Low Analyte Concentrations Research Articles

High-Sensitivity, High-Resolution Miniaturized Spectrometers for Ultraviolet to Near-Infrared Using Guided-Mode Resonance Filters

Miniaturized spectrometers have significantly advanced real-time analytical capabilities in fields such as environmental monitoring, healthcare diagnostics, and industrial quality control by enabling precise on-site spectral analysis. However, achieving high sensitivity and spectral resolution within compact devices remains a significant challenge, particularly when detecting low-concentration analytes or subtle spectral variations critical for chemical and molecular analysis. This study introduces an innovative approach employing guided-mode resonance filters (GMRFs) to address these limitations. Functioning similarly to notch filters, GMRFs selectively block specific spectral bands while allowing others to pass, maximizing energy extraction from incident light and enhancing spectral encoding. Our design incorporates narrow band-stop filters, which are essential for accurate spectrum reconstruction, resulting in improved resolution and sensitivity. Our spectrometer delivers a spectral resolution of 0.8 nm over a range of 370–810 nm. It achieves sensitivity values that are more than ten times greater than those of conventional grating spectrometers during fluorescence spectroscopy of mouse jejunum. This enhanced sensitivity and resolution are particularly beneficial for chemical and biological applications, facilitating the detection of trace analytes in complex matrices. Furthermore, the spectrometer’s compatibility with complementary metal oxide semiconductor (CMOS) technology enables scalable and cost-effective production, fostering broader adoption in chemical analysis, materials science, and biomedical research. This study underscores the transformative potential of the GMRF-based spectrometer as an innovative tool for advancing chemical and interdisciplinary analytical applications.

Three-Dimensional (3D) Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Sensing Low-Concentration Molecules in Solution.

The use of surface-enhanced Raman spectroscopy (SERS) in liquid solutions has always been challenging due to signal fluctuations, inconsistent data, and difficulties in obtaining reliable results, especially at very low analyte concentrations. In our study, we introduce a new method using a three-dimensional (3D) SERS substrate made of silica microparticles (SMPs) with attached plasmonic nanoparticles (NPs). These SMPs were placed in low-concentration analyte solutions for SERS analysis. In the first approach to perform SERS in a 3D environment, glycerin was used to immobilize the particles, which enabled high-resolution SERS imaging. Additionally, we conducted time-dependent SERS measurements in an aqueous solution, where freely suspended SMPs passed through the laser focus. In both scenarios, EFs larger than 200 were achieved, which enabled the detection of low-abundance analytes. Our study demonstrates a reliable and reproducible method for performing SERS in liquid environments, offering significant advantages for the real-time analysis of dynamic processes, sensitive detection of low-concentration molecules, and potential applications in biomolecular interaction studies, environmental monitoring, and biomedical diagnostics.

Melt-blown polypropylene nonwoven as an efficient and eco-economic sorbent for pipette tip micro-solid phase extraction for the determination of tyrosine kinase inhibitors

BackgroundThe detection of tyrosine kinase inhibitors (TKIs) in biological fluids is essential due to their critical role in cancer therapy and the variability in individual drug metabolism, which necessitates precise dosing. Traditional methods for analyzing TKIs in biological fluids, such as blood plasma, typically involve complex sample preparation techniques that can be resource-intensive, environmentally burdensome, and not sufficiently sensitive for low-concentration analytes. There is a pressing need for more efficient, economical, and environmentally friendly methods that can enhance sensitivity and throughput without compromising accuracy. ResultsThis study explores the use of melt-blown polypropylene nonwoven (MBPP), commonly found in face masks, as a novel sorbent for pipette-tip micro-solid phase extraction (PT-μSPE). MBPP demonstrated excellent hydrophobicity and significant mesoporous adsorption capacity. An extraction device was fashioned by inserting a segment of MBPP (15 mg) into a 200 μL disposable plastic pipette tip, which was then attached to a 2.5 mL disposable plastic syringe. The MBPP's fabric form removes the need for a frit, allowing the extraction process to be completed in just 3 min through simple plunger manipulation. The method achieved extraction recoveries ranging from 60.5 % to nearly 100 %. Subsequent method validation using liquid chromatography-tandem mass spectrometry (LC-MS/MS) showed satisfactory linearity (coefficient of determination R2 > 0.993), accuracy (relative recoveries: 86.3%–114.8 %), and precision (relative standard deviation: 3.4%–11.3 %), with detection limits between 0.022 and 0.135 ng mL−1. SignificanceThe introduction of MBPP for PT-μSPE represents a significant advancement in the bioanalytical detection of TKIs, offering a highly efficient, cost-effective, and environmentally sustainable method. It compares favorably with existing techniques, offering advantages in terms of cost, environmental impact, and ease of use. This approach has the potential to be widely adopted for routine monitoring of TKIs in clinical settings.

