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Purpose: COVID-19 (coronavirus disease 2019) is an infectious disease caused by SARS-CoV-2, first reported in 2019 in Wuhan, China. Among the common complications is a pro-inflammatory and hypercoagulative response that compromises the vasculature among various organs., Methods: In this report, we present the postmortem retinal findings of five patients observed by means of optical microscopy and transmission and scanning electron microscopy techniques., Results: Clinical manifestations such as retinal hemorrhages and exacerbated inflammatory infiltrate, altered ultra structure with swollen mitochondria and pyknotic cells in both layers of the retina were observed in all analyzed eyes., Conclusion: Our data point to the fragility of this tissue in cases of severe COVID-19.

Background: Coronavirus disease (COVID-19) induces inflammation, coagulopathy following platelet and monocyte activation, and fibrinolysis, resulting in elevated D-dimer levels. Activated platelets and monocytes produce microvesicles (MVs). We analyzed the differences in platelet and monocyte MV counts in mild, moderate, and severe COVID-19, as well as their correlation with D-dimer levels., Methods: In this cross-sectional study, blood specimens were collected from 90 COVID-19 patients and analyzed for D-dimers using SYSMEX CS-2500. Platelet MVs (PMVs; PMVCD42b + and PMVCD41a + ), monocyte MVs (MMVs; MMVCD14 + ), and phosphatidylserine-binding annexin V (PS, AnnV + ) were analyzed using a BD FACSCalibur instrument., Results: PMV and MMV counts were significantly increased in COVID-19 patients. AnnV + PMVCD42b + and AnnV + PMVCD41a + cell counts were higher in patients with severe COVID-19 than in those with moderate clinical symptoms. The median (range) of AnnV + PMVCD42b + (MV/μL) in mild, moderate, and severe COVID-19 was 1,118.3 (328.1-1,910.5), 937.4 (311.4-2,909.5), and 1,298.8 (458.2-9,703.5), respectively ( P =0.009). The median (range) for AnnV + PMVCD41a + (MV/μL) in mild, moderate, and severe disease was 885.5 (346.3-1,682.7), 663.5 (233.8-2,081.5), and 1,146.3 (333.3-10,296.6), respectively ( P =0.007). D-dimer levels (ng/mL) weak correlated with AnnV + PMVCD41a + ( P =0.047, r=0.258)., Conclusions: PMV PMVCD42b + and PMVCD41a + counts were significantly increased in patients with severe clinical symptoms, and PMVCD41a + counts correlated with D-dimer levels. Therefore, MV counts can be used as a potential biomarker of COVID-19 severity.

Background: Porcine deltacoronavirus (PDCoV) is a swine enteropathogenic coronavirus that affects young pigs, causing vomiting, acute diarrhea, dehydration, and even death. There is growing evidence that PDCoV can undergo cross-species as well as zoonotic transmissions. Due to the frequent outbreaks of this deadly virus, early detection is essential for effective prevention and control. Therefore, developing a more convenient and reliable method for PDCoV detection is the need of the hour., Results: This study utilized a high-affinity monoclonal antibody as the capture antibody and a horseradish peroxidase labeled polyclonal antibody as the detection antibody to develop an enzyme-linked immunosorbent assay (DAS-ELSA) for PDCoV detection.Both antibodies target the PDCoV nucleocapsid (N) protein. The findings of this study revealed that DAS-ELISA was highly specific to PDCoV and did not cross-react with other viruses to cause swine diarrhea. The limit of detection of the virus titer using this method was 10 3 TCID 50 /mL of PDCoV particles. The results of a parallel analysis of 239 known pig samples revealed a coincidence rate of 97.07% (κ = 0.922) using DAS-ELISA and reverse transcriptase PCR (RT-PCR). The DAS-ELISA was used to measure the one-step growth curve of PDCoV in LLC-PK cells and the tissue distribution of PDCoV in infected piglets. The study found that the DAS-ELISA was comparable in accuracy to the TCID 50 method while measuring the one-step growth curve. Furthermore, the tissue distribution measured by DAS-ELISA was also consistent with the qRT-PCR method., Conclusion: The developed DAS-ELISA method can be conveniently used for the early clinical detection of PDCoV infection in pigs, and it may also serve as an alternative method for laboratory testing of PDCoV., (© 2024. The Author(s).)

Background: Predictive modelling using pre-epidemic data have long been used to guide public health responses to communicable disease outbreaks and other health disruptions. In this study, cancer registry and related health data available 2-3 months from diagnosis were used to predict changes in cancer detection that otherwise would not have been identified until full registry processing was completed about 18-24 months later. A key question was whether these earlier data could be used to predict cancer incidence ahead of full processing by the cancer registry as a guide to more timely health responses. The setting was the Australian State of New South Wales, covering 31 % of the Australian population. The study year was 2020, the year of emergence of the COVID-19 pandemic., Methods: Cancer detection in 2020 was modelled using data available 2-3 months after diagnosis. This was compared with data from full registry processing available from 2022. Data from pre-pandemic 2018 were used for exploratory model building. Models were tested using pre-pandemic 2019 data. Candidate predictor variables included pathology, surgery and radiation therapy reports, numbers of breast screens, colonoscopies, PSA tests, and melanoma excisions recorded by the universal Medical Benefits Schedule (MBS). Data were analysed for all cancers collectively and 5 leading types., Results: Compared with full registry processing, modelled data for 2020 had a >95 % accuracy overall, indicating key points of inflexion of cancer detection over the COVID-disrupted 2020 period. These findings highlight the potential of predictive modelling of cancer-related data soon after diagnosis to reveal changes in cancer detection during epidemics and other health disruptions., Conclusions: Data available 2-3 months from diagnosis in the pandemic year indicated changes in cancer detection that were ultimately confirmed by fully-processed cancer registry data about 24 months later. This indicates the potential utility of using these early data in an early-warning system., Competing Interests: Declaration of Competing Interest No conflicts of interest have been declared., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Multiplex analysis as an immunochip-in-a well format for simultaneous detection of post-vaccinal antibodies to three poultry infections (Newcastle disease, infectious bronchitis and bursal disease) in one chicken sera was developed. The immunochip had a microarray format printed on the bottom of a standard microtiter plate well and consisted of 36 microspots (d = 400 μm each) with three lines of viral antigens absorbed in a gradient of five decreasing concentrations. Optimization of assay conditions revealed the necessity of careful choice of the reaction buffer due to the high tendency of chicken IgY to exhibit unspecific binding. The best results were obtained for PBS buffer (pH 6.0) supplied with 0.1% Tween 20. Assay results were visualized by a number of coloured microspots that were correlated with the specific antibody titre in the analysed serum. High (> 8000), medium (3000-8000) or low (1000-3000) antibody titre level for each of three infections could be quickly assessed in one probe visually or with the help of smartphone. ELISA results (antibody titres) and visual gradient immunochip results interpretation (high, medium, low antibody level/titre) for 63 chicken sera with multiple levels of post-vaccinal antibodies against Newcastle disease, infectious bronchitis and bursal disease were in good correlation., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Bovine coronavirus (BCoV) is one of the important causes of diarrhoea in cattle. The virus is responsible for the high fatality rate associated with acute diarrhoea in calves. Rapid and accurate tests need to be conducted to detect the virus and minimise economic losses associated with the disease. Nucleic acid-based detection assays including PCR is an accurate test for detecting pathogens. However, these tests need skilled personnel, time and expensive devices. In this study, we developed a novel assay for the detection of BCoV in clinical cases. This novel assay combined reverse transcription-recombinase polymerase amplification with CRISPR/Cas13 and conducted a rapid visualisation of cleavage activity using a Lateral Flow Device. A conserved sequence of the BCV M gene was used as a target gene and the assays were tested in terms of specificity, sensitivity and time consumption. The result showed the specificity of the assay as 100% with no false positives being detected. Ten copies of the input RNA were enough to detect the virus and perform the assay. It took up to forty minutes for reading the results. Conducted together, the assay should be used as a rapid test to clinically diagnose infectious pathogens including bovine coronavirus. However, the assay needed the RNA to be extracted from the clinical sample in order to detect the virus. Therefore, more studies are needed to optimise the assay to be able to detect the virus in the clinical sample without extracting the RNA., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

