Qualitative Detection Research Articles

A novel early gas kick monitoring method using the difference between downhole dual measurement points pressure and a genetic algorithm-based model

Prompt monitoring of early gas kicks is critical to drilling safety. Untimely detection or inappropriate control measures can easily lead to well-blowouts, resulting in enormous human and economic losses. Existing early gas kick monitoring methods need more functionality. They must provide solutions for qualitative detection and quantitative inversion of the annulus gas fraction. Firstly, this paper establishes a gas kick simulation model to describe the changes in annulus pressure accurately and verifies its accuracy using laboratory data. Secondly, the pattern of change in the annulus flow rate and its relationship with annulus gas fraction during gas kick are analyzed. In addition, the method for detecting gas kick and the model for calculating the annulus gas fraction are proposed. Finally, an annulus flow rate inversion method based on the difference between downhole dual measurement points pressure and a genetic algorithm is presented, the method's stability is analyzed, and the distance between two measurement points is optimized. The results indicate that a gas kick at the bottom of the well increases the annulus flow rate, which serves as a critical parameter for early gas kick detection. The method for annulus flow rate inversion is minimally affected by the accuracy of downhole pressure and temperature measurements. The gas kick monitoring method detects gas kicks 31.0 min earlier than the conventional pit gain method with an average relative error of less than 10% in the annulus gas fraction backward value. To improve the accuracy of the gas kick monitoring method, the optimal distance between two measurement points is 30 m, and the minimum annulus gas fraction is 3.85%. The combination of the early gas kick monitoring method with the downhole dual-measurement point measurement system has significant value in guiding the reduction of downhole gas kick risks and optimizing the well control scheme.

Deep learning of electromechanical admittance data augmented by generative adversarial networks for flexural performance evaluation of RC beam structure

Deep learning networks facilitate automated damage identification and performance evaluation for concrete structures using electromechanical impedance/admittance (EMI/EMA) technique, while data quantity and quality limit the performance of such a data-driven network. For the first time, this paper proposed a data-augmentation approach using deep-convolutional admittance generative adversarial networks (AdmiGAN) to solve data deficiency and measurement inefficiency for deep learning-based flexural performance evaluation of reinforced concrete (RC) structures. In the approach, a new data normalization procedure was developed to collaboratively foster AdmiGAN-based EMA data synthesis, and synthetic datasets were fed into an adaptive convolutional neural network (CNN) for deep learning. Proof-of-concept experiment was conducted on a four-point bending RC beam structure, which was continuously monitored from initial loading to final failure by three surface-bonded piezoelectric ceramic lead zirconate titanate (PZT) patches. Qualitative detection of stress and damage was performed by traditional feature analysis of EMA signatures, automated performance evaluation was attempted by using CNN approach. Results demonstrated that the AdmiGAN required merely 5 groups of EMA signatures to generate high-accuracy dataset with 174 times of speed faster than conventional measurement method, and the AdmiGAN cooperated with CNN provided a new paradigm of data-driven structural performance evaluation with high accuracy, efficiency, and intelligence.

Shared hairpin structure electrochemical aptasensor based on ZrO2@Ni/Co-MOFs@AuNPs for dual-target detection of Cd2+ and S.aureus

Heavy metals and foodborne pathogens have become key pollutants that harm aquatic products, seriously endangering food safety and human health. Therefore, in this study, a ratiometric electrochemical aptamer sensor with a novel signal amplification strategy was constructed using ZrO2 as the substrate and Ni/Co-MOFs@AuNPs cubic nanomaterials to increase the specific surface area to simultaneously detect Cd2+ and S.aureus. The shared hairpin complementary chains modified with ferropene (Fc) could simultaneously bind to the Cd2+ and S.aureus aptamers modified with methylene blue (MB) and anthrquinone-2-carboxylic acid (AQ). The ratios of MB and AQ to Fc were used to realize the qualitative and quantitative detection of Cd2+ and S.aureus. Under the optimal conditions, the electrochemical aptamer sensor for Cd2+ and S.aureus was in the range of 1.00 × 10−2-1.00 × 104 ng/L and 1.00 × 101-1.00 × 107 CFU/mL, and the lowest detection limit was 1.91 × 10−4 ng/L and 1.37 CFU/mL, respectively. The aptasensor constructed in this paper can realize the simultaneous detection of Cd2+ and S.aureus in scallop and fish, providing a new detection method for the simultaneous detection of a variety of aquatic products pollutants.

