RESUMEN
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.
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Aptámeros de Nucleótidos , Técnicas Biosensibles , Técnicas Electroquímicas , Límite de Detección , SARS-CoV-2 , Aptámeros de Nucleótidos/química , Técnicas Biosensibles/instrumentación , Técnicas Biosensibles/métodos , Técnicas Electroquímicas/métodos , Técnicas Electroquímicas/instrumentación , SARS-CoV-2/aislamiento & purificación , Humanos , Glicoproteína de la Espiga del Coronavirus/análisis , COVID-19/diagnóstico , Diseño de Equipo , Calibración , Betacoronavirus/aislamiento & purificación , Frío , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/virología , PandemiasRESUMEN
BACKGROUND: The conduct of virtual physical examination has provided significant information for the diagnosis during a teleconsultation session, especially during the COVID-19 pandemic, where in-person physical examinations have been greatly compromised. OBJECTIVE: The aim of this scoping review was to provide a comprehensive overview of the available evidence concerning virtual physical examination (VPE) in all healthcare settings during the COVID-19 pandemic. The review focuses on types of VPE, technological and non-technological approaches, patient and clinician experiences, as well as barriers and facilitators of VPE. METHODS: A literature search was conducted across three databases, namely MEDLINE, Embase, and Scopus. Only studies in the English language with primary research data collected from December 2019 to January 2023 were included. A narrative analysis, highlighting patients' and clinicians' experiences, was conducted on the included studies. This scoping review was reported using The PRISMA extension for scoping reviews (PRISMA-ScR) Checklist. RESULTS: A total of 25 articles meeting eligibility criteria were identified. Three major types of VPE included were musculoskeletal, head and neck, and chest exams. Sixteen studies involved specific technological aids, while three studies involved non-technological aids. Patients found VPE helped them to better assess their disease conditions, or aided their clinicians' understanding of their conditions. Clinicians also reported that VPE had provided enough clinically relevant information for decision-making in 2 neurological evaluations. Barriers to conducting VPE included technological challenges, efficacy concerns, confidence level of assistants, as well as patient health conditions, health literacy, safety, and privacy. CONCLUSIONS: Patients found virtual physical examination (VPE) helpful in understanding their own conditions, and clinicians found it useful for better assessing patient's conditions. From the clinicians' point of view, VPE provided sufficient clinically relevant information for decision-making in neurological evaluations. Major barriers identified for VPE included technological issues, patient's health conditions, and their health literacy.
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COVID-19 , Pandemias , Examen Físico , Consulta Remota , SARS-CoV-2 , Humanos , COVID-19/epidemiología , Betacoronavirus , Neumonía Viral/epidemiología , Neumonía Viral/diagnóstico , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/diagnósticoRESUMEN
Porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV) and transmissible gastroenteritis virus (TGEV) are three clinically common coronaviruses causing diarrhea in pigs, with indistinguishable clinical signs and pathological changes. Rapid, portable and reliable differential diagnosis of these three pathogens is crucial for the prompt implementation of appropriate control measures. In this study, we developed a triplex nucleic acid assay that combines reverse transcription recombinase-aided amplification (RT-RAA) with lateral flow assay (LFA) by targeting the most conserved genomic region in the ORF1b genes of PEDV, PDCoV and TGEV. The entire detection process of the triplex RT-RAA-LFA assay included 10-min nucleic acid amplification at 42 °C and 5-min visual LFA readout at room temperature. The assay could specifically differentiate PEDV, PDCoV and TGEV without cross-reaction with any other major swine pathogens. Sensitivity analysis showed that the triplex RT-RAA-LFA assay was able to detect the viral RNA extracted from the spiked fecal samples with the minimum of 1 × 100 TCID50 PEDV, 1 × 104 TCID50 PDCoV, and 1 × 102 TCID50 TGEV per reaction, respectively. Further analysis showed that the 95 % detection limit (LOD) of triplex RT-RAA-LFA for PEDV, PDCoV, and TGEV were 22, 478, and 205 copies of recombinant plasmids per reaction, respectively. The diagnostic performance of triplex RT-RAA-LFA was compared with that of PEDV, PDCoV and TGEV respective commercial real-time RT-PCR kits by testing 114 clinical rectal swab samples in parallel. The total diagnostic coincidence rates of triplex RT-RAA-LFA with real-time RT-PCR kits of PEDV, PDCoV and TGEV were 100 %, 99.1 % and 99.1 %, respectively, and their Kappa values were 1.00, 0.958 and 0.936, respectively. Collectively, the RT-RAA-LFA assay is a powerful tool for the rapid, portable, visual, and synchronous differential diagnosis of PEDV, PDCoV, and TGEV.