Periodic Arrays of Plasmonic Ag-Coated Multiscale 3D-Structures with SERS Activity: Fabrication, Modelling and Characterisation.

Surface enhanced Raman spectroscopy (SERS) is gaining importance as sensing tool. However, wide application of the SERS technique suffers mainly from limitations in terms of uniformity of the plasmonics structures and sensitivity for low concentrations of target analytes. In this work, we present SERS specimens based on periodic arrays of 3D-structures coated with silver, fabricated by silicon top-down micro and nanofabrication (10 mm × 10 mm footprint). Each 3D-structure is essentially an octahedron on top of a pyramid. The width of the top part-the octahedron-was varied from 0.7 µm to 5 µm. The smallest structures reached an analytical enhancement factor (AEF) of 3.9 × 107 with a relative standard deviation (RSD) below 20%. According to finite-difference time-domain (FDTD) simulations, the origin of this signal amplification lies in the strong localization of electromagnetic fields at the edges and surfaces of the octahedrons. Finally, the sensitivity of these SERS specimens was evaluated under close-to-reality conditions using a portable Raman spectrophotometer and monitoring of the three vibrational bands of 4-nitrobenzenethiol (4-NBT). Thus, this contribution deals with fabrication, characterization and simulation of multiscale 3D-structures with SERS activity.

A novel design of symmetrical grating built on D-shaped optical fiber sensor-based surface plasmon resonance

Surface Plasmon Resonance (SPR) is an electromagnetic phenomenon that occurs during the interaction between metals and dielectric materials. Fiber sensors show much attention in the last few decades because of their extremely sensitive performance. A novel design of a Dual symmetrical grating D-shaped fiber (Dual SGD-SF) based plasmonic sensor was theoretically studied. The effects of grating depth and gold and silver thickness were investigated. For the Dual SGD-SF sensor design at analyte RI = 1.5 and grating depth = 0.3 μm, the resonance wavelength at the maximum loss was 2.4 μm. The maximum wavelength sensitivity, resolution, and FOM for Dual SGD-SF were obtained at 2000 nm/RIU, 0.00005 RIU, and 22.22 RIU−1, respectively. This design was proposed for sensing very low concentrations of analyte and helps to discover the variations of refractive indices compared to high-purity liquids. To the best of our knowledge, using a symmetrical grating design as a refractive index sensor has not previously been reported.

Fabrication of Glucose Fluorescent Aptasensor Based on CdTe Quantum Dots.

Diabetes is a chronic metabolic disease characterized by high blood glucose (or blood sugar) levels, which harms the heart, blood vessels, eyes, kidneys, and nerves over time. So, it is crucial to regularly control glucose concentration in biological fluids to check its targets, reduce unpleasant symptoms of high and low blood sugar, and avoid long-term diabetes complications. This study developed a simple, rapid, sensitive, and cost-effective fluorescence system for glucose determination. The fluorescent Aptasensor was fabricated using cadmium telluride quantum dots (CdTe QDs) modified with thioglycolic acid and functionalized with thiol-glucose-aptamer through ligand exchange. The thiol-glucose-aptamer interacted directly with CdTe QDs, increasing fluorescence intensity. However, it decreased when the target molecules of glucose were introduced. The structural and morphological characteristics of the Aptasensor were confirmed by various analytical methods such as UV-visible spectroscopy, Fourier-transform infrared spectroscopy (FT-IR), field emission scanning electron microscopy (FESEM), energy dispersive x-ray spectroscopy (EDX), transmission electron microscopy (TEM), atomic force microscopy (AFM), and dynamic light scattering (DLS). According to the typical Stern-Volmer equation, the relationship between fluorescent quenching and target concentration was linear with a detection limit (LOD) of 0.13 ± 1.95 × 10-11 mol L-1 and a relative standard deviation (RSD) of 1.05%. The Aptasensor demonstrated high specificity towards the target and stability over 28 days. Furthermore, it detected glucose in human serum and urine with a recovery rate of up to 99.74%. The results indicate that the fluorescent Aptasensor could be valuable in developing robust sensing technology for low-concentrated analytes.

