Increased Detection Sensitivity Research Articles

Exploring Pore Formation and Gas Sensing Kinetics Using Conjugated Polymer-Small Molecule Blends.

Controlling miscibility between mixture components helps induce spontaneous phase separation into distinct domain sizes, thereby resulting in porous conjugated polymer (CP) films with different pore sizes after selective removal of auxiliary components. The miscibility of the CP mixture can be tailored by blending auxiliary model components designed by reflecting the difference in solubility parameters with the CP. The pore size increases as the difference in solubility parameters between the matrix CP and auxiliary component increases. Electrical properties are not critically damaged even after forming pores in the CP; however, excessive pore formation enables pores to spread to the vicinity of the dielectric layer of CP-based field-effect transistors (FETs), leading to partial loss of the carrier-transporting active channel in the FET. The porous structure is advantageous for not only increasing detection sensitivity but also improving the detection speed when porous CP films are applied to FET-based gas sensors for NO2 detection. The quantitative analysis of the response-recovery trend of the FET sensor using the Langmuir isotherm suggests that the response speed can be improved by more than 2.5 times with a 50-fold increase in NO2 sensitivity compared with pristine CP, which has no pores.

Evaluation of different molecular systems for detection and quantification of SARS-CoV-2 RNA from wastewater samples

Wastewater-based epidemiology has proved to be a suitable approach for tracking the spread of epidemic agents including SARS-CoV-2 RNA. Different protocols have been developed for quantitative detection of SARS-CoV-2 RNA from wastewater samples, but little is known on their performance. In this study we compared three protocols based on Reverse Transcription Real Time-PCR (RT-PCR) and one based on Droplet Digital PCR (ddPCR) for SARS-CoV-2 RNA detection from 35 wastewater samples. Overall, SARS-CoV-2 RNA was detected by at least one method in 85.7 % of samples, while 51.4 %, 22.8 % and 8.6 % resulted positive with two, three or all four methods, respectively. Protocols based on commercial RT-PCR assays and on Droplet Digital PCR showed an overall higher sensitivity vs. an in-house assay. The use of more than one system, targeting different genes, could be helpful to increase detection sensitivity.

Unveiling Inter- and Intra-Patient Sequence Variability with a Multi-Sample Coronavirus Target Enrichment Approach

Amid the global challenges posed by the COVID-19 pandemic, unraveling the genomic intricacies of SARS-CoV-2 became crucial. This study explores viral evolution using an innovative high-throughput next-generation sequencing (NGS) approach. By taking advantage of nasal swab and mouthwash samples from patients who tested positive for COVID-19 across different geographical regions during sequential infection waves, our study applied a targeted enrichment protocol and pooling strategy to increase detection sensitivity. The approach was extremely efficient, yielding a large number of reads and mutations distributed across 10 distinct viral gene regions. Notably, the genes Envelope, Nucleocapsid, and Open Reading Frame 8 had the highest number of unique mutations per 1000 nucleotides, with both spike and Nucleocapsid genes showing evidence for positive selection. Focusing on the spike protein gene, crucial in virus replication and immunogenicity, our findings show a dynamic SARS-CoV-2 evolution, emphasizing the virus–host interplay. Moreover, the pooling strategy facilitated subtle sequence variability detection. Our findings painted a dynamic portrait of SARS-CoV-2 evolution, emphasizing the intricate interplay between the virus and its host populations and accentuating the importance of continuous genomic surveillance to understand viral dynamics. As SARS-CoV-2 continues to evolve, this approach proves to be a powerful, versatile, fast, and cost-efficient screening tool for unraveling emerging variants, fostering understanding of the virus’s genetic landscape.

Detection of sgRNA via SHERLOCK as Potential CRISPR Related Gene Doping Control Strategy.