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Infecciones por Coronavirus , Deltacoronavirus , Heces , Técnicas de Amplificación de Ácido Nucleico , Virus de la Diarrea Epidémica Porcina , ARN Viral , Sensibilidad y Especificidad , Enfermedades de los Porcinos , Virus de la Gastroenteritis Transmisible , Animales , Porcinos , Virus de la Gastroenteritis Transmisible/aislamiento & purificación , Virus de la Gastroenteritis Transmisible/genética , Virus de la Diarrea Epidémica Porcina/aislamiento & purificación , Virus de la Diarrea Epidémica Porcina/genética , Enfermedades de los Porcinos/diagnóstico , Enfermedades de los Porcinos/virología , ARN Viral/genética , ARN Viral/aislamiento & purificación , Heces/virología , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/virología , Diagnóstico Diferencial , Deltacoronavirus/aislamiento & purificación , Deltacoronavirus/genética , Técnicas de Amplificación de Ácido Nucleico/métodos , Técnicas de Amplificación de Ácido Nucleico/veterinaria , Gastroenteritis Porcina Transmisible/diagnóstico , Gastroenteritis Porcina Transmisible/virología , Técnicas de Diagnóstico Molecular/métodos , Diarrea/virología , Diarrea/veterinaria , Diarrea/diagnósticoRESUMEN
Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an emerging alpha-coronavirus that causes diarrhea in piglets and results in serious economic losses. During SADS-CoV infection, the spike protein (S) serves as a crucial structural component of the virion, interacting with receptors and eliciting the production of neutralizing antibodies. Due to the potential risk of zoonotic transmission of SADS-CoV, the identification and screening of epitopes on the S glycoproteins will be crucial for development of sensitive and specific diagnostic tools. In this study, we immunized BALB/c mice with recombinant SADS-CoV S trimer protein and generated two S1-specific monoclonal antibodies (mAbs): 8D6 and 6E9, which recognized different linear B-cell epitopes. The minimal fragment recognized by mAb 8D6 was mapped to 311NPDQRD316, the minimal fragment recognized by mAb 6E9 was mapped to 492ARFVDRL498. Homology analysis of the regions corresponding to 13 typical strains of different SADS-CoV subtypes showed high conservation of these two epitopes. These findings contribute to a deeper understanding of the structure of the SADS-CoV S protein, which is valuable for vaccine design and holds potential for developing diagnostic methods to detect SADS-CoV.
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Alphacoronavirus , Anticuerpos Monoclonales , Epítopos de Linfocito B , Ratones Endogámicos BALB C , Glicoproteína de la Espiga del Coronavirus , Animales , Glicoproteína de la Espiga del Coronavirus/inmunología , Glicoproteína de la Espiga del Coronavirus/química , Epítopos de Linfocito B/inmunología , Epítopos de Linfocito B/química , Ratones , Porcinos , Anticuerpos Monoclonales/inmunología , Alphacoronavirus/inmunología , Mapeo Epitopo , Infecciones por Coronavirus/inmunología , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/virología , Secuencia de Aminoácidos , Anticuerpos Antivirales/inmunología , Anticuerpos Neutralizantes/inmunologíaRESUMEN
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 103 TCID50/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 TCID50 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.
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Deltacoronavirus , Ensayo de Inmunoadsorción Enzimática , Enfermedades de los Porcinos , Animales , Ensayo de Inmunoadsorción Enzimática/veterinaria , Ensayo de Inmunoadsorción Enzimática/métodos , Porcinos , Enfermedades de los Porcinos/virología , Enfermedades de los Porcinos/diagnóstico , Enfermedades de los Porcinos/inmunología , Deltacoronavirus/aislamiento & purificación , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/virología , Infecciones por Coronavirus/inmunología , Anticuerpos Monoclonales/inmunología , Sensibilidad y Especificidad , Antígenos Virales/análisis , Antígenos Virales/inmunología , Anticuerpos Antivirales/sangreRESUMEN
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.
