Application of Fiber Loop Ringdown Spectroscopy Technique for a New Approach to Beta-Amyloid Monitoring for Alzheimer Disease's Early Detection

A novel fiber optic biosensor was purposed for a new approach to monitor amyloid beta protein fragment 1-42 (Aβ42) for Alzheimer's Disease (AD) early detection. The sensor was fabricated by etching a part of fiber from single mode fiber loop in pure hydrofluoric acid solution and utilized as a Local Optical Refractometer (LOR) to monitor the change Aβ42 concentration in Artificial Cerebrospinal Fluid (ACSF). The Fiber Loop Ringdown Spectroscopy (FLRDS) technique is an ultra-sensitive measurement technique with low-cost, high sensitivity, real-time measurement, continuous measurement and portability features that was utilized with a fiber optic sensor for the first time for the detection of a biological signature in an ACSF environment. Here, the measurement is based on the total optical loss detection when specially fabricated sensor heads were immersed into ACSF solutions with and without different concentrations of Aβ42 biomarkers since the bulk refractive index change was performed. Baseline stability and the reference ring down times of the sensor head were measured in the air as 0.87% and 441.6 μs  3.9 μs, respectively. Afterward, the total optical loss of the system was measured when the sensor head was immersed in deionized water, ACSF solution, and ACSF solutions with Aβ42 in different concentrations. The lowest Aβ42 concentration of 2 ppm was detected by LOR. Results showed that LOR fabricated by single-mode fibers for FLRDS system design are promising candidates to be utilized as fiber optic biosensors after sensor head modification and have a high potential for early detection applications of not only AD but possibly also several fatal diseases such as diabetes and cancer.

Outer-Surface Functionalized Solid-State Nanochannels for Enhanced Sensing Properties: Progress and Perspective

Solid-state nanochannel-based sensing systems have been established as vigorous tools for sensing plentiful biomarkers due to their label-free, highly sensitive, and high-throughput screening. However, research on solid-state nanochannels has predominantly centered on the functional groups modified on the inner wall, neglecting investigations into the outer surface. Actually, the outer surface, as a part of the nanochannels, also plays a key role in regulating ionic current. When the target nears the entrance of the nanochannel and prepares to pass through, it would also interact with functional groups located on the nanochannel's outer surface, leading to subsequent alterations in the ionic current. Recently, the probes on the outer surface have experimentally demonstrated their ability to independently regulate ionic current, unveiling advantages in in situ target detection, especially for targets larger than the diameter of the nanochannels that cannot pass through them. Here, we review the progress over the past decade in nanochannels featuring diverse outer-surface functionalization aimed at enhanced sensing performance, including charge modification, wettability adjustment, and probe immobilization. In addition, we present the promises and challenges posed by outer-surface functionalized nanochannels and discuss possible directions for their future deployments.

Whispers in the Blood: Leveraging MicroRNAs for Unveiling Autologous Blood Doping in Athletes

The prevalence of autologous blood transfusions (ABTs) presents a formidable challenge in maintaining fair competition in sports, as it significantly enhances hemoglobin mass and oxygen capacity. In recognizing ABT as a prohibited form of doping, the World Anti-Doping Agency (WADA) mandates stringent detection methodologies. While current methods effectively identify homologous erythrocyte transfusions, a critical gap persists in detecting autologous transfusions. The gold standard practice of longitudinally monitoring hematological markers exhibits promise but is encumbered by limitations. Despite its potential, instances of blood doping often go undetected due to the absence of definitive verification processes. Moreover, some cases remain unpenalized due to conservative athlete-sanctioning approaches. This gap underscores the imperative need for a more reliable and comprehensive detection method capable of unequivocally differentiating autologous transfusions, addressing the challenges faced in accurately identifying such prohibited practices. The development of an advanced detection methodology is crucial to uphold the integrity of anti-doping measures, effectively identifying and penalizing instances of autologous blood transfusion. This, in turn, safeguards the fairness and equality essential to competitive sports. Our review tackles this critical gap by harnessing the potential of microRNAs in ABT doping detection. We aim to summarize alterations in the total microRNA profiles of erythrocyte concentrates during storage and explore the viability of observing these changes post-transfusion. This innovative approach opens avenues for anti-doping technologies and commercialization, positioning it as a cornerstone in the ongoing fight against doping in sports and beyond. The significance of developing a robust detection method cannot be overstated, as it ensures the credibility of anti-doping efforts and promotes a level playing field for all athletes.

Wearable Sensor Patch with Hydrogel Microneedles for In Situ Analysis of Interstitial Fluid

Continuous real-time monitoring of biomarkers in interstitial fluid is essential for tracking metabolic changes and facilitating the early detection and management of chronic diseases such as diabetes. However, developing minimally invasive sensors for the in situ analysis of interstitial fluid and addressing signal delays remain a challenge. Here, we introduce a wearable sensor patch incorporating hydrogel microneedles for rapid, minimally invasive collection of interstitial fluid from the skin while simultaneously measuring biomarker levels in situ. The sensor patch is stretchable to accommodate the swelling of the hydrogel microneedles upon extracting interstitial fluid and adapts to skin deformation during measurements, ensuring consistent sensing performance in detecting model biomarker concentrations, such as glucose and lactate, in a mouse model. The sensor patch exhibits in vitro sensitivities of 0.024 ± 0.002 μA mM-1 for glucose and 0.0030 ± 0.0004 μA mM-1 for lactate, with corresponding linear ranges of 0.1-3 and 0.1-12 mM, respectively. For in vivo glucose sensing, the sensor patch demonstrates a sensitivity of 0.020 ± 0.001 μA mM-1 and a detection range of 1-8 mM. By integrating a predictive model, the sensor patch can analyze and compensate for signal delays, improving calibration reliability and providing guidance for potential optimization in sensing performance. The sensor patch is expected to serve as a minimally invasive platform for the in situ analysis of multiple biomarkers in interstitial fluid, offering a promising solution for continuous health monitoring and disease management.

Undifferentially Expressed CXXC5 as a Transcriptionally Regulatory Biomarker of Breast Cancer

This work hypothesizes that some genes undergo radically changed transcription regulations (TRs) in breast cancer (BC), but don't show differential expressions for unknown reasons. The TR of a gene is quantitatively formulated by a regression model between the expression of this gene and multiple transcription factors (TFs). The difference between the predicted and real expression levels of a gene in a query sample is defined as the mqTrans value of this gene, which quantitatively reflects its regulatory changes. This work systematically screens the undifferentially expressed genes with differentially expressed mqTrans values in 1036 samples across five datasets and three ethnic groups. This study calls the 25 genes satisfying the above hypothesis in at least four datasets as dark biomarkers, and the strong dark biomarker gene CXXC5 (CXXC Finger Protein 5) is even supported by all the five independent BC datasets. Although CXXC5 does not show differential expressions in BC, its transcription regulations show quantitative associations with BCs in diversified cohorts. The overlapping long noncoding RNAs (lncRNAs) may have contributed their transcripts to the expression miscalculations of dark biomarkers. The mqTrans analysis serves as a complementary view of the transcriptome-based detections of biomarkers that are ignored by many existing studies.