During the COVID-19 pandemic, pneumonia was the leading cause of respiratory failure and death. In addition to SARS-COV-2, it can be caused by several other bacterial and viral agents. Even today, variants of SARS-COV-2 are endemic and COVID-19 cases are common in many places. The symptoms of COVID-19 are highly diverse and robust, ranging from invisible to severe respiratory failure. Current detection methods for the disease are time-consuming and expensive with low accuracy and precision. To address such situations, we have designed a framework for COVID-19 and Pneumonia detection using multiple deep learning algorithms further accompanied by a deployment scheme. In this study, we have utilized four prominent deep learning models, which are VGG-19, ResNet-50, Inception V3 and Xception, on two separate datasets of CT scan and X-ray images (COVID/Non-COVID) to identify the best models for the detection of COVID-19. We achieved accuracies ranging from 86% to 99% depending on the model and dataset. To further validate our findings, we have applied the four distinct models on two more supplementary datasets of X-ray images of bacterial pneumonia and viral pneumonia. Additionally, we have implemented a flask app to visualize the outcome of our framework to show the identified COVID and Non-COVID images. The findings of this study will be helpful to develop an AI-driven automated tool for the cost effective and faster detection and better management of COVID-19 patients., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Islam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study evaluated the use of endemic enteric coronaviruses polymerase chain reaction (PCR)-negative testing results as an alternative approach to detect the emergence of animal health threats with similar clinical diseases presentation. This retrospective study, conducted in the United States, used PCR-negative testing results from porcine samples tested at six veterinary diagnostic laboratories. As a proof of concept, the database was first searched for transmissible gastroenteritis virus (TGEV) negative submissions between January 1st, 2010, through April 29th, 2013, when the first porcine epidemic diarrhea virus (PEDV) case was diagnosed. Secondly, TGEV- and PEDV-negative submissions were used to detect the porcine delta coronavirus (PDCoV) emergence in 2014. Lastly, encountered best detection algorithms were implemented to prospectively monitor the 2023 enteric coronavirus-negative submissions. Time series (weekly TGEV-negative counts) and Seasonal Autoregressive-Integrated Moving-Average (SARIMA) were used to control for outliers, trends, and seasonality. The SARIMA's fitted and residuals were then subjected to anomaly detection algorithms (EARS, EWMA, CUSUM, Farrington) to identify alarms, defined as weeks of higher TGEV-negativity than what was predicted by models preceding the PEDV emergence. The best-performing detection algorithms had the lowest false alarms (number of alarms detected during the baseline) and highest time to detect (number of weeks between the first alarm and PEDV emergence). The best-performing detection algorithms were CUSUM, EWMA, and Farrington flexible using SARIMA fitted values, having a lower false alarm rate and identified alarms 4 to 17 weeks before PEDV and PDCoV emergences. No alarms were identified in the 2023 enteric negative testing results. The negative-based monitoring system functioned in the case of PEDV propagating epidemic and in the presence of a concurrent propagating epidemic with the PDCoV emergence. It demonstrated its applicability as an additional tool for diagnostic data monitoring of emergent pathogens having similar clinical disease as the monitored endemic pathogens., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Serafini Poeta Silva et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Infectious bronchitis (IB) is an acute, highly contagious contact respiratory disease of chickens caused by infectious bronchitis virus (IBV). IBV is very prone to mutation, which brings great difficulties to the prevention and control of the disease. Therefore, there is a pressing need for a method that is fast, sensitive, specific, and convenient for detecting IBV. In this study, a real-time fluorescence-based recombinase-aided amplification (RF-RAA) method was established. Primers and probe were designed based on the conserved regions of the IBV M gene and the reaction concentrations were optimized, then the specificity, sensitivity, and reproducibility of this assay were tested. The results showed that the RF-RAA method could be completed at 39℃ within 20 min, during which the results could be interpreted visually in real-time. The RF-RAA method had good specificity, no cross-reaction with common poultry pathogens, and it detected a minimum concentration of template of 2 copies/μL for IBV. Besides, its reproducibility was stable. A total of 144 clinical samples were tested by RF-RAA and real-time quantitative PCR (qPCR), 132 samples of which were positive and 12 samples were negative, and the coincidence rate of the two methods was 100 %. In conclusion, the developed RF-RAA detection method is rapid, specific, sensitive, reproducible, and convenient, which can be utilized for laboratory detection and clinical diagnosis of IBV., Competing Interests: Declaration of Competing Interest There is no conflict of interest in this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Porcine epidemic diarrhea virus (PEDV), an enteric coronavirus, induces severe vomiting and acute watery diarrhea in unweaned piglets. The pig industry has suffered tremendous financial losses due to the high mortality rate of piglets caused by PEDV. Consequently, a simple and rapid on-site diagnostic technology is crucial for preventing and controlling PEDV. This study established a detection method for PEDV using recombinase-aided amplification (RAA) and Pyrococcus furiosus Argonaute (PfAgo), which can detect 100 copies of PEDV without cross-reactivity with other pathogens. The entire reaction of RAA and PfAgo to detect PEDV does not require sophisticated instruments, and the reaction results can be observed with the naked eye. Overall, this integrated RAA-PfAgo cleavage assay is a practical tool for accurately and quickly detecting PEDV. KEY POINTS: • PfAgo has the potential to serve as a viable molecular diagnostic tool for the detection and diagnosis of viral genomes • The RAA-PfAgo detection technique has a remarkable level of sensitivity and specificity • The RAA-PfAgo detection system can identify PEDV without needing advanced equipment., (© 2024. The Author(s).)

Real-time, high-frequency measurements of pharmaceuticals, metabolites, exogenous antigens, and other biomolecules in biological samples can provide critical information for health management and clinical diagnosis. Electrochemical aptamer-based (EAB) sensor is a promising analytical technique capable of achieving these goals. However, the issues of insufficient sensitivity, frequent calibration and lack of adapted portable electrochemical device limit its practical application in immediate detection. In response we have fabricated an on-chip-integrated, cold-hot Janus EAB (J-EAB) sensor based on the thermoelectric coolers (TECs). Attributed to the Peltier effect, the enhanced/suppressed current response can be generated simultaneously on cold/hot sides of the J-EAB sensor. The ratio of the current responses on the cold and hot sides was used as the detection signal, enabling rapid on-site, calibration-free determination of small molecules (procaine) as well as macromolecules (SARS-CoV-2 spike protein) in single step, with detection limits of 1 μM and 10 nM, respectively. We have further demonstrated that the J-EAB sensor is effective in improving the ease and usability of the actual detection process, and is expected to provide a universal, low-cost, fast and easy potential analytical tool for other clinically important biomarkers, drugs or pharmaceutical small molecules., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Porcine epidemic diarrhea virus (PEDV) and rotavirus has posed a significant threat to the pig industry annually across different nations, resulting in huge economic losses. The frequent co-infection of these two viruses in clinical settings complicates the process of differential diagnoses. Rapid and accurate detection of PEDV and rotavirus is in great demand for timely diarrhea disease prevention and control. In this study, tris stabilized AuNPs were prepared and a sensitive lateral flow immunoassay (LFIA) sensor was developed for the simultaneous and rapid detection of PEDV and rotavirus on site. After the system optimization, the established LFIA can simultaneously identify PEDV and rotavirus with limits of detection (LOD) of 1.25 × 10 3 TCID 50 mL -1 and 3.13 × 10 2 pg mL -1 , respectively. When applying for clinical samples, the LFIA show a concordance of 95 % and 100 % to reverse transcript polymerase chain reaction (RT-PCR) for PEDV and rotavirus respectively. Therefore, this LFIA can qualitatively detect PEDV and rotavirus in 18 min with high sensitivity and accuracy without any sophisticated equipment and operation, making it a promising candidate for the early diagnosis of PEDV or/and rotavirus diarrhea on site., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Hailan Chen reports financial support was provided by Bama County for Talents in Science and Technology. Qianlian Su reports financial support was provided by Project for Enhancing Young and Middle-aged Teacher's Research Basis Ability in Universities in Guangxi. Hui You reports financial support was provided by Guangxi Bagui Scholar Program. Jiakang He reports financial support was provided by Guangxi Key R&D Program Project.]., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: To evaluate the factors associated with mortality among coronavirus disease-2019 patients with preexisting hypertension., Methods: The retrospective, cross-sectional study was conducted from June 15 to July 7, 2021, after approval from Dr Soetomo General Province Hospital, Indonesia, and comprised data from the coronavirus disease-2019 registry in the East Java province of Indonesia from March 2020 to June 2021. Data was collected for adult patients infected by coronavirus disease-2019 with pre-existing hypertension Data was analysed using SPSS 23., Results: Of the 2,732 patients in the registry, 425(15.6%) with median age 56.5 years (interquartile range: 50-64 years) had pre-existing hypertension. Of them, 251(59.06%) were males, and 110(25.9%) had died while in hospital. Mortality was associated with older age; higher white blood cell counts at admission and lower platelet count (p<0.05). In addition, electrocardiogram parameters associated with mortality were faster heart rate and ST abnormality (p<0.05)., Conclusions: Older age, high white blood cell level, lower platelet count, faster heart rate, and ST abnormality at admission were found to be the predictors of mortality among hospitalised coronavirus disease-2019 patients with pre-existing hypertension.