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Sistemas CRISPR-Cas , Enfermedades de los Bovinos , Coronavirus Bovino , Diarrea , Sensibilidad y Especificidad , Animales , Bovinos , Coronavirus Bovino/aislamiento & purificación , Coronavirus Bovino/genética , Diarrea/veterinaria , Diarrea/virología , Diarrea/diagnóstico , Enfermedades de los Bovinos/virología , Enfermedades de los Bovinos/diagnóstico , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/virología , Infecciones por Coronavirus/diagnósticoRESUMEN
BACKGROUND: Although dromedary camels (Camelus dromedarius) are known to be the host reservoir for MERS-CoV, the virus causing Middle East respiratory syndrome (MERS), zoonotic transmission pathways and camel subpopulations posing highest transmission risk are poorly understood. Extensively managed herds, ubiquitous across the Arabian Peninsula, present a major potential source of primary infection. In this study we aimed to address key knowledge gaps regarding MERS epidemiology among high-risk communities associated with such herds, which is essential information for effective control strategies. METHODS: We did a cross-sectional study between Sept 27, 2017, and Oct 11, 2018, among members of livestock-owning households in southern Jordan (Aqaba East, Aqaba West, Ma'an East, and Ma'an West regions), with random selection of households (house and tent dwellings) from Ministry of Agriculture lists via computer-generated randomisation lists. Household visits were done, with questionnaires administered to household members regarding potential risk factors for MERS-CoV exposure in the past 6 months and blood samples and nasal and oral swabs collected, alongside physical examination data including blood pressure and blood glucose. Children younger than 5 years and individuals without capacity to provide informed consent were excluded. Serum was tested for IgG antibodies to MERS-CoV spike protein (S1 subunit) and nucleocapsid (N) protein with in-house indirect ELISAs, and viral RNA was detected in nasal and oral samples by RT-PCR. The primary outcome was evidence of MERS-CoV exposure (ascertained by seropositive status on S1 or N ELISAs, or a positive swab sample on RT-PCR); secondary outcomes were potential associations between possible risk factors and seropositive status. RT-PCR data were to be presented descriptively. Seroprevalence estimates were obtained at the individual and household levels, and associations between hypothetical risk factors and seropositive status were assessed with use of mixed-effects logistic regression. FINDINGS: We sampled 879 household members (median age 27 years [IQR 16-44]; 471 [54%] males and 408 [46%] females) from 204 households. 72 (8%) household members were seropositive on S1 ELISA (n=25, 3%) or N ELISA (n=52, 6%). No positive nasal or oral swab samples were identified on RT-PCR. Within-household clustering was identified for seropositivity on S1 ELISA (intraclass correlation coefficient 0·88 [0·35-0·96]) but not N ELISA (0·00 [0·00-0·27]). On multivariable analysis, S1 ELISA seropositivity was associated with frequently (≥weekly) interacting with young (age <1 year) camels (adjusted odds ratio [ORadj] 3·85 [95% CI 1·41-11·61], p=0·011), with frequent kissing and petting (ORadj 4·56 [1·55-15·42], p=0·0074), and frequent feeding and watering (ORadj 4·97 [1·80-15·29], p=0·0027) of young camels identified as risk activities. Attending camel races (ORadj 3·73 [1·11-12·47], p=0·029), frequently feeding and watering camels of any age (ORadj 3·18 [1·12-10·84], p=0·040), and elevated blood glucose (>150 mg/dL; ORadj 4·59 [1·23-18·36], p=0·021) were also associated with S1 ELISA seropositivity. Among individuals without history of camel contact, S1 ELISA seropositivity was associated with sharing a household with an S1 ELISA-positive household member (ORadj 8·92 [1·06-92·99], p=0·044), and with sharing a household with an S1 ELISA-positive household member with history of camel contact (ORadj 24·74 [2·72-306·14], p=0·0050). N ELISA seropositivity was associated with age (categorical, p=0·0069), a household owning a young camel (age <18 months; ORadj 1·98 [1·02-4·09], p=0·043), and frequently feeding and watering camels of any age (ORadj 1·98 [1·09-3·69]; p=0·025). INTERPRETATION: The study findings highlight the importance of effective MERS-CoV surveillance and control strategies among camel-owning communities in Jordan and the Arabian Peninsula. Juvenile dromedaries pose increased risk for zoonotic MERS-CoV transmission and should be prioritised for vaccination once such vaccines become available. Among high-risk communities, vaccination strategies should prioritise camel-owning households, particularly individuals engaged in camel husbandry or racing, and household members who are older or diabetic, with evidence to suggest secondary within-household transmission. FUNDING: UK Medical Research Council and US National Institute of Allergy and Infectious Diseases.
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Anticuerpos Antivirales , Camelus , Infecciones por Coronavirus , Ensayo de Inmunoadsorción Enzimática , Composición Familiar , Ganado , Coronavirus del Síndrome Respiratorio de Oriente Medio , Estudios Transversales , Jordania/epidemiología , Coronavirus del Síndrome Respiratorio de Oriente Medio/inmunología , Coronavirus del Síndrome Respiratorio de Oriente Medio/aislamiento & purificación , Humanos , Femenino , Adulto , Factores de Riesgo , Masculino , Animales , Persona de Mediana Edad , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/transmisión , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/sangre , Camelus/virología , Adulto Joven , Adolescente , Anticuerpos Antivirales/sangre , Anticuerpos Antivirales/análisis , Ganado/virología , Niño , Estudios Seroepidemiológicos , Preescolar , AncianoRESUMEN
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.
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Infecciones por Coronavirus , Virus de la Diarrea Epidémica Porcina , Enfermedades de los Porcinos , Virus de la Gastroenteritis Transmisible , Animales , Porcinos , Virus de la Gastroenteritis Transmisible/genética , Virus de la Gastroenteritis Transmisible/aislamiento & purificación , Virus de la Diarrea Epidémica Porcina/aislamiento & purificación , Virus de la Diarrea Epidémica Porcina/genética , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/virología , Infecciones por Coronavirus/epidemiología , Enfermedades de los Porcinos/virología , Enfermedades de los Porcinos/diagnóstico , Estudios Retrospectivos , Gastroenteritis Porcina Transmisible/diagnóstico , Gastroenteritis Porcina Transmisible/virología , Gastroenteritis Porcina Transmisible/epidemiología , Reacción en Cadena de la Polimerasa/métodos , Deltacoronavirus/genética , Deltacoronavirus/aislamiento & purificación , Estados Unidos/epidemiologíaRESUMEN
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.
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COVID-19 , Aprendizaje Profundo , SARS-CoV-2 , Tomografía Computarizada por Rayos X , COVID-19/diagnóstico por imagen , Humanos , Tomografía Computarizada por Rayos X/métodos , SARS-CoV-2/aislamiento & purificación , Neumonía Viral/diagnóstico por imagen , Pandemias , Algoritmos , Neumonía/diagnóstico por imagen , Neumonía/diagnóstico , Infecciones por Coronavirus/diagnóstico por imagen , Infecciones por Coronavirus/diagnóstico , Internet , BetacoronavirusRESUMEN
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.
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COVID-19 , Electrocardiografía , Hipertensión , Pandemias , SARS-CoV-2 , Humanos , COVID-19/mortalidad , COVID-19/complicaciones , COVID-19/epidemiología , Masculino , Persona de Mediana Edad , Indonesia/epidemiología , Femenino , Hipertensión/epidemiología , Hipertensión/mortalidad , Hipertensión/complicaciones , Estudios Transversales , Estudios Retrospectivos , Infecciones por Coronavirus/mortalidad , Infecciones por Coronavirus/complicaciones , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/diagnóstico , Neumonía Viral/mortalidad , Neumonía Viral/complicaciones , Neumonía Viral/epidemiología , Neumonía Viral/diagnóstico , Betacoronavirus , Anciano , Factores de Edad , Adulto , Recuento de Leucocitos , Factores de Riesgo , Recuento de Plaquetas , Mortalidad HospitalariaRESUMEN
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 31â¯% 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 >95â¯% 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.
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COVID-19 , Detección Precoz del Cáncer , Neoplasias , Pandemias , Sistema de Registros , Humanos , COVID-19/epidemiología , COVID-19/diagnóstico , Neoplasias/epidemiología , Neoplasias/diagnóstico , Incidencia , Detección Precoz del Cáncer/estadística & datos numéricos , Detección Precoz del Cáncer/métodos , Femenino , Masculino , SARS-CoV-2/aislamiento & purificación , Australia/epidemiología , Nueva Gales del Sur/epidemiología , Epidemias , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/diagnósticoRESUMEN
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 × 103 TCID50 mL-1 and 3.13 × 102 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.
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Cromatografía de Afinidad , Oro , Nanopartículas del Metal , Virus de la Diarrea Epidémica Porcina , Rotavirus , Oro/química , Virus de la Diarrea Epidémica Porcina/aislamiento & purificación , Rotavirus/aislamiento & purificación , Animales , Nanopartículas del Metal/química , Porcinos , Cromatografía de Afinidad/métodos , Límite de Detección , Infecciones por Rotavirus/diagnóstico , Infecciones por Rotavirus/veterinaria , Infecciones por Rotavirus/virología , Enfermedades de los Porcinos/diagnóstico , Enfermedades de los Porcinos/virología , Inmunoensayo/métodos , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/virología , Infecciones por Coronavirus/veterinariaRESUMEN
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.
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Anticuerpos Antivirales , Infecciones por Birnaviridae , Pollos , Enfermedad de Newcastle , Enfermedades de las Aves de Corral , Vacunas Virales , Animales , Pollos/inmunología , Anticuerpos Antivirales/sangre , Enfermedad de Newcastle/diagnóstico , Enfermedad de Newcastle/inmunología , Infecciones por Birnaviridae/veterinaria , Infecciones por Birnaviridae/inmunología , Infecciones por Birnaviridae/diagnóstico , Infecciones por Birnaviridae/virología , Enfermedades de las Aves de Corral/diagnóstico , Enfermedades de las Aves de Corral/virología , Enfermedades de las Aves de Corral/inmunología , Vacunas Virales/inmunología , Virus de la Bronquitis