Detection Of High Levels Research Articles

Modelling multiplex testing for outbreak control

During the SARS-CoV-2 pandemic, polymerase chain reaction (PCR) and lateral flow device (LFD) tests were frequently deployed to detect the presence of SARS-CoV-2. Many of these tests were singleplex, and only tested for the presence of a single pathogen. Multiplex tests can test for the presence of several pathogens using only a single swab, which can allow for: surveillance of more pathogens, targeting of antiviral interventions, a reduced burden of testing, and lower costs. Test sensitivity however, particularly in LFD tests, is highly conditional on the viral concentration dynamics of individuals. To inform the use of multiplex testing in outbreak detection it is therefore necessary to investigate the interactions between outbreak detection strategies and the differing viral concentration trajectories of key pathogens. Viral concentration trajectories are estimated for SARS-CoV-2, and Influenza A/B. Testing strategies for the first five symptomatic cases in an outbreak are then simulated and used to evaluate key performance indicators. Strategies that use a combination of multiplex LFD and PCR tests achieve; high levels of detection, detect outbreaks rapidly, and have the lowest burden of testing across multiple pathogens. Influenza B was estimated to have lower rates of detection due to its modelled viral concentration dynamics. Data availability statementThe SARS-CoV-2 viral load trajectory data may be accessed by contacting Killingley et. al. The influenza A/B viral load trajectory may be accessed at https://github.com/bcowling/pediatric-vaccine-trial/tree/master/data.

DCASAM: advancing aspect-based sentiment analysis through a deep context-aware sentiment analysis model

Aspect-level sentiment analysis plays a pivotal role in fine-grained sentiment categorization, especially given the rapid expansion of online information. Traditional methods often struggle with accurately determining sentiment polarity when faced with implicit or ambiguous data, leading to limited accuracy and context-awareness. To address these challenges, we propose the Deep Context-Aware Sentiment Analysis Model (DCASAM). This model integrates the capabilities of Deep Bidirectional Long Short-Term Memory Network (DBiLSTM) and Densely Connected Graph Convolutional Network (DGCN), enhancing the ability to capture long-distance dependencies and subtle contextual variations.The DBiLSTM component effectively captures sequential dependencies, while the DGCN component leverages densely connected structures to model intricate relationships within the data. This combination allows DCASAM to maintain a high level of contextual understanding and sentiment detection accuracy.Experimental evaluations on well-known public datasets, including Restaurant14, Laptop14, and Twitter, demonstrate the superior performance of DCASAM over existing models. Our model achieves an average improvement in accuracy by 1.07% and F1 score by 1.68%, showcasing its robustness and efficacy in handling complex sentiment analysis tasks.These results highlight the potential of DCASAM for real-world applications, offering a solid foundation for future research in aspect-level sentiment analysis. By providing a more nuanced understanding of sentiment, our model contributes significantly to the advancement of fine-grained sentiment analysis techniques.

A Comprehensive Review on Pesticide Residues in Human Urine.

Numerous studies worldwide have evaluated pesticide residues detected in urine. This review serves as a contribution to this field by presenting an overview of scientific research studies published from 2001 to 2023, including details of study characteristics and research scope. Encompassing 72 papers, the review further delves into addressing key challenges in study design and method used such as sampling and analytical approaches, results adjustments, risk assessment, estimations, and results evaluation. The review explores urinary concentrations and detection frequency of metabolites of organophosphates and pyrethroids, as well as herbicides such as 2,4-D and glyphosate and their metabolites, across various studies. The association of the results with demographic and lifestyle variables were explored. While farmers generally have higher pesticide exposure, adopting organic farming practices can reduce the levels of pesticides detected in their urine. Residence close to agricultural areas has shown high exposure in some cases. Dietary exposure is especially high among people adopting a conventionally grown plant-rich dietary pattern. A higher detection level and frequency of detection are generally found in females and children compared to males. The implications of transitioning to organic and sustainable plant-rich diets for reducing pesticide exposure and potential health benefits for both adults and children require further investigation.