Amphiphilic Particle-Stabilized Nanoliter Droplet Reactors with a Multimodal Portable Reader for Distributive Biomarker Quantification

Compartmentalization, leveraging microfluidics, enables highly sensitive assays, but the requirement for significant infrastructure for their design, build, and operation limits access. Multimaterial particle-based technologies thermodynamically stabilize monodisperse droplets as individual reaction compartments with simple liquid handling steps, precluding the need for expensive microfluidic equipment. Here, we further improve the accessibility of this lab on a particle technology to resource-limited settings by combining this assay system with a portable multimodal reader, thus enabling nanoliter droplet assays in an accessible platform. We show the utility of this platform in measuring N-terminal propeptide B-type natriuretic peptide (NT-proBNP), a heart failure biomarker, in complex medium and patient samples. We report a limit of detection of ∼0.05 ng/mL and a linear response between 0.2 and 2 ng/mL in spiked plasma samples. We also show that, owing to the plurality of measurements per sample, "swarm" sensing acquires better statistical quantitation with a portable reader. Monte Carlo simulations show the increasing capability of this platform to differentiate between negative and positive samples, i.e., below or above the clinical cutoff for acute heart failure (∼0.1 ng/mL), as a function of the number of particles measured. Our platform measurements correlate with gold standard ELISA measurement in cardiac patient samples, and achieve lower variation in measurement across samples compared to the standard well plate-based ELISA. Thus, we show the capabilities of a cost-effective droplet-reader system in accurately measuring biomarkers in nanoliter droplets for diseases that disproportionately affect underserved communities in resource-limited settings.

Using Machine Learning and Silver Nanoparticle-Based Surface-Enhanced Raman Spectroscopy for Classification of Cardiovascular Disease Biomarkers

Characterizing complex biofluids using surface-enhanced Raman spectroscopy (SERS) coupled with machine learning (ML) has been proposed as a powerful tool for point-of-care detection of clinical disease. ML is well-suited to categorizing otherwise uninterpretable, patient-derived SERS spectra that contain a multitude of low concentration, disease-specific molecular biomarkers among a dense spectral background of biological molecules. However, ML can generate false, non-generalizable models when data sets used for model training are inadequate. It is thus critical to determine how different SERS experimental methodologies and workflow parameters can potentially impact ML disease classification of clinical samples. In this study, a label-free, broadband, Ag nanoparticle-based SERS platform was coupled with ML to assess simulated clinical samples for cardiovascular disease (CVD), containing randomized combinations of five key CVD biomarkers at clinically relevant concentrations in serum. Raman spectra obtained at 532, 633, and 785 nm from up to 300 unique samples were classified into physiological and pathological categories using two standard ML models. Label-free SERS and ML could correctly classify randomized CVD samples with high accuracies of up to 90.0% at 532 nm using as few as 200 training samples. Spectra obtained at 532 nm produced the highest accuracies with no significant increase achieved using multiwavelength SERS. Sample preparation and measurement methodologies (e.g., different SERS substrate lots, sample volumes, sample sizes, and known variations in randomization and experimental handling) were shown to strongly influence the ML classification and could artificially increase classification accuracies by as much as 27%. This detailed investigation into the proper application of ML techniques for CVD classification can lead to improved data set acquisition required for the SERS community, such that ML on labeled and robust SERS data sets can be practically applied for future point-of-care testing in patients.

Extraordinarily Stable Hairpin-Based Biosensors for Rapid Detection of DNA Ligases

DNA ligases are essential enzymes involved in DNA replication and repair processes in all organisms. These enzymes seal DNA breaks by catalyzing the formation of phosphodiester bonds between juxtaposed 5' phosphate and 3' hydroxyl termini in double-stranded DNA. In addition to their critical roles in maintaining genomic integrity, DNA ligases have been recently identified as diagnostic biomarkers for several types of cancers and recognized as potential drug targets for the treatment of various diseases. Although DNA ligases are significant in basic research and medical applications, developing strategies for efficiently detecting and precisely quantifying these crucial enzymes is still challenging. Here, we report our design and fabrication of a highly sensitive and specific biosensor in which a stable DNA hairpin is utilized to stimulate the generation of fluorescence signals. This probe is verified to be stable under a wide range of experimental conditions and exhibits promising performance in detecting DNA ligases. We anticipate that this hairpin-based biosensor will significantly benefit the development of new targeting strategies and diagnostic tools for certain diseases.

Heterometallic ZnHoMOF as a Dual-Responsive Luminescence Sensor for Efficient Detection of Hippuric Acid Biomarker and Nitrofuran Antibiotics

Developing efficient and sensitive MOF-based luminescence sensors for bioactive molecule detection is of great significance and remains a challenge. Benefiting from favorable chemical and thermal stability, as well as excellent luminescence performance, a porous Zn(II)Ho(III) heterometallic-organic framework (ZnHoMOF) was selected here as a bifunctional luminescence sensor for the early diagnosis of a toluene exposure biomarker of hippuric acid (HA) through "turn-on" luminescence enhancing response and the daily monitoring of NFT/NFZ antibiotics through "turn-off" quenching effects in aqueous media with high sensitivity, acceptable selectivity, good anti-interference, exceptional recyclability performance, and low detection limits (LODs) of 0.7 ppm for HA, 0.04 ppm for NFT, and 0.05 ppm for NFZ. Moreover, the developed sensor was employed to quantify HA in diluted urine samples and NFT/NFZ in natural river water with satisfactory results. In addition, the sensing mechanisms of ZnHoMOF as a dual-response chemosensor in efficient detection of HA and NFT/NFZ antibiotics were conducted from the view of photo-induced electron transfer (PET), as well as inner filter effects (IFEs), with the help of time-dependent density functional theory (TD-DFT) and spectral overlap experiments.

Editorial: The Application of Proteogenomics to Urine Analysis for the Identification of Novel Biomarkers of Prostate Cancer: An Exploratory Study

In this editorial context, we aim to leverage the potential of proteogenomics, which integrates genomic and proteomic data, to discover novel biomarkers that can aid in the diagnosis and management of prostate cancer. We highlight the importance of proteogenomics for understanding the functional consequences of somatic mutations in cancer and demonstrating how proteogenomic analysis can provide insights into the effects of genetic alterations on the proteomic landscape and identify potential therapeutic targets. This article also emphasizes the potential of urine analysis for the detection of prostate cancer. Overall, our editorial paper provides general insights on the application of proteogenomics to urine analysis for the identification of novel biomarkers of prostate cancer.

Nanotechnology boosts the efficiency of tumor diagnosis and therapy

The incidence and mortality of cancer are gradually increasing. The highly invasive and metastasis of tumor cells increase the difficulty of diagnosis and treatment, so people pay more and more attention to the diagnosis and treatment of cancer. Conventional treatment methods, including surgery, radiotherapy and chemotherapy, are difficult to eliminate tumor cells completely. And the emergence of nanotechnology has boosted the efficiency of tumor diagnosis and therapy. Herein, the research progress of nanotechnology used for tumor diagnosis and treatment is reviewed, and the emerging detection technology and the application of nanodrugs in clinic are summarized and prospected. The first part refers to the application of different nanomaterials for imaging in vivo and detection in vitro, which includes magnetic resonance imaging, fluorescence imaging, photoacoustic imaging and biomarker detection. The distinctive physical and chemical advantages of nanomaterials can improve the detection sensitivity and accuracy to achieve tumor detection in early stage. The second part is about the nanodrug used in clinic for tumor treatment. Nanomaterials have been widely used as drug carriers, including the albumin paclitaxel, liposome drugs, mRNA-LNP, protein nanocages, micelles, membrane nanocomplexes, microspheres et al., which could improve the drug accumulate in tumor tissue through enhanced permeability and retention effect to kill tumor cells with high efficiency. But there are still some challenges to revolutionize traditional tumor diagnosis and anti-drug resistance based on nanotechnology.

