Rapid Quantitative Analysis Research Articles

3D printed microfluidic chemiluminescence PoC device with self-powering and integrated incubating system: Validation via ALP detection on disposable µPADs

Point-of-Care (PoC) devices have become the fundamental requirement for rapid diagnostics and quantitative analysis at locations convenient to patients. This work reports a fully portable, pocket-friendly, self-powering, and temperature-controlled 3D printed chemiluminescence (CL) device. Moreover, the CL device leveraged the omnipresent smartphone as a detector unit to capture the CL signals. The device also contains a removable magnetic locking smartphone holder, making it universal. Further, the CL device integrates a microfluidic µPAD based detection methodology to monitor the abnormal levels of crucial bio-analyte alkaline phosphatase (ALP). The alkaline phosphatase (ALP) hydrolysis reaction with l-Ascorbic acid 2 phosphate releases a by-product, ascorbic acid (AA). The produced AA is a radical scavenger that quenches the CL signal, thereby facilitating the detection of ALP. Excellent performance of the developed CL device was observed in detecting the ALP with good linearity ranging from 1 mU/L to 10 mU/L and a detection limit of 0.59 mU/L. Subsequently, the device was tested for real-time ALP detection in human blood serum samples. Interestingly, the obtained results were less than 7 % error, compared to clinical samples. The developed fully portable 3D printed CL device with integrated electronics can be a future benchmark for mass production of susceptible devices in detecting various analytes.

Quantitative analysis of hydrogen isotope gas mixtures by low resolution quadrupole mass spectrometer

Quadrupole mass spectrometry (QMS) has an important application in the field of rapid on-line analysis of hydrogen isotopes. However, due to the interference of isotope fractionation effect and mass overlap peaks, accurate quantitative analysis of hydrogen isotopes by quadrupole mass spectrometry has always been a challenging problem. For the calibration of a low-resolution quadrupole mass spectrometry, standard samples of hydrogen isotopes gas mixtures with different HD contents were prepared by platinum catalyst that accelerated hydrogen isotope exchange reaction. The results show that the fraction of ionized fragments of various hydrogen isotopes in the mixture is stable and less affected by the coexistence of other isotopes. Taking the main fragment peak as the calibration basis, considering the isotope fractionation effect and mass overlap peak interference, the calibration curve between hydrogen isotope abundance and mass spectral signal was obtained by systematic correction method, and the linear correlation coefficient is 0.9991. The average relative errors between the correction values and the standard values of isotope abundance measured are 1.87% (hydrogen content) and 3.43% (deuterium content), respectively. The method developed in this work can be used for rapid on-line quantitative analysis of hydrogen isotope gas mixtures.

Flexible Amperometric Immunosensor Based on Colloidal Quantum Dots for Detecting the Myeloperoxidase (MPO) Systemic Inflammation Biomarker

Myeloperoxidase (MPO) has been demonstrated to be a biomarker of neutrophilic inflammation in various diseases. Rapid detection and quantitative analysis of MPO are of great significance for human health. Herein, an MPO protein flexible amperometric immunosensor based on a colloidal quantum dot (CQD)-modified electrode was demonstrated. The remarkable surface activity of CQDs allows them to bind directly and stably to the surface of proteins and to convert antigen-antibody specific binding reactions into significant currents. The flexible amperometric immunosensor provides quantitative analysis of MPO protein with an ultra-low limit of detection (LOD) (31.6 fg mL-1), as well as good reproducibility and stability. The detection method is expected to be applied in clinical examination, POCT (bedside test), community physical examination, home self-examination and other practical scenarios.

Multiplex Chroma Response Wearable Hydrogel Patch: Visual Monitoring of Urea in Body Fluids for Health Prognosis.