Apprehensions about gene doping have grown consistently due to advancements in gene engineering techniques, particularly with the emergence of clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR/Cas)-based tools. These tools not only provide unprecedented possibilities for illicit performance enhancement by athletes but also offer new avenues for the detection of gene doping through biosensing of nucleic acids. Hence, pursuing on a previous study, an analytical method based on reverse transcriptase-recombinase polymerase amplification (RT-RPA) and subsequent qualitative nucleic acid detection by means of Specific High Sensitive Enzymatic Reporter UnLOCKing (SHERLOCK) was optimized for the direct detection of sgRNA associated with Streptococcus pyogenes in serum. Detection device, assay parameters, and sample handling were adjusted, to overcome previously determined assay limitations. The conducted method characterization confirmed the methods' specificity and increased detection sensitivity from 100 pM to 1 fM sgRNA in 100 μL of serum. Furthermore, reanalysis of in vivo mouse administration samples collected in a previous proof-of-concept study was conducted with successful identification of sgRNA in all anticipated postadministration samples within the 24-h collection period. Those findings support the applicability of the refined analytical procedure for the detection of illegal doping attempts via ribonucleoprotein-based CRISPR/Cas application through sgRNA identification, offering a new potential doping control strategy for CRISPR related gene doping.

Abstract 791: Evaluation of BCR spike-in controls using DriverMap adaptive immune receptor (AIR) profiling technology

Abstract The DriverMap™ Adaptive Immune Receptor (AIR) repertoire profiling assay employs multiplex RT-PCR for comprehensive profiling of CDR3 or full-length receptor profiling of all variable heavy and light chains of T-cell receptors (TCR) and B-cell receptors (BCR) from either RNA or DNA. In this study, initiated by a U.S. Food and Drug Administration (FDA) consortium to compare performance of different BCR repertoire profiling technologies, we tested spike-ins in peripheral blood mononuclear cell (PBMC) RNA and DNA control mixtures prepared from nine different B-cell lines. We measured the sensitivity, linearity and accuracy of AIR RNA and DNA BCR profiling for the IGH, IGK and IGL chains of the spike-in controls. Our comprehensive analysis, encompassing CDR3 profiling and full-length receptor profiling (CDR1, CDR2, and CDR3) sequencing, revealed a 100X increase in sensitivity of detection of spike-in controls in RNA compared to the DNA assay. The high sensitivity of the full-length DriverMap AIR RNA assay allowed the detection of controls from all nine cell lines, with 8 out of 9 cell lines detected in the DNA assay, which demonstrates the robustness of the DriverMap AIR profiling technology. This study highlights the remarkable sensitivity of the AIR RNA assay in quantifying transcripts. This approach enables the detection of low-frequency BCR clonotypes, which is particularly advantageous when working with samples containing low numbers of B cells. Furthermore, our AIR DNA assay in combination with spike-in controls offers a quantitative tool for minimal residual disease (MRD) applications, providing accurate insight into cell numbers, which then facilitates tracking clonal expansion of immune cells. Citation Format: Alex Chenchik, Tianbing Liu, Mikhail Makhanov, Dongfang Hu, Khadija Ghias, Paul Diehl. Evaluation of BCR spike-in controls using DriverMap adaptive immune receptor (AIR) profiling technology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 791.

Lanthanide-Assisted Nanozyme Performs Optical and Magnetic Resonance Dual-Modality Logical Signal for In Vitro Diagnosis.

The iron nanozyme-based colorimetric method, which is widely applied for biosubstrate detection in in vitro diagnosis (IVD), faces some limitations. The optimal catalytic conditions of iron nanozymes necessitate a strong acidic environment, high temperature, and other restrictive factors; additionally, the colorimetric results are highly influenced by optical interferences. To address these challenges, iron nanozymes doped with various transition elements were efficiently prepared in this study, and notably, the manganese-modified one displayed a high catalytic activity owing to its electron transfer property. Furthermore, the introduction of lanthanide ions into the catalytic reactions, specifically the neodymium ion, significantly boosted the generation efficiency of hydroxyl radicals; importantly, this enhancement extended to a wide range of pH levels and temperatures, amplifying the detection signal. Moreover, the nanozyme's superparamagnetic characteristic was also employed to perform a logical optical and magnetic resonance dual-modality detection for substrates, effectively eliminating background optical interference and ensuring a reliable verification of the signal's authenticity. Based on this magnetic signal, the integration of natural glucose oxidase with the nanozyme resulted in a notable 61.5% increase in detection sensitivity, surpassing the capabilities of the traditional colorimetric approach. Consequently, the incorporation of lanthanide ions into the magnetic nanozyme enables the effective identification of physiological biomarkers through the dual-modality signal. This not only guarantees enhanced sensitivity but also demonstrates significant potential for future applications.