Emerging Microfluidic Devices for Sample Preparation of Undiluted Whole Blood to Enable the Detection of Biomarkers

Blood testing allows for diagnosis and monitoring of numerous conditions and illnesses; it forms an essential pillar of the health industry that continues to grow in market value. Due to the complex physical and biological nature of blood, samples must be carefully collected and prepared to obtain accurate and reliable analysis results with minimal background signal. Examples of common sample preparation steps include dilutions, plasma separation, cell lysis, and nucleic acid extraction and isolation, which are time-consuming and can introduce risks of sample cross-contamination or pathogen exposure to laboratory staff. Moreover, the reagents and equipment needed can be costly and difficult to obtain in point-of-care or resource-limited settings. Microfluidic devices can perform sample preparation steps in a simpler, faster, and more affordable manner. Devices can be carried to areas that are difficult to access or that do not have the resources necessary. Although many microfluidic devices have been developed in the last 5 years, few were designed for the use of undiluted whole blood as a starting point, which eliminates the need for blood dilution and minimizes blood sample preparation. This review will first provide a short summary on blood properties and blood samples typically used for analysis, before delving into innovative advances in microfluidic devices over the last 5 years that address the hurdles of blood sample preparation. The devices will be categorized by application and the type of blood sample used. The final section focuses on devices for the detection of intracellular nucleic acids, because these require more extensive sample preparation steps, and the challenges involved in adapting this technology and potential improvements are discussed.

Biomarker Detection in Early Diagnosis of Cancer: Recent Achievements in Point-of-Care Devices Based on Paper Microfluidics

Microfluidics is very crucial in lab-on-a-chip systems for carrying out operations in a large-scale laboratory environment on a single chip. Microfluidic systems are miniaturized devices in which the fluid behavior and control can be manipulated on a small platform, with surface forces on the platform being greater than volumetric forces depending on the test method used. In recent years, paper-based microfluidic analytical devices (μPADs) have been developed to be used in point-of-care (POC) technologies. μPADs have numerous advantages, including ease of use, low cost, capillary action liquid transfer without the need for power, the ability to store reagents in active form in the fiber network, and the capability to perform multiple tests using various measurement techniques. These benefits are critical in the advancement of paper-based microfluidics in the fields of disease diagnosis, drug application, and environment and food safety. Cancer is one of the most critical diseases for early detection all around the world. Detecting cancer-specific biomarkers provides significant data for both early diagnosis and controlling the disease progression. μPADs for cancer biomarker detection hold great promise for improving cure rates, quality of life, and minimizing treatment costs. Although various types of bioanalytical platforms are available for the detection of cancer biomarkers, there are limited studies and critical reviews on paper-based microfluidic platforms in the literature. Hence, this article aims to draw attention to these gaps in the literature as well as the features that future platforms should have.

Highly Stable InSe-FET Biosensor for Ultra-Sensitive Detection of Breast Cancer Biomarker CA125

Two-dimensional materials-based field-effect transistors (FETs) are promising biosensors because of their outstanding electrical properties, tunable band gap, high specific surface area, label-free detection, and potential miniaturization for portable diagnostic products. However, it is crucial for FET biosensors to have a high electrical performance and stability degradation in liquid environments for their practical application. Here, a high-performance InSe-FET biosensor is developed and demonstrated for the detection of the CA125 biomarker in clinical samples. The InSe-FET is integrated with a homemade microfluidic channel, exhibiting good electrical stability during the liquid channel process because of the passivation effect on the InSe channel. The InSe-FET biosensor is capable of the quantitative detection of the CA125 biomarker in breast cancer in the range of 0.01-1000 U/mL, with a detection time of 20 min. This work provides a universal detection tool for protein biomarker sensing. The detection results of the clinical samples demonstrate its promising application in early screenings of major diseases.

Recent Development of Fluorescent Nanodiamonds for Optical Biosensing and Disease Diagnosis

The ability to precisely monitor the intracellular temperature directly contributes to the essential understanding of biological metabolism, intracellular signaling, thermogenesis, and respiration. The intracellular heat generation and its measurement can also assist in the prediction of the pathogenesis of chronic diseases. However, intracellular thermometry without altering the biochemical reactions and cellular membrane damage is challenging, requiring appropriately biocompatible, nontoxic, and efficient biosensors. Bright, photostable, and functionalized fluorescent nanodiamonds (FNDs) have emerged as excellent probes for intracellular thermometry and magnetometry with the spatial resolution on a nanometer scale. The temperature and magnetic field-dependent luminescence of naturally occurring defects in diamonds are key to high-sensitivity biosensing applications. Alterations in the surface chemistry of FNDs and conjugation with polymer, metallic, and magnetic nanoparticles have opened vast possibilities for drug delivery, diagnosis, nanomedicine, and magnetic hyperthermia. This study covers some recently reported research focusing on intracellular thermometry, magnetic sensing, and emerging applications of artificial intelligence (AI) in biomedical imaging. We extend the application of FNDs as biosensors toward disease diagnosis by using intracellular, stationary, and time-dependent information. Furthermore, the potential of machine learning (ML) and AI algorithms for developing biosensors can revolutionize any future outbreak.

Saliva diagnostics: emerging techniques and biomarkers for salivaomics in cancer detection

INTRODUCTION

The pursuit of easy-to-use, non-invasive and inexpensive diagnostics is an urgent task for clinicians and scientists. Saliva is an important component of body fluid with regular changes of contents under various pathophysiological conditions, and the biomarkers identified from saliva shows high application potentials and values in disease diagnostics. This review introduces the latest developments in saliva research, with an emphasis on the detection and application of salivary biomarkers in cancer detection.

AREAS COVERED

Detection of disease-specific biomarkers in saliva samples by existing salivaomic methods can be used to diagnose various human pathological conditions and was introduced in details. This review also covers the saliva collection methods, the analytical techniques as well as the corresponding commercial products, with an aim to describe an holistic process for saliva-based diagnostics.

EXPERT OPINION

Saliva, as a non-invasive and collectable body fluid, can reflect the pathophysiological changes of the human body to a certain extent. Identification of reliable saliva biomarkers can provide a convenient way for cancer detection in clinical applications.

Modular Micro Raman Reader Instrument for Fast SERS-Based Detection of Biomarkers

Sensitive detection of biomarkers is very critical in the diagnosis, management, and monitoring of diseases. Recent efforts have suggested that bioassays using surface-enhanced Raman scattering as a signal read-out strategy possess certain unique beneficial features in terms of sensitivity and low limits of detection which set this method apart from its counterparts such as fluorescence, phosphorescence, and radiolabeling. Surface-enhanced Raman scattering (SERS) has also emerged as an ideal choice for the development of multiplexed bioassays. Such promising features have prompted the need for the development of SERS-based tools suitable for point-of-care applications. These tools must be easy to use, portable, and automated for the screening of many samples in clinical settings if diagnostic applications are considered. The availability of such tools will result in faster and more reliable detection of disease biomarkers, improving the accessibility of point-of-care diagnostics. In this paper, we describe a modular Raman reader instrument designed to create such a portable device suitable for screening a large number of samples with minimal operator assistance. The device's hardware is mostly built with commercially available components using our unique design. Dedicated software was created to automatically run sample screening and analyze the data measured. The mRR is an imaging system specifically created to automate measurements, eliminating human bias while enhancing the rate of data collection and analysis ~2000 times. This paper presents both the design and capabilities of the custom-built modular Raman reader system (mRR) capable of automated and fast measurements of sandwich immunoassay samples on gold substrates using modified gold nanoparticles as Raman tags. The limit of detection (LOD) of the tested MUC4-specific iSERS assay was measured to be 0.41 µg/mL.