Occurrence, dissipation and processing factors of multi-pesticides in goji berry

As medicine and food homology substance, goji berry is consumed worldwide in the form of fresh, dried and juice; however, pesticide residues have become one of the problems that essentially threaten its quality during cultivation and processing. In this study, a total of 75 dried goji berries were sampled from markets across China, and for the determination of 62 analytes, 28 pesticides were identified. Nine pesticides with high detectable rates and residual levels were selected for folia spraying, and their half-lives were found to range from 1.04 to 2.21 d. The processing factors (PFs) of juice were between 0.25 and 1.02, and this was mainly related with their octanol-water partition coefficient (logKow values). Washing could reduce pesticides residues to varying degrees with the removal rates between 17.00% and 74.05%. Sun drying with higher PF values in the range of 0.61–5.91 exhibited more obvious enrichment effect compared to oven drying. Commercial goji berry had cumulative chronic dietary risks with the hazard index (HI) values of 1.61%−4.97%. Its acute risk quotients (HQas) for consumers were 543.32%−585.92% and were mainly due to insecticides. These results provide important references for rationalizing pesticide application during goji berry cultivation and for the improvement of process to ensure food safety.

ZLN005 alleviates PBDE-47 induced impairment of mitochondrial translation and neurotoxicity through PGC-1α/ERRα axis

Recent studies are identified the mitochondria as critical targets of 2, 2′, 4, 4′-tetrabromodiphenyl ether (PBDE-47) induced neurotoxicity. This study aimed at examining the impact of PBDE-47 exposure on mitochondrial translation, and its subsequent effect on PBDE-47 neurotoxicity. The Sprague-Dawley (SD) rat model and neuroendocrine pheochromocytoma (PC12) cells were adopted for the measurements of mitochondrial ATP levels, mitochondrial translation products, and expressions of important mitochondrial regulators, such as required meiotic nuclear division 1 (RMND1), estrogen-related receptor α (ERRα), and peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α). To delve into the role of PGC-1α/ERRα axis in mitochondrial translation, 2-(4-tert-butylphenyl) benzimidazole (ZLN005) was employed. Both cellular and animal model results shown that PBDE-47 impeded PGC-1α/ERRα axis and mitochondrial translation. PBDE-47 suppressed mitochondrial function in rat hippocampus and PC12 cells by decreasing relative mitochondrial DNA (mtDNA) content, mitochondrial translation products, and mitochondrial ATP levels. Particularly, ZLN005 reversed PBDE-47 neurotoxicity by enhancing mitochondrial translation through activation of PGC-1α/ERRα axis, yet suppressing PGC-1α with siRNA attenuates its neuroprotective effect in vitro. In conclusion, this work highlights the importance of mitochondrial translation in PBDE-47 neurotoxicity by presenting results from cellular and animal models and suggests a potential therapeutic approach through activation of PGC-1α/ERRα axis. Environmental implicationPBDEs have attracted extensive attention because of their high lipophilicity, persistence, and detection levels in various environmental media. Increasing evidence has shown that neurodevelopmental disorders in children are associated with PBDE exposure. Several studies have also found that perinatal PBDE exposure can cause long-lasting neurobehavioral abnormalities in experimental animals. Our recent studies have also demonstrated the impact of PBDE-47 exposure on mitochondrial biogenesis and dynamics, leading to memory and neurobehavioral deficits. Therefore, we explore whether the pathological mechanism of PBDE-47-induced neurotoxicity involves the regulation of mitochondrial translation through the PGC-1α/ERRα axis.

Study of a genetic collection of strawberry (Fragaria L.) for resistance to powdery mildew.

Powdery mildew (Sphaerotheca macularis Mag. (syn. Podosphaera aphanis Wallr.)) is a dangerous disease of strawberry (Fragaria L.). The resistance of strawberry to powdery mildew is controlled polygenically. Several genetic loci with a large contribution to disease resistance have been identified in various strawberry varieties. Diagnostic DNA markers have been developed for QTL 08 To-f. They showed a high level of reliable gene detection in mapping populations. The purpose of this study was assessment of a strawberry genetic collection for resistance to powdery mildew and identification of promising strawberry forms for breeding for resistance to S. macularis. The objects of the study were wild species of the genus Fragaria L., varieties and selected seedlings of strawberry (Fragaria × ananassa Duch.) created in the I.V. Michurin Federal Scientific Center, and strawberry varieties introduced from various ecological and geographical regions. To identify QTL 08 To-f, DNA markers IB535110 and IB533828 were used. Locus 08 To-f was detected in 23.2 % of the analyzed strawberry genotypes, including wild species F. moschata and F. orientalis, strawberry varieties of Russian breeding (Bylinnaya and Sudarushka) and foreign breeding (Florence, Korona, Malwina, Ostara, Polka and Red Gauntlet). The correlation between the presence of markers IB535110 and IB533828 and phenotypic resistance (powdery mildew effect on strawberry plants is absent) was 0.649. The determination coefficient (R2 ) showing the contribution of the studied locus to the manifestation of the trait was 0.421, that is, in 42.1 % of cases resistance was explained by the presence of QTL 08 To-f, and in 57.9 % of cases, by other genetic factors. All strawberry genotypes with locus 08 To-f were characterized by high field resistance to S. macularis in the conditions of Michurinsk, Tambov region. Thus, locus 08 To-f is promising for conferring resistance on local powdery mildew races, and markers IB535110 and IB533828 can be used in marker-assisted breeding programs to create powdery mildewresistant strawberry genotypes.