TWO-DIMENSIONAL ION CHROMATOGRAPHY TANDEM-MASS SPECTROMETRIC (2D-IC-MS/MS) METHOD FOR THE ANALYSIS OF PHOSPHORUS COMPOUNDS IN SOIL

Investigations into soil organic phosphorus (Po) dynamics are instrumental in understanding the transformations and processes responsible for ecosystem productivity. However, quantitative analysis of Po in a soil environment is extremely challenging due to low target analyte concentrations and matrix interferences with chromatography and analysis. Consequently, a two-dimensional ion chromatography-tandem mass spectrometric (2D-IC-MS/MS) method was developed to estimate soil Po concentrations. The first dimension diverted early eluting anions to waste while preconcentrating P compounds in a trap column, followed by chromatographic separation and detection in the second dimension. Detection was done using a mass spectrometer, and quantification was performed using the multiple reaction monitoring scan (MRM) method. The linear range of the studied P compounds, mostly nucleotides, was 0.05 – 50 ng/mL. Most P compounds were detected and quantified in calcareous subsoil samples in the concentration ranges 0.70 – 51.78 ng/g. The developed method achieved chromatographic separation that allowed unambiguous identification of isobars/isomers and isotopologues contributing to interferences in MS detection. However, improvements to the extraction method and post-clean-up procedures are required due to the complexity of soil extract composition, extreme matrix effect and/or loss of analyte during preconcentration. The method is ideal for simultaneously analyzing P compounds from environmental samples to elucidate key components of the soil P dynamics.

Near real-time quantification of microbial volatile organic compounds from mycoparasitic fungi: Potential for advanced monitoring and pest control

Microbial volatile organic compounds (MVOCs) are thought to play a key role in the interactions between mycoparasitic fungi, such as the biocontrol agent Trichoderma atroviride (T. atroviride), and their environment. However, the analysis of MVOC emissions from fungal samples is challenging because of low analyte concentrations, typically in the ppbV-range, and the complex chemical nature of biological samples. In a recent study using proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS) to determine MVOC emissions from T. atroviride, many product ions were unspecific, as they could arise from a large number of possible analytes. The aim of the present study was to determine whether fast gas chromatography (fast-GC) coupled to PTR-ToF-MS could be used to overcome this issue and constitute a suitable on-line, near real-time method to identify and quantify fungal MVOC emissions in the ppbV-to-ppmV regime. Using gas standards of eleven MVOCs known to be emitted by T. atroviride such as 6-amyl-α-pyrone (6-PP), 2-pentylfuran, 1-octen-3-ol, 2-heptanone, 3-octanone, 2-methyl-1-propanol, 2-pentanone, 3-methyl-1-butanol, 3-methylbutanal, acetone and ethanol, we developed a fast-GC method with a total runtime of 180 s which significantly enhances the analytical specificity of PTR-ToF-MS compared to conventional PTR-ToF-MS without fast-GC separation. Limits of detection were on the order of 0.1–4 ppbV. The increased analytical specificity demonstrated notable benefits, especially for MVOCs having partially overlapping distributions of product ions when analyzed directly using PTR-ToF-MS.In order to demonstrate the applicability of the analytical method, we analysed T. atroviride samples in four biological replicates twice daily over a duration of five days. Using the fast-GC method, nine out of the eleven MVOC species considered in this study in the headspace of T. atroviride could be identified and quantified and their time evolution over the five-day incubation period determined. The measured volume mixing ratios (VMRs) ranged from single-digit ppbV (2-pentylfuran) up to few ppmV (6-PP and ethanol), with the other compounds in the 10-to-100-ppbV range (1-octen-3-ol, 2-heptanone, 2-methyl-1-propanol, 3-methyl-1-butanol, 3-methylbutanal and acetone).Our results suggest that fast-GC-PTR-ToF-MS is a method well-suited for the analysis of gas-phase samples of biological origin, including but not limited to (mycoparasitic) fungi, in a wide range of VMRs from sub-ppbV to few-ppmV.

