Poor Detection Sensitivity Research Articles

Long afterglow nanoprobes labeled image enhancement using deep learning in rapid and sensitive lateral flow immunoassay

Point-of-care testing (POCT) is currently the predominant method of in vitro diagnostics, with lateral flow immunoassay(LFIA) being commonly utilized in POCT. The performance of the probe in LFIA will directly affect the results of the detection. Therefore, the selection of probes is particularly important. However, the current commercially produced probes generally suffer from short luminescence lifetime, high detection cost, and poor anti-interference capability. Meanwhile, the traditional detection system has difficulties in detecting weakly positive samples. These ultimately lead to the problem of poor detection sensitivity. In order to address the above issues, we have synthesized an ultralong organic phosphorescence nanoprobe (UOPN). The UOPNs exhibit a long afterglow phosphorescence signal of around 300 ms after being excited, which can be used to eliminate endogenous interference. Meanwhile, focusing on the problem of poor detection of weakly positive samples in conventional detection systems, and the weak inherent signal of UOPNs, resulting in a low signal-to-noise ratio, we have developed a detection system that combines image processing and neural network-driven analysis for long afterglow image analysis. Through the analysis of the long afterglow images of serum amyloid A (SAA) in human blood, a detection limit of 0.01 μg/mL and a linear range of 0.1–251 μg/mL were achieved. The whole analysis was completed within 5 minutes. After pre-processing with the denoising algorithm, the system demonstrated an impressive classification accuracy of 99.24 %, validating the reliability of the detection system. This approach has further enhanced the sensitivity of immunoassay, contributing to the advancement of point-of-care testing.

Conquering the beyond Rule of Five Space with an Optimized High-Throughput Caco-2 Assay to Close Gaps in Absorption Prediction.

Current drug development tends towards complex chemical molecules, referred to as "beyond rule of five" (bRo5) compounds, which often exhibit challenging physicochemical properties. Measuring Caco-2 permeability of those compounds is difficult due to technical limitations, including poor recovery and detection sensitivity. We implemented a novel assay, with optimized incubation and analytics, to measure permeability close to equilibrium. In this setup an appropriate characterization of permeability for bRo5 compounds is achievable. This equilibrated Caco-2 assay was verified with respect to data validity, compound recovery, and in vitro to in vivo correlation for human absorption. Compared to a standard assay, it demonstrated comparable performance in predicting the human fraction absorbed (fa) for reference compounds. The equilibrated assay also successfully characterized the permeability of more than 90% of the compounds analyzed, the majority of which were bRo5 (68%). These compounds could not be measured using the standard assay. Permeability and efflux ratio (ER) were highly predictive for in vivo absorption for a large set of internal bRo5 compounds. Reference cut-offs enabled the correct classification of high, moderate, and low absorption. This optimized equilibrated Caco-2 assay closes the gap for a high-throughput cellular permeability method in the bRo5 chemical space.

A novel competitive color-tone change fluorescence immunochromatographic assay for the ultrasensitive detection of pesticide and veterinary drug residues

One important challenge faced by competitive immunoassay techniques is the inability to visually distinguish weak color changes in the T-line during the detection of trace analyte concentrations. In this study, we introduced multi-color fluorescence into the immunoassay system and developed a novel competitive dual-channel color-tone change fluorescent immunochromatographic assay (CFICA) for the visual and quantitative detection of kanamycin (KAN) and carbendazim (CBZ). At the same time, we have developed matching, portable fluorescence-reading equipment, which can analyse the spectral data of the RGB channel individually and can effectively solve the problems of the traditional single-fluorescence reader – large reading error and poor detection sensitivity. After optimization, our CFICA, combined with the corresponding instrument, achieved low limits of detection (LOD) for KAN and CBZ, as low as 1.98 and 12.82 pg/mL, respectively. We believe that this CFICA detection system, with its high accuracy, low error, and multi-color detection capabilities, holds tremendous potential for visual and multi-channel competitive point-of-care testing.