ZnO Nanorods Coated Single-Mode-Multimode-Single-Mode Optical Fiber Sensor for VOC Biomarker Detection

This work demonstrated a ZnO-coated optical fiber sensor for the detection of a volatile organic compound (VOC) biomarker for diabetes for detecting isopropanol (IPA) markers. A coreless silica fiber (CSF) was connected to a single-mode fiber (SMF) at both ends to achieve a SMF-CSF-SMF structure. CSF is the sensing region where multimode interference (MMI) generates higher light interaction at the interface between the fiber and sensing medium, leading to enhanced sensitivity. Optimization of the CSF length was conducted numerically to attain the highest possible coupling efficiency at the output. Surface functionalization was achieved via hydrothermal growth of ZnO nanorods directly onto the CSF at low temperatures. The optical fiber-based sensor was successfully fabricated and tested with 20%, 40%, 60%, 80%, and 100% of IPA. The sensor response was recorded using an optical spectrometer and analyzed for sensor sensitivity. The fabricated sensor shows the potential to detect isopropanol with the sensitivity of 0.053 nm/%IPA vapor. Further improvement of the sensor sensitivity and selectivity is also proposed for future work.

Optimization of Printed Polyaniline Composites for Gas Sensing Applications

Polyaniline (PANI) films are promising candidates for electronic nose-based IoT applications, but device performances are influenced by fabrication parameters and ambient conditions. Affinities of different PANI composites to analytes for gas sensing applications remain elusive. In this study, we investigate the material properties in detail for two different dopant systems: F4TCNQ and carbon black. Using a reproducibility-driven approach, we investigate different dopant concentrations in regard to their sensitivity and specificity towards five relevant markers for breath cancer diagnosis. We benchmark the system using ammonia measurements and evaluate limits of detection. Furthermore, we provide statistical analysis on reproducibility and pave the way towards machine learning discrimination via principal component analysis. The influence of relative humidity on sensor hysteresis is also investigated. We find that F4TCNQ-doped PANI films show improved reproducibility compared to carbon black-doped films. We establish and quantify a tradeoff between sensitivity, reproducibility, and environmental stability by the choice of dopant and concentrations ratios.

Clinical significance of differential serum-signatures for early prediction of severe dengue among Eastern Indian patients

Dengue infection can result in simple dengue fever or life-threatening severe dengue. Early identification of severe patients is needed for proper disease management. Dengue infection was screened among 168 symptomatic patients by qRT-PCR, anti-dengue IgM, and IgG ELISA. Dengue patients were categorized according to WHO classification. Viral load and dengue serotypes were determined by qRT-PCR. Levels of acute-phase-proteins (SAP, SAA2; CRP and ApoA1), endothelial (Ang2, VEGF), coagulation (fibrinogen) markers were determined by sandwich ELISA/immunoturbidimetry/western-blotting. Hepatic (ALT, AST, ALP) and other blood biochemical parameters were studied by autoanalyzer and haematology cell counter. Statistical analysis and protein-protein-interaction network were performed by GraphPad-Prism and STRINGS database, respectively. Among 87 dengue patients, significantly higher levels of Ang2, VEGF, CRP, SAA2, ApoA1, AST, ALT, and AST/ALT ratio and low level of fibrinogen were detected in severe-dengue cases compared to dengue without warning-signs, with seven of them severely altered during febrile-phase. Higher fold-change of Ang2 and VEGF as well as decreased fibrinogen were observed among patients with haemorrhagic-manifestation, clinical-fluid accumulation and thrombocytopenia. Functional network analysis predicted Ang2, VEGF, and CRP to be functionally and physically connected and SAA2 and ApoA1 to be functioning together. Correlation analyses also validated this connectivity by a strong positive correlation between Ang2, VEGF, and CRP. PCA analysis followed by hierarchical clustering heatmap analysis segregated severe-dengue patients from the rest, with VEGF, Ang2, ApoA1, AST, and ALT clearly distinguishing the severe-dengue group. Thus, serum levels of VEGF, Ang2, ApoA1, AST, and ALT might act as potential biomarkers for predicting dengue severity during the early stage.

Full-Color Long-Lived Room Temperature Phosphorescence in Aqueous Environment

Long-lived room temperature phosphorescence (RTP) materials are widely utilized in the field of biological and chemical sensing, due to their unique characteristics of long-lived luminescence and no background autofluorescence. However, the realization of full-color RTP in aqueous solution still remains a great challenge. Herein, a feasible strategy for achieving high stability and full-color RTP of carbon dots (CDs)-based composite materials in aqueous environment is reported by constructing a rigid hydrogen bonds' network. The obtained m,p-CDs@CA composite materials exhibit deep-blue RTP with phosphorescence quantum yield of 23.2% and lifetime of 1.74 s, and the afterglow can last for over 12 s. More importantly, the m,p-CDs@CA composite materials are desirable in the detection of biomarkers, because of excellent stability, dispersion, and long-lived RTP properties. The m,p-CDs@CA suspension also displays excellent sensitivity, and a limitation of detection as low as 5.61 and 550 nm for biomarkers 5-hydroxyindole-3-acetic acid (HIAA) and serotonin (5-hydroxytryptamine, HT), respectively. Meanwhile, the sensing performance exhibits excellent selectivity even in the presence of other competitive species in blood plasma and urine. With superior selectivity, the long-lived phosphorescence probe based on m,p-CDs@CA suspension can be as an effective biomarker for carcinoid identification, which has potential application in clinical analysis.

Silicon Nanodisk Huygens Metasurfaces for Portable and Low-Cost Refractive Index and Biomarker Sensing

Biomarker detection and bulk refractive index sensing are important across multiple industries ranging from early medical diagnosis to chemical process quality control. The bulky size, high cost, and complex architecture of existing refractive index and biomarker sensing technologies limit their use to highly skilled environments like hospitals, large food processing plants, and research labs. Here, we demonstrate a compact and inexpensive refractive index sensor based on resonant dielectric photonic nanoantenna arrays or metasurfaces. These dielectric resonances support Mie dipole and asymmetric resonances that shift with changes in their external environment. A single-wavelength transmission measurement in a portable (<250 in.³), low-cost (<$4000) sensor shows sensitivity to 1.9 × 10^-6 change in the fluid refractive index without the use of a spectrometer or other complex optics. Our sensor assembly allows for measurements using multiple metasurfaces with identical resonances or varying resonance types for enhanced diagnostics on the same chip. Furthermore, a 10 kDa culture filtrate peptide CFP-10, a marker for human tuberculosis, is detected with our sensor with 10 pM resolution. This system has the potential to enable facile, fast, and highly sensitive measurements with adequate limits of detection for personalized biomedical diagnoses.

Graphene Biodevices for Early Disease Diagnosis Based on Biomarker Detection

The early diagnosis of diseases plays a vital role in healthcare and the extension of human life. Graphene-based biosensors have boosted the early diagnosis of diseases by detecting and monitoring related biomarkers, providing a better understanding of various physiological and pathological processes. They have generated tremendous interest, made significant advances, and offered promising application prospects. In this paper, we discuss the background of graphene and biosensors, including the properties and functionalization of graphene and biosensors. Second, the significant technologies adopted by biosensors are discussed, such as field-effect transistors and electrochemical and optical methods. Subsequently, we highlight biosensors for detecting various biomarkers, including ions, small molecules, macromolecules, viruses, bacteria, and living human cells. Finally, the opportunities and challenges of graphene-based biosensors and related broad research interests are discussed.