Visual wearable devices can rapid intuitively monitor biomarkers in body fluids to indicate the human health status and provide valuable reference for further medical diagnosis. However, unavoidable interference factors such as skin color, natural light, and background luminescence can interfere with the visualization accuracy of flexible wearable devices, limiting their practical sensing application. Here, we designed a wearable sensing patch via an embedded upconversion optical probe in a 3D porous polyacrylamide hydrogel, exhibiting a multiplex chroma response to urea based on the inner filter effect, which overcomes the susceptibility to external conditions due to its near-infrared excited luminescence and improves the resolution and accuracy of visual sensing. Furthermore, a highly compatible portable sensing platform combined with a smartphone was designed to achieve in situ rapid quantitative analysis of urea. The limit of detection values of the upconversion optical probe and hydrogel sensor are as low as 1.4 and 30 μM respectively, exhibiting the practicality in different scenarios. The designed sensing patch provides a convenient and accurate sensing strategy for the detection of biomarkers in body fluids and has the potential to be developed into a point-of-care device to provide disease early warning and clinical diagnosis.

Quantitative Label-Free SERS Detection of Trace Fentanyl in Biofluids with a Freestanding Hydrophobic Plasmonic Paper Biosensor.

The prevalence of fentanyl abuse raises global public health concerns with an unprecedented surge in overdose deaths. Rapid identification and quantification of fentanyl in biofluids is of paramount importance to combat fentanyl abuse for law enforcement agencies and promptly treat patients for medical professionals. Herein, a freestanding surface-enhanced Raman spectroscopy (SERS) biosensor with excellent condensing enrichment capability, termed FrEnSERS biosensor, is reported for quantitative label-free detection of trace fentanyl in biofluids. This biosensor comprises a reduced graphene oxide membrane decorated with high-density hydrophobic Au nanostars. A combination of the high SERS enhancement and the focusing effect for analyte enrichment of the hydrophobic surface accounts for the remarkable SERS performance of the FrEnSERS biosensor. We demonstrate that the FrEnSERS biosensor achieves the sensitive and quantitative detection of fentanyl in both serum and urine over a wide dynamic range spanning more than 4 orders of magnitude, with a limit of detection of 0.47 ng/mL for serum samples and 0.73 ng/mL for urine samples. Our biosensor is sensitive, cost-effective, and reliable for rapid quantitative analysis of fentanyl in biofluids with great promise for forensic analysis and clinical diagnosis.

A Rapid Quantitative Analysis of Bicomponent Fibers Based on Cross-Sectional In-Situ Observation.

To accelerate the industrialization of bicomponent fibers, fiber-based flexible devices, and other technical fibers and to protect the property rights of inventors, it is necessary to develop fast, economical, and easy-to-test methods to provide some guidance for formulating relevant testing standards. A quantitative method based on cross-sectional in-situ observation and image processing was developed in this study. First, the cross-sections of the fibers were rapidly prepared by the non-embedding method. Then, transmission and reflection metallographic microscopes were used for in-situ observation and to capture the cross-section images of fibers. This in-situ observation allows for the rapid identification of the type and spatial distribution structure of the bicomponent fiber. Finally, the mass percentage content of each component was calculated rapidly by AI software according to its density, cross-section area, and total test samples of each component. By comparing the ultra-depth of field microscope, differential scanning calorimetry (DSC), and chemical dissolution method, the quantitative analysis was fast, accurate, economical, simple to operate, energy-saving, and environmentally friendly. This method will be widely used in the intelligent qualitative identification and quantitative analysis of bicomponent fibers, fiber-based flexible devices, and blended textiles.

Simultaneous, Label-Free and High-throughput SERS Detection of Multiple Pesticides on Ag@Three-Dimensional Silica Photonic Microsphere Array

Rapid identification and quantitative simultaneous analysis for multiple pesticide in real samples based on surface-enhanced Raman spectroscopy (SERS) is still a challenge because of sample complexity, reproducibility, and stability of SERS substrate. With use of colloidal silver nanoparticles loaded three-dimensional (3D) silica photonic microspheres (SPMs) array as the analytical platform, a SERS-based array assay for multiple pesticides was developed in this work. The silver nanoparticles were fixed into the gaps formed by the self-assembled nanospheres of the 3D SPMs to produce "hot spots", on which the Raman enhanced effect was up to 9.86 × 107 and the maximum electric field enhancement effect reached to 9.75 times, ensuring the target pesticides on the surface of the SERS-substrate integrated SPM can be detected sensitively. Using 2,4-dichlorophenoxyacetic acid (2,4-D), glyphosate, and imidacloprid as the testing pesticides, the label-free and high-throughput SERS assay for simultaneous detection of the pesticides was established, giving good linear detection ranges (0.1-204.8 μg/mL for 2,4-D, 0.3-247.9 μg/mL for glyphosate, and 0.2-204.8 μg/mL for imidacloprid) and low detection limits (3.03 ng/mL for 2,4-D, 3.14 ng/mL for glyphosate, and 8.82 ng/mL for imidacloprid). The spiked recovery rates in the real samples were measured in the range of 82-112%, which was consistent with that of the classical standard methods. The label-free 3D SERS array analytical platform provides a powerful tool for high-throughput and low-cost screening of multiple pesticide residues in real samples.