More small tools for sweet challenges: advances in microfluidic technologies for glycan analysis

Carbohydrates, also known glycans, are ubiquitous in nature and exhibit a wide array of biological functions essential to life. Glycans often exist as conjugates of proteins or lipids and reside predominantly at the surface of cells, where their structure and composition are known to vary in a disease-dependent fashion. This observation has encouraged the development of tools for monitoring glycan patterns on individual molecules, cells, and tissues, to elucidate the links between glycosylation and disease for therapeutic and diagnostic applications. Over the past 2 decades, microfluidic technology has emerged as an advantageous tool for profiling the glycan content of biological systems. Miniaturizing carbohydrate analysis can circumvent several challenges commonly encountered with conventional-scale analytical techniques such as low throughput and poor detection sensitivity. The latter is often complicated by the low abundance of glycans in biological specimens and the complexity of carbohydrate structures, which often necessitates extensive concentration and purification of glycans to discern their structural features. We previously examined the application of microfluidics in the synthesis of carbohydrates in a recent paper (Pinnock et al., Anal. Bioanal. Chem., 2022, 414 (18), 5139–63). This review builds upon that discussion by delving into the application of microfluidics in the complementary field of carbohydrate analysis. Special attention is given to applications related to glycomics and the ways that microfluidics have enhanced the sensitivity, reproducibility, and throughput of carbohydrate identification and structural characterization.

The Feasibility of Digital Testing using a Smartphone Application for Precision Brain Health Monitoring in the Framingham Heart Study

AbstractBackgroundEarly detection of cognitive decline is critical to identify effective treatments for Alzheimer’s disease and related dementias. The inherent heterogeneity of behaviors associated with brain health may obscure the signals derived from a typical neuropsychological evaluation, partly because of the limited frequency of assessment with which it can be conducted. This may lead to inaccurate or poor detection sensitivity. Digital health technology using smartphone applications enables frequent assessment and, thereby, more precise monitoring of brain health. The current study sought to examine the feasibility of using smartphone application‐based tasks in community‐based participants from the Framingham Heart Study (FHS).MethodThe smartphone application consists of three blocks of assessments, lasting approximately 15‐20 minutes (Figure 1). Block 1: Participants answer questions to ensure that they can see the stimuli and hear the instructions adequately. Block 2: Participants complete a series of cognitive tasks and respond to open‐ended questions which are voice recorded. Block 3: To ensure that performance is not influenced by external factors, participants respond to questions, for example, about their experiences with using the smartphone application.ResultTo date, 318 FHS participants have been enrolled into the study. Of these, as of 12/09/2022, 168 participants’ first assessment period has been completed within the two week period after being enrolled in the study. Of the 168 participants, a large majority (81%; n = 136) completed all the tasks, while the remaining 32 completed partial assessment. Table 1 reveals that the overall percentage of participants who have been enrolled in the study and the percentage of those who completed their first assessment are highly similar.ConclusionFindings reveal that older adults from a large, community‐based study are able to successfully download and complete the first set of tasks using their smartphone application. As data collection is ongoing, the number of older adults recruited into the study is expected to increase exponentially. These results indicate that it is feasible to monitor brain health on an on‐going basis using self‐administered smartphone applications, potentially creating an effective, lower cost, and scalable approach to detect significant changes in cognitive functions earlier and more accurately in the preclinical neurodegenerative process.

Image denoising for laser ultrasonic inspection of wire arc additive-manufactured components with a rough surface

ABSTRACT Laser ultrasonic testing (LUT) is a non-contact and non-destructive testing (NDT) technique which can detect the wire arc additive manufacturing (WAAM) component defect in hot state. However, the complex surface topography of the WAAM component induces a low signal to noise ratio (SNR) and a poor detection sensitivity. In this paper, a denoising method based on improved empirical mode decomposition with adaptive noise (ICEEMDAN) and Wavelet Packet Transform (WPT) was applied in the LUT of the WAAM component. All the signals in the LUT scan maps with low SNR were decomposed into a series of intrinsic mode functions (IMFs) using ICEEMDAN. The Pearson correlation coefficient of the original signal and the IMFs were calculated. The high frequency (HF) and low frequency (LF) IMFs with correlation coefficients under the threshold were denoised using WPT and deleted, respectively. The denoised IMFs and the IMFs without processing were stacked up to compose the denoised signal and plot the denoised scan maps. The denoising results show that the proposed method improved the LUT efficiency and sensitivity. Finally, the denoising method was applied and verified in the LUT of the WAAM nuclear power pipeline nozzle.