Visual Intrusion Detection Based On CBAM-Capsule Networks

Abstract Intrusion detection has become a research focus in internet information security, with deep learning algorithms playing a crucial role in its development. Typically, intrusion detection data are transformed into a two-dimensional matrix by segmenting, stacking and padding them with zeros for input into deep learning models. However, this method consumes computational resources and fails to consider the correlation between features. In this paper, we transform the data into images through visualization operations and propose an information entropy weighted scheme to optimize the collision element problem during the transformation process. This method enhances the correlation between pixel frame features, leading to approximately 2% improvement in accuracy of the classification model when using the generated image samples for detection in experiments. To address the issues of insensitivity to target feature locations and incomplete feature extraction in traditional neural networks, this paper introduces a new network model called CBAM-CapsNet, which combines the advantages of the lightweight Convolutional Block Attention Module and capsule networks. Experimental results on the UNSW-NB15 and IDS-2017 datasets demonstrate that the proposed model achieves accuracies of 92.94% and 99.72%, respectively. The F1 scores obtained are 91.83% and 99.56%, indicating a high level of detection.

Viral etiology of measles-like rash in Guinean children during the COVID epidemic in 2022.

Covid-19 in West Africa masked outbreaks of vaccine-preventable diseases such as the measles epidemic in children in Guinea in 2021-2022 characterized by a lack of confirmation of suspected clinical cases. During weeks 13-22 of 2022, saliva samples were collected from 213 children (3-60 months old) with measles-like symptoms within the St Gabriel dispensary in Conakry. Samples were processed in Virus Transport Medium (VTM) and tested on the same day by triplex reverse transcriptase -real-time polymerase chain reaction for Measles, Rubella and RNaseP. Samples were also tested for HHV6 and Parvovirus B19, viruses causing clinical signs similar to measles. We confirmed 146 (68.5%) measles cases, 27 (12.7%) rubella, 5 (2.3%) double-positive measles-rubella, 35 (16.4%) HHV-6 and 8 (3.75%) Parvovirus B19. To test the assay's robustness, 27 samples were kept at 26-30°C. Measles and rubella were still detected after 7 days at 26-30°C, and after 21 days measles and rubella were still detectable in all samples but one. Sequencing indicated the circulation of the B3 measles genotype, as expected in West Africa. This study highlights the robustness of the measles/rubella diagnostic test on saliva samples stored in VTM. The high level of rubella detection questioned the single valence measles vaccination strategy.

The increase in the incidence of syphilis in the Russian Federation: foreign migrant citizens as a risk group for the spread of the disease

Relevance. The incidence of sexually transmitted infections (STIs) has a serious impact on the health and lives of children, adolescents and adults. Syphilis, like most STIs, is a socially significant disease, while among the factors influencing the spread of this infection, migration processes, including labor migration, occupy a special place.
 Aims. To study syphilis in foreign migrants in the Russian Federation and individual subjects of the state in recent years.
 Material and methods. A retrospective epidemiological analysis of the incidence of syphilis among the population of the Russian Federation and foreign migrants was performed. The data from Federal Statistical Monitoring Form No. 9 and No. 34 was used with reference to STIs incidence in 2011–2022 in Russia and in its regions.
 Results. Among foreign migrant citizens, the incidence rates were higher than the Russian average: 1.5–2.0 times before 2020, and 4 times in 2021 and 2022. The proportion of registered cases of syphilis among foreign citizens in 2021 was 36.4%, significantly exceeding this figure not only in 2020 (18.2%), but also in previous years (16.7–21.2%). An increase in the number of foreign citizens with syphilis was observed in 2021 in all federal districts of the Russian Federation, while the number of syphilis cases detected in this contingent of people varied significantly between different regions of the Russian Federation. The main share (98.1%) in the structure of syphilis detected in foreign citizens was latent forms of the disease.
 Conclusions. The high level of detection of syphilis in foreign migrant citizens and the predominance of latent forms of the disease in this population represent a potential epidemiological danger of the spread of infection. In connection with the current situation, it seems necessary to develop and implement permanent and controlled algorithms for monitoring STIs in risk groups, including foreign migrant citizens.