Porcine viral diarrhea is a common ailment in clinical settings, causing significant economic losses to the swine industry. Notable culprits behind porcine viral diarrhea encompass transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and porcine rotavirus-A (PoRVA). Co-infections involving the viruses are a common occurrence in clinical settings, thereby amplifying the complexities associated with differential diagnosis. As a consequence, it is therefore necessary to develop a method that can detect and differentiate all four porcine diarrhea viruses (TGEV, PEDV, PDCoV, and PoRVA) with a high sensitivity and specificity. Presently, polymerase chain reaction (PCR) is the go-to method for pathogen detection. In comparison to conventional PCR, TaqMan real-time PCR offers heightened sensitivity, superior specificity, and enhanced accuracy. This study aimed to develop a quadruplex real-time RT-qPCR assay, utilizing TaqMan probes, for the distinctive detection of TGEV, PEDV, PDCoV, and PoRVA. The quadruplex real-time RT-qPCR assay, as devised in this study, exhibited the capacity to avoid the detection of unrelated pathogens and demonstrated commendable specificity, sensitivity, repeatability, and reproducibility, boasting a limit of detection (LOD) of 27 copies/μL. In a comparative analysis involving 5483 clinical samples, the results from the commercial RT-qPCR kit and the quadruplex RT-qPCR for TGEV, PEDV, PDCoV, and PoRVA detection were entirely consistent. Following sample collection from October to March in Guangxi Zhuang Autonomous Region, we assessed the prevalence of TGEV, PEDV, PDCoV, and PoRVA in piglet diarrhea samples, revealing positive detection rates of 0.2 % (11/5483), 8.82 % (485/5483), 1.22 % (67/5483), and 4.94 % (271/5483), respectively. The co-infection rates of PEDV/PoRVA, PEDV/PDCoV, TGEV/PED/PoRVA, and PDCoV/PoRVA were 0.39 %, 0.11 %, 0.01 %, and 0.03 %, respectively, with no detection of other co-infections, as determined by the quadruplex real-time RT-qPCR. This research not only established a valuable tool for the simultaneous differentiation of TGEV, PEDV, PDCoV, and PoRVA in practical applications but also provided crucial insights into the prevalence of these viral pathogens causing diarrhea in Guangxi., Competing Interests: Declaration of competing interest Hechao Zhu, Geng Wang, Teng Yu, Weichao Zhang and Lumei Ni are employees of Guangxi Yangxiang Co., LTD. The remaining authors declared that they have no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Avian infectious bronchitis virus (IBV) still causes serious economic losses in the poultry industry. Currently, there are multiple prevalent genotypes and serotypes of IBVs. It is imperative to develop a new diagnosis method that is fast, sensitive, specific, simple, and broad-spectrum. A monoclonal hybridoma cell, N2D5, against the IBV N protein was obtained after fusion of myeloma SP2/0 cells with spleen cells isolated from the immunized Balb/c mice. The N2D5 monoclonal antibody (mAb) and the previously prepared mouse polyclonal antibody against the IBV N protein were used to target IBV as a colloidal gold-mAb conjugate and a captured antibody, respectively, in order to develop an immunochromatographic strip. The optimal pH and minimum antibody concentration in the reaction system for colloidal gold-mAb N2D5 conjugation were pH 6.5 and 30 μg/mL, respectively. Common avian pathogens were tested to evaluate the specificity of the strip and no cross-reaction was observed. The sensitivity of the strip for detecting IBV was 10 -1.4522 EID50/mL. The strip showed a broad-spectrum cross-reactive capacity for detecting IBV antigens, including multiple IBV genotypes in China and all of the seven serotypes of IBV that are currently prevalent in southern China. Additionally, the result can be observed within 2 min without any equipment. The throat and cloacal swab samples of chickens that were artificially infected with three IBV strains were tested using the developed strip and the qPCR method; the strip test demonstrated a high consistency in detecting IBV via qPCR gene detection. In conclusion, the immunochromatographic strip that was established is rapid, sensitive, specific, simple, practical, and broad-spectrum; additionally, it has the potential to serve as an on-site rapid detection method of IBV and can facilitate the surveillance and control of the disease, especially in resource-limited areas., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

This study describes the development and preliminary validation of a new serological assay using MERS-CoV S1 protein in an indirect enzyme-linked immunosorbent assay (ELISA) format. This assay has the advantage of being able to test MERS-CoV serum samples in a PC2 laboratory without the need for a high-level biocontainment laboratory (PC3 or PC4), which requires highly trained and skilled staff and a high level of resources and equipment. Furthermore, this MERS-CoV S1 ELISA enables a larger number of samples to be tested quickly, with results obtained in approximately five hours. The MERS-CoV S1 ELISA demonstrated high analytical specificity, with no cross-reactivity observed in serum of animals infected with other viruses, including different coronaviruses. We tested 166 positive and 40 negative camel serum samples and have estimated the diagnostic sensitivity (DSe) to be 99.4% (95% CI: 96.7 - 100.0%) and diagnostic specificity (DSp) to be 100% (95% CI: 97.2%-100.0%) relative to the assigned serology results (ppNT and VNT) using a S/P ratio cut-off value of >0.58. The findings of this study showed that our MERS-CoV S1 ELISA was more sensitive than the commercial EUROIMMUN ELISA (Se 99.4% vs 84.9%) and comparable to the ppNT assay, and therefore could be used as a diagnostic aid in countries in the Middle East where MERS-CoV is endemic in dromedary camels. The assay reagents and protocol were easily adapted and transferred from an Australian laboratory to a laboratory in the University of Hong Kong. Thus, the results described here show that the MERS-CoV S1 ELISA represents a cheap, rapid, robust, and reliable assay to support surveillance of MERS-CoV in camels in endemic regions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The infection of canine coronavirus (CCoV) causes a highly contagious disease in dogs with acute gastroenteritis. The efficient serological diagnostics is critical for controlling the disease caused by CCoV. Nucleocapsid (N) protein of CCoV is an important target for developing serological approaches. However, little is known about the antigenic sites in the N protein of CCoV. In this study, we generated a monoclonal antibody (mAb) against the N protein of CCoV, designated as 13E8, through the fusion of the sp2/0 cells with the spleen cells from a mouse immunized with the purified recombinant GST-N protein. Epitope mapping revealed that mAb 13E8 recognized a novel linear B cell epitope in N protein at 294-314aa (named as EP-13E8) by using a serial of truncated N protein through Western blot and ELISA. Sequence analysis showed that the sequence of EP-13E8 was highly conserved (100 %) among different CCoV strains analyzed, but exhibited a low similarity (31.8-63.6 %) with the responding sequence in other coronaviruses of the same genus such as FCoV, PEDV and HCoV except for TGEV (95.5 % identity). Structural assay suggested that the epitope of EP-13E8 were located in the close proximity on the surface of the N protein. Overall, the mAb 13E8 against N protein generated and its epitope EP-13E8 identified here paid the way for further developing epitope-based serological diagnostics for CCoV., Competing Interests: Declaration of Competing Interest All the authors have no conflicting financial interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Viral diarrhea is the predominant digestive tract sickness in piglings, resulting in substantial profit losses in the porcine industry. Porcine rotavirus A (PoRVA) and porcine epidemic diarrhea virus (PEDV) are the main causes of grave gastroenteritis and massive dysentery, especially in piglets. PoRVA and PEDV have high transmissibility, exhibit similar clinical symptoms, and frequently co-occur. Therefore, to avoid financial losses, a quick, highly efficient, objective diagnostic test for the prevention and detection of these diseases is required. Enzymatic recombinase amplification (ERA) is a novel technology based on isothermal nucleic acid amplification. It demonstrates high sensitivity and excellent specificity, with a short processing time and easy operability, compared with other in vitro nucleic acid amplification technologies. In this study, a dual ERA method to detect and distinguish between PEDV and PoRVA nucleic acids was established. The method shows high sensitivity, as the detection limits were 10 1 copies/μL for both viruses. To test the usefulness of this method in clinical settings, we tested 64 swine clinical samples. Our results were 100% matched with those acquired using a commercially available kit. Therefore, we have successfully developed a dual diagnostic ERA nucleic acids method for detecting and distinguishing between PEDV and PoRVA., Competing Interests: Declaration of competing interest We don't have any kind of conflict of interest. All authors contributed to the writing of the manuscript. All authors reviewed the manuscript and agreed to publish., (Copyright © 2024 Elsevier Inc. All rights reserved.)