Toward Sensitive and Reliable Surface-Enhanced Raman Scattering Imaging: From Rational Design to Biomedical Applications

Early specific detection through indicative biomarkers and precise visualization of lesion sites are urgent requirements for clinical disease diagnosis. However, current detection and optical imaging methods are insufficient for these demands. Molecular imaging technologies are being intensely studied for reliable medical diagnosis. In the past several decades, molecular imaging with surface-enhanced Raman scattering (SERS) has significant advances from analytical chemistry to medical science. SERS is the inelastic scattering generated from the interaction between photons and substances, presenting molecular structure information. The outstanding SERS virtues of high sensitivity, high specificity, and resistance to biointerference are highly advantageous for biomarker detection in a complex biological matrix. In this work, we review recent progress on the applications of SERS imaging in clinical diagnostics. With the assistance of SERS imaging, the detection of disease-related proteins, nucleic acids, small molecules, and pH of the cellular microenvironment can be implemented for adjuvant medical diagnosis. Moreover, multimodal imaging integrates the high penetration and high speed of other imaging modalities and imaging precision of SERS imaging, resulting in final complete and accurate imaging outcomes and exhibiting robust potential in the discrimination of pathological tissues and surgical navigation. As a promising molecular imaging technology, SERS imaging has achieved remarkable performance in clinical diagnostics and the biomedical realm. It is expected that this review will provide insights for further development of SERS imaging and promote the rapid progress and successful translation of advanced molecular imaging with clinical diagnostics.

DNAzyme-Based Biosensors: Immobilization Strategies, Applications, and Future Prospective

Since their discovery almost three decades ago, DNAzymes have been used extensively in biosensing. Depending on the type of DNAzyme being used, these functional oligonucleotides can act as molecular recognition elements within biosensors, offering high specificity to their target analyte, or as reporters capable of transducing a detectable signal. Several parameters need to be considered when designing a DNAzyme-based biosensor. In particular, given that many of these biosensors immobilize DNAzymes onto a sensing surface, selecting an appropriate immobilization strategy is vital. Suboptimal immobilization can result in both DNAzyme detachment and poor accessibility toward the target, leading to low sensing accuracy and sensitivity. Various approaches have been employed for DNAzyme immobilization within biosensors, ranging from amine and thiol-based covalent attachment to non-covalent strategies involving biotin-streptavidin interactions, DNA hybridization, electrostatic interactions, and physical entrapment. While the properties of each strategy inform its applicability within a proposed sensor, the selection of an appropriate strategy is largely dependent on the desired application. This is especially true given the diverse use of DNAzyme-based biosensors for the detection of pathogens, metal ions, and clinical biomarkers. In an effort to make the development of such sensors easier to navigate, this paper provides a comprehensive review of existing immobilization strategies, with a focus on their respective advantages, drawbacks, and optimal conditions for use. Next, common applications of existing DNAzyme-based biosensors are discussed. Last, emerging and future trends in the development of DNAzyme-based biosensors are discussed, and gaps in existing research worthy of exploration are identified.

COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

COVID-19, also known as SARS-CoV-2 is a novel, respiratory virus currently plaguing humanity. Genetically, at its core, it is a single-strand positive-sense RNA virus. It is a beta-type Coronavirus and is distinct in its structure and binding mechanism compared to other types of coronaviruses. Testing for the virus remains a challenge due to the small market available for at-home detection. Currently, there are three main types of tests for biomarker detection: viral, antigen and antibody. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) remains the gold standard for viral testing. However, the lack of quantitative detection and turnaround time for results are drawbacks. This manuscript focuses on recent advances in COVID-19 detection that have lower limits of detection and faster response times than RT-PCR testing. The advancements in sensing platforms have amplified the detection levels and provided real-time results for SARS-CoV-2 spike protein detection with limits as low as 1 fg/mL in the Graphene Field Effect Transistor (FET) sensor. Additionally, using multiple biomarkers, detection levels can achieve a specificity and sensitivity level comparable to that of PCR testing. Proper biomarker selection coupled with nano sensing detection platforms are key in the widespread use of Point of Care (POC) diagnosis in COVID-19 detection.

Frequency Shift Surface-Enhanced Raman Spectroscopy Sensing: An Ultrasensitive Multiplex Assay for Biomarkers in Human Health

The sensitive and selective detection of biomarkers for human health remains one of the grand challenges of the analytical sciences. Compared to established methods (colorimetric, (chemi) luminescent), surface-enhanced Raman spectroscopy (SERS) is an emerging alternative with enormous potential for ultrasensitive biological detection. Indeed even attomolar (10^-18 M) detection limits are possible for SERS due to an orders-of-magnitude boosting of Raman signals at the surface of metallic nanostructures by surface plasmons. However, challenges remain for SERS assays of large biomolecules, as the largest enhancements require the biomarker to enter a "hot spot" nanogap between metal nanostructures. The frequency-shift SERS method has gained popularity in recent years as an alternative assay that overcomes this drawback. It measures frequency shifts in intense SERS peaks of a Raman reporter during binding events on biomolecules (protein coupling, DNA hybridization, etc.) driven by mechanical transduction, charge transfer, or local electric field effects. As such, it retains the excellent multiplexing capability of SERS, with multiple analytes being identifiable by a spectral fingerprint in a single read-out. Meanwhile, like refractive index surface plasmon resonance methods, frequency-shift SERS measures the shift of an intense signal rather than resolving a peak above noise, easing spectroscopic resolution requirements. SERS frequency-shift assays have proved particularly suitable for sensing large, highly charged biomolecules that alter hydrogen-bonding networks upon specific binding. Herein we discuss the frequency-shift SERS method and promising applications in (multiplex) biomarker sensing as well as extensions to ion and gas sensing and much more.

EnRank: An Ensemble Method to Detect Pulmonary Hypertension Biomarkers Based on Feature Selection and Machine Learning Models

Pulmonary hypertension (PH) is a common disease that affects the normal functioning of the human pulmonary arteries. The peripheral blood mononuclear cells (PMBCs) served as an ideal source for a minimally invasive disease diagnosis. This study hypothesized that the transcriptional fluctuations in the PMBCs exposed to the PH arteries may stably reflect the disease. However, the dimension of a human transcriptome is much higher than the number of samples in all the existing datasets. So, an ensemble feature selection algorithm, EnRank, was proposed to integrate the ranking information of four popular feature selection algorithms, i.e., T-test (Ttest), Chi-squared test (Chi2), ridge regression (Ridge), and Least Absolute Shrinkage and Selection Operator (Lasso). Our results suggested that the EnRank-detected biomarkers provided useful information from these four feature selection algorithms and achieved very good prediction accuracy in predicting the PH patients. Many of the EnRank-detected biomarkers were also supported by the literature.

Enzyme-Free Electrochemical Nano-Immunosensor Based on Graphene Quantum Dots and Gold Nanoparticles for Cardiac Biomarker Determination

An ultrasensitive enzyme-free electrochemical nano-immunosensor based on a screen-printed gold electrode (SPGE) modified with graphene quantum dots (GQDs) and gold nanoparticles (AuNPs) was engineered to detect cardiac troponin-I (cTnI) for the early diagnosis of acute myocardial infarction (AMI). The GQDs and in-house synthesized AuNPs were implanted onto the SPGE and allowed for anti-cTnI immobilization prior to quantifying cTnI. The biomarker could be determined in a wide concentration range using square-wave voltammetry (SWV), cyclic voltammetry (CV), electron impedance spectroscopy (EIS) and amperometry. The analyses were performed in buffer, as well as in human serum, in the investigation ranges of 1–1000 and 10–1000 pg mL⁻¹, respectively. The detection time ranged from 10.5–13 min, depending on the electrochemical method employed. The detection limit was calculated as 0.1 and 0.5 pg mL⁻¹ for buffer and serum, respectively. The sensitivity of the immunosensor was found to be 6.81 µA cm⁻² pg mL⁻¹, whereas the binding affinity was determined to be <0.89 pM. The sensor showed high specificity for cTnI with slight responses for nonspecific biomolecules. Each step of the sensor fabrication was characterized using CV, SWV, EIS and atomic force microscopy (AFM). Moreover, AuNPs, GQDs and their nanocomposites were characterized by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). This is the first immunosensor that represents the successful determination of an analyte using four different electrochemical techniques. Such a sensor could demonstrate a promising future for on-site detection of AMI with its sensitivity, cost-effectiveness, rapidity and specificity.