Pilot Study on Newborn Screening for Spinal Muscular Atrophy.

Newborn screening (NBS) in Portugal is a significant public health measure to provide early detection for specific disorders so that early treatment is possible. Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder that causes degeneration of anterior horn cells in the human spinal cord and subsequent loss of motor neurons. Its incidence is estimated in 1.6000-11.800 live births. A pilot study on 100.000 newborns is being carried out at the neonatal screening laboratory with the aim of determining the specificity, sensitivity, and feasibility of the SMA screening at the NBS laboratory in Portugal. The study presented here was based on data obtained from neonatal screening, involving the analysis of 25.000 newborns. SMA screening is performed by a qualitative detection of exon 7 of the SMN1 gene. The assay was performed using a commercially available real-time PCR, the Eonis SMN1, TREC, and KREC kit. The dried blood spots of a total of 25.000 newborns were tested; among these newborns, two were diagnosed as having SMA with survival motor neuron 1 (SMN1) deletion. These two SMA-positive samples were sent to a specialized clinical centre and a peripheral blood sample was sent to the reference laboratory for confirmation of the exon 7 deletion and determination of the SMN2 copy number. Early diagnosis and intervention are important for SMA treatment to be effective; the treatment should be started at the pre-symptomatic stage of SMA. Thus, newborn screening for SMA is strongly recommended. Currently, targeted therapies for SMA are available, and attempts are being made worldwide to include SMA screening in newborns.

Epidemiology of acute respiratory viral infections of children with cancer before the COVID-19 pandemic

Children with cancer became a major high-risk group during the COVID-19 pandemic. It has become difficult for patients to reach practical and safe care and treatment all over the world. The late diagnosis of many childhood cancers was driven by limited access to healthcare due to the pandemic and fears of COVID-19 that prevented parents from making an early medical assessment of their child's symptoms. Acute respiratory diseases are an important cause of morbidity and mortality in children with cancer, regardless of the COVID-19 pandemic and were seen less frequently in the pandemic during the lockdown and distant education period in comparison to the time before the pandemic in children with cancer. Acute respiratory viral infections frequently cause febrile neutropenia attacks in children under five years of age. A three year retrospective cross-sectional study was performed in a tertiary care university hospital. Children with cancer who presented to the Department of Pediatric Hematology and Oncology with the diagnosis of acute respiratory viral infection were included in the study if they had available results of multiplex polymerase chain reaction (PCR) of nasopharyngeal aspirate samples. The qualitative detection of 18 respiratory viruses and four bacterias were detected by the real-time multiplex polymerase chain reaction. Sixty-six patients with 93 acute respiratory viral infection were included in this study. Seventy of 93 (75%) samples were positive for at least one pathogen. The most common three viruses were HRV, Influenza H1N1, and Influenza H1N3, respectively. Other than COVID-19, the risk of severe acute respiratory viral infections are always important in children with cancer and during the pandemic, hygiene measures and social restrictions caused a reduction in the number of acute respiratory viral infection. This study is critical because it shows the distribution of agents in children with cancer who had acute viral upper respiratory tract infections in the near term before the pandemic.