COVID-19 is a kind of coronavirus that appeared in China in the Province of Wuhan in December 2019. The most significant influence of this virus is its very highly contagious characteristic which may lead to death. The standard diagnosis of COVID-19 is based on swabs from the throat and nose, their sensitivity is not high enough and so they are prone to errors. Early diagnosis of COVID-19 disease is important to provide the chance of quick isolation of the suspected cases and to decrease the opportunity of infection in healthy people. In this research, a framework for chest X-ray image classification tasks based on deep learning is proposed to help in early diagnosis of COVID-19. The proposed framework contains two phases which are the pre-processing phase and classification phase which uses pre-trained convolution neural network models based on transfer learning. In the pre-processing phase, different image enhancements have been applied to full and segmented X-ray images to improve the classification performance of the CNN models. Two CNN pre-trained models have been used for classification which are VGG19 and EfficientNetB0. From experimental results, the best model achieved a sensitivity of 0.96, specificity of 0.94, precision of 0.9412, F1 score of 0.9505 and accuracy of 0.95 using enhanced full X-ray images for binary classification of chest X-ray images into COVID-19 or normal with VGG19. The proposed framework is promising and achieved a classification accuracy of 0.935 for 4-class classification., (© 2024. The Author(s).)

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

Widespread distribution of porcine epidemic diarrhea virus (PEDV) has led to catastrophic losses to the global pig farming industry. As a result, there is an urgent need for rapid, sensitive and accurate tests for PEDV to enable timely and effective interventions. In the present study, we develop and validate a floating gate carbon nanotubes field-effect transistor (FG CNT-FET)-based portable immunosensor for rapid identification of PEDV in a sensitive and accurate manner. To improve the affinity, a unique PEDV spike protein-specific monoclonal antibody is prepared by purification, and subsequently modified on FG CNT-FET sensor to recognize PEDV. The developed FET biosensor enables highly sensitive detection (LoD: 8.1 fg/mL and 10 0.14 TCID 50 /mL for recombinant spike proteins and PEDV, respectively), as well as satisfactory specificity. Notably, an integrated portable platform consisting of a pluggable FG CNT-FET chip and a portable device can discriminate PEDV positive from negative samples and even identify PEDV and porcine deltacoronavirus within 1 min with 100% accuracy. The portable sensing platform offers the capability to quickly, sensitively and accurately identify PEDV, which further points to a possibility of point of care (POC) applications of large-scale surveillance in pig breeding facilities., (© 2024. The Author(s).)

To date, there is no licensed vaccine for Middle East respiratory syndrome coronavirus (MERS-CoV). Therefore, MERS-CoV is one of the diseases targeted by the Coalition for Epidemic Preparedness Innovations (CEPI) vaccine development programs and has been classified as a priority disease by the World Health Organization (WHO). An important measure of vaccine immunogenicity and antibody functionality is the detection of virus-neutralizing antibodies. We have developed and optimized a microneutralization assay (MNA) using authentic MERS-CoV and standardized automatic counting of virus foci. Compared to our standard virus neutralization assay, the MNA showed improved sensitivity when analyzing 30 human sera with good correlation of results (Spearman's correlation coefficient r = 0.8917, p value < 0.0001). It is important to use standardized materials, such as the WHO international standard (IS) for anti-MERS-CoV immunoglobulin G, to compare the results from clinical trials worldwide. Therefore, in addition to the neutralizing titers (NT 50  = 1384, NT 80  = 384), we determined the IC 50 and IC 80 of WHO IS in our MNA to be 0.67 IU/ml and 2.6 IU/ml, respectively. Overall, the established MNA is well suited to reliably quantify vaccine-induced neutralizing antibodies with high sensitivity., (© 2024. The Author(s).)

The endemic outbreak of SADS-CoV has resulted in economic losses and potentially threatened the safety of China's pig industry. The molecular epidemiology of SADS-CoV in pig herds has been investigated in many provinces in China. However, there are no data over a long-time span, and there is a lack of extensive serological surveys to assess the prevalence of SADS-CoV in Chinese swine herds since the discovery of SADS-CoV. In this study, an indirect anti-SADS-CoV IgG enzyme-linked immunosorbent assay (ELISA) based on the SADS-CoV S1 protein was established to investigate the seroprevalence of SADS-CoV in Chinese swine herds. Cross-reactivity assays, indirect immunofluorescence, and western blotting assays showed that the developed ELISA had excellent SADS-CoV specificity. In total, 12,978 pig serum samples from 29 provinces/municipalities/autonomous regions in China were tested from 2022 to 2023. The results showed that the general seroprevalence of SADS-CoV in China was 59.97%, with seroprevalence ranging from 16.7% to 77.12% in different provinces and from 42.61% to 68.45% in different months. SADS-CoV is widely prevalent in China, and its seroprevalence was higher in Northeast China, North China, and Central China than in other regions. Among the four seasons, the prevalence of SADS-CoV was the highest in spring and the lowest in autumn. The results of this study provide the general seroprevalence profile of SADS-CoV in China, facilitating the understanding of the prevalence of SADS-CoV in pigs. More importantly, this study is beneficial in formulating preventive and control measures for SADS-CoV and may provide directions for vaccine development., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Liu, Zhao, Yang, Liu, Luo, Zhu, Huang, Sheng, Du and Jin.)

Porcine deltacoronavirus (PDCoV) is a major cause of diarrhea and diarrhea-related deaths among piglets and results in massive losses to the overall porcine industry. The clinical manifestations of porcine diarrhea brought on by the porcine epidemic diarrhea virus (PEDV), porcine transmissible gastroenteritis virus (TGEV), and PDCoV are oddly similar to each other. Hence, the identification of different pathogens through molecular diagnosis and serological techniques is crucial. Three novel detection methods for identifying PDCoV have been developed utilizing recombinase-aided amplification (RAA) or reverse transcription recombinase-aided amplification (RT-RAA) in conjunction with Pyrococcus furiosus Argonaute (PfAgo): RAA-PfAgo, one-pot RT-RAA-PfAgo, and one-pot RT-RAA-PfAgo-LFD. The indicated approaches have a detection limit of around 60 copies/μL of PDCoV and do not cross-react with other viruses including PEDV, TGEV, RVA, PRV, PCV2, or PCV3. The applicability of one-pot RT-RAA-PfAgo and one-pot RT-RAA-PfAgo-LFD were examined using clinical samples and showed a positive rate comparable to the qPCR method. These techniques offer cutting-edge technical assistance for identifying, stopping, and managing PDCoV.

