (46.6 and 37.1, respectively). We also examined the receiver operating characteristic curve for t-PSA, and the area under the curve (AUC) is estimated to be 0.9063, the AUC being used to measure the performance of a test to correctly identify diseased and nondiseased subjects.

Enhanced Plasmonic Biosensor Utilizing Paired Antibody and Label-Free Fe3O4 Nanoparticles for Highly Sensitive and Selective Detection of Parkinson's α-Synuclein in Serum.

Parkinson's disease (PD) is an acute and progressive neurodegenerative disorder, and diagnosis of the disease at its earliest stage is of paramount importance to improve the life expectancy of patients. α-Synuclein (α-syn) is a potential biomarker for the early diagnosis of PD, and there is a great need to develop a biosensing platform that precisely detects α-syn in human body fluids. Herein, we developed a surface plasmon resonance (SPR) biosensor based on the label-free iron oxide nanoparticles (Fe3O4 NPs) and paired antibody for the highly sensitive and selective detection of α-syn in serum samples. The sensitivity of the SPR platform is enhanced significantly by directly depositing Fe3O4 NPs on the Au surface at a high density to increase the decay length of the evanescent field on the Au film. Moreover, the utilization of rabbit-type monoclonal antibody (α-syn-RmAb) immobilized on Au films allows the SPR platform to have a high affinity-selectivity binding performance compared to mouse-type monoclonal antibodies as a common bioreceptor for capturing α-syn molecules. As a result, the current platform has a detection limit of 5.6 fg/mL, which is 20,000-fold lower than that of commercial ELISA. The improved sensor chip can also be easily regenerated to repeat the α-syn measurement with the same sensitivity. Furthermore, the SPR sensor was applied to the direct analysis of α-syn in serum samples. By using a format of paired α-syn-RmAb, the SPR sensor provides a recovery rate in the range from 94.5% to 104.3% to detect the α-syn in diluted serum samples precisely. This work demonstrates a highly sensitive and selective quantification approach to detect α-syn in human biofluids and paves the way for the future development in the early diagnosis of PD.

Machine Learning Approaches to Predict In-Hospital Mortality among Neonates with Clinically Suspected Sepsis in the Neonatal Intensive Care Unit.

BACKGROUND: preterm and critically ill neonates often experience clinically suspected sepsis during their prolonged hospitalization in the neonatal intensive care unit (NICU), which can be the initial sign of final adverse outcomes. Therefore, we aimed to utilize machine learning approaches to predict neonatal in-hospital mortality through data-driven learning. METHODS: a total of 1095 neonates who experienced clinically suspected sepsis in a tertiary-level NICU in Taiwan between August 2017 and July 2020 were enrolled. Clinically suspected sepsis was defined based on clinical features and laboratory criteria and the administration of empiric antibiotics by clinicians. The variables used for analysis included patient demographics, clinical features, laboratory data, and medications. The machine learning methods used included deep neural network (DNN), k-nearest neighbors, support vector machine, random forest, and extreme gradient boost. The performance of these models was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: the final in-hospital mortality of this cohort was 8.2% (90 neonates died). A total of 765 (69.8%) and 330 (30.2%) patients were randomly assigned to the training and test sets, respectively. Regarding the efficacy of the single model that most accurately predicted the outcome, DNN exhibited the greatest AUC (0.923, 95% confidence interval [CI] 0.953-0.893) and the best accuracy (95.64%, 95% CI 96.76-94.52%), Cohen's kappa coefficient value (0.74, 95% CI 0.79-0.69) and Matthews correlation coefficient value (0.75, 95% CI 0.80-0.70). The top three most influential variables in the DNN importance matrix plot were the requirement of ventilator support at the onset of suspected sepsis, the feeding conditions, and intravascular volume expansion. The model performance was indistinguishable between the training and test sets. CONCLUSIONS: the DNN model was successfully established to predict in-hospital mortality in neonates with clinically suspected sepsis, and the machine learning algorithm is applicable for clinicians to gain insights and have better communication with families in advance.