Lifting the Concentration Limit of Mass Photometry by PEG Nanopatterning.

Mass photometry (MP) is a rapidly growing optical technique for label-free mass measurement of single biomolecules in solution. The underlying measurement principle provides numerous advantages over ensemble-based methods but has been limited to low analyte concentrations due to the need to uniquely and accurately quantify the binding of individual molecules to the measurement surface, which results in diffraction-limited spots. Here, we combine nanoparticle lithography with surface PEGylation to substantially lower surface binding, resulting in a 2 orders of magnitude improvement in the upper concentration limit associated with mass photometry. We demonstrate the facile tunability of degree of passivation, enabling measurements at increased analyte concentrations. These advances provide access to protein-protein interactions in the high nanomolar to low micromolar range, substantially expanding the application space of mass photometry.

Comparative evaluation of wavelength-scanning Otto and Kretschmann configurations of SPR biosensors for low analyte concentration measurement

Abstract The growing demand for compound characterization has stimulated research, particularly in surface plasmon resonance technology. This technique monitors changes in the light-reflecting properties of a sample medium in close contact and in interaction with a plasmonic surface (typically a metal such as gold) due to shifts in the fundamental plasmon resonance of the surface. The Otto and Kretschmann configurations are commonly used in this method. When an analyte is expensive, scarce, or hazardous, it is advantageous to reduce the sample required for testing, making optimization of sample use interesting. This challenge requires trade-offs between sensitivity and LoD. This work compares two sensors in the indicated configurations designed for minimal analyte requirement (in this case, Ag nanoparticle suspensions) using the wavelength scanning technique. The results show that the Kretschmann configuration is the most efficient for characterizing nanoparticle suspensions due to its construction characteristics, ease of use, and the characteristics of the obtained response. The final arrangement is a quasi-point sensor that only requires 6μL of analyte and has a sensitivity of 4.17x10−4 RIU/λ (RIU is the refractive index unit). This study contributes to the exploration of advantages and limitations in the design and operation of SPR sensors. The work also underlies the need for future research to enhance the selectivity and versatility of these devices.

Molybdenum Disulfide-Assisted Spontaneous Formation of Multistacked Gold Nanoparticles for Deep Learning-Integrated Surface-Enhanced Raman Scattering.

Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanoscale architectures by using soluble processes remains a challenge. Herein, we report a biosensing platform that integrates deep learning with surface-enhanced Raman scattering (SERS), featuring large-area, close-packed three-dimensional (3D) architectures of molybdenum disulfide (MoS2)-assisted gold nanoparticles (AuNPs) for the on-site screening of coronavirus disease (COVID-19) using human tears. Some AuNPs are spontaneously synthesized without a reducing agent because the electrons induced on the semiconductor surface reduce gold ions when the Fermi level of MoS2 and the gold electrolyte reach equilibrium. With the addition of polyvinylpyrrolidone, a two-dimensional large-area MoS2 layer assisted in the formation of close-packed 3D multistacked AuNP structures, resembling electroless plating. This platform, with a convolutional neural network-based deep learning model, achieved outstanding SERS performance at subterascale levels despite the microlevel irradiation power and millisecond-level acquisition time and accurately assessed susceptibility to COVID-19. These results suggest that our platform has the potential for rapid, low-damage, and high-throughput label-free detection of exceedingly low analyte concentrations.

Exploring the potential of multiomics liquid biopsy testing in the clinical setting of lung cancer.