Introduction of multilayered magnetic core–dual shell SERS tags into lateral flow immunoassay: A highly stable and sensitive method for the simultaneous detection of multiple veterinary drugs in complex samples

Direct, convenient, and sensitive monitoring of the residues of multiple drugs in complex environments is important but remains a challenge. Here, we report a surface-enhanced Raman scattering (SERS)-based multiplexed lateral flow immunoassay (LFA) that supports the simultaneous and sensitive detection of commonly used drugs kanamycin, ractopamine, clenbuterol, and chloramphenicol in unprocessed complex samples through the dual signal amplification strategy of numerous efficient hotspots and magnetic enrichment. Multilayered magnetic-core dual-shell nanoparticles (MDAu@Ag) with controllable subtle nanogaps were fabricated via the polyethyleneimine-mediated layer-by-layer (LBL) assembly of two layers of Au@Ag satellites onto superparamagnetic Fe3O4 cores and conjugated with specific antibodies as multifunctional tags in the LFA system for rapid capture, separation, and quantitative analysis. Two Raman reporters were embedded in internal nanogaps and modified on the surface of MDAu@Ag for the simultaneous and ultrasensitive detection of four targets on two test lines, which greatly simplified the fabrication and signal reading of SERS-LFA. The proposed assay can rapidly detect multiple drug residues in 35 min with detection limits down to pg/mL level. Moreover, the MDAu@Ag–based SERS-LFA demonstrated better stability, higher throughput, and superior sensitivity (at least 400 times) than traditional colloidal gold immunochromatography, showing its great potential in the field of point-of-care testing.

Prism Design for Spectral Flow Cytometry

Flow cytometers are instruments used for the rapid quantitative analysis of cell suspension. Traditional flow cytometry uses multi-channel filters to detect fluorescence, whereas full-spectrum fluorescence based on dispersion detection is a more effective and accurate method. The application of various dispersion schemes in flow cytometry spectroscopy has been studied. From the perspective of modern detectors and demand for the miniaturization of flow cytometry, prism dispersion exhibits higher and more uniform light energy utilization, meaning that it is a more suitable dispersion method for small flow cytometers, such as microfluidic flow cytometers. Prism dispersion designs include the size, number, and placement of prisms. By deducing the formula of the final position of light passing through the prism and combining it with the formula of transmittance, the design criteria of the top angle and the incident angle of the prism in pursuit of the optimum transmittance and dispersion index can be obtained. Considering the case of multiple prisms, under the premise of pursuing a smaller size, the optimal design criteria for dispersion system composed of multiple prisms can be obtained. The design of prism dispersion fluorescence detection was demonstrated with a microfluidic flow cytometer, and the effectiveness of the design results was verified by microsphere experiments and practical biological experiments. This design criterion developed in this study is generally applicable to spectral flow cytometers.

Covalent organic framework film-based laser desorption/ionization mass spectrometry for rapid and sensitive quantification of homocysteine in human serum.