Comparison of the Rapid Antigen Test to RT-qPCR in Diagnosis of SARS-CoV-2: A University Experience in Northern Cyprus

Objective: As an alternative to RT-qPCR assays used in the diagnosis SARS-CoV-2, antigen-detecting rapid diagnostic tests (Ag-RDTs) are available for the qualitative detection of SARS-CoV-2 in nasopharyngeal swab samples. The aim of this study was to assess the accuracy and reliability of Ag-RDTs as a diagnostic method of detecting SARS-CoV-2 positive cases within a given population.
 Methods: In first phase of this investigation, 357 nasopharyngeal swab samples were screened for SARS-CoV-2 using Ag-RDTs. For the purposes of this study RT-qPCR was then applied to the same 357 nasopharyngeal swab samples in order to compare the reliability of the two detection methods. In the second phase of this investigation, Ag-RDTs were applied to an additional 75 nasopharyngeal swab samples that were already known to be RT-qPCR positive. 
 Results: In the first phase of this investigation, of the 357 samples screened using Ag-RDTs 14 samples were positive for SARS-CoV-2, in contrast, when RT-qPCR analysis was applied to the same 357 samples no SARS-CoV-2 samples were detected. Therefore, the false antigen positivity was determined to be at 3.9%. In the second phase of this investigation 75 RT-qPCR positive samples were re-evaluated with a rapid antigen test. Twenty-four of the 75 RT-qPCR positive sample were undetected.
 Conclusion: Solely relying on rapid antigen tests to detect SARS-CoV-2 infections in the community could consequently result in infectious individuals remaining in the population. The impact of false negative rapid test results can be reduced by implementing confirmatory RT-qPCR analysis particularly in symptomatic patients.

High-density Au nanoshells assembled onto Fe3O4 nanoclusters for integrated enrichment and photothermal/colorimetric dual-mode detection of SARS-CoV-2 nucleocapsid protein

Traditional lateral flow immunoassays (LFIA) suffer from insufficient sensitivity, difficulty for quantitation, and susceptibility to complex substrates, limiting their practical application. Herein, we developed a polyethylenimine (PEI)-mediated approach for assembling high-density Au nanoshells onto Fe3O4 nanoclusters (MagAushell) as LFIA labels for integrated enrichment and photothermal/colorimetric dual-mode detection of SARS-CoV-2 nucleocapsid protein (N protein). PEI layer served not only as “binders” to Fe3O4 nanoclusters and Au nanoshells, but also “barriers” to ambient environment. Thus, MagAushell not only combined magnetic and photothermal properties, but also showed good stability. With MagAushell, N protein was first separated and enriched from complex samples, and then loaded to the strip for detection. By observation of the color stripes, qualitative detection was performed with naked eye, and by measuring the temperature change under laser irradiation, quantification was attained free of sophisticated instruments. The introduction of Fe3O4 nanoclusters facilitated target purification and enrichment before LFIA, which greatly improved the anti-interference ability and increased the detection sensitivity by 2 orders compared with those without enrichment. Moreover, the high loading density of Au nanoshells on one Fe3O4 nanocluster enhanced the photothermal signal of the nanoprobe significantly, which could further increase the detection sensitivity. The photothermal detection limit reached 43.64 pg/mL which was 1000 times lower than colloidal gold strips. Moreover, this method was successfully applied to real samples, showing great application potential in practice. We envision that this LFIA could serve not only for SARS-CoV-2 detection but also as a general test platform for other biotargets in clinical samples.

Abstract 31 Chagas Disease Screening in Pregnancy: Lessons from Screening Maternal Donors from Publicly Banked Umbilical Cord Blood

Abstract Introduction Screening for Chagas disease in the perinatal setting has the dual benefit of identifying cases in young adults, for whom treatment can reduce morbidity, and providing the opportunity for early intervention in the case of vertical transmission to infants. North Carolina (NC) has experienced substantial growth in populations from Chagas-endemic regions; however, routine perinatal Trypanosoma cruzi antibody screening is not performed in the state. However, T. cruzi antibody screening is performed on all mothers donating their baby’s cord blood to the Carolina Cord Blood Bank (CCBB), an FDA-licensed public cord blood bank in NC. Objectives We aim to identify the prevalence of positive T. cruzi screening serology within a large cohort of maternal cord blood donors in NC. Methods This is a retrospective review of positive screening serology for T. cruzi in all maternal donors of their baby’s cord blood to the CCBB in NC from 7/1/2007–05/31/2023. Screening serology was performed using a chemiluminescent microparticle immunoassay for the qualitative detection of antibodies to T. cruzi. Results Among 26,698 cord blood donations screened over 16 years, 45 samples (0.17%) had a positive T. cruzi antibody screen. Of the 3,787 donations from patients self-identifying as Hispanic or Latino (14% of the cohort), 15 (0.4%) had a positive screen. The prevalence of a positive T. cruzi screen in donated cord blood was 1.7 per 1,000 cord blood donations. Discussion Our data highlight the prevalence of Chagas disease in a non-endemic region and suggest that targeted screening may be a feasible screening strategy for the state. They also demonstrate an additional value to maternal health for donors to public cord blood banks. Further evaluation is needed to determine if these patients had confirmatory testing and whether they were linked to care.