PH-dependent adsorption of the sulfamethoxazole antibiotic on HKUST-1@CNS nanocomposite corroborating efficiency, mechanistic, and kinetic studies

Sulfonamide antibiotics, such as sulfamethoxazole (SMX), are found to be pollutants mostly generated from pharmaceutical wastewater with very high detection levels.

Intrusion detection based on graph-directed analytics of the big data

Attack graphs are a popular area of research that display all the paths an trespasser can take to penetrate a network. Existing graph generation methods rely heavily on expert opinion regarding network vulnerabilities and topology. An intrusion detection system based on graph-directed analytics of the big data analytics, which is based on machine learning, is proposed, which made it possible to obtain good accuracy results and a high level of attack detection during its testing. Keywords attack, graph, detection, machine learning, network

Laser Fencing Surveillance System With Email Alert

This work presents an antitheft alert system that integrates multiple technologies to offer a high level of detection, monitoring, and barrier protection through cost-effective methods and equipment. It implements a virtual LASER fence framework, enabling individuals to establish real-time surveillance at locations such as homes, farms, or any other area of interest. The proposed system detects objects that cross the vision line between the laser source and optical detector. When the laser beam is interrupted, alert data—including an instant notification via email and recorded footage of the intrusion—is sent to the security provider’s device using internet services like Gmail. The system is powered by a Raspberry Pi as the central processor, along with components like the Pi camera and laser modules. This solution addresses issues found in existing frameworks and ensures non-destructive consequences for the intruder.

Efficacy of whole-cell-based monovalent and bivalent vaccines against Streptococcus iniae and Flavobacterium covae in fingerling Asian seabass (Lates calcarifer)

Streptococcosis and columnaris caused by Streptococcus spp. and Flavobacterium spp. have been recognized as critical problems in Asian seabass aquaculture development because they cause severe mortality. In this study, we identified various isolates of S. iniae and F. covae from diseased Asian seabass farmed in Thailand for use as candidates for vaccine development. The efficacy of the vaccines was evaluated by challenge tests and immune parameter analyses in fish that received whole-cell-based monovalent and bivalent vaccines containing S. iniae (Sin) and F. covae (Fco) delivered by top-dressed feed (TD) and intraperitoneal injection (IP). The results showed that all vaccinated groups exhibited increased antibody titers compared with control fish that peaked on day 28 after booster administration with high detection levels in the Sin-IP and Fco-IP groups. Moreover, the immune responses to the injected monovalent vaccines (Sin-IP and Fco-IP) were better than the responses in the other vaccinated groups. The hematological and innate immunological parameters were significantly increased by Sin-IP and Fco-IP, particularly lysozyme activity, nitroblue tetrazolium (NBT) activity, bactericidal activity, and white blood cell numbers, and immune-related genes, including IgM, MHC-IIα, TCRß and CD4, were significantly upregulated in the head kidney, whole blood and spleen (P < 0.05). After experimental challenge, survival in the Sin-IP and Fco-IP groups was significantly higher than that in the Sin-TD, Fco-TD, Sin + Fco-TD, and Sin + Fco-IP groups, with 80.0 % and 60.0 % survival after S. iniae and F. covae infection, respectively. In contrast, survival after bacterial challenge in the control groups was 10 % in each group. Histopathological analysis revealed that Sin-IP- and Fco-IP-vaccinated fish exhibited significantly more goblet cells in the intestines and melanomacrophage centers (MMCs) in the head kidney and spleen than those in the other groups (P < 0.05). Overall, the results of our study indicated that the monovalent vaccines Sin-IP and Fco-IP provoked better vaccine efficacy and immune responses than their orally administered counterparts, and these results are consistent with those from the immunological assays that showed significantly increased responses after immunization.