Management of Persistent Pulmonary Air Leak with the Drentech™ Simple System. Case Report

Persistent pulmonary air leak affects between 10-15% of pulmonary surgical procedures, generally requiring management through the use of conventional chest drainage systems (water-sealed pleural chamber) of subjective interpretation due to poor detection sensitivity. of leaks, resulting in increased morbidity, hospital stay, and costs.

Significantly increased Raman enhancement enabled by hot-electron-injection-induced synergistic resonances on anisotropic ReS2 films.

Two-dimensional (2D) materials are an excellent platform for surface-enhanced Raman spectroscopy (SERS). However, a poor detection sensitivity hinders their practical application. Exciton resonance (μex) can improve SERS significantly by lending intensity to nearby charge-transfer resonance. Coincidentally, for ReS2, the enhanced μex can be achieved through the injection of excited-state electrons which can adjust the energy band to the SERS detection range. Moreover, ReS2 has strong anisotropic properties, which adds an additional dimension for SERS. Therefore, ReS2 is an ideal candidate to realize highly sensitive anisotropic SERS. In this paper, the metallic T phase of ReS2 is introduced to the semiconducting Td phase by phase engineering. The photoinduced electron tunneling from the T phase to the Td phase can tune exciton emissions to the visible region, which effectively facilitates the photoinduced charge transfer processes. With RhB as the probe molecule, the synergistic resonance effects improve the limit of detection to 10-9 M with the enhancement factor up to about 108. Meanwhile, the obtained ultrasensitive SERS substrates also show good uniformity, stability as well as unique anisotropy. Our results open a new perspective in the improvement of the SERS performance.

Hyphenating temperature gradient elution with refractive index detection through temperature-responsive liquid chromatography

Refractive index detection (RID) is attractive because it allows approaching the benefits of universal detection with liquid chromatography, by which ideally standard independent calibration and hence compound independent quantification becomes possible. Nevertheless, the implementation of RID has remained limited as it offers poor detection sensitivity while only being compatible with isocratic mobile phases. The implementation of compositional solvent gradients has remained prohibitively challenging in commercial HPLC-RID systems due to the resulting drastic alterations in refractive index and extreme baseline drift. While the refractive index is also highly dependent on temperature, more leeway appears possible to mitigate the problem, particularly when the used temperature gradients can be limited. Temperature-responsive liquid chromatography (TRLC) allows obtaining isocratic reversed phase type of separations, whereby retention is modulated via temperature changes ∼ 15 °C–20 °C above and below the polymer conversion temperature. Elution profiles, reminiscent of what can be obtained with solvent gradients in conventional RPLC, can then be obtained by enacting downwards temperature gradients on the columns. This work comprises a proof-of-principle to illustrate the possibilities of combining thermal gradient TRLC with RID. The observed baseline drift appeared thereby very minor (<5 nRIU min-1), and hence easily controllable. Short chain fatty acids are used as representative compounds to assess this new approach. Overlapping calibration lines are accordingly obtained for all fatty acids between butyric and decanoic acid.

Detection and quantification of Verticillium dahliae and V. longisporum by droplet digital PCR versus quantitative real-time PCR.

Vascular wilt, caused by Verticillium dahliae and V. longisporum, limits the quality and yield of agricultural crops. Although quantitative real-time PCR (qPCR) has greatly improved the diagnosis of these two pathogens over traditional, time-consuming isolation methods, the relatively poor detection sensitivity and high measurement bias for traceable matrix-rich samples need to be improved. Here, we thus developed a droplet digital PCR (ddPCR) assay for accurate, sensitive detection and quantification of V. dahliae and V. longisporum. We compared the analytical and diagnostic performance in detail of ddPCR and the corresponding qPCR assay against the genomic DNA (gDNA) of the two fungi from cultures and field samples. In our study, the species specificity, quantification linearity, analytical sensitivity, and measurement viability of the two methods were analyzed. The results indicated that ddPCR using field samples enhanced diagnostic sensitivity, decreased quantification bias, and indicated less susceptibility to inhibitors compared with qPCR. Although ddPCR was as sensitive as qPCR when using gDNA from cultures of V. dahliae and V. longisporum, its detection rates using field samples were much higher than those of qPCR, potentially due to the inhibition from residual matrix in the extracts. The results showed that digital PCR is more sensitive and accurate than qPCR for quantifying trace amounts of V. dahliae and V. longisporum and can facilitate management practices to limit or prevent their prevalence.