Listeria monocytogenes detection on food contact surfaces: suitability of different swab materials

The high binding capacity of Listeria monocytogenes to food contact surfaces increases the risk of cross-contamination in food. In addition to appropriate cleaning and disinfection procedures, a suitable sampling plan and technique for the earliest possible detection are necessary for prevention. This paper evaluates the sensitivity of 3 swab materials (cotton, viscose and nylon-flocked) for the qualitative and quantitative detection of L. monocytogenes on food contact surfaces (100 cm2). A L. monocytogenes cocktail of 3 serotypes (IIa, IIb and IVb) was applied to stainless steel, polyvinyl chloride, polytetrafluoroethylene and high-density polyethylene surfaces at a concentration of approx. 1.0 × 101-1.0 × 102 CFU/100 cm2 and approx. 4.0 × 104 CFU/100 cm2. The surfaces were sampled after 15 min of incubation by 3 different swabs using the double-swab technique, and then stored for 4 and 24 h until processing. The results of the qualitative and quantitative tests showed a few statistically significant differences in the detectability of L. monocytogenes by different swab materials, which implies that the detection rate of L. monocytogenes on a certain food contact surfaces can be increased by using the respective most suitable swab.

Impact of storage time in dried blood samples (DBS) and dried plasma samples (DPS) for point-of-care hepatitis C virus (HCV) RNA quantification and HCV core antigen detection.

The scale-up of hepatitis C virus (HCV) diagnosis and treatment requires affordable and simple tools to improve access to care, especially in low- and middle-income settings with limited infrastructure or high-risk populations. Dried blood and plasma samples (DBS and DPS) are useful alternative for hepatitis C detection in settings lacking adequate infrastructure. We evaluated the performance of DBS and DPS vs plasma in a point-of-care HCV RNA quantitative assay (Xpert HCV Viral Load-Cepheid), and compared HCV core antigen (HCVcAg) detection by the Architect HCV core antigen assay (Abbott) in DBS vs serum. The dried samples were stored at room temperature for different storage times to reproduce the time from sampling to testing in settings with centralized diagnosis or when testing mobile populations. HCV RNA quantification in DBS and DPS presented 100% sensitivity and specificity and a high correlation for up to 3 months of storage. HCV viremia showed a mean decrease of 0.5 log10 IU/mL (DBS) and 0.3 log10 IU/mL (DPS) for storage times up to 1 month. Architect HCVcAg detection presented high sensitivity/specificity (96%/100%) in DBS tested immediately after sampling, decreasing to 86% sensitivity after 7 days of storage. However, sensitivity increased when an optimized cut-off was applied for each storage time. We conclude that DBS and DPS are suitable samples for HCV RNA detection and quantification, being DPS more reliable for shorter storage times. DBS can be also used for HCVcAg qualitative detection and the sensitivity can be increased when adjusting the cut-off values. IMPORTANCE Hepatitis C infection remains a global burden despite the effectiveness of antivirals. In the WHO roadmap to accomplish HCV elimination by 2030, HCV diagnosis is one of the main targets. However, identifying patients in resource-limited settings and high-risk populations with limited access to healthcare remains a challenge and requires innovative approaches that allow decentralized testing. The significance of our research is in verifying the good performance of dried samples for HCV diagnosis using two different diagnostics assays and considering the effect of room temperature storage in this sample format. We confirmed dried samples are an interesting alternative for HCV screening and reflex testing in resource-limited settings or high-risk populations.