The Attenuation and Scattering Signature of Fluid Reservoirs and Tectonic Interactions in the Central‐Southern Apennines (Italy)

AbstractDespite the high detection level of the Italian seismic network and the risk associated with its fault networks, Central‐Southern Italy has no unique geophysical model of the crust able to illuminate its complex tectonics. Here, we obtain seismic attenuation and scattering tomography models of this area; both reveal high attenuation and scattering anomalies characterizing the entire Apenninic Chain and related to its East‐ and West‐dipping extensional Quaternary tectonic alignments. Fault‐associated fractured zones become preferential ways for circulating and degassing high‐attenuation CO2‐bearing fluids. A previously undetected fluid source area is a high‐attenuation volume below the Matese complex, while a similar smaller anomaly supports a fluid source near L'Aquila. The most prominent low attenuation and scattering volumes reveal a locked aseismic zone corresponding to the Fucino‐Morrone‐Porrara fault systems, representing a zone of significant seismic hazard.

Investigation of the antimicrobial susceptibility patterns of marine cyanobacteria in Bohai Bay: Cyanobacteria may be important hosts of antibiotic resistance genes in marine environment

Marine cyanobacteria, as widely distributed and photosynthetically autotrophic bacteria in the ocean, may contribute to the global dissemination of antibiotic resistance genes (ARGs) and develop a different antimicrobial susceptibility pattern from heterotrophic bacteria and cyanobacteria from freshwater environments. However, studies on antimicrobial susceptibility and the carriage of ARGs in marine cyanobacteria are still very limited. In this study, the antibiotic resistance characteristics of cyanobacteria in nearshore waters were examined through field monitoring and laboratory investigations, which included PCR detection and ARG transformation. The results showed a positive correlation between marine cyanobacteria and some ARGs in the nearshore waters of Bohai Bay. Moreover, most screened cyanobacteria showed high minimum inhibitory concentration (MIC) values for polymyxins, tetracyclines, kanamycin, and sulfonamides, moderate MIC values for streptomycin, chloramphenicol, rifampicin, and norfloxacin, and low MIC values for roxithromycin and cephalosporins. The blaTEM, blaKPC, sul1, sul2, strA, tetA, tetB, tetC, tetM, mdfA, and intI1 genes were detected in the screened marine cyanobacteria. The highest detection rates were observed for blaTEM (93.3 %), sul1 (56.6 %), sul2 (90 %), and strA (73.3 %). The detection rate of tetA (33.3 %) was the highest among the tetracycline resistance genes, and mdfA, a multidrug-resistant pump gene with resistance to tetracycline, also showed a high detection level (23.3 %). Overall, most of the screened marine cyanobacteria were found to tolerate multiple antibiotics in seawater, and the condition of the ARGs carriage was serious. Furthermore, the screened marine Synechocystis sp. C12-2 demonstrated the ability to accept ARGs on the RP4 plasmid through natural transformation and showed reduced sensitivity to ampicillin, suggesting the possibility that some marine cyanobacteria could acquire ARGs from the environment through horizontal gene transfer. Thus, marine cyanobacteria may play an important role in the propagation of marine ARGs.

Detection of Unauthorized Actions in Networks Using Wavelet Analysis

Signal processing techniques are used to analyze and detect network anomalies because of their ability to detect new and unknown intrusions. The paper proposes a method of modeling network signals for the detection of network anomalies, which combines wavelet approximation and the theory of system identification. To characterize the behavior of network traffic, fifteen functions are provided, which are used as input signals within the system. At the same time, it is assumed that security violations within the network can be detected by checking abnormal patterns of system functioning according to audit data.&#x0D; Despite the fact that machine learning methods have achieved significant results in detecting network anomalies, they still face the difficulty of using the implemented algorithms, in the presence of differences in the behavior of the training data and test data, which in turn leads to inefficient performance of the algorithms. This effect is exacerbated by the limitation of algorithms to detect previously unknown types of attacks due to the large number of false positives.&#x0D; The paper develops a new method of modeling network signals for detecting anomalies in networks using wavelet analysis. In particular, the general architecture of the approach consists of three components: feature analysis, modeling of normal network traffic based on wavelet approximation and prediction using ARX model, intrusion or non-intrusion decision making&#x0D; The result is evaluated using the DARPA intrusion detection dataset, which performs a comprehensive analysis of the intrusions in the dataset. Evaluation results show that this approach provides a high level of detection of both instances and types of attacks.