Role of Corticomedullary phase in increasing detection sensitivity of Urinary bladder cancer

Role of Corticomedullary phase in increasing detection sensitivity of Urinary bladder cancer

A stable, highly concentrated fluorous nanoemulsion formulation for in vivo cancer imaging via 19F-MRI.

Magnetic resonance imaging (MRI) is a routine diagnostic modality in oncology that produces excellent imaging resolution and tumor contrast without the use of ionizing radiation. However, improved contrast agents are still needed to further increase detection sensitivity and avoid toxicity/allergic reactions associated with paramagnetic metal contrast agents, which may be seen in a small percentage of the human population. Fluorine-19 (19F)-MRI is at the forefront of the developing MRI methodologies due to near-zero background signal, high natural abundance of 100%, and unambiguous signal specificity. In this study, we have developed a colloidal nanoemulsion (NE) formulation that can encapsulate high volumes of the fluorous MRI tracer, perfluoro-[15-crown-5]-ether (PFCE) (35% v/v). These nanoparticles exhibit long-term (at least 100 days) stability and high PFCE loading capacity in formulation with our semifluorinated triblock copolymer, M2F8H18. With sizes of approximately 200 nm, these NEs enable in vivo delivery and passive targeting to tumors. Our diagnostic formulation, M2F8H18/PFCE NE, yielded in vivo 19F-MR images with a high signal-to-noise ratio up to 100 in a tumor-bearing mouse model at clinically relevant scan times. M2F8H18/PFCE NE circulated stably in the vasculature, accumulated in high concentration of an estimated 4-9 × 1017 19F spins/voxel at the tumor site, and cleared from most organs over the span of 2 weeks. Uptake by the mononuclear phagocyte system to the liver and spleen was also observed, most likely due to particle size. These promising results suggest that M2F8H18/PFCE NE is a favorable 19F-MR diagnostic tracer for further development in oncological studies and potential clinical translation.

Application and development of a TaqMan-based real-time PCR assay for rapid detection of snakehead vesiculovirus.

Snakehead vesiculovirus (SHVV) is one of the primary pathogens responsible for viral diseases in the snakehead fish. A TaqMan-based real-time PCR assay was established for the rapid detection and quantification of SHVV in this study. Specific primers and fluorescent probes were designed for phosphoprotein (P) gene, and after optimizing the reaction conditions, the results indicated that the detection limit of this method could reach 37.1 copies, representing a 100-fold increase in detection sensitivity compared to RT-PCR. The specificity testing results revealed that this method exhibited no cross-reactivity with ISKNV, LMBV, RSIV, RGNNV, GCRV, and CyHV-2. Repetition experiments demonstrated that both intra-batch and inter-batch coefficients of variation were not higher than 1.66%. Through in vitro infection experiments monitoring the quantitative changes of SHVV in different tissues, the results indicated that the liver and spleen exhibited the highest viral load at 3 poi. The TaqMan-based real-time PCR method established in this study exhibits high sensitivity, excellent specificity, and strong reproducibility. It can be employed for rapid detection and viral load monitoring of SHVV, thus providing a robust tool for the clinical diagnosis and pathogen research of SHVV.

Application of computer-aided detection for NCCN-based follow-up recommendation in subsolid nodules: Effect on inter-observer agreement.