Application of convolutional neural network for monitoring the condition of strawberries

The article proposes a method for improving the accuracy of diagnosing calcium deficiency in strawberry plants, suggests the use of machine learning algorithms, such as convolutional neural networks (CNN), which makes it possible to train a model on a data set for qualitative detection of signs of calcium deficiency in the leaves. A dataset of images of healthy leaves and leaves with signs of calcium deficiency was collected, the method of artificially increasing the volume of the training sample (image augmentation) was applied, by horizontal and vertical reflection of objects in the images, rotation by a given angle and random addition of «noise». To train a convolutional neural network, an algorithm for obtaining RGB images using a robotic platform is proposed. A modern model of the YOLOv7 neural network was used as a means of detecting the signs of calcium deficiency in the leaves of strawberry in the images. The configuration of the YOLOv7 machine learning algorithm for recognizing areas of damage to strawberry leaves caused by calcium deficiency has been determined. To train the YOLOv7 model, the Transfer learning method was used. To assess the quality of the object recognition algorithms, the metric mAP (mean average precision) – 0.454 was used, the metric F1-score (F-measure) – 0.53, the average absolute error (Mean Absolute Percentage Error, MAPE) of the analyzed model of the YOLOv7 neural network was calculated. The analysis of the results showed that the YOLOv7 model recognized the «Calciuemdeficiency» class, with a MAPE index equal to 7.52 %. The analysis of the research results showed that timely monitoring of the condition of garden strawberries on an industrial plantation carried out using a wheeled robotic platform with the use of the YOLOv7 convolutional neural network for processing the data obtained will allow to determine calcium deficiency in the leaves of strawberry plants with high accuracy up to 94.43 % at the early stages of pathology development.

Machine Learning Techniques for Effective Pathogen Detection Based on Resonant Biosensors.

We describe a machine learning (ML) approach to processing the signals collected from a COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine (SVM) were used to process both the raw data and the feature engineering data, and high performance for the qualitative detection of the SARS-CoV-2 virus with concentration down to 1 TCID50/mL was achieved. Valid detection experiments contained 486 negative and 108 positive samples, and control experiments, in which biosensors without antibody functionalization were used to detect SARS-CoV-2, contained 36 negative samples and 732 positive samples. The data distribution patterns of the valid and control detection dataset, based on T-distributed stochastic neighbor embedding (t-SNE), were used to study the distinguishability between positive and negative samples and explain the ML prediction performance. This work demonstrates that ML can be a generalized effective approach to process the signals and the datasets of biosensors dependent on resonant modes as biosensing mechanism.

Carrying Asymptomatic Malaria In Ouéllé Locality, And Surrounding Villages, In Southeastern Gabon: An Epidemiological Analysis, In Rural Central Africa

Background: Malaria remains a major public health problem in sub-Saharan Africa, and particularly in Gabon. In an epidemiological analysis in a rural area, the present study assessed asymptomatic malaria carriage in Ouéllé, and surrounding villages, in South-eastern Gabon: an epidemiological analysis, in a rural area of central Africa. Patients and method: This prospective, cross-sectional study was conducted from June 26 to 28, 2023. The sociodemographic characteristics of the participants were obtained. A small portion of blood collected by finger prick from each participant was used for qualitative detection of malaria-causing Plasmodium infection, using a Malaria Test MeriScreenTM Pf/PAN Ag lateral flow immunochromatographic assay. Results of analysis by R software version 4.0.3, were considered significant at p≤0.05.Results: Of the 321 people registered for the present study, 97 (30.22%) (95% CI: 0.25 - 0.36) (n=97), tested positive for malaria, compared with 224 (69.78%) ((95% CI: 0.64 - 0.75) (n=224). While a univariate analysis of the prevalence of malaria carriage according to gender showed no statistically significant association between the variables p=0.56, a univariate analysis of the prevalence of malaria carriage according to age group indicated that only participants aged between 28 and 57 (OR =0.17; 95% CI: [0.04 - 0.73] p=0. 007*), and according to each locality, the analysis showed that participants from Mvengué (OR =0.17; CI 95% : [0.04 - 0.73] p=0.007*), Djoutou (OR =0.17; CI 95% : [0.04 - 0.73] p=0. 007*), and Mouyabi (OR =0.17; 95% CI: [0.04 - 0.73] p=0.007*), were statistically susceptible to malaria were significantly associated with malaria carriage in the present study.Conclusion: These results, which indicate the persistence of asymptomatic malaria in Ouéllé and surrounding villages, call on Gabon's health authorities to redouble their efforts to combat malaria throughout the country.