In this study, virological surveillance focused on coronaviruses in marmots in the Alpine region in 2022, captured as part of a population control reduction program in the Livigno area. Seventy-six faecal samples were randomly collected from marmots at the time of capture and release and tested for genome detection of pan-coronavirus, pan-pestivirus, canine distemper virus, and influenza A and D virus. Nine faecal samples were positive in the Pan-CoV RT-PCR, while all were negative for the other viruses. Pan-coronavirus positives were further identified using Illumina's complete genome sequencing, which showed the highest homology with Bovine Coronavirus previously detected in roe deer in the Alps. Blood samples (n.35) were collected randomly from animals at release and tested for bovine coronavirus (BCoV) antibodies using competitive ELISA and VNT. Serological analyses revealed that 8/35 sera were positive for BCoV antibodies in both serological tests. This study provides molecular and serological evidence of the presence of BCoV in an alpine marmot population due to a likely spillover event. Marmots share areas and pastures with roe deer and other wild ruminants, and environmental transmission is a concrete possibility.

Emerging coronaviruses (CoVs) are understood to cause critical human and domestic animal diseases; the spillover from wildlife reservoirs can result in mild and severe respiratory illness in humans and domestic animals and can spread more readily in these naïve hosts. A low-cost CoV molecular method that can detect a variety of CoVs from humans, animals, and environmental specimens is an initial step to ensure the early identification of known and new viruses. We examine a collection of 50 human, 46 wastewater, 28 bat, and 17 avian archived specimens using 3 published pan-CoV PCR assays called Q-, W-, and X-CoV PCR, to compare the performance of each assay against four CoV genera. X-CoV PCR can detect all four CoV genera, but Q- and W-CoV PCR failed to detect δ-CoV. In total, 21 (42.0%), 9 (18.0%), and 21 (42.0%) of 50 human specimens and 30 (65.22%), 6 (13.04%), and 27 (58.70%) of 46 wastewater specimens were detected using Q-, W-, and X-CoV PCR assays, respectively. The X-CoV PCR assay has a comparable sensitivity to Q-CoV PCR in bat CoV detection. Combining Q- and X-CoV PCR assays can increase sensitivity and avoid false negative results in the early detection of novel CoVs., Competing Interests: The authors declare no conflicts of interest.

Porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and swine acute diarrhea syndrome coronavirus (SADS-CoV) cause intestinal diseases with similar manifestations in suckling piglets. In this study, we developed a multiplex real-time PCR for differential diagnosis of PEDV, PDCoV, and SADS-CoV. The assay demonstrated high specificity with a detection limit of 5 copies/µl for each virus. The assay specifically detected PEDV, PDCoV, and SADS-CoV and excluded all other swine pathogens circulating in pigs. Furthermore, the assay exhibited satisfactory performance in analyzing clinical samples. The data indicate that the newly developed multiplex real-time PCR method can be applied for differential diagnosis of porcine enteric coronaviruses., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Objective: To construct a deep learning-based target detection method to help radiologists perform rapid diagnosis of lesions in the CT images of patients with novel coronavirus pneumonia (NCP) by restoring detailed information and mining local information., Methods: We present a deep learning approach that integrates detail upsampling and attention guidance. A linear upsampling algorithm based on bicubic interpolation algorithm was adopted to improve the restoration of detailed information within feature maps during the upsampling phase. Additionally, a visual attention mechanism based on vertical and horizontal spatial dimensions embedded in the feature extraction module to enhance the capability of the object detection algorithm to represent key information related to NCP lesions., Results: Experimental results on the NCP dataset showed that the detection method based on the detail upsampling algorithm improved the recall rate by 1.07% compared with the baseline model, with the AP50 reaching 85.14%. After embedding the attention mechanism in the feature extraction module, 86.13% AP50, 73.92% recall, and 90.37% accuracy were achieved, which were better than those of the popular object detection models., Conclusion: The feature information mining of CT images based on deep learning can further improve the lesion detection ability. The proposed approach helps radiologists rapidly identify NCP lesions on CT images and provides an important clinical basis for early intervention and high-intensity monitoring of NCP patients., Competing Interests: 利益冲突　所有作者均声明不存在利益冲突, (© 2024《四川大学学报（医学版）》编辑部 版权所有Copyright ©2024 Editorial Board of Journal of Sichuan University (Medical Sciences).)

Zoonotic coronaviruses (CoVs) caused major human outbreaks in the last two decades. One of the biggest challenges during future CoV disease is ensuring rapid detection and diagnosis at the early phase of a zoonotic event, and active surveillance to the zoonotic high-risk CoVs appears the best way at the present time to provide early warnings. However, there is neither an evaluation of spillover potential nor diagnosis tools for the majority of CoVs. Here, we analyzed the viral traits, including population, genetic diversity, receptor and host species for all 40 alpha- and beta-CoV species, where the human-infecting CoVs are from. Our analysis proposed 20 high-risk CoV species, including 6 of which jumped to human, 3 with evidence of spillover but not to human and 11 without evidence of spillover yet, which prediction were further supported by an analysis of the history of CoV zoonosis. We also found three major zoonotic sources: multiple bat-origin CoV species, the rodent-origin sub-genus Embecovirus and the CoV species AlphaCoV1. Moreover, the Rhinolophidae and Hipposideridae bats harbour a significantly higher proportion of human-threatening CoV species, whereas camel, civet, swine and pangolin could be important intermediate hosts during CoV zoonotic transmission. Finally, we established quick and sensitive serologic tools for a list of proposed high-risk CoVs and validated the methods in serum cross-reaction assays using hyper-immune rabbit sera or clinical samples. By comprehensive risk assessment of the potential human-infecting CoVs, our work provides a theoretical or practical basis for future CoV disease preparedness.

Infectious bronchitis virus (IBV), a gammacoronavirus within the Coronaviridae family, is an economically important etiological disease agent in chickens. Both early diagnosis and determination of the immune status of chickens are important for controlling IBV outbreaks in chicken flocks. The N protein is the most abundantly expressed virus-derived protein during IBV infection and can induce a strong immune response by producing antibodies during early infection or immunization. In this study, we found that the amino acid sequences of the N protein between CK/CH/LJL/04I and the other 22 IBVs were conserved, especially in the 1-160 amino acid region. Based on the sequence similarities, the three recombinant proteins, rN160 (amino acid positions 1-160), rN266 (144-409), and rN409 (1-409), were expressed using the Escherichia coli system and subsequently purified. The results demonstrated that the antigenicity and reactivity of rN160 were better than those of rN266 and rN409. As a result, an indirect enzyme-linked immunosorbent assay (ELISA) (rN160 ELISA) was developed to detect the IBV antibody based on the rN160 protein. Using 1,500 clinical field serum samples, the relative sensitivity, specificity, and accuracy of the rN160 ELISA were 98.97%, 92.34%, and 97.93%, respectively, compared to those of a commercial ELISA kit (IDEXX), indicating a strong positive correlation between the two methods. Taken together, these results reveal that the rN160 ELISA is a rapid, simple, and sensitive method for detecting group-specific IBV antibodies for epidemiological investigation and antibody-level monitoring.

Background: In pediatric patients, the common cold coronavirus (ccCoV) usually causes mild respiratory illness. There are reports of coronavirus causing central nervous system (CNS) infection in experimental animal models. Some immunocompromised patients have also been reported to have fatal CNS infections with ccCoV. The aim of this study was to investigate the clinical characteristics of CNS complications related to ccCoV infection., Methods: From January 2014 to December 2019, a retrospective analysis was performed of medical records from hospitalized patients under 19 years of age whose ccCoV was detected through polymerase chain reaction in respiratory specimens. The CNS complications were defined as clinically diagnosed seizure, meningitis, encephalopathy, and encephalitis., Results: A total of 436 samples from 420 patients were detected as ccCoV. Among the 420 patients, 269 patients were immunocompetent and 151 patients were immunocompromised. The most common type of ccCoV was OC43 (52% in immunocompetent, 37% in immunocompromised). CNS complications were observed in 9.4% (41/436). The most common type of CNS complication was the fever-provoked seizure under pre-existing neurologic disease (42% in immunocompetent and 60% in immunocompromised patients). Among patients with CNS complications, two immunocompetent patients required intensive care unit admission due to encephalitis. Three patients without underlying neurological disease started anti-seizure medications for the first time at this admission. There was no death related to ccCoV infection., Conclusion: ccCoV infection may cause severe clinical manifestations such as CNS complications or neurologic sequelae, even in previously healthy children., Competing Interests: The authors have no potential conflicts of interest to disclose., (© 2023 The Korean Academy of Medical Sciences.)