Computer-aided detection (CAD) of pulmonary nodules reduces the impact of observer variability, improving the reliability and reproducibility of nodule assessments in clinical practice. Therefore, this study aimed to assess the impact of CAD on inter-observer agreement in the follow-up management of subsolid nodules. A dataset comprising 60 subsolid nodule cases was constructed based on the National Cancer Center lung cancer screening data. Five observers independently assessed all low-dose computed tomography scans and assigned follow-up management strategies to each case according to the National Comprehensive Cancer Network (NCCN) guidelines, using both manual measurements and CAD assistance. The linearly weighted Cohen's kappa test was used to measure agreement between paired observers. Agreement among multiple observers was evaluated using the Fleiss kappa statistic. The agreement of the five observers for NCCN follow-up management categorization was moderate when measured manually, with a Fleiss kappa score of 0.437. Utilizing CAD led to a notable enhancement in agreement, achieving a substantial consensus with a Fleiss kappa value of 0.623. After using CAD, the proportion of major and substantial management discrepancies decreased from 27.5% to 15.8% and 4.8% to 1.5%, respectively (p < 0.01). In 23 lung cancer cases presenting as part-solid nodules, CAD significantly elevates the average sensitivity in detecting lung cancer cases presenting as part-solid nodules (overall sensitivity, 82.6% vs. 92.2%; p < 0.05). The application of CAD significantly improves inter-observer agreement in the follow-up management strategy for subsolid nodules. It also demonstrates the potential to reduce substantial management discrepancies and increase detection sensitivity in lung cancer cases presenting as part-solid nodules.

Detection of Covid-19 with Dual-Signal Probes in Paper Microfluidics

Current Covid-19 detection methods commercialized today that use colorimetric probes havethe advantage of short response time but the issue of low sensitivity. Other methods considerfluorescent probes that increase sensitivity but lead to longer response times. In this work,both fluorescence probes and colorimetric probes are integrated into a microfluidic paper strip.Both probes are incorporated into a single microfluidic paper strip to optimize sensitivity andefficiency. As a result, the use of colorimetric probes allows for the advantages of antibodyabsorption to be utilized for a short response time to detect antigens without need an extraexcitation source while fluorescent probes increase detection sensitivity and compensate forthe low sensitivity of colorimetric probes. The dual-signal probe displays capacity for greatlyimproving the accuracy and timeliness of standard Covid-19 detection in test kits.

Glucose Oxidase Patterned Meta‐Chemical Surface for Sensing Glucose Using Dip‐Pen Nanolithography

AbstractNumerous studies have been done to advance the development of efficient, simple, and cheap sensors, especially for glucose, which are important in the pharmaceutical and food industries. The most common sensors and biosensors used today are based on electrochemistry. The novelty of this study is the use of dip‐pen nanolithography (DPN) in order to pattern a mixture of glucose oxidase with PMMA as nanoclusters and develop meta‐chemical surface (MCS), which leads to highly efficient working electrodes with increased detection sensitivity compared to the today‐known glucose sensors ( M was detected in the current study). Our novel and important results support the feasibility of using DPN to develop sensors on various electrode surfaces patterned with different active species, especially in systems requiring target substance detection over large concentration ranges.

Rate of Missed Intracranial Colloid Cysts on MRI and CT.

Intracranial colloid cysts of the third ventricle are rare; however, they may be symptomatic. They can create a mass effect on the foramina of Monro, resulting in acute hydrocephalus. Colloid cysts are detectable on CT and MRI but are commonly missed. In this paper, we investigate the rate of missed colloid cysts on MRI and/or CT imaging within our multihospital metropolitan medical group. A retrospective, institutional review board-approved search of the network-wide picture archiving and communication system (PACS) from January 1, 2010, to October 31, 2020, was performed to identify reports including a "colloid cyst" in MRI brain or CT head imaging. Results without imaging and/or surgical confirmation of intracranial colloid cysts were excluded, rendering 229 cases. A PACS review of these cases was performed by two neuroradiologists to determine instances where the cyst had previously been imaged but not diagnosed on either CT or MRI. Two hundred twenty-nine subjects had confirmed colloid cysts through imaging and/or surgical reports. Of these, 46 had prior imaging depicting a colloid cyst either on CT and/or MRI without mention on the interpretative report, resulting in a non-detection rate of 20.1%. Intracranial colloid cysts can be missed at a considerably high rate, which is concerning given their clinically unpredictable nature and ability to cause significant morbidity and mortality. As such, it is important to take a proactive approach to searching for these cysts as part of a regular imaging search pattern and to continue to determine new methods of increasing detection sensitivity.