The transformative role of artificial intelligence (AI) and multiomics could enhance the diagnostic and prognostic capabilities of liquid biopsy (LB) for lung cancer (LC). Despite advances, the transition from tissue biopsies to more sophisticated, non-invasive methods like LB has been impeded by challenges such as the heterogeneity of biomarkers and the low concentration of tumour-related analytes. The advent of multiomics - enabled by deep learning algorithms - offers a solution by allowing the simultaneous analysis of various analytes across multiple biological fluids, presenting a paradigm shift in cancer diagnostics. Through multi-marker, multi-analyte and multi-source approaches, this review showcases how AI and multiomics are identifying clinically valuable biomarker combinations that correlate with patients' health statuses. However, the path towards clinical implementation is fraught with challenges, including study reproducibility and lack of methodological standardization, thus necessitating urgent solutions to solve these common issues.

Nanopore Blockade Sensors for Quantitative Analysis Using an Optical Nanopore Assay.

Nanopore sensing is a popular biosensing strategy that is being explored for the quantitative analysis of biomarkers. With low concentrations of analytes, nanopore sensors face challenges related to slow response times and selectivity. Here, we demonstrate an approach to rapidly detect species at ultralow concentrations using an optical nanopore blockade sensor for quantitative detection of the protein vascular endothelial growth factor (VEGF). This sensor relies on monitoring fluorescent polystyrene nanoparticles blocking nanopores in a nanopore array of 676 nanopores. The fluorescent signal is read out using a wide-field fluorescence microscope. Nonspecific blockade events are then distinguished from specific blockade events based on the ability to pull the particles out of the pore using an applied electric field. This allows the detection of VEGF at sub-picomolar concentration in less than 15 min.

Practical Guide to Large Amplitude Fourier-Transformed Alternating Current Voltammetry-What, How, and Why.

Fourier-transformed alternating current voltammetry (FTacV) is a technique utilizing a combination of a periodic (frequently sinusoidal) oscillation superimposed onto a staircase or linear potential ramp. The advanced utilization of a large amplitude sine wave induces substantial nonlinear current responses. Subsequent filter processing (via Fourier-transformation, band selection, followed by inverse Fourier-transformation) generates a series of harmonics in which rapid electron transfer processes may be separated from non-Faradaic and competing electron transfer processes with slower kinetics. Thus, FTacV enables the isolation of current associated with redox processes under experimental conditions that would not generate meaningful data using direct current voltammetry (dcV). In this study, the enhanced experimental sensitivity and selectivity of FTacV versus dcV are illustrated in measurements that (i) separate the Faradaic current from background current contributions, (ii) use a low (5 μM) concentration of analyte (exemplified with ferrocene), and (iii) enable discrimination of the reversible [Ru(NH3)6]3+/2+ electron-transfer process from the irreversible reduction of oxygen under a standard atmosphere, negating the requirement for inert gas conditions. The simple, homebuilt check-cell described ensures that modern instruments can be checked for their ability to perform valid FTacV experiments. Detailed analysis methods and open-source data sets that accompany this work are intended to facilitate other researchers in the integration of FTacV into their everyday electrochemical methodological toolkit.

A self-driven multifunctional microfluidic sweat analysis system for efficient sweat collection and real-time monitoring

Wearable sweat sensors offer the opportunity for non-invasive and real-time monitoring of metabolite information in sweat, enabling individuals to dynamically monitor their physiology states at the molecular level. However, sweat possesses characteristics such as small volume, volatility, susceptibility to epidermal contamination, and low analyte concentrations, making its reliable collection and detection challenge for wearable sweat sensors. In this work, we develop a self-driven multifunctional microfluidic sweat analysis system (SMMSAS) for efficient sweat collection and detection. The SMMSAS features with a wetting contrast for the sweat, which comprises superhydrophobic inlet, superhydrophilic microchannel enriched with nanofiber, and an absorbent test paper. Such a feature enables the spontaneous sweat transports in the form of dropwise due to the exertion of “Laplace force-capillary force-capillary force” on sweat, thereby facilitating the real-time sweat detection. SMMSAS integrated with the functions of impedance and colorimetry analysis is able to simultaneously record the multiple information in sweat, including sweat volume, sweating rate, total electrolyte concentration, glucose concentration, and pH value, all of which are important to reflect the physiological state of the human body. We also demonstrate the capability of SMMSAS in real-time monitoring the sweating conditions of the human body, which is attributed to its fast responsiveness (∼ 100 ms) for the wide range sweating rate (0.5−15 μL/min) and various total electrolyte concentration (0−80 mM), paving the way for next-generation personalized healthcare.