Homocysteine (hcy) is a metabolite in the human body and an important determinant of cardiovascular health. To assist in the assessment of human cardiovascular safety, a rapid and accurate quantitative analysis method must be developed. Laser desorption/ionization mass spectrometry (LDI-MS) has been widely used in biological, chemical and medical analysis due to its excellent characteristics of high throughput, low sample consumption and high speed. Herein, a LDI-MS method based on covalent organic framework (COF) film was developed for rapid and sensitive determination of hcy in human serum using an isotope-labeled internal standard. We tried to cultivate COFs on indium-tin oxide (ITO) substrate at room temperature to form thin film, which was used in LDI-MS. Compared with the traditional organic matrices, the COF film showed clean background and high signal response for the detection of hcy. In addition, using COF film as the substrate that can analyze a series of small molecules such as amino acids, bisphenols (Bps), estrogens, drugs, etc., with high signal intensity and clean background. We evaluated the limit of detection (LOD) and the reproducibility of this method. Finally, the calibration curve was made for the quantification of serum hcy using isotope labeled internal standard, and was applied to the rapid determination of hcy in clinical human serum. COF film-assisted LDI-MS had higher response signal and cleaner background compared to four conventional organic matrices. The LOD of the method for hcy was 0.5 μmol/L, equivalent to 500 fmol. This method exhibited excellent performance for small molecule compounds including amino acids, Bps, drugs, and estrogens. The reproducibilities of this method for shot-to-shot and dot-to-dot were proved to be good. This method was applied to the rapid analysis of hcy in clinical human serum, showing good correlation with those obtained by hospital testing. The COF film-based LDI-MS method showed simple sample preparation, short analysis time, clean background and good reproducibility for hcy analysis. As an important indicator of human health, the detection of serum hcy is of great significance to human health.

Rapid quantitative analysis of rare earth elements Lu and Y in rare earth ores by laser induced breakdown spectroscopy combined with iPLS-VIP and partial least squares.

Rare earth ores are complex in composition and diverse in mineral composition, requiring high technical requirements for the selection of rare earth ores. It is of great significance to explore the on-site rapid detection and analysis methods of rare earth elements in rare earth ores. Laser induced breakdown spectroscopy (LIBS) is an important tool to detect rare earth ores, which can be used for in situ analyses without complicated sample preparation. In this study, a rapid quantitative analysis method for rare earth elements Lu and Y in rare earth ores was established by LIBS combined with an iPLS-VIP hybrid variable selection strategy and partial least squares (PLS) method. First, the LIBS spectra of 25 samples were studied using laser induced breakdown spectrometry. Second, taking the spectrum processed by wavelet transform (WT) as the input variables, PLS calibration models based on interval partial least squares (iPLS), variable importance projection (VIP) and iPLS-VIP hybrid variable selection were constructed to quantitatively analyze rare earth elements Lu and Y, respectively. The results show that the WT-iPLS-VIP-PLS calibration model has better prediction performance for rare earth elements Lu and Y, and the optimal coefficient of determination (R2) of Lu and Y were 0.9897 and 0.9833, the root mean square error (RMSE) were 0.8150 μg g-1 and 97.1047 μg g-1, and the mean relative error (MRE) were 0.0754 and 0.0766, respectively. It shows that LIBS technology combined with the iPLS-VIP and PLS calibration model provides a new method for in situ quantitative analysis of rare earth elements in rare earth ores.

Rapid quantitative analysis of slag acidity by laser induced breakdown spectroscopy combined with random forest

Rapid quantitative analysis of slag acidity by laser induced breakdown spectroscopy combined with random forest

Cu2O/Co3O4 nanoarrays for rapid quantitative analysis of hydrogen sulfide in blood.

2D heterostructure nanoarrays have emerged as a promising sensing material for rapid disease detection applications. In this study, a bio-H2S sensor based on Cu2O/Co3O4 nanoarrays was proposed, the controllable preparation of the nanoarrays being achieved by exploring the experimental parameters of the 2D electrodeposition in situ assembly process. The nanoarrays were designed as a multi-barrier system with strict periodicity and long-range order. Based on the interfacial conductance modulation and vulcanization reaction of Cu2O and Co3O4, the sensor exhibited superior sensitivity, selectivity, and stability to H2S in human blood. In addition, the sensor exhibited a reasonable response to 0.1 μmol L-1 Na2S solution, indicating that it had a low detection limit for practical applications. Moreover, first-principles calculations were performed to study changes in the heterointerface during the sensing process and the mechanism of rapid response of the sensor. This work demonstrated the reliability of Cu2O/Co3O4 nanoarrays applied in portable sensors for the rapid detection of bio-H2S.

Quantitative analysis of phenanthrene in soil by fluorescence spectroscopy coupled with the CARS-PLS model.