For rapid and reliable detection of porcine epidemic diarrhea virus (PEDV) from pig clinical samples, a multiplex, real-time, reverse transcription loop-mediated isothermal amplification (mqRT-LAMP) was developed using two sets of primers and assimilating probes specific to the PEDV N gene and the Sus scrofa β-actin gene, which was used as an endogenous internal positive control (EIPC) to avoid false-negative results. The assay specifically amplified both target genes of PEDV and EIPC in a single reaction without any interference but did not amplify other porcine viral nucleic acids. The limit of detection was 10 copies/μL, 100-fold lower than that of a reverse transcription-polymerase chain reaction (RT-PCR) and equivalent to that of quantitative/real-time RT-PCR (qRT-PCR). This assay has high repeatability and reproducibility with coefficients of variation < 4.0%. The positive signal of the mqRT-LAMP assay was generated within 25 min, demonstrating advantages in rapid detection of PEDV over RT-PCR or qRT-PCR assay, which require at least 2 h turnaround times. In clinical evaluation, the detection rate of PEDV by mqRT-LAMP assay (77.3%) was higher than that of RT-PCR assay (69.7%), and comparable to qRT-PCR (76.8%) with almost 100% concordance (kappa value 0.98). The developed mqRT-LAMP assay can serve as an advanced alternative method for PEDV diagnosis because it has high sensitivity and specificity, rapidity, and reliability even in resource-limited laboratories.

Background: Since the first human case of Middle East Respiratory Syndrome (MERS) caused by Coronavirus (MERS-CoV) in 2012, several evidence bases have shown one-humped camels as the main reservoir host, from which infection is transmitted to humans., Aim: Serological investigation of MERS in dromedary camels in Wasit province (Iraq), detection severity of infection, and association to some risk factors., Methods: A total of 455 dromedary camels were selected randomly from two main districts in Wasit province, Iraq, during January and April (2023). Sera of all study camels were examined by enzyme-linked immunosorbent assay (ELISA), and titers of positive study animals were categorized according to their severity., Results: Serological testing yielded 37.58% positive animals for MERS infection. According to the severity of positive ODs (titer), a total of 53.22%, 30.99%, 12.28%, and 3.51% showed mild, moderate, strong, and very strong infections, respectively. Regarding risk factors, significant elevation in seropositivity was seen in camels of >3-6 and >6 years old and reduced in camels of £3 years old with an elevated risk of MERS with increased age. Regionally, seropositivity and relative risk were increased in the camels of Shaykh Sa'd when compared with Al-Numaniyah. Regarding sex, no significant variation was detected between seropositive females and males; however, male camels appeared at higher risk than females. Association between the severity of MERS infection and risk factors revealed that there was a significant increase in mild and moderate infections in female camels of >6 years old; whereas strong and very strong infections were seen in male camels of 3 3-6 years old. Mild and very strong infections were recorded in Shaykh Sa'd; while moderate and strong infections in Al-Numaniyah., Conclusion: The study indicated a longstanding existence of MERS-CoV in camels of Wasit province; therefore, recent infections or active viral excretion are required for confirmation by molecular approaches., Competing Interests: All authors have no conflict of interest to disclose.

Porcine deltacoronavirus (PDCoV) is an emerging discovered coronavirus that causes significant losses in the global swine industry. This study aimed to establish an indirect ELISA method for detecting PDCoV antibodies using the truncated gene of PDCoV spike protein (S). The purified S protein was used as the coating antigen for the polyclonal antibody. The conditions were optimized to establish an indirect ELISA detection method for PDCoV based on the S protein, which showed good specificity and no cross-reaction with SVV-VP1, ASFV-P72, GETV-E2, PRV-gE, etc. The method has high repeatability, with coefficients of variation within and between batches less than 10%. Compared with the commercial kit, the positive coincidence rate is 86.40%, the negative coincidence rate is 89.43%, and the total coincidence rate is 91.76%. This ELISA can be used for PDCoV serological investigation and antibody evaluation. It can also lay the foundation for further research and development of PDCoV S protein ELISA antibody detection kit., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Porcine epidemic diarrhea virus (PEDV) and porcine delta-coronavirus (PDCoV) are economically important pathogens that cause diarrhea in sows and acute death of newborn piglets. Moreover, the emerging PDCoV was reported to infect children. The current situation is that vaccine prevention has not met expectations, and emergency containment strategies following outbreaks cannot prevent the damages and losses already incurred. Therefore, a more sensitive detection method, that is both convenient and enables accurate and effective sequencing, that will provide early warning of PEDV and PDCoV is necessary. This will enable active, effective, and comprehensive prevention and control, which will possibly reduce disease occurrences., Results: Duplex nested RT-PCR (dnRT-PCR) is an ideal method to achieve early warning and monitoring of PEDV and PDCoV diseases, and to additionally investigate any molecular epidemiological characteristics. In this study, two pairs of primers were designed for each virus based upon the highly conserved N protein sequences of both PEDV and PDCoV strains retrieved from the NCBI Genbank. After optimization of the reaction conditions, the dnRT-PCR assay amplified a 749-bp fragment specific to PEDV and a 344-bp fragment specific to PDCoV. Meanwhile, the specificity and sensitivity of the primers and clinical samples were tested to verify and establish this dnRT-PCR method. The limit of detection (LoD)for both PEDV and PDCoV was 10 copies/µL. The results showed that among 251 samples, 1 sample contained PEDV infection, 19 samples contained a PDCoV infection, and 8 samples were infected with both viruses, following the use of dnRT-PCR. Subsequently, the positive samples were sent for sequencing, and the sequencing results confirmed that they were all positive for the viruses detected using dnRT-PCR, and conventional RT-PCR detection was conducted again after the onset of disease. As these results were consistent with previous results, a detection method for PEDV and PDCoV using dnRT-PCR was successfully established. In conclusion, the dnRT-PCR method established in this study was able to detect both PEDV and PDCoV, concomitantly., Conclusions: The duplex nested RT-PCR method represents a convenient, reliable, specific, sensitive and anti-interference technique for detecting PEDV and PDCoV, and can additionally be used to simultaneously determine the molecular epidemiological background., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Porcine deltacoronavirus (PDCoV) is an enteropathogen that causes diarrhea in piglets and may undergo cross-species transmission. The prevention and control of PDCoV are complicated, and a sensitive, specific, and accessible method of diagnosis would be advantageous. Whereas qPCR is a standard approach for detecting PDCoV, it is not effectively sensitive. In the present study, we report such a strategy using an RT-PCR-based RspCas13d detection system and its efficacy in clinical sample diagnosis. The detection limit of this method was 4 copies/μL and no cross-reaction with other viruses such as the porcine epidemic diarrhea virus, classical swine fever virus, pseudorabies virus, porcine reproductive and respiratory syndrome virus, transmissible gastroenteritis virus and porcine rotavirus. The method was also effective in clinical samples. In summary, we demonstrate that RT-PCR-based RspCas13d detection system is an extremely sensitive and specific nucleic acid-based approach for detecting PDCoV. KEY POINTS: • RspCas13d can be used as a candidate molecular diagnostic tool to diagnose viral genomes. • A novel method is proposed using an RT-PCR-based RspCas13d detection system and its effectiveness in the detection of PDCoV. • The RT-PCR-based RspCas13d detection system has excellent sensitivity and specificity., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a newly discovered emerging alphacoronavirus. SADS-CoV shares over 90% genome sequence identity with bat alphacoronavirus HKU2. SADS-CoV was associated with severe diarrhea and high mortality rates in piglets. Accurate serological diagnosis of SADS-CoV infection is key in managing the emerging SADS-CoV. However, thus far there have been no effective antibody-based diagnostic tests for diagnose of SADS-CoV exposure. Here, monoclonal antibody (MAb) 6E8 against SADS-CoV N protein accurately recognized SADS-CoV infection. Then, MAb 6E8 was utilized as a blocking antibody to develop blocking ELISA (bELISA). We customized the rN coating antigen with concentration 0.25 μg/mL. According to receiver operator characteristic curve analysis, the cutoff value of the bELISA was determined as 38.19% when the max Youden index was 0.955, and specificity was 100%, and sensitivity was 95.5%. Specificity testing showed that there was no cross-reactivity with other serum positive swine enteric coronaviruses, such as porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), porcine deltacoronavirus (PDCoV), porcine rotavirus (PoRV), and porcine sapelovirus (PSV). In conclusion, we customized a novel and high-quality blocking ELISA for detection of SADS-CoV infection, and the current bELISA will be linked to a clinical and epidemiological assessment of SADS-CoV infection. IMPORTANCE SADS-CoV was reported to be of high potential for dissemination among various of host species. Accurate serological diagnosis of SADS-CoV infection is key in managing the emerging SADS-CoV. However, thus far there have been no effective antibody-based diagnostic tests for diagnose of SADS-CoV exposure. We customed a novel and high-quality bELISA assay for detection of SADS-CoV N protein antibodies, and the current bELISA will be linked to a clinical and epidemiological assessment of SADS-CoV infection., Competing Interests: The authors declare no conflict of interest.