Paper Microfluidics and Tailored Gold Nanoparticles for Nonenzymatic, Colorimetric Multiplex Biomarker Detection

The plasmonic properties of gold nanoparticles (AuNPs) are a promising tool to develop sensing alternatives to traditional, enzyme-catalyzed reactions. The need for sensing alternatives, especially in underdeveloped areas of the world, has given rise to the application of nonenzymatic sensing approaches paired with cellulosic substrates to biochemical analysis. Herein, we present three individual, low-step, wet-chemistry, colorimetric assays for three target biomarkers, namely, glucose, uric acid, and free cholesterol, relevant in diabetes control and their translation into paper-based assays and microfluidic platforms for multiplexed analysis. For glucose determination, an in situ AuNPs synthesis approach was applied into the developed μPAD, giving semiquantitative measures in the physiologically relevant range. For uric acid and cholesterol determination, modified AuNPs were used to functionalize paper with a gold-on-paper approach with the optical properties changing based on different aggregation degrees and hydrophobic properties of particles dependent on analyte concentration. These paper-based assays show sensitivity ranges and limits of detection compatible for target analyte level determination and detection limits comparable to those of similar enzymatic, colorimetric systems, relying only on plasmonic transduction without the need for enzymatic activity or other chromogenic substrates. The resulting paper-based assays were integrated into a single 3D, multiplex paper-based device using paper microfluidics, showing the capability for performing different colorimetric assays with distinct requirements in terms of sample flow and sample uptake in test zones using a combination of both horizontal and vertical flows inside the same device. The presented device allows for multiparametric, colorimetric measures of different metabolite levels from a single complex sample matrix drop using digital color analysis, showing the potential for development of low-cost, low-complexity tools for diagnostics toward the point-of-care.

Demonstration of a Label-Free and Low-Cost Optical Cavity-Based Biosensor Using Streptavidin and C-Reactive Protein

An optical cavity-based biosensor (OCB) has been developed for point-of-care (POC) applications. This label-free biosensor employs low-cost components and simple fabrication processes to lower the overall cost while achieving high sensitivity using a differential detection method. To experimentally demonstrate its limit of detection (LOD), we conducted biosensing experiments with streptavidin and C-reactive protein (CRP). The optical cavity structure was optimized further for better sensitivity and easier fluid control. We utilized the polymer swelling property to fine-tune the optical cavity width, which significantly improved the success rate to produce measurable samples. Four different concentrations of streptavidin were tested in triplicate, and the LOD of the OCB was determined to be 1.35 nM. The OCB also successfully detected three different concentrations of human CRP using biotinylated CRP antibody. The LOD for CRP detection was 377 pM. All measurements were done using a small sample volume of 15 µL within 30 min. By reducing the sensing area, improving the functionalization and passivation processes, and increasing the sample volume, the LOD of the OCB are estimated to be reduced further to the femto-molar range. Overall, the demonstrated capability of the OCB in the present work shows great potential to be used as a promising POC biosensor.

Regioselective SN2-Type Reaction for the Oriented and Irreversible Immobilization of Antibodies to a Glass Surface Assisted by Boronate Formation

Antibodies have exquisite specificities for molecular recognition, which have led to their incorporation into array sensors that are crucial for research, diagnostic, and therapeutic applications. Many of these platforms rely heavily on surface-bound reactive groups to covalently tether antibodies to solid substrates; however, this strategy is hindered by a lack of orientation control over antibody immobilization. Here, we report a mild electrophilic phenylsulfonate (tosylate) ester-containing boronic acid affinity ligand for attaching antibodies to glass slides. A high level of antibody coupling located near the Fc region of the boronated antibody complex could be achieved by the proximal nucleophilic amino acid driven substitution reaction at the phenylsulfonate center. This enabled the full-length antibodies to be permanently tethered onto surfaces in an oriented manner. The advantages of this strategy were demonstrated through the individual and multiplex detection of protein and serum biomarkers. This strategy not only confers stability to the immobilized antibodies but also presents a different direction for the irreversible attachment of antibodies to solid supports in an orientation-controlled way.

Reproducibility challenges for biomarker detection with uncertain but informative experimental data

Recent studies have revealed that circulating microRNAs are promising biomarkers for detecting toxicity or disease. Quantitative real-time polymerase chain reaction (qPCR) is often used to measure the levels of microRNAs. Besides complete and certain data, investigators inevitably have observed technically incomplete or uncertain qPCR data. Investigators usually set incomplete observations equal to the maximum quality number of qPCR cycles, apply the complete-observation method, or choose not to analyze targets with incomplete observations. Using biostatistical knowledge and published studies, we show that three commonly applied methods tend to cause biased inference and decrease reproducibility in biomarker detection. More efforts are needed to address the challenges to identify and detect reliable, novel circulating biomarkers in liquid biopsies.

Direct kinetic fingerprinting and digital counting of single protein molecules

The sensitive and accurate quantification of protein biomarkers plays important roles in clinical diagnostics and biomedical research. Sandwich ELISA and its variants accomplish the capture and detection of a target protein via two antibodies that tightly bind at least two distinct epitopes of the same antigen and have been the gold standard for sensitive protein quantitation for decades. However, existing antibody-based assays cannot distinguish between signal arising from specific binding to the protein of interest and nonspecific binding to assay surfaces or matrix components, resulting in significant background signal even in the absence of the analyte. As a result, they generally do not achieve single-molecule sensitivity, and they require two high-affinity antibodies as well as stringent washing to maximize sensitivity and reproducibility. Here, we show that surface capture with a high-affinity antibody combined with kinetic fingerprinting using a dynamically binding, low-affinity fluorescent antibody fragment differentiates between specific and nonspecific binding at the single-molecule level, permitting the direct, digital counting of single protein molecules with femtomolar-to-attomolar limits of detection (LODs). We apply this approach to four exemplary antigens spiked into serum, demonstrating LODs 55- to 383-fold lower than commercially available ELISA. As a real-world application, we establish that endogenous interleukin-6 (IL-6) can be quantified in 2-µL serum samples from chimeric antigen receptor T cell (CAR-T cell) therapy patients without washing away excess serum or detection probes, as is required in ELISA-based approaches. This kinetic fingerprinting thus exhibits great potential for the ultrasensitive, rapid, and streamlined detection of many clinically relevant proteins.

Integrative biomarker detection on high-dimensional gene expression data sets: a survey on prior knowledge approaches

Gene expression data provide the expression levels of tens of thousands of genes from several hundred samples. These data are analyzed to detect biomarkers that can be of prognostic or diagnostic use. Traditionally, biomarker detection for gene expression data is the task of gene selection. The vast number of genes is reduced to a few relevant ones that achieve the best performance for the respective use case. Traditional approaches select genes based on their statistical significance in the data set. This results in issues of robustness, redundancy and true biological relevance of the selected genes. Integrative analyses typically address these shortcomings by integrating multiple data artifacts from the same objects, e.g. gene expression and methylation data. When only gene expression data are available, integrative analyses instead use curated information on biological processes from public knowledge bases. With knowledge bases providing an ever-increasing amount of curated biological knowledge, such prior knowledge approaches become more powerful. This paper provides a thorough overview on the status quo of biomarker detection on gene expression data with prior biological knowledge. We discuss current shortcomings of traditional approaches, review recent external knowledge bases, provide a classification and qualitative comparison of existing prior knowledge approaches and discuss open challenges for this kind of gene selection.