Analysis of Different Nanostructures of ISFET Biosensors Towards Liposome Detection

Proteins are needed by all living cells for structural and functional purposes. However, some proteins such as liposome instability may result in medication leaks that could harm cells. The detection of liposomes is dependent on the complex interactions between proteins, which are necessary for both their structural integrity and functional characteristics. This emphasizes the critical role that proteins play in the precise identification and examination of liposomal structures. Ion-sensitive field-effect transistor (ISFET) biosensor has gained popularity in the clinical research field for biomolecule detection due to its high detection sensitivity, mass-production capability, and low manufacturing cost. Nanohub BioSensorLab software was used to analyze the performance of different structures of ISFET (planar, cylindrical nanowire, nanosphere and double-gate FET) by simulating the settling time and selectivity of the biosensors. As the structural dimension expands from 1D to 3D, the settling time increases by three folds at the lowest analyte concentration. The fastest settling times were achieved by planar ISFET and double-gate FET. For selectivity measurements, an enhanced selectivity was achieved by increasing the concentration of the target molecule and decreasing the concentration of the parasitic molecule. A higher selectivity is determined by the higher Signal-to-Noise Ratio (SNR) value. The SNR increased linearly corresponds to the increase in the concentration of the target molecule as well as the decrease in the parasitic molecule’s concentration. The parasitic molecule's size increase of 1 nm causes a rise in SNR of 5.00×103.

Fiber-in-tube SPME-CapLC-MS/MS method to determine Aβ peptides in cerebrospinal fluid obtained from Alzheimer's patients

Mass spectrometry is characterized by its high sensitivity, ability to measure very low analyte concentrations, specificity to distinguish between closely related compounds, availability to generate high-throughput methods for screening, and high multiplexing capacity. This technique has been used as a platform to analyze fluid biomarkers for Alzheimer's disease. However, more effective sample preparation procedures, preferably antibody-independent, and more automated mass spectrometry platforms with improved sensitivity, chromatographic separation, and high throughput are needed for this purpose. This short communication discusses the development of a fiber-in-tube SPME-CapLC-MS/MS method to determine Aβ peptides in cerebrospinal fluid obtained from Alzheimer's disease patients. To obtain the fiber-in-tube SPME capillary, we longitudinally packed 22 nitinol fibers coated with a zwitterionic polymeric ionic liquid into the same length of the PEEK tube. In addition, this communication compares this fiber-in-tube SPME method with the conventional HPLC scale (HPLC-MS/MS) and when directly coupled to CapESI-MS/MS without chromatographic separation, and, as a case study, discusses the benefits and challenges inherent in miniaturizing the flow scale of the sample preparation technique (fiber-in-tube SPME) to the CapLC-MS/MS system. Fiber-in-tube SPME-CapLC-MS/MS provided LLOQ ranging from 0.09 to 0.10 ng mL−1, accuracy ranging from 91 to 117 % (recovery), and reproducibility of less than 18 % (RSD). Analysis of the cerebrospinal fluid samples obtained from Alzheimer's disease patients evidenced that the method is robust. At the capillary scale (10 µL min−1), this innovative method presented higher analytical sensitivity than the conventional HPLC-MS/MS scale. Although fiber-in-tube SPME directly coupled to CapESI-MS/MS offers advantages in terms of high throughput, the sample was dispersed and non-quantitatively desorbed from the capillary at low flow rate. These results highlighted that chromatographic separation is important to decrease the matrix effect and to achieve higher detectability, which is indispensable for bioanalysis.