Polycyclic aromatic hydrocarbons (PAHs) are typical organic pollutants in soil and are teratogenic and carcinogenic. Therefore, rapid and accurate analysis of PAHs in soil can provide a theoretical basis and data support for soil contamination risk assessment. In this work, a fluorescence spectroscopy technique combined with partial least squares (PLS) was proposed for rapid quantitative analysis of phenanthrene (PHE) in soil. At first, the fluorescence spectra of 29 soil samples with different concentrations (0.3-10 mg g-1) of PHE were collected by RF-5301 PC fluorescence spectrophotometer. Secondly, the effects of different spectral preprocessing methods were investigated on the prediction performance of the PLS calibration model. And then, the influence of competitive adaptive reweighted sampling (CARS) wavelength points on the prediction performance of PLS calibration model was discussed. Finally, according to the selected wavelength points, a quantitative analytical model for PHE content in soil was constructed using the PLS calibration method. To further explore the predictive performance of the CARS-PLS calibration model, the predictive results were compared with those of the RAW spectrum-partial least squares calibration model (RAW-PLS) and the wavelet transform-standard normal variation (WT-SNV) calibration model. The CARS-PLS calibration model showed the optimal predictive performance and its coefficient of determination of cross-validation (R cv 2) and root mean square error of 10-fold cross-validation (RMSEcv) were 0.9957 and 18.98%, respectively. The coefficient of determination of prediction set (R p 2) and root mean square error of prediction set (RMSEp) were 0.9963 and 16.13%, respectively. Hence, the CARS algorithm based on fluorescence spectrum coupled with PLS can give a rapid and accurate quantitative analysis of the PHE content in soil.

Rapid Analysis of Four Alkaloids in Uncaria rhynchophylla by Core-Shell Column HPLC and Quantitative Analysis of Multi-Components by Single Marker (QAMS)

As a traditional herbal medicine, the major alkaloids in Uncaria rhynchophylla have been proven to have blood pressure-lowering and sedative effects. It is essential to develop an effective method for the determination of the major alkaloids in U. rhynchophylla. In this research, a rapid quantitative analysis involving multi-components analysis by a single marker strategy coupled with core-shell column HPLC was adopted to analyse four alkaloids (corynoxeine, isocorynoxeine, isorhynchophylline, rhynchophylline) in U. rhynchophylla. Isorhynchophylline was selected as the internal reference substance, the content of which was determined by the traditional external standard method. Relative correction factors (RCF) between isorhynchophylline and the other three alkaloids were calculated respectively. The results showed that the QAMS method had good robustness under different HPLC instruments. Nineteen batches of U. rhynchophylla were tested. No significant difference was observed between the results by QAMS and EMS (Correlation coefficient > 0.99, p > 0.05). The QAMS method could be employed as a rapid, effective technique for the quality control of U. rhynchophylla.

Pathological Detection of Micro and Fuzzy Gastric Cancer Cells Based on Deep Learning

In recent years, with the increasing incidence of cancer, regular physical examination is an important way to find cancer. Nuclear screening is an important method for the diagnosis of gastrointestinal diseases, but it is challenging in the face of small and fuzzy gastrointestinal images. Different from traditional medical objects, pathological slice images are mostly blurry and tiny, which is somewhat difficult to detect and segment. The traditional diagnostic method lacks rapid quantitative analysis and has a certain delay in medical diagnosis, and traditional image processing uses morphological features and pixel distribution to extract features; it is often difficult to achieve the desired effect on small blurry images. This paper proposes a small, microfuzzy pathology detection algorithm based on the attention mechanism; the YOLOv5 is improved under small and micro fuzzy scenarios of the detection of cancer cells in the full field of digital pathology and tests it in the gastric cancer slice dataset. The network structure is improved, and the ability to learn features on small and micro targets is enhanced according to the law of feature distribution. Spatial and channel changes in network attention and attention weight distribution. In the deep blur scenario, the attention mechanism is added to optimize its recognition ability, and the test result shows F1_score is 0.616, and the mAP is 0.611, which can provide the decision support for clinical judgment.