BioDog, biomarker detection for improving identification power of breast cancer histologic grade in methylomics

Aim: Breast cancer histologic grade (HG) is a well-established prognostic factor. This study aimed to select methylomic biomarkers to predict breast cancer HGs. Materials & methods: The proposed algorithm BioDog firstly used correlation bias reduction strategy to eliminate redundant features. Then incremental feature selection was applied to find the features with a high HG prediction accuracy. The sequential backward feature elimination strategy was employed to further refine the biomarkers. A comparison with existing algorithms were conducted. The HG-specific somatic mutations were investigated. Results & conclusions: BioDog achieved accuracy 0.9973 using 92 methylomic biomarkers for predicting breast cancer HGs. Many of these biomarkers were within the genes and lncRNAs associated with the HG development in breast cancer or other cancer types.

Diagnostic Optical Sequencing

Advances in precision medicine require high-throughput, inexpensive, point-of-care diagnostic methods with multiomics capability for detecting a wide range of biomolecules and their molecular variants. Optical techniques have offered many promising advances toward such diagnostics. However, the inability to squeeze light with several hundred nanometer wavelengths into angstrom-scale volume for single-nucleotide measurements has hindered further progress. This limitation has been circumvented by analyzing the relative nucleobase content with Raman spectroscopy, in an optical sequencing method. Here, we performed optical sequencing measurements on positively charged silver nanoparticles to achieve 93.3% accuracy for predicting nucleobase content in label-free DNA k-mer blocks (where k = 10) as well as measurements on RNA and chemically modified nucleobases for extensions to transcriptomic and epigenetic studies. Our high-accuracy measurements were then used with a content-scoring database searching algorithm to correctly identify a β-lactamase gene from the MEGARes antibiotic resistance database and confirm the Pseudomonas aeruginosa pathogen of origin from <12 block content measurements (<15% coverage) of the gene. These results prove the feasibility of an optical sequencing platform as a diagnostic method. With the versatile range of available plasmonic substrates offering simple data acquisition, varying resolution (single-molecule to the ensemble), and multiplexing, this optical sequencing platform has potential as the rapid, cost-effective method needed for broad-spectrum biomarker detection.

Programmable DNA Nanoswitch Sensing with Solid-State Nanopores

Sensing performance of solid-state nanopores is limited by the fast kinetics of small molecular targets. To address this challenge, we translate the presence of a small target to a large conformational change of a long polymer. In this work, we explore the performance of solid-state nanopores for sensing the conformational states of molecular nanoswitches assembled using the principles of DNA origami. These programmable single-molecule switches show great potential in molecular diagnostics and long-term information storage. We investigate the translocation properties of linear and looped nanoswitch topologies using nanopores fabricated in thin membranes, ultimately comparing the performance of our nanopore platform for detecting the presence of a DNA analogue to a sequence found in a Zika virus biomarker gene with that of conventional gel electrophoresis. We found that our system provides a high-throughput method for quantifying several target concentrations within an order of magnitude by sensing only several hundred molecules using electronics of moderate bandwidth that are conventionally used in nanopore sensing systems.

Towards Understanding Non-Infectious Growth-Rate Retardation in Growing Pigs

For growth-rate retardation in commercial growing pigs suffering from non-infectious diseases, no biomarker is available for early detection and prevention of the condition or for the diagnosis of affected animals. The point in question is that the underlying pathological pathway of the condition is still unknown and multiple nutritional or management issues could be the cause of the disease. Common health status markers such as acute phase proteins, adenosine deaminase activity or total antioxidant capacity did not show any alteration in the saliva of animals with growth-rate retardation, so other pathways should be affected. The present study investigates saliva samples from animals with the same commercial crossbreed, sex and age, comparing control pigs and pigs with growth-rate retardation. A proteomics approach based on two-dimensional gel electrophoresis including mass spectrometry together with validation experiments was applied for the search of proteins that could help understand disease mechanisms and be used for early disease detection. Two proteins were detected as possible markers of growth-rate retardation, specifically S100A12 and carbonic anhydrase VI. A decrease in innate immune response was confirmed in pigs with growth-rate retardation, however further studies should be necessary to understand the role of the different CA VI proteoforms observed.

Evaluation of Molecularly Imprinted Polymers for Point-of-Care Testing for Cardiovascular Disease

Molecular imprinting is a rapidly growing area of interest involving the synthesis of artificial recognition elements that enable the separation of analyte from a sample matrix and its determination. Traditionally, this approach can be successfully applied to small analyte (<1.5 kDa) separation/ extraction, but, more recently it is finding utility in biomimetic sensors. These sensors consist of a recognition element and a transducer similar to their biosensor counterparts, however, the fundamental distinction is that biomimetic sensors employ an artificial recognition element. Molecularly imprinted polymers (MIPs) employed as the recognition elements in biomimetic sensors contain binding sites complementary in shape and functionality to their target analyte. Despite the growing interest in molecularly imprinting techniques, the commercial adoption of this technology is yet to be widely realised for blood sample analysis. This review aims to assess the applicability of this technology for the point-of-care testing (POCT) of cardiovascular disease-related biomarkers. More specifically, molecular imprinting is critically evaluated with respect to the detection of cardiac biomarkers indicative of acute coronary syndrome (ACS), such as the cardiac troponins (cTns). The challenges associated with the synthesis of MIPs for protein detection are outlined, in addition to enhancement techniques that ultimately improve the analytical performance of biomimetic sensors. The mechanism of detection employed to convert the analyte concentration into a measurable signal in biomimetic sensors will be discussed. Furthermore, the analytical performance of these sensors will be compared with biosensors and their potential implementation within clinical settings will be considered. In addition, the most suitable application of these sensors for cardiovascular assessment will be presented.

Programmable Paper-Based Microfluidic Devices for Biomarker Detections

Recent advanced paper-based microfluidic devices provide an alternative technology for the detection of biomarkers by using affordable and portable devices for point-of-care testing (POCT). Programmable paper-based microfluidic devices enable a wide range of biomarker detection with high sensitivity and automation for single- and multi-step assays because they provide better control for manipulating fluid samples. In this review, we examine the advances in programmable microfluidics, i.e., paper-based continuous-flow microfluidic (p-CMF) devices and paper-based digital microfluidic (p-DMF) devices, for biomarker detection. First, we discuss the methods used to fabricate these two types of paper-based microfluidic devices and the strategies for programming fluid delivery and for droplet manipulation. Next, we discuss the use of these programmable paper-based devices for the single- and multi-step detection of biomarkers. Finally, we present the current limitations of paper-based microfluidics for biomarker detection and the outlook for their development.

Reversible Immuno-Infrared Sensor for the Detection of Alzheimer's Disease Related Biomarkers

The development of biosensors for medical purposes is a growing field. An immuno-infrared biosensor for the preclinical detection of Alzheimer's disease (AD) in body fluids was developed. The key element of this sensor is an ATR crystal with chemically modified surface to catch the biomarker out of the body fluid. So far, the immuno-infrared sensor can be used only once and requires time-consuming steps of sensor exchange, sensor cleaning, and novel surface functionalization. Here, we developed an immuno-infrared sensor providing a reusable surface and showcase its performance by the detection of the AD biomarker proteins Aβ and Tau in human cerebrospinal fluid (CSF). The sensor surface is covalently coated with the immunoglobulin binding proteins Protein A or Protein G. These were employed for noncovalent immobilization of antibodies and the subsequent immobilization and analysis of their antigens. The reversible antibody immobilization can be repeated several times with the same or different antibodies. Further, the more specific binding of the antibody via its Fc region instead of the conventional NHS coupling leads to a 3-4-fold higher antigen binding capacity of the antibody. Thus, the throughput, sensitivity, and automation capacity of the immuno-infrared biosensor are significantly increased as compared to former immuno-infrared assays. This immuno-sensor can be used with any antibody that binds to Protein A or Protein G.

Scalable biclustering - the future of big data exploration?