Remote Raman Detection of Trace Explosives by Laser Beam Focusing and Plasmonic Spray Enhancement Methods.

Remote Raman spectroscopy is a technique that can detect and identify different target molecules through Raman vibrational modes from a remote distance. However, the current remote Raman technique is restricted by poor detection sensitivity, and it is still extremely challenging for trace explosive detection. Here, in order to achieve trace explosive detection from a remote distance, we innovatively propose two enhanced Raman spectroscopy methods by using a plasmonic spray and a laser beam focusing/Raman signal collecting instrument. In brief, a facile convex lens can converge the laser beam and collect Raman scattering signals, and a plasmonic spray can be used for surface-enhanced Raman scattering. Under the combination of the above enhancement methods, we achieve remote Raman detection of a variety of trace explosives with a concentration of ∼1 μg/cm2 from a distance of 30 m. These novel methods demonstrate a simple approach that significantly improves the capability of remote detection of trace chemicals for further applications.

Defect-Rich Monolayer MoS2 as a Universally Enhanced Substrate for Surface-Enhanced Raman Scattering.

Monolayer 2H-MoS2 has been widely noticed as a typical transition metal dichalcogenides (TMDC) for surface-enhanced Raman scattering (SERS). However, monolayer MoS2 is limited to a narrow range of applications due to poor detection sensitivity caused by the combination of a lower density of states (DOS) near the Fermi energy level as well as a rich fluorescence background. Here, surfaced S and Mo atomic defects are fabricated on a monolayer MoS2 with a perfect lattice. Defects exhibit metallic properties. The presence of defects enhances the interaction between MoS2 and the detection molecule, and it increases the probability of photoinduced charge transfer (PICT), resulting in a significant improvement of Raman enhancement. Defect-containing monolayer MoS2 enables the fluorescence signal of many dyes to be effectively burst, making the SERS spectrum clearer and making the limits of detection (LODs) below 10−8 M. In conclusion, metallic defect-containing monolayer MoS2 becomes a promising and versatile substrate capable of detecting a wide range of dye molecules due to its abundant DOS and effective PICT resonance. In addition, the synergistic effect of surface defects and of the MoS2 main body presents a new perspective for plasma-free SERS based on the chemical mechanism (CM), which provides promising theoretical support for other TMDC studies.

Exploring spectroscopic X-ray nano-imaging with Zernike phase contrast enhancement

Spectroscopic full-field transmission X-ray microscopy (TXM-XANES), which offers electrochemical imaging with a spatial resolution of tens of nanometers, is an extensively used unique technique in battery research. However, absorption-based bright-field imaging has poor detection sensitivity for nanoscale applications. Here, to improve the sensitivity, we explored spectroscopic X-ray nano imaging with Zernike phase contrast (ZPC-XANES). A pinhole-type Zernike phase plate, which was optimized for high-contrast images with minimal artifacts, was used in this study. When the absorption is weak, the Zernike phase contrast improves the signal-to-noise ratio and the contrast of images at all energies, which induces the enhancement of the absorption edge step. We estimated that the absorption of the samples should be higher than 2.2% for reliable spectroscopic nano-imaging based on XANES spectroscopy analysis of a custom-made copper wedge sample. We also determined that there is a slight absorption peak shift and sharpening in a small absorption sample due to the inflection point of the refractive index at the absorption edge. Nevertheless, in the case of sub-micron sized cathode materials, we believe that better contrast and higher resolution spectroscopic images can be obtained using ZPC-XANES.