Infectious bronchitis virus (IBV) infection can be associated with respiratory, renal, and/or reproductive diseases in chickens. Under natural conditions, conjunctiva, mucosa of upper respiratory tract, and cloaca are the main routes of IBV entry. Experimentally, the study of IBV infection involved various routes of inoculation. This study investigated the impact of adding the trachea as a potential route of viral entry to the oculo-nasal infection on the host responses, pathogenicity, and tissue tropism of the Canadian IBV Delmarva (DMV/1639) strain in laying chickens. Specific-pathogen-free laying chickens were divided into three experimental groups: control group (Con group), oculo-nasal challenged group (ON group), and oculo-nasal/intratracheal challenged group (ON/IT group); all groups were observed for 12 days post-infection (dpi). The clinical signs and reduction in egg production in the ON/IT group started slightly earlier compared to the ON group. At 12 dpi, the gross lesions in the ON/IT group were confined to the ovary, while the ON group showed regressed ovary and atrophied oviduct. Only the ON group showed significantly higher microscopic lesion scores in the lung, kidney, magnum, and uterus compared to the control group at 12 dpi. The oviduct tissues of the ON group showed a significant increase in B cells infiltration compared to ON/IT and control groups. The viral shedding (detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR)), tissue tropism (detected either by qRT-PCR or immunohistochemistry (IHC)), T/natural killer cells infiltration in reproductive tract (detected by IHC), and antibody-mediated immune responses (measured by enzyme-linked immunosorbent assay) showed similar patterns in the ON and ON/IT groups., Competing Interests: Declaration of Competing Interest All of the authors including corresponding author have no declarations of competing interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: In our current digital world, smartphones are no longer limited to communication but are used in various real-world applications. In the healthcare industry, smartphones have sensors that can record data about our daily activities. Such data can be used for many healthcare purposes, such as elderly healthcare services, early disease diagnoses, and archiving patient data for further use. However, the data collected from the various sensors involve high dimensional features, which are not equally helpful in human activity recognition (HAR)., Methods: This paper proposes an algorithm for selecting the most relevant subset of features that will contribute efficiently to the HAR process. The proposed method is based on a hybrid version of the recent Coronavirus Disease Optimization Algorithm (COVIDOA) with Simulated Annealing (SA). SA algorithm is merged with COVIDOA to improve its performance and help escape the local optima problem., Results: The UCI-HAR dataset from the UCI machine learning repository assesses the proposed algorithm's performance. A comparison is conducted with seven well-known feature selection algorithms, including the Arithmetic Optimization Algorithm (AOA), Gray Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Reptile Search Algorithm (RSA), Zebra Optimization Algorithm (ZOA), Gradient-Based Optimizer (GBO), Seagull Optimization Algorithm (SOA), and Coyote Optimization Algorithm (COA) regarding fitness, STD, accuracy, size of selected subset, and processing time., Conclusions: The results proved that the proposed approach outperforms state-of-the-art HAR techniques, achieving an average performance of 97.82% in accuracy and a reduction ratio in feature selection of 52.7%.

Avian infectious bronchitis (IB) is a highly contagious disease caused by infectious bronchitis virus (IBV). Vaccination is an effective approach for controlling IBV. Therefore, reliable immune monitoring for IB is critical for poultry. In this study, a novel peptide derived from S2 protein was used to develop an enzyme-linked immunosorbent assay (ELISA) for the detection of broadly cross-reactive antibodies against IBV. The peptide-based ELISA (pELISA) showed good specificity and sensitivity in detecting IBV antibodies against different serotypes. A semilogarithmic regression method for determining IBV antibody titers was also established. Antibody titers detected by pELISA and calculated with this equation were statistically similar to those evaluated by indirect fluorescence assay (IFA). Moreover, the comparison analysis showed a 96.07% compatibility between the pELISA and IDEXX ELISA. All these data demonstrate that the pELISA generated here can be as a rapid and reliable serological surveillance tool for monitoring IBV infection or vaccination., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Infectious diseases of young and adult birds with respiratory syndrome are a significant deterrent to the development of industrial poultry farming due to decreased productivity and significant mortality. The only effective method of combating viral diseases is timely and targeted vaccination, which largely depends on laboratory diagnostic results., Aim: This article aims to study the real-time reverse transcription polymerase chain reaction, (RT-PCR) which has the prospect of more effective diagnosis of vaccine strains of chicken infectious bronchitis and Newcastle disease., Methods: The fastest and most accurate method for the differential diagnosis of pathogens in an associative viral infection is RT-PCR. The method proposed in the article for selecting primers for amplification made it possible to use this method for the simultaneous interspecies differential diagnosis of two or more viral agents, significantly accelerating their diagnosis., Results: The correlation of the nucleotide sequence obtained from sequencing to a specific virus strain is complicated by the lack of a single nomenclature mechanism for separating genetic groups., Conclusion: The results of this study will allow easy and fast typing of sequences into known and databased virus strains and avoid further confusion in the nomenclature of genetic groups in the future.

Porcine viral diarrhea is very common in clinical practice and has caused huge losses to the pig industry. Porcine epidemic diarrhea virus (PEDV), porcine rotavirus (PoRV), and porcine deltacoronavirus (PDCoV) are important pathogens of porcine viral diarrhea. Co-infection situations among these three viruses in clinics are common, which increases the difficulty of differential diagnosis. Currently, polymerase chain reaction (PCR) is commonly used to detect pathogens. TaqMan real-time PCR is more sensitive than conventional PCR and has better specificity and accuracy. In this study, a triplex real-time RT-PCR assay based on TaqMan probes was developed for differential detection of PEDV, PoRV, and PDCoV. The triplex real-time RT-PCR assay developed in this study could not detect unrelated pathogens and showed satisfactory specificity, sensitivity, repeatability, and reproducibility with a limit of detection (LOD) of 6.0 × 10 1 copies/μL. Sixteen clinical samples were used to compare the results of the commercial RT-PCR kit and the triplex RT-PCR for PEDV, PoRV, and PDCoV detection, and the results were completely consistent. A total of 112 piglet diarrhea samples collected from Jiangsu province were next used to study the local prevalence of PEDV, PoRV, and PDCoV. The positive rates of PEDV, PoRV, and PDCoV detected by the triplex real-time RT-PCR were 51.79% (58/112), 59.82% (67/112), and 2.68% (3/112), respectively. The co-infections of PEDV and PoRV were frequent (26/112, 23.21%), followed by the co-infections of PDCoV and PoRV (2/112, 1.79%). This study established a useful tool for simultaneous differentiation of PEDV, PoRV, and PDCoV in practice and provided valuable information on the prevalence of these diarrhea viral pathogens in Jiangsu province.

Background: Equine coronavirus (ECoV) causes fever, lethargy, anorexia and gastrointestinal signs in horses. There has been limited information about the prevalence and seasonality of ECoV among Thoroughbreds in Japan., Objectives: To understand the epidemiology and to evaluate the potential risk of ECoV infection to the horse industry in Japan., Study Design: Longitudinal., Methods: The virus-neutralisation (VN) test was performed using sera collected three times a year at 4 months intervals from 161 yearlings and at 6-7 months intervals from 181 active racehorses in Japan in 2017-2018, 2018-2019 and 2019-2020. VN titre ≥1:8 was defined as seropositive, and ≥4-fold increase in titres between paired sera was regarded as indicative of infection., Results: The VN test showed that 44.1% (71/161) of yearlings were seropositive in August, when they first entered the yearling farm. The infection rate was significantly higher between August and December (60.9%, 98/161) than between December and the following April (5.6%, 9/161; p = 0.002). Among the racehorses, it was significantly higher between November and the following May (15.5%, 28/181) than between the preceding April/May and November (0%; p = 0.02). The morbidity rates during the estimated periods of viral exposure were 39.2% in the yearlings and 4% in the racehorses. No horses showed any severe clinical signs., Main Limitations: Clinical records did not cover the period during horses' absence from the training centre., Conclusions: ECoV was substantially prevalent in Thoroughbred yearlings and racehorses in Japan, and there was a difference in epizootic pattern between these populations in terms of predominant periods of infection. ECoV infection was considered to be responsible for some of the pyretic cases in the yearlings. However, no diseased horses were severely affected in either population, suggesting that the potential risk of ECoV infection to the horse industry in Japan is low., (© 2022 EVJ Ltd.)