A Reflective Spectroscopy and Mineralogical Investigation of Cosmetic Blush (Wet‘N’Wild) Potentially for Forensic Investigations Related to Interpersonal Violence—An Experimental Feasibility Study

Interpersonal violence is a rising issue in global society and new approaches are being sought to combat the problem. Within this context, expanding forensic techniques to better document violent crime scenes is critical for improving and acquiring legal evidence, such as proving or tracing contact between victims and suspects. This project aims to demonstrate the potential for forensic investigations in the context of interpersonal violence using a field-based reflective spectroscopy approach. For this, a common cosmetic, Wet‘N’Wild “Color Icon” blush in the shade “Pearlescent Pink”, was mineralogically characterized using transmission electron microscopy and powder X-ray diffraction and subsequently investigated via reflective spectroscopy on a variety of common substrates. Differing amounts of the cosmetic product, ranging from 0.001 g to 0.075 g, were applied to a variety of substrates using a simple push method to simulate forcible contact and material transfer. Substrates included a pine wood block; (calcareous) sand from Tulum, Mexico; Ottawa sand; tile; Pergo wood; linoleum; closet material; carpets; and fabrics. The reflective spectra of cosmetic–substrate combinations were measured via an ASD FieldSpec 4 Hi-Res spectroradiometer. The Wet‘N’Wild cosmetic was reliably detected on various substrates relevant to crime scenes. Minor amounts (as low as 0.02 mg/mm2) could be detected, and average limits of detection of 0.03 mg/mm2) were achieved; however, a calcareous sand (Tulum) had a high level of detection (&gt;0.38 mg/mm2), suggesting that further investigation is needed for more complex sand substrates. The use of the ASD spectroradiometer as a forensic tool within the context of crime scene documentation shows promise. Future work should expand the characterization of cosmetic materials across a broad range of substrates and consider systematic studies of specific population groups. Furthermore, combining this approach with hyperspectral imaging at crime scenes is a promising future direction for crime scene documentation. This work therefore demonstrates a novel method for investigating cosmetics within the context of interpersonal violence and provides a foundation for future laboratory and field work using the ASD FieldSpec 4 and hyperspectral imaging systems.

Artichoke deep learning detection network for site-specific agrochemicals UAS spraying

Input optimization is a distinguishing characteristic of Precision Agriculture approaches, helping reduce the environmental impact and costs and increase vegetable production quality. Thanks to the high automation evolution of Unmanned Aerial Systems (UAS), a new approach derived from their combination with Deep Learning techniques is leading to significant improvements in agricultural management practices. The study aims at artichoke plants detection and georeferencing as a first step for an on-the-fly, real time, UAS spraying system, and use the gathered information to monitor crop development through a multi-temporal approach. A commercial UAS, equipped with an RGB sensor, acquired images of the artichoke field located in Sardinia (Italy) during the 2021–2022 season in different crop growth stages. The FPN (Feature Pyramid Network), trained and compared with the YOLOv5 (You Only Look Once) network, showed a high detection level with an average F1 score of around 90%, and satisfactory off-line performances on the Nvidia Jetson Nano board. YOLOv5 achieved the best overall result. The FPN recorded a lower recall, which is desirable to achieve a minimum number of detection errors and limit the leakage of agrochemicals on false-positive targets. The multi-temporal approach influenced detection performances, with an inverse response of precision and recall metrics. The growing index trend showed a distinct value in October, peaking at the beginning of December as expected. The proposed approach contributes to designing future automatic and reliable site-specific UAS agrochemicals application and the classification of management zones.

High Levels of Detection of Nonpneumococcal Species of Streptococcus in Saliva from Adults in the United States.