Increasing Detection Sensitivity for Rare and Endangered Species in Kansas through Development of An Aquatic Environmental DNA Sampling Protocol

Increasing Detection Sensitivity for Rare and Endangered Species in Kansas through Development of An Aquatic Environmental DNA Sampling Protocol

Machine learning approach to surface plasmon resonance bio-chemical sensor based on nanocarbon allotropes for formalin detection in water

This article investigates the design of a surface plasmon resonance (SPR) sensor that utilizes carbon nanotubes (CNT) and graphene to detect formalin concentration in water. The proposed sensor's design optimization and performance evaluation are achieved by implementing Gradient Boosting Regression (GBR), a machine learning (ML) algorithm, and the artificial hummingbird algorithm. An iterative transfer matrix technique is employed to create training and test sets for machine learning analysis, and a dataset of 8505 × 8 is obtained. The optimized thickness of Ag, CNT, and graphene 51.71 nm, 0.489 nm, and 4.32 nm were obtained using the artificial hummingbird algorithm. The results demonstrate that the SPR sensor achieves excellent reflectance curves, leading to a significant increase in detection sensitivity of 340.44 deg./RIU. Other characteristic parameters such as detection accuracy (DA), full width at half maximum (FWHM), and figure of merit (FoM) have also been evaluated.

Quantitative analysis evaluation of image reconstruction algorithms between digital and analog PET-CT

Positron emission tomography – computed tomography (PET-CT) is a non-invasive diagnostic tool that is widely used in oncology imaging. High quality diagnostic images and quantitative accuracy are often restricted by image noise, adequate spatial resolution and contrast ratio.Ordered Subset Expectation Maximisation (OSEM) is a widely used statistical iterative reconstruction algorithm in PET-CT due to its dependability, reconstruction quality and adequate signal-to-noise ratio. However, OSEM requires a large number of iterations to achieve high quantitative accuracy which results in increasing image noise. A novel algorithm, HYPER DPR (developed by United Imaging Healthcare) is an artificial intelligence-based reconstruction method that aims to provide increased sensitivity, higher spatial resolution and less noise.This study evaluates the accuracy and sensitivity of HYPER DPR against OSEM using reconstructed images from analog and digital PET-CT. Results demonstrate that both OSEM and HYPER DPR reconstruction algorithms in digital PET-CT has greater spatial resolution, increased detection sensitivity and less image noise when compared to analog PET-CT. Digital PET-CT and HYPER DPR enables better small lesion detection and increased resolution, thus resulting in better disease detection and improved patient management. Increased sensitivity of digital PET-CT results in low dose scans from reduced radiotracer injections, therefore having higher patient output.

Ultrasensitive metasurface-based sensors for fingerprint spectra extraction of L-glutamate at ultra-low concentration

Terahertz-infrared (THz-infrared) absorption spectroscopy comprises distinctive spectroscopic data that serves as a potent method for the detection and analysis of biomolecules, owing to its capability to capture unique fingerprint spectral patterns associated with different structural substances. Nonetheless, the extraction of molecular characterization data with utmost sensitivity for substances present in low concentrations remains a formidable task that necessitates resolution, especially for the micro detection of neurotransmitters such as L-glutamate intricately linked to neurological disorders. Here, we construct Fano resonant modes with strong near-field by breaking the symmetry of the metallic split ring in the meta-atom, benefiting the susceptible substance detection. By scaling the structural parameters, a metasurface-based sensor working at the range of 1.15 to 2.69 THz was fabricated, which consisted of 15 metasurfaces operating at different resonance frequencies. And in agreement with results obtained by typical transmission absorption spectroscopy analysis of 0.1 mg tablets, the molecular fingerprint information of L-glutamate has been experimentally identified by comparing the resonance intensity changes with/without covering 5μg of L-glutamate, implying an increased detection sensitivity to 1/20. the proposed metasurface-based sensors with broadband Fano resonances are deemed to provide a new paradigm for enabling low-concentration, easy-to-use, and label-free biomolecule research and promise to drive the development of integrated non-destructive testing medical devices.