Detection of prostate-specific antigen with a paired surface plasma wave biosensor.

In this study, we demonstrated that an amplitude-sensitive paired surface plasma wave biosensor (PSPWB) is capable of real-time detection of prostate-specific antigen (PSA) in diluted human serum without labeling. Experimentally, the detection limit of PSPWB was 8.4 x 10(-9) refractive index unit (RIU) and the PSPWB could measure PSA in a phosphate buffered saline solution from 10 fg/mL ( approximately 300 aM) to 100 pg/mL ( approximately 3 pM) successfully, with demonstration of a linear relationship between PSA concentrations and surface plasmon resonance (SPR) signals. Therefore, results were obtained over a wide dynamic range 5 orders of magnitude for analyte concentration. In addition, the PSPWB successfully detected PSA in diluted human serum as well. These experimental results indicate that the PSPWB is capable of detection with high sensitivity over a wide range by using SPR-based biosensors and has a capability of detecting biological analytes in clinical sample without complicated operating procedures.

Diagnostic detection of human lung cancer-associated antigen using a gold nanoparticle-based electrochemical immunosensor.

The development of rapid and sensitive methods for the detection of immunogenic tumor-associated antigen is important not only for understanding their roles in cancer immunology but also for the development of clinical diagnostics. Alpha-enolase (ENO1), a p48 molecule, is widely distributed in a variety of tissues, whereas gamma-enolase (ENO2) and beta-enolase (ENO3) are found exclusively in neuron/neuroendocrine and muscle tissues, respectively. Because ENO1 has been correlated with small cell lung cancer, nonsmall cell lung cancer, and head and neck cancer, it can be used as a potential diagnostic marker for lung cancer. In this study, we developed a simple, yet novel and sensitive, electrochemical sandwich immunosensor for the detection of ENO1; it operates through physisorption of anti-ENO1 monoclonal antibody on polyethylene glycol-modified disposable screen-printed electrode as the detection platform, with polyclonal secondary anti-ENO1-tagged, gold nanoparticle (AuNP) congregates as electrochemical signal probes. The immunorecognition of the sample ENO1 by the congregated AuNP@antibody occurred on the surface of the electrodes; the electrochemical signal from the bound AuNP congregates was obtained after oxidizing them in 0.1 M HCl at 1.2 V for 120 s, followed by the reduction of AuCl(4-) in square wave voltammetry (SWV) mode. The resulting sigmoidally shaped dose-response curves possessed a linear dynamic working range from 10(-8) to 10(-12) g/mL. This AuNP congregate-based assay provides an amplification approach for detecting ENO1 at trace levels, leading to a detection limit as low as 11.9 fg (equivalent to 5 microL of a 2.38 pg/mL solution).

Quantitative measurement of binding kinetics in sandwich assay using a fluorescence detection fiber-optic biosensor.

Fiber-optic biosensors have been studied intensively because they are very useful and important tools for monitoring biomolecular interactions. Here we describe a fluorescence detection fiber-optic biosensor (FD-FOB) using a sandwich assay to detect antibody-antigen interaction. In addition, the quantitative measurement of binding kinetics, including the association and dissociation rate constants for immunoglobulin G (IgG)/anti-mouse IgG, is achieved, indicating 0.38 x 10(6) M(-1) s(-1) for k(a) and 3.15 x 10(-3) s(-1) for k(d). These constants are calculated from the fluorescence signals detected on fiber surface only where the excited evanescent wave can be generated. Thus, a confined fluorescence-detecting region is achieved to specifically determine the binding kinetics at the vicinity of the interface between sensing materials and uncladded fiber surface. With this FD-FOB, the mathematical deduction and experimental verification of the binding kinetics in a sandwich immunoassay provide a theoretical basis for measuring rate constants and equilibrium dissociation constants. A further measurement to study the interaction between human heart-type fatty acid-binding protein and its antibody gave the calculated kinetic constants k(a), k(d), and K(D) as 8.48 x 10(5) M(-1) s(-1), 1.7 x 10(-3) s(-1), and 2.0 nM, respectively. Our study is the first attempt to establish a theoretical basis for the florescence-sensitive immunoassay using a sandwich format. Moreover, we demonstrate that the FD-FOB as a high-throughput biosensor can provide an alternative to the chip-based biosensors to study real-time biomolecular interaction.