Accurate and reliable surface-enhanced Raman spectroscopy assay for early detection of SARS-CoV-2 RNA with exceptional sensitivity

This research proposes a highly sensitive and simple surface-enhanced Raman spectroscopy (SERS) assay for the detection of SARS-CoV-2 RNA using suitably designed probes specific for RdRp and N viral genes attached to a Raman marker. The sensitivity of the assay was optimized through precise adjustments to the conditions of immobilization and hybridization processes of the target RNA, including modifications to factors such as time and temperature. The assay achieved a remarkable sensitivity down to 58.39 copies/mL, comparable to or lower than the sensitivities reported for commercial fluorescent polymerase chain reaction (PCR) based methods. It has good selectivity in discriminating SARS-CoV-2 RNA against other respiratory viruses, respiratory syncytial virus (RSV), and influenza A virus. The reliability of the assay was validated by testing 24 clinical samples, including 12 positive samples with varying cycle threshold (Ct) values and 12 negative samples previously tested using real-time PCR. The assay consistently predicted true results that were in line with the PCR results for all samples. Furthermore, the assay demonstrated a notable limit of detection (LOD) of Ct (38 for RdRp gene and 37.5 for N-gene), indicating its capability to detect low concentrations of the target analyte and potentially facilitating early detection of the pathogen.

Periodic magnetic modulation enhanced electrochemical analysis for highly sensitive determination of genomic DNA methylation

DNA methylation aberrations have a strong correlation with cancer in early detection, diagnosis, and prognosis, which make them possible candidate biomarkers. Electrochemical biosensors offer rapid protocols for detecting DNA methylation status with minimal pretreatment of samples. However, the inevitable presence of background current in the time domain, including electrochemical noise and variations, limits the detection performance of these biosensors, especially for low concentration analytes. Here, we propose an ultrasensitive frequency-domain electrochemical analysis strategy to effectively separate the weak signals from background current. To achieve this, we employed periodic magnetic field modulation of magnetic beads (MBs) on and off the electrode surface to generate a periodic electrochemical signal for subsequent frequency-domain analysis. By capturing labeled MBs with as low as 0.5 pg of DNA, we successfully demonstrated a highly sensitive electrochemical method for determination of genome-wide DNA methylation levels. We also validated the effectiveness of this methodology using DNA samples extracted from three types of hepatocellular carcinoma (HCC) cell lines. The results revealed varying genomic methylation levels among different HCC cell lines, indicating the potential application of this approach for early-stage cancer detection in terms of DNA methylation status.

Spironolactone metabolite causes falsely increased progesterone in the Abbott Architect immunoassay

BackgroundImmunoassays are important for routine clinical testing and medical diagnosis. However, they are limited by cross-reactivity especially at low analyte concentrations. There is a critical need to investigate compounds that can interfere with immunoassays. Herein, we describe the identification of canrenone, a spironolactone metabolite that falsely increases progesterone concentrations on the Abbott Architect i2000 Immunoassay. MethodsSerum samples and assay diluents were spiked with spironolactone or canrenone and progesterone concentrations were measured on the Architect i2000 and Immulite XPi immunoassay platforms. Blood samples from patients taking spironolactone were analyzed with liquid chromatography-tandem mass spectrometry to evaluate the intrinsic response of progesterone concentrations to the presence of canrenone. ResultsWe measured approximately 10-fold higher progesterone concentrations on the Abbott Architect i2000 compared to reference immunoassay analyzers (Siemens Immulite XPi and Roche Cobas e601/602), suggesting an analytical error which is unique to the Architect i2000 antibody and/or assay conditions. By measuring serum progesterone after addition of spironolactone or canrenone to serum samples, we found that canrenone falsely increased progesterone on the Architect i2000 immunoassay. However, this interference was more pronounced at low serum progesterone concentrations. Moreover, a strong positive correlation was seen between canrenone and measured serum progesterone concentrations. ConclusionsOur investigations are important for individuals who require progesterone measurements using the Architect i2000 immunoassay, especially because it is unlikely for clinicians to order canrenone measurements alongside progesterone measurements for individuals taking spironolactone. Further research is needed to determine whether canrenone can influence progesterone measurements on other immunoassay systems.