Fluoropolymer Functionalization of Organ-on-Chip Platform Increases Detection Sensitivity for Cannabinoids.

Microfluidic technology is applied across various research areas including organ-on-chip (OOC) systems. The main material used for microfluidics is polydimethylsiloxane (PDMS), a silicone elastomer material that is biocompatible, transparent, and easy to use for OOC systems with well-defined microstructures. However, PDMS-based OOC systems can absorb hydrophobic and small molecules, making it difficult and erroneous to make quantitative analytical assessments for such compounds. In this paper, we explore the use of a synthetic fluoropolymer, poly(4,5-difluoro-2,2-bis(trifluoromethyl)-1,3-dioxole-co-tetrafluoroethylene) (Teflon™ AF 2400), with excellent "non-stick" properties to functionalize OOC systems. Cannabinoids, including cannabidiol (CBD), are classes of hydrophobic compounds with a great potential for the treatment of anxiety, depression, pain, and cancer. By using CBD as a testing compound, we examined and systematically quantified CBD absorption into PDMS by means of an LC-MS/MS analysis. In comparison to the unmodified PDMS microchannels, an increase of approximately 30× in the CBD signal was detected with the fluoropolymer surface modification after 3 h of static incubation. Under perfusion conditions, we observed an increase of nearly 15× in the CBD signals from the surface-modified microchannels than from the unmodified microchannels. Furthermore, we also demonstrated that fluoropolymer-modified microchannels are compatible for culturing hCMEC/D3 endothelial cells and for CBD perfusion experiments.

Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision.

The detection of circular RNA molecules (circRNAs) is typically based on short-read RNA sequencing data processed using computational tools. Numerous such tools have been developed, but a systematic comparison with orthogonal validation is missing. Here, we set up a circRNA detection tool benchmarking study, in which 16 tools detected more than 315,000 unique circRNAs in three deeply sequenced human cell types. Next, 1,516 predicted circRNAs were validated using three orthogonal methods. Generally, tool-specific precision is high and similar (median of 98.8%, 96.3% and 95.5% for qPCR, RNase R and amplicon sequencing, respectively) whereas the sensitivity and number of predicted circRNAs (ranging from 1,372 to 58,032) are the most significant differentiators. Of note, precision values are lower when evaluating low-abundance circRNAs. We also show that the tools can be used complementarily to increase detection sensitivity. Finally, we offer recommendations for future circRNA detection and validation.

2-fluoro-1-methylpyridinium p-toluene sulfonate: a new LC-MS/MS derivatization reagent for vitamin D metabolites

Vitamin D analysis by MS faces several analytical challenges, including inefficient ionization, nonspecific fragmentation, interferences from epimers, isomers, and isobars, as well as very low concentration levels. In this study, we used 2-fluoro-1-methylpyridinium (FMP) p-toluene sulfonate for derivatization of vitamin D3 metabolites to increase detection sensitivity and allow for full chromatographic separation of vitamin D isomers and epimers. UHPLC-MS/MS was used for measurement of five vitamin D3 metabolites in human serum. Compared with Amplifex and 4-phenyl-1,2,4-triazolin-3,5-dion, the FMP p-toluene sulfonate reaction required less time to be performed. The method was optimized and validated to ensure accuracy, precision, and reliability. In-house and commercial quality control samples were used to assure the quality of the results for 25-hydroxyvitamin D3. The method showed very good linearity and intraday and interday accuracy and precision; coefficients of determination (r2) ranged between 0.9977 and 0.9992, relative recovery from 95 to 111%, and coefficient of variation from 0.9 to 11.3. Stability tests showed that the extracted derivatized serum samples were stable for 24 h after storage at −20°C; 24,25-dihydroxyvitamin D3 and 1,25-dihydroxyvitamin D3-FMP derivatives were stable for 1 week at −80°C. The method was applied to samples of healthy individuals for quantitative determination of vitamin D3, the two epimers of 25-hydroxyvitamin D3 and 24,25-dihydroxyvitamin D3.