Differential-phase surface plasmon resonance biosensor.

In this paper, a novel differential-phase-sensitive surface plasmon resonance biosensor (DP-SPRB) is proposed and developed, in which a two-frequency laser is integrated with a differential amplifier in order to analytically convert the phase modulation into amplitude modulation. With the use of the conventional envelope detection technique, the differential phase is precisely decoded in real time in terms of the demodulated amplitude. In order to verify high detection sensitivity of the DP-SPRB, a sucrose-water solution and glycerin-water solution at low concentrations were both tested, and the experimental results confirm that the detection sensitivity on wt % concentration of the sucrose solution is 0.00001%. Moreover, the real-time monitoring mouse IgG/antimouse IgG interaction shows the minimum concentration of mouse IgG to be at 10 fg/mL. To our knowledge, this is the highest sensitivity ever measured by a surface plasmon resonance biosensor. However, because of the limited dynamic range of DP-SPRB, it can only apply to biomolecule interactions at extremely low concentration.

Polarized photon-pairs heterodyne polarimetry for ultrasensitive optical activity detection of a chiral medium.

A polarized photon-pairs heterodyne polarimetry is proposed in order to measure in an ultrasensitive manner the circular birefringence of a chiral medium via optical rotation detection. A balanced detector is integrated into this polarimeter. Thus, shot-noise-limited detection by this polarimeter can be achieved. Experimentally, the detection sensitivity for the circular birefringence of a glucose-water solution up to partial differential |n(r) - n(l)| = 2 x 10(-11) at 10 mg/dL is verified. To our knowledge, this is the highest sensitivity ever measured of a chiral liquid solution based on single traveling sample cell geometry. Finally, when compared to a fiber loop ring-resonator in the frequency domain for a chiral liquid, this polarimeter shows an order of 10(4) enhancement on the sensitivity of natural optical activity measurement.

Tyramine detection using PEDOT:PSS/AuNPs/1-methyl-4-mercaptopyridine modified screen-printed carbon electrode with molecularly imprinted polymer solid phase extraction.

Tyramine (4-hydroxyphenethylamine), which is a monoamine metabolized by monoamine oxidase (MAO), exists widely in plants, animals, fermented foods, and salted foods. The incidence of hypertension, or "cheese effect", which is associated with a large dietary intake of tyramine while taking MAO inhibitors has been reported; therefore, the measurement of tyramine is an urgent concern. Herein, an efficient approach that integrates a molecular imprinting polymer for solid phase extraction (MISPE) technique with a sensitive electrochemical sensing platform (SPCE/PEDOT: PSS/AuNP/1-m-4-MP) for the quantification of tyramine is presented. Enhanced electrode conductivity was achieved sequentially by constructing a conductive polymer (PEDOT: PSS) on a screen-printed carbon electrode (SPCE), followed by electrodeposition with gold nanoparticles (AuNPs) and, finally, by modification with positively charged 1-methyl-4-mercaptopyridine (1-m-4-MP) using an Au-S bond. Tyramine was isolated selectively and pre-concentrated by the MISPE technique; electroanalysis that used differential pulse voltammetry (DPV) in NaOH (0.1M, pH 13) was conducted successively. Experimental parameters (such as modes of electrode modification, ratio of PEDOT: PSS, pH of electrolyte, time required for AuNP deposition, and 1-m-4-MP concentrations) that were associated with optimal detection conditions were evaluated also. We obtained a linear concentration range (5-100nM, R2=0.9939) with LOD and sensitivity at 2.31nM, and 3.11µAnM-1cm-2, respectively. The applicability of our technique was demonstrated by analyzing tyramine in spiked serum and milk. The feature of our newly developed analytical methods that coupled sample pre-treatment (sample clean-up and pre-concentration) with sensitive detection makes it a promising tool for quantifying of tyramine.