While the sensitivity of detection of pneumococcal carriage can be improved by testing respiratory tract samples with quantitative PCR (qPCR), concerns have been raised regarding the specificity of this approach. We therefore investigated the reliability of the widely used lytA qPCR assay when applied to saliva samples from older adults in relation to a more specific qPCR assay (piaB). During the autumn/winter seasons of 2018/2019 and 2019/2020, saliva was collected at multiple time points from 103 healthy adults aged 21 to 39 (n = 34) and >64 (n = 69) years (n = 344 total samples). Following culture enrichment, extracted DNA was tested using qPCR for piaB and lytA. By sequencing the variable region of rpsB (S2 typing), we identified the species of bacteria isolated from samples testing lytA-positive only. While 30 of 344 (8.7%) saliva samples (16.5% individuals) tested qPCR-positive for both piaB and lytA, 52 (15.1%) samples tested lytA-positive only. No samples tested piaB-positive only. Through extensive reculture attempts of the lytA-positive samples collected in 2018/2019, we isolated 23 strains (in 8 samples from 5 individuals) that were also qPCR-positive for only lytA. Sequencing determined that Streptococcus mitis and Streptococcus infantis were predominantly responsible for this lytA-positive qPCR signal. We identified a comparatively large proportion of samples generating positive signals with the widely used lytA qPCR and identified nonpneumococcal Streptococcus species responsible for this signal. This highlights the importance of testing for the presence of multiple gene targets in tandem for reliable and specific detection of pneumococcus in polymicrobial respiratory tract samples. IMPORTANCE Testing saliva samples with quantitative PCR (qPCR) improves the sensitivity of detection of pneumococcal carriage. The qPCR assay targeting lytA, the gene encoding the major pneumococcal autolysin, has become widely accepted for the identification of pneumococcus and is even considered the "gold standard" by many. However, when applying this approach to investigate the prevalence of pneumococcal carriage in adults in New Haven, CT, USA, we identified nonpneumococcal Streptococcus spp. that generate positive signals in this widely used assay. By testing also for piaB (encoding the iron acquisition ABC transporter lipoprotein, PiaB), our findings demonstrate the importance of testing for the presence of multiple gene targets in tandem for reliable molecular detection of pneumococcus in respiratory tract samples; targeting only lytA may lead to an overestimation of true carriage rates.

Development of a new immunodiagnostic tool for poultry coccidiosis using an antigen-capture sandwich assay based on monoclonal antibodies detecting an immunodominant antigen of Eimeria

This study was conducted to develop an antigen-capture ELISA that detects an immunodominant antigen of Eimeria, 3-1E which is present in all Eimeria species, using a set of 3-1E-specific mouse monoclonal antibodies (mAbs). Highly sensitive 3-1E-specific antigen-capture ELISA was established using compatible mAb pairs (#318 and #320) selected from 6 mAbs (#312, #317, #318, #319, #320, and #323) with high binding activity against recombinant 3-1E protein. These anti-3-1E mAbs specifically recognized E. tenella sporozoites and a higher level of 3-1E was detected in the lysate of sporozoites than in sporocysts. Immunofluorescence assay (IFA) using 2 mAbs (#318 and #320) showed specific staining around the membrane of E. tenella sporozoites. In order to measure the changes in the 3-1E level during in coccidiosis, serum, feces, jejunal, and cecal contents were individually collected daily for 7-days postinfection (dpi) with E. maxima and E. tenella. The new ELISA was sensitive and specific for 3-1E detection in all samples collected daily from E. maxima- and E. tenella-infected chickens for a week, and the detection sensitivity ranges were 2 to 5 ng/mL and 1 to 5 ng/mL in serum, 4 to 25 ng/mL and 4 to 30 ng/mL in feces, 1 to 3 ng/mL and 1 to 10 ng/mL in cecal contents, and 3 to 65 ng/mL and 4 to 22 ng/mL in jejunal contents. Following coccidiosis, the overall 3-1E levels started to increase from 4 dpi, and the highest production was shown on 5 dpi. Among the samples collected from Eimeria-infected chickens, the highest detection level was found in the jejunal contents of E. maxima-infected chickens. Furthermore, the level of IFN-γ in serum was significantly (P < 0.05) increased from 3 dpi and peaked on 5 dpi post E. maxima infection. Post E. tenella infection, the level of IFN-γ in serum gradually (P < 0.05) increased from 2 to 5 dpi and plateaued at 7 dpi. The level of TNF-α in serum was rapidly (P < 0.05) increased from 4 dpi and those levels were kept until 7 dpi post both Eimeria infections (E. maxima and E. tenella). More importantly, the daily changes in the 3-1E levels in different samples from E. maxima- and E. tenella-infected chickens were effectively monitored with this new antigen-capture ELISA. Therefore, this new immunoassay is a sensitive diagnostic tool to monitor coccidiosis in a large field population in the commercial poultry farms before clinical symptoms develop using serum, feces, and gut samples during the entire period of infection cycle starting from 1 d after infection.