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an emerging swine enteric alphacoronavirus that can cause acute diarrhea, vomiting, dehydration, and death of newborn piglets. In this study, we developed a double-antibody sandwich quantitative enzyme-linked immunosorbent assay (DAS-qELISA) for detection of SADS-CoV by using an anti-SADS-CoV N protein rabbit polyclonal antibody (PAb) and a specific monoclonal antibody (MAb) 6E8 against the SADS-CoV N protein. The PAb was used as the capture antibodies and HRP-labeled 6E8 as the detector antibody. The detection limit of the developed DAS-qELISA assay was 1 ng/mL of purified antigen and 10 1.08 TCID 50 /mL of SADS-CoV, respectively. Specificity assays showed that the developed DAS-qELISA has no cross-reactivity with other swine enteric coronaviruses, such as porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), and porcine deltacoronavirus (PDCoV). Three-day-old piglets were challenged with SADS-CoV and collected anal swab samples which were screened for the presence of SADS-CoV by using DAS-qELISA and reverse transcriptase PCR (RT-PCR). The coincidence rate of the DAS-qELISA and RT-PCR was 93.93%, and the kappa value was 0.85, indicating that DAS-qELISA is a reliable method for applying antigen detection of clinical samples. KEY POINTS: • The first double-antibody sandwich quantitative enzyme-linked immunosorbent assay for detection SADS-CoV infection. • The custom ELISA is useful for controlling the SADS-CoV spread., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The RNA synthesis of porcine epidemic diarrhea virus (PEDV) is a sophisticated process performed by a multilingual viral replication complex, together with cellular factors. A key enzyme of this replication complex is RNA-dependent RNA polymerase (RdRp). However, there is limited knowledge about PEDV RdRp. In our present study, a polyclonal antibody against RdRp was prepared by using a prokaryotic expression vector pET-28a-RdRp to study the function of PEDV RdRp and provide a tool to investigate PEDV pathogenesis. In addition, the enzyme activity and half-life of PEDV RdRp were investigated. The result showed that the polyclonal antibody against PEDV RdRp was successfully prepared and was able to be used to detect PEDV RdRp by immunofluorescence and western blotting. Additionally, enzyme activity of PEDV RdRp reached nearly 2 pmol/μg/h and the half-life of PEDV RdRp was 5.47 h., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Porcine epidemic diarrhea (PED) is a severe contagious intestinal disease caused by the porcine epidemic diarrhea virus (PEDV), which leads to high mortality in piglets. In this study, by analyzing a total of 53 full-length spike genes and COE domain regions of PEDVs, the conserved COE fragment of the spike protein from the dominant strain SC1402 was chosen as the target protein and expressed successfully in Pichia pastoris ( P. pastoris ). Furthermore, an indirect enzyme-linked immunosorbent assay (iELISA) based on the recombinant COE protein was developed for the detection of anti-PEDV antibodies in pig sera. The results showed that under the optimized conditions, the cut-off value of COE-based indirect ELISA (COE-iELISA) was determined to be 0.12. Taking the serum neutralization test as standard, the relative sensitivity of the COE-iELISA was 94.4% and specificity 92.6%. Meanwhile, no cross-reactivity to other porcine pathogens was noted with this assay. The intra-assay and inter-assay coefficients of variation were less than 7%. Moreover, 164 vaccinated serum samples test showed that overall agreement between COE-iELISA and the actual diagnosis result was up to 99.4%. More importantly, the developed iELISA exhibited a 95.08% agreement rate with the commercial ELISA kit (Kappa value = 0.88), which suggested that the expressed COE protein was an effective antigen in serologic tests and the established COE-iELISA is reliable for monitoring PEDV infection in pigs or vaccine effectiveness., Competing Interests: The authors declare no conflicts of interest.

Infectious bronchitis (IB) is a highly contagious viral disease of chickens caused by IB virus (IBV) that can cause substantial economic losses in the poultry industry. IBV variant infections have been continuously reported since the initial description in the 1930s. QX-like IBVs are the predominant circulating genotype globally. A homologous QX vaccine has superior protection efficacy compared with that of other available vaccines, and the combination of Massachusetts (Mass)-like and QX-like strains is being used to combat QX-like IBV infections. Inoculation of embryonated chicken eggs is the standard method for the titration of IBV, and the titer is expressed as 50% egg infectious dose (EID 50 ) . However, this method cannot effectively distinguish or quantify different genotypic strains in a mixture of different viruses, especially in the absence of neutralizing monoclonal antibodies. In this study, quantitative real-time PCR (RT-qPCR) was applied using specific primers for the QX- and Mass-like strains to quantitate IBV infection and for comparison with the conventional virus titration quantitative method. A strong positive correlation was observed between RT-qPCR cycle threshold values and the different EID 50 concentrations. This method was further used to titrate bivalent IB vaccines, and the amount of individual genotype virus was determined based on specific primers. Thus, this RT-qPCR assay may be used as a highly specific, sensitive, and rapid alternative to the EID 50 assay for titering IBVs., Competing Interests: Conflict of interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Feline coronavirus (FCoV) includes two biotypes: feline infectious peritonitis virus (FIPV) and feline enteric coronavirus (FECV). Although both biotypes can infect cats, their pathogenicities differ. The FIPV biotype is more virulent than the FECV biotype and can cause peritonitis or even death in cats, while most FECV biotypes do not cause lesions. Even pathogenic strains of the FECV biotype can cause only mild enteritis because of their very low virulence. This article reviews recent progress in FCoV research with regard to FCoV etiological characteristics; epidemiology; clinical symptoms and pathological changes; pathogenesis; and current diagnosis, prevention and treatment methods. It is hoped that this review will provide a reference for further research on FCoV and other coronaviruses., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Infectious bronchitis virus (IBV) is a coronavirus responsible for major health problems in the poultry industry. New virus strains continue to appear, causing large economic losses. To develop a rapid and accurate new quantitative assay for diagnosis of the virus without DNA extraction, we selected highly specific single-stranded DNA (ssDNA) aptamers with a high affinity to IBV, using the systematic evolution of ligands by exponential enrichment (SELEX) technology for aptamer screening, followed by high-throughput sequencing technology. Two of these aptamers, AptIBV5 and AptIBV2, were used to establish homogenous and solid-phase proximity ligation assays (PLAs). The developed assays were evaluated for their sensitivity and specificity using collected field samples and then compared to the newly developed sandwich enzyme-linked aptamer assay (ELAA) and reverse transcription-quantitative PCR (qRT-PCR), as the gold-standard method. The solid-phase PLA showed a lower limit of detection and a broader dynamic range than the two other assays. The developed technique may serve as an alternative assay for the diagnosis of IBV, with the potential to be extended to the detection of other important animal or human viruses. IMPORTANCE Infectious bronchitis virus (IBV) causes high morbidity and mortality and large economic losses in the poultry industry. The virus has the ability to genetically mutate into new IBV strains, causing devastating disease and outbreaks. To better monitor the emergence of this virus, the development of a rapid and highly sensitive diagnostic method should be implemented. For this, we generated aptamers with high affinity and specificity to the IBV in an ssDNA library. Using two high-affinity aptamers, we developed a sandwich ELAA and a very sensitive aptamer-based proximity ligation assay (PLA). The new assay showed high sensitivity and specificity and was used to detect IBV in farm samples. The PLA was compared to the newly developed sandwich ELAA and qRT-PCR, as the gold-standard technique.