An innovative application of time-domain spectroscopy on localized surface plasmon resonance sensing.

White-light scanning interferometry (WLSI) is often used to study the surface profiles and properties of thin films because the strength of the technique lies in its ability to provide fast and high resolution measurements. An innovative attempt is made in this paper to apply WLSI as a time-domain spectroscopic system for localized surface plasmon resonance (LSPR) sensing. A WLSI-based spectrometer is constructed with a breadboard of WLSI in combination with a spectral centroid algorithm for noise reduction and performance improvement. Experimentally, the WLSI-based spectrometer exhibits a limit of detection (LOD) of 1.2 × 10-3 refractive index units (RIU), which is better than that obtained with a conventional UV-Vis spectrometer, by resolving the LSPR peak shift. Finally, the bio-applicability of the proposed spectrometer was investigated using the rs242557 tau gene, an Alzheimer's and Parkinson's disease biomarker. The LOD was calculated as 15 pM. These results demonstrate that the proposed WLSI-based spectrometer could become a sensitive time-domain spectroscopic biosensing platform.

Use of liposomal amplifiers in total internal reflection fluorescence fiber-optic biosensors for protein detection.

Evanescent-wave excited fluorescence technology has been demonstrated to enhance sensitivity and reduce matrix effects, making it suitable for biosensor development. In this study, we developed a liposome-based, total internal reflection fluorescence, fiber-optic biosensor (TIRF-FOB) for protein detection, which integrates a liposomal amplifier and sandwich immunoassay format with TIRF-FOB. In addition, the antibody-tagged and fluorophore-entrapped liposomes for heterogeneous detection of target molecules were designed and synthesized. This biosensor successfully detected the target protein (model analyzed here is IgG) with a limit of detection (LOD) of 2.0 attomoles for the target protein (equivalent to 2.0 pg/mL of protein presented in 150 µL of sample solution). The features of this ultra-sensitive liposomal TIRF-FOB are (i) fluorescence is excited via evanescent waves and amplified via liposomes; (ii) the use of two polyclonal antibodies in the sandwich assay format increases the specificity and lowers the cost of our assay. Based on the exceptional detection sensitivity and cost-effectiveness, we believe that the proposed biosensor has great potential as a practical, clinical diagnostic tool in the near future.

Diagnosis of human metapneumovirus in patients hospitalized with acute lower respiratory tract infection using a metal-enhanced fluorescence technique.

Human metapneumovirus (hMPV) is a common respiratory tract infection in children. However, conventional immunofluorescence assays (IFAs) for detecting hMPV in respiratory samples have limited reliability with a sensitivity and false-negative predictive value of 58.1% and approximately 17.8%, respectively. In this study, hMPV was measured in 91 clinical respiratory samples (55 sputum and 36 nasopharyngeal aspirate samples), which were obtained from children under three years of age, utilizing our previously developed high-throughput metal-enhanced fluorescence (MEF)-based biosensor (HT-MEFB). The sensitivity of HT-MEFB for hMPV detection in the 91 samples was improved by up to 77.4% compared with that obtained with IFAs, and the specificity of HT-MEFB for hMPV detection was 91.7%. In addition, the specificity and accuracy obtained after the selection of 55 sputum samples as the analyzed specimen reached 92.3% and 90.9%, respectively. Thus, in terms of accuracy, high throughput, and sensitivity, HT-MEFB exhibits considerable potential for hMPV detection in clinical settings.