A comprehensive quality control evaluation for standard decoction of Smilax glabra Roxb based on HPLC-MS-UV/CAD methods combined with chemometrics analysis and network pharmacology

An effective, sensitive, and rapid method was developed for the quality control evaluation of the standard decoction of Smilax glabra Roxb (SGR). SGR is a primary ingredient of the traditional functional foods of turtle jelly and SGR tea. Chemometrics, Network Pharmacology, and molecular docking were used to screen for six quality markers. Multiple extraction parameters were optimized. HPLC-UV/CAD-QAMS was used to rapidly quantify the six quality markers (neoastilbin, astilbin, neoisoastilbin, isoastilbin, quercitrin, and isoengeletin) in 10 batches of the standard decoction of SGR samples. The relative correction factor (RCF) values of the five compounds were close to 1, demonstrating that the charged aerosol detection (CAD) showed a consistent response to compounds with similar parent nucleus structures. This method can serve as a guide for rapid quantitative analysis of the multi-components of the SGR standard decoction and all the traditional functional foods of turtle jelly with the homology of medicine.

An integrated microfluidic device for the simultaneous detection of multiple antibiotics

Residual antibiotics in food pose a serious long-term threat to human health. Therefore, an on-site visualization method for antibiotic detection is required. However, the requirements of traditional antibiotic testing methods in terms of operator proficiency and equipment cost hinder the rapid point-of-care-testing detection of suspected samples. Herein, we reported an integrated microfluidic device combining a microfluidic chip containing cruciform valves with immunochromatographic strips for the rapid detection of multiple antibiotics in milk. The rapid qualitative and quantitative analysis of four types of antibiotics (sulfonamides, β-lactams, streptomycin, and tetracyclines) was performed using mobile phone photography and mobile phone application analysis. The detection time was maintained at 10 min. The limits of detection (LODs) for the four antibiotics were 0.15, 0.12, 0.25, and 0.29 ng/mL, respectively, and the selectivity for the different antibiotics was observed even in a highly complex matrix. This device successfully integrated separation and real-time detection onto a chip and might provide a promising perspective for the detection of multiple antibiotics in milk.

Fast quantification of diclofenac sodium content in commercially available tablets by transmission Raman spectroscopy with PLS

AbstractA new technology based on transmission Raman spectroscopy was developed for the determination of diclofenac sodium (DS) in commercially available tablets using chemometric tools such as partial least squares (PLS). Based on multifactor orthogonal design of experiment (DOE), we established an initial model consisting of 150 handmade tablets. By adding only two commercially available tablets spectra to the initial model, it was successfully applied to the determination of the active pharmaceutical ingredient (API) of three commercially available diclofenac sodium tablets. The results showed that the relative error of content measured by TRS for three brands of tablets was less than 4% and the RSD of 20 commercially available tablets under brand of Ouyi was 0.49%. The method can ensure high accuracy and good repeatability in rapid nondestructive quantitative analysis and can be used as a new technology for quality control on production lines to monitor drugs in real time.

Near-the-Line Steel Slag Analysis Using Laser-Induced Breakdown Spectroscopy: Traditional Univariate Versus Machine Learning Calibration Methods.

This work is focused on rapid quantitative analysis of slag in the steel industry for improved process control. The novel approach in this work is a direct comparison of two methods to calibrate and quantify spectral data from the slags. Calibration was first done with the most prevalent method in quantitative optical emission spectroscopy (OES) of solids, the univariate ratio method. The second method is an advanced multivariate analysis (MVA) algorithm termed Elastic Net, allowing to include several lines for each element in the calibration functions. In both methods, the output is mass fraction ratios of the analyte element (or compound) to a matrix element (compound). The actual mass fractions of each compound are calculated by sum normalization assuming the matrix to make up the difference up to 100%. The metric used to evaluate the performance of the methods in terms of accuracy is the parameter σrel calculated as the ratio of the root mean square (RMS) deviation from values obtained by X-ray fluorescence (XRF) divided by the average mass fraction of the compound, expressed in percent. A bit surprising, the main outcome of the comparison is that there is very little difference in the performance of the two methods. One exception is the analysis of MgO, where the elastic net gives significantly better accuracy. Presumably, this is due to the use of multiple lines for Mg to build the calibration function. This is very encouraging, since MgO is a major compound in most slags that needs to be determined accurately. It is suggested to improve accuracy further by means of separate calibrations for a limited number of slag types.