Study of Capacitive Coupling Sensor Fused With High Voltage XLPE Cable Joint

A capacitive coupling sensor for partial discharge detection with the fusion of high voltage XLPE cable joint is designed in this paper. The sensor is to address partial discharge signals leading to transmission attenuation and external interference causing poor field detection sensitivity. First, a coaxial waveguide transmission model was established of high-frequency electrical signals in the body and joint. The result showed that the signal transmission attenuation was minimized while the sensor electrodes were closely attached to the outer semi-conductive layer of the body. Second, the equivalent circuit model was constructed of the capacitive coupling sensor fused with the 110 kV straight passing joint. The specific installation location, main structure size, detection bandwidth, and sensitivity of the sensor in the joint area were determined, which was to maximize the coupling output signal amplitude and transfer function amplitude. Finally, a lightning surge voltage test was carried out with the integration of the fusion of the joint voltage thermal cycling. Simulation and measurement show the following: while the sensor is installed in the cable metal sleeve break and the electrodes are closed to the overall semi-conductive layer, there is excellent performance for partial discharge detection in the frequency range of 1–300 MHz, with a sensitivity of 5 pC.

Ultrasensitive detection of butyrylcholinesterase activity based on self-polymerization modulated fluorescence of sulfur quantum dots

Butyrylcholinesterase (BChE) is an important clinical diagnosing index for liver dysfunction and organophosphate toxicity. However, the current assays for BChE activity are suffering from the relative poor detection sensitivity. In this work, an ultrasensitive fluorescence assay for BChE activity was developed based on the self-polymerization modulated fluorescence of sulfur quantum dots (S-dots). The luminescence of S-dots can be quenched by the self-polymerized dopamine. The hydrolysate of substrates, thiocholine, under the catalysis of BChE can reduce dopamine, which results in the inhibition of self-polymerization and the fluorescence recovery of S-dots. BChE can be quantitatively detected by recording the recovered fluorescence of S-dots, and a linear relationship is observed between the ratio of fluorescence and the concentration of BChE in the range from 0.01 to 10 U/L. A limit of detection as low as 0.0069 U/L calculated, which is the lowest number so far. The assay also shows excellent selectivity towards various interference species and acetylcholinesterase. These features allowed the direct detection of BChE activity in human serum, demonstrating the great practical applications of our assay.

Determination of new carmine in beverages by one step rapid solid phase extraction based on metal organic framework extractant

胭脂红是一种广泛应用的偶氮类色素,我国对其在食品中的添加量有严格规定。由于食品基质的复杂性,针对这类痕量色素很难建立一种灵敏度高、富集性强且高效便捷的检测方法。研究利用卟啉环中的羧基与金属锆离子的配位作用制备了一种高比表面积的金属有机骨架材料(PCN-222),并将纳米材料填入注射式固相萃取装置中,以简化前处理过程,用于快速萃取饮料中胭脂红色素。采用多种表征手段研究了PCN-222纳米材料的形貌、结构及性能。较高的比表面积和静电作用共同决定了新型萃取剂对胭脂红色素具有极强的富集性能。通过优化萃取剂用量、样品溶液pH值、洗脱条件和洗脱剂体积等萃取条件,使目标物实现瞬时吸附,样品前处理时间缩短至5 min。在最佳条件下,该方法可使样品在高、中、低3个水平的加标回收试验中的回收率达到99.5%~109.4%,相对标准偏差小于3%,方法的检出限为0.1 μg/L(S/N=3),定量限为0.3 μg/L(S/N=10)。此外,针对所合成的材料进行萃取-解吸后发现,PCN-222在重复使用4次后仍保持90%以上的萃取能力,表明材料具备可循环性。该方法通过制备的新型金属骨架材料建立了一种高效、便捷、绿色环保的前处理技术,极低的检出限、较高的准确度和较好的重复性表明方法适用于饮料中痕量色素胭脂红的富集和检测。新型固相萃取技术的开发为食品安全检测提供了新思路。

Perovskite-Nanosheet Sensitizer for Highly Efficient Organic X-ray Imaging Scintillator