Biclustering is a technique of discovering local similarities within data. For many years the complexity of the methods and parallelization issues limited its application to big data problems. With the development of novel scalable methods, biclustering has finally started to close this gap. In this paper we discuss the caveats of biclustering and present its current challenges and guidelines for practitioners. We also try to explain why biclustering may soon become one of the standards for big data analytics.

Flexible Biosensors for the Impedimetric Detection of Protein Targets Using Silk-Conductive Polymer Biocomposites

To expand the applications of flexible biosensors in point-of-care healthcare applications beyond monitoring of biophysical parameters, it is important to devise strategies for the detection of various proteins and biomarkers. Here, we demonstrate a flexible, fully organic, biodegradable, label-free impedimetric biosensor for the critical biomarker, vascular endothelial growth factor (VEGF). This biosensor was constructed by photolithographically patterning a conducting ink consisting of a photoreactive silk sericin coupled with a conducting polymer. These functional electrodes are printed on flexible fibroin substrates that are controllably thick and can be free-standing, or conform to soft surfaces. Detection was accomplished via the antibody to VEGF which was immobilized within the conducting matrix. The results indicated that the developed flexible biosensor was highly sensitive and selective to the target protein, even in challenging biofluids such as human serum. The biosensors themselves are biocompatible and degradable. Through this work, the developed flexible biosensor based on a simple and label-free strategy can find practical applications in the monitoring of wound healing or early disease diagnosis.

Colorimetric and Fluorescent Dual-Mode Immunoassay Based on Plasmon-Enhanced Fluorescence of Polymer Dots for Detection of PSA in Whole Blood

Although enormous efforts have been devoted to the development of new types of fluorometric immunochromatographic test strip (ICTS) with improved sensitivity over the past years, it still remains a big challenge to design ICTS with colorimetric and fluorescent bimodal signal readout for rapid yet accurate detection of cancer markers in a clinic. Scientists have tried to prepare bimodal reporters by combining fluorescent dyes with metal nanomaterials, but their fluorescence was easily quenched by metal nanomaterials through surface energy transfer, making dual colorimetric and fluorometric ICTS very difficult to be achieved. As compared to conventional fluorescent probes, semiconducting polymer dots (Pdots) exhibit extraordinary fluorescence brightness and facile surface functionalization, which are very suitable to be engineered as bimodal signal reporting reagents. Here, we integrated highly fluorescent Pdots with strongly plasmonic Au nanorods to form Pdot-Au hybrid nanocomposites with dual colorimetric and fluorescent readout abilities. We further utilized these nanohybrids in ICTS for qualitatively fast screening (colorimetry) as well as quantitatively accurate determination (fluorometry) of prostate-specific antigen (PSA) within 10 min. By taking advantage of the plasmon-enhanced fluorescence of Pdots on Au nanorods, this immunoassay possesses much better detection sensitivity of 1.07 pg/mL for PSA, which is at least 2 orders of magnitude lower than that of conventional fluorometric ICTS. Moreover, the direct detection of PSA from human whole blood collected without sample pretreatment makes this Pdot-based ICTS platform promising for on-site point-of-care diagnostics.

Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination

AIM

Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important.

RESULTS

We put forward a new feature-selection method that was used to find clinical markers for pancreatic cancer by combination of Support Vector Machine Recursive Feature Elimination (SVM-RFE) and Large Margin Distribution Machine Recursive Feature Elimination (LDM-RFE) algorithms. As a result, seven differentially expressed genes were predicted as specific biomarkers for pancreatic cancer because of their highest accuracy of classification on cancer and normal samples.

CONCLUSION

Three (MMP7, FOS and A2M) out of the seven predicted gene markers were found to encode proteins secreted into urine, providing potential diagnostic evidences for pancreatic cancer.

Single Exhale Biomarker Breathalyzer

A single exhale breathalyzer comprises a gas sensor that satisfies the following stringent conditions: high sensitivity to the target gas, high selectivity, stable response over extended period of time and fast response. Breathalyzer implementation includes a front-end circuit matching the sensitivity of the sensor that provides the readout of the sensor signal. We present here the characterization study of the response stability and response time of a selective Nitric Oxide (NO) sensor using designed data acquisition system that also serves as a foundation for the design of wireless handheld prototype. The experimental results with the described sensor and data acquisition system demonstrate stable response to NO concentration of 200 ppb over the period of two weeks. The experiments with different injection and retraction times of the sensor exposure to constant NO concentration show a fast response time of the sensor (on the order of 15 s) and the adequate recovery time (on the order of 3 min) demonstrating suitability for the single exhale breathalyzer.

Analysis of gentisic acid and related renal cell carcinoma biomarkers using reversed-phase liquid chromatography with water-rich mobile phases

The problem of longer retention times using water-rich mobile phases in reversed phase liquid chromatography (RPLC) has been addressed using hydrophobic alcohols such as butanol in very low quantities (approximately 0.1%) as the organic modifier. Advantages of water-rich mobile phases in RPLC for the separation of water-soluble and weakly retained compounds are improved separation of congeners and better tuning of RPLC separations. This is demonstrated in the separation of gentisic acid and related renal cell carcinoma (RCC) biomarkers in urine with a Zorbax C₁₈ column and a mobile phase of 0.1% (volume/volume) butanol in water with 0.6% (volume/volume) acetic acid. Calibration curves for the RCC biomarkers were linear over the concentration range investigated (5 ppm to 1000 ppm). Detection limits for the RCC biomarkers were 0.85ppm (quinolinic acid), 1.75ppm (gentisic acid), and 1.25ppm (4-hydroxybenzoic acid). Recovery tests using synthetic urine samples containing 20 ppm, 100 ppm, and 700 pm of each RCC biomarker were successful for all compounds.

Nanochannel-Confined Graphene Quantum Dots for Ultrasensitive Electrochemical Analysis of Complex Samples

Herein, we present an electrochemical sensing platform based on nanochannel-confined graphene quantum dots (GQDs) that is able to detect a spectrum of small analytes in complex samples with high sensitivity. Vertically ordered mesoporous silica-nanochannel film (VMSF) is decorated on the supporting electrode, conferring the electrode with excellent antifouling and anti-interference properties through steric exclusion and electrostatic repulsion. The synthesized GQDs with different functionalities are confined in the nanochannels of VMSF through electrophoresis, serving as the recognition element and signal amplifier. Without the usual need of tedious pretreatment, ultrasensitive and fast detection of Hg²⁺, Cu²⁺, and Cd²⁺ (with limits of detection (LOD) of 9.8 pM, 8.3 pM, and 4.3 nM, respectively) and dopamine (LOD of 120 nM) in complex food (Hg²⁺-contaminated seafood), environmental (soil-leaching solution), and biological (serum) samples are realized as proof-of-concept demonstrations.

Supramolecular Polymeric Assemblies for the Selective Depletion of Abundant Acidic Proteins in Serum

The analysis of low-level protein biomarkers in serum is precluded by the presence of other highly abundant serum proteins. Hence, the preliminary removal of serum albumin along with other abundant proteins in serum (i.e., immunoglobulins, transferrin, haptoglobin, α-2-macroglobulin, and apolipoproteins) is often a requirement prior to any biomarker analysis. In this work, we take advantage of the low isoelectric points (pI's) of these highly abundant proteins to selectively deplete them from serum by extraction using functionalized amphiphilic polymeric nanoassemblies. The selectivity of extraction is dependent on the pI of the protein and the extraction pH, which holds true even for extremely complex protein mixtures like serum. High extraction capacity is achieved by optimizing the extraction conditions and is found to be comparable to currently available methods for depletion. Depletion of these abundant acidic proteins allows for the enhanced detection of higher pI proteins and enables a 3 orders of magnitude increase in detection sensitivity for a putative cancer biomarker, demonstrating the utility of these polymeric assemblies for enhancing the analysis of the serum proteome.