Longitudinal study of antibody response following SARS-CoV-2 vaccination with Pfizer-BioNTech BNT162b2

Abstract Objectives To assess the immunity of healthcare and non-healthcare workers in the Alcoy health area (Spain) after completing three doses of the Pfizer-BioNTech vaccine and how it relates with individual factors. Methods We conducted a prospective, observational, longitudinal, analytical study to observe immunogenicity in healthcare and non-healthcare workers at Virgen de los Lirios Hospital following administration of three doses of the Pfizer-BioNTech vaccine. Anti-SARS-CoV-2 spike protein IgG antibody concentrations were determined, while COVID-19 infections were identified by qualitative detection of IgG against the nucleocapsid protein. Samples from volunteers were analyzed 15 days, 3 months, and 6 months after receiving the second vaccine dose, and 12 months after receiving the third (booster) dose. A questionnaire was used to collect demographic data, risk factors, and use of immunosuppressive drugs. Statistical analyses were performed with SPSS software, and mean antibody levels over time were compared using ANOVA. Results Participation was 99.5 % (199/200). The IgG concentration was higher in men and in obese individuals. No significant changes were noted in factors such as smoking. Conclusions All participants developed humoral immunity, except for three subjects who were receiving immunosuppressive treatment. Participants with previous COVID-19 infection had higher antibody levels.

Selective identification and quantification of VOCs using metal nanoparticles decorated SnO2 hollow-spheres based sensor array and machine learning

Accurate and selective detection of target gas/volatile organic compounds (VOCs) is of utmost importance. The chemiresistive gas sensors have been a desirable candidate due to their compact footprint and ease of fabrication, but they show poor selectivity. This work presents a combination of nanomaterials-based chemiresistive gas sensors with machine learning (ML) techniques to achieve sensitive, selective, and quantified detection of tested VOCs. The sensor array consists of four separate sensing layers over interdigitated electrodes-based platform. The sensing materials were comprised of silver, gold, palladium, and platinum nanoparticles decorated on tin oxide hollow-sphere structures which were successfully synthesized through chemical routes and characterized accordingly. Surface decoration of different metal nanoparticles has produced sensitive and diverse sensing patterns among the tested VOCs. The sensing mechanism and related gas sensing kinetics were then analyzed to explain high sensitivity and diverse sensing phenomena. The subsequent incorporation of ML models has resulted in qualitative and quantitative detection of VOCs. A comparative analysis was carried out among different types of applied features and ML models with reasoning. Particularly, a deep neural network (DNN) model with time series (TS) response sequence as input information, delivered the best performance. The DNN_TS model presented an average classification accuracy of 98.33 %, in conjunction with excellent concentration prediction. The DNN_TS model showed a very fast prediction time of 2.74 µs with adaptive learning while utilizing minimum computing resources, which favors the real-time sensing capability. The reported results promote the development of an autonomous, smart, and selective gas sensor system for real-time applications.

Evaluation of the validity of the HPV viral load compared to conventional techniques for the detection of high-grade anal intraepithelial lesions in men with HIV who have sex with men.