The weak X-ray capture capability of organic scintillators always leads to poor imaging resolution and detection sensitivity. Here, we realize an efficient and reabsorption-free organic scintillator at the interface of perovskite nanosheets using a very efficient energy transfer strategy. Our steady-state and ultrafast time-resolved experiments supported by density functional theory calculations demonstrate that an efficient interfacial energy transfer from the perovskite nanosheet to the organic chromophore with thermally activated delayed fluorescence (TADF) character can be achieved. Interestingly, we found that the direct harnessing of both singlet and triplet excitons of the TADF chromophores also contributed greatly to its remarkably enhanced radioluminescence intensity and X-ray sensitivity. A high X-ray imaging resolution of 135 μm and a low detection limit of 38.7 nGy/s were achieved in the fabricated X-ray imaging scintillator.

Electroosmotic flow assisted pseudophase to pseudophase microextraction for stacking in capillary zone electrophoresis

A stacking technique is proposed to improve the poor detection sensitivity of capillary zone electrophoresis (CZE) with UV detection. A long injection (e.g., 12.4 cm plug) of model anionic analytes prepared in a dilute solution of hexadecyltrimethylammonium bromide (CTAB) was enriched 26–34-x (compared to a typical or 2.1 mm sample injection) via the injection of a micellar solution of sodium dodecyl sulfate (SDS) prior to CZE separation. During sample injection, the CTAB formed a stationary pseudophase coating, which trapped the analytes at the inner walls of a fused silica capillary. The SDS micelles then released the CTAB admicelles via the formation of solution CTAB-SDS catanionic micelles during SDS plug injection and voltage application. As the SDS micelles moved through the sample zone, the formation of the catanionic micelles then released and accumulated the analytes at the front of the injected SDS zone. The stacking technique is called electroosmotic flow (EOF) assisted pseudophase to pseudophase microextraction because the EOF was essential for the formation of CTAB-SDS catanionic micelles for microextraction. Also, the CTAB and SDS aggregates are both pseudophases, which were used to retain and release the analytes from the capillary wall, respectively.

High-sensitivity determination of available cobalt in soil using laser-induced breakdown spectroscopy assisted with laser-induced fluorescence.

Conventional laser-induced breakdown spectroscopy could not conduct high-sensitivity determination of available cobalt due to spectral interference and weak spectral intensity. To improve the poor detection sensitivity of available cobalt in soil, available cobalt was extracted from soil and prepared. Laser-induced breakdown spectroscopy assisted with laser-induced fluorescence was introduced to excite and detect the cobalt element. The results showed that coefficients of the calibration curve for the available cobalt element could reach 0.9991, and the limits of detection could reach 0.005 mg/kg in soil under optimized conditions, which were all much better than conventional LIBS and reach the international minimum detection standards. This work provides a possible approach for detecting available trace elements in soil.

Automated Detection of Posterior Myocardial Infarction From Vectorcardiogram Signals Using Fourier–Bessel Series Expansion Based Empirical Wavelet Transform

Posterior myocardial infarction (PMI) is a fatal condition of the human heart, wherein the posterior coronary circulation becomes disrupted. If left untreated, the PMI can cause a severe heart attack. To detect PMI, the conventional 12-lead standard electrocardiogram signals demonstrate poor detection sensitivity due to the absence of posterior sensing electrodes. Contrastingly, the three lead vectorcardiogram (VCG) signal has the sensor electrodes placed on the posterior side, thereby improving the reliability of PMI diagnosis. In this letter, we use VCG signals for the classification of PMI and healthy control (HC) subjects. The abnormalities in the electrical conduction due to PMI are captured using Fourier–Bessel series expansion based empirical wavelet transform, followed by the singular value decomposition (SVD). The resultant feature space is then utilized to classify PMI and HC segments using a support vector machine (SVM) classifier with various kernels, namely, linear, Gaussian, and radial basis function (RBF). The SVM with RBF kernel has resulted in the maximum classification accuracy, sensitivity, and specificity of 95.52, 91.08, and 97.45%, respectively, over the Physikalisch-Technische Bundesanstalt diagnostic database. Thus, the proposed method has the potential to be used in the clinical setting for accurate and robust PMI detection.