The incidence of high-grade anal intraepithelial lesions (HSILs) has increased in recent years among men who have sex with men with human immunodeficiency virus (HIV). This work evaluated the validity of the human papilloma virus viral load (HPV-VL) versus cytological and qualitative HPV results to detect HSILs. From May 2017 to January 2020, 93 men who have sex with men and HIV were included in an anal cancer screening program from the Infectious Diseases Unit at a tertiary-care hospital in Alicante (Spain). The gold-standard for the screening of anal HSILs is the anal biopsy using high-resolution anoscopy. The diagnostic methods compared against gold-standard were HPV-16-VL, HPV-18-VL, and HPV-16-18-VL co-testing, anal cytology, and qualitative HPV detection. The receiver operating characteristic (ROC) curve and cut-off points for HPV-VL were calculated. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Cohen's Kappa coefficient (κ) were also calculated. The mean patient age was 44.6 ± 9.5 years. All of them received antiretroviral treatment, 96.8% had an HIV viral load of <50 copies/mL and 17.2% had a previous diagnosis of AIDS. The diagnosis of the anal biopsies were: 19.4% (n=18) HSIL, 29.1% (n=27) LSIL, and 51.6% (n=48) negative. An HPV-16-VL >6.2 copies/cell was detected in the HSIL biopsy samples (p=0.007), showing a sensitivity of 100% and a specificity of 46.2%. HPV-18-VL and HPV16-18-VL co-testing showed a sensitivity of 75% and 76.9% and a specificity of 72.7% and 61.3%, respectively. The highest PPV was 50% obtained with the cytology and HPV-18-VL. The HPV-16-VL showed a NPV of 100%, followed by 88.9% in the HPV-18-VL and 87% in the abnormal cytology. Cohen's Kappa coefficient were: HPV-18-VL (κ=0.412), abnormal cytology (κ=0.353) and HPV-16-VL (κ=0.338). HPV-VL testing improved the detection sensitivity but not the specificity for HSIL biopsies compared to anal cytology and the qualitative detection of HPV. In men who have sex with men and HIV the HPV-VL could be an useful tool for diagnosis of HSILs in anal cancer screening programs. Further studies will be needed to evaluate the clinical implications of HPV-VL in these programs.

Effect of Natural Dye on the Spectral Response of the Heterojunction Ag/ZnO/Ps/Si/Ag for Photodetector Application

Zinc oxide and dye are utilized to absorb and convert incident photons to electric energy using a sandwich construction with an active area of 1.5 × 1.5 cm2, which improves the photodetector’s performance as a light sensor. A variable variation of solution concentration according to the ratio of mass and volume was used to extract natural dye from Barago officinalis. The Barago officinalis absorbance was investigated by spectrophotometer at a wavelength of 200–1000 nm. This indicates that UV absorption has occurred, and note that when an increase in the spectral response at concentration of 1, there appears an improvement in the infrared region with a wave length of 950 nm and the enhanced sensitivity in the long wavelength region could be attributed to formation of dye aggregates within the devices which led to the highest value of qualitative detection up to 1.3 × 10[Formula: see text] W[Formula: see text] cm Hz[Formula: see text] thus increasing quantum efficiency to (119)% at the wavelength (950 nm).

Coiled-Coil-Based Biofunctionalization of 100 nm Gold Nanoparticles with the Trastuzumab Antibody for the Detection of HER2-Positive Cancer Cells.

We compared different biofunctionalization strategies for immobilizing trastuzumab, an IgG targeting the HER2 biomarker, onto 100 nm spherical gold nanoparticles because of the E/K coiled-coil peptide heterodimer. First, Kcoil peptides were grafted onto the gold surface while their Ecoil partners were genetically encoded at the C-terminus of trastuzumab's Fc region, allowing for a strong and specific interaction between the antibodies and the nanoparticles. Gold nanoparticles with no Kcoil peptides on their surface were also produced to immobilize Ecoil-tagged trastuzumab antibodies via the specific adsorption of their negatively charged Ecoil tags on the positively charged gold surface. Finally, the nonspecific adsorption of wild-type trastuzumab on the gold surface was also assessed, with and without Kcoil peptides grafted on it beforehand. We developed a thorough workflow to systematically compare the immobilization strategies regarding the stability of nanoparticles, antibody coverage, and ability to specifically bind to HER2-positive breast cancer cells. All nanoparticles were highly monodisperse and retained their localized surface plasmon resonance properties after biofunctionalization. A significant increase in the amount of immobilized antibodies was observed with the two oriented coil-based strategies compared to nonspecific adsorption. Finally, all biofunctionalization strategies allowed for the detection of HER2-positive breast cancer cells, but among the investigated approaches, we recommend using the E/K coiled-coil-based strategy for gold nanoparticle biofunctionalization because it allows for the qualitative and quantitative detection of HER2-positive cells with a higher contrast compared to HER2-negative cells.

Difunctional Magnetic Nanoparticles Employed in Immunochromatographic Assay for Rapid and Quantitative Detection of Carcinoembryonic Antigen.

Immunochromatographic assay (ICA) plays an important role in in vitro diagnostics because of its simpleness, convenience, fastness, sensitivity, accuracy, and low cost. The employment of magnetic nanoparticles (MNPs), possessing both excellent optical properties and magnetic separation functions, can effectively promote the performances of ICA. In this study, an ICA based on MNPs (MNP-ICA) has been successfully developed for the sensitive detection of carcinoembryonic antigen (CEA). The magnetic probes were prepared by covalently conjugating carboxylated MNPs with the specific monoclonal antibody against CEA, which were not only employed to enrich and extract CEA from serum samples under an external magnetic field but also used as a signal output with its inherent optical property. Under the optimal parameters, the limit of detection (LOD) for qualitative detection with naked eyes was 1.0 ng/mL, and the quantitative detection could be realized with the help of a portable optical reader, indicating that the ratio of optical signal intensity correlated well with CEA concentration ranging from 1.0 ng/mL to 64.0 ng/mL (R2 = 0.9997). Additionally, method comparison demonstrated that the magnetic probes were beneficial for sensitivity improvement due to the matrix effect reduction after magnetic separation, and the MNP-ICA is eight times higher sensitive than ICA based on colloidal gold nanoparticles. The developed MNP-ICA will provide sensitive, convenient, and efficient technical support for biomarkers rapid screening in cancer diagnosis and prognosis.

Identification of SARS-CoV-2 biomarkers in saliva by transcriptomic and proteomics analysis

The detection of SARS-CoV-2 biomarkers by real time PCR (rRT-PCR) has shown that the sensitivity of the test is negatively affected by low viral loads and the severity of the disease. This limitation can be overcome by the use of more sensitive approaches such as mass spectrometry (MS), which has not been explored for the detection of SARS-CoV-2 proteins in saliva. Thus, this study aimed at assessing the translational applicability of mass spectrometry-based proteomics approaches to identify viral proteins in saliva from people diagnosed with COVID-19 within fourteen days after the initial diagnosis, and to compare its performance with rRT-PCR. After ethics approval, saliva samples were self-collected by 42 COVID-19 positive and 16 healthy individuals. Samples from people positive for COVID-19 were collected on average on the sixth day (± 4 days) after initial diagnosis. Viable viral particles in saliva were heat-inactivated followed by the extraction of total proteins and viral RNA. Proteins were digested and then subjected to tandem MS analysis (LC-QTOF-MS/MS) using a data-dependent MS/MS acquisition qualitative shotgun proteomics approach. The acquired spectra were queried against a combined SARS-CoV-2 and human database. The qualitative detection of SARS-CoV-2 specific RNA was done by rRT-PCR. SARS-CoV-2 proteins were identified in all COVID-19 samples (100%), while viral RNA was detected in only 24 out of 42 COVID-19 samples (57.1%). Seven out of 18 SARS-CoV-2 proteins were identified in saliva from COVID-19 positive individuals, from which the most frequent were replicase polyproteins 1ab (100%) and 1a (91.3%), and nucleocapsid (45.2%). Neither viral proteins nor RNA were detected in healthy individuals. Our mass spectrometry approach appears to be more sensitive than rRT-PCR for the detection of SARS-CoV-2 biomarkers in saliva collected from COVID-19 positive individuals up to 14 days after the initial diagnostic test. Based on the novel data presented here, our MS technology can be used as an effective diagnostic test of COVID-19 for initial diagnosis or follow-up of symptomatic cases, especially in patients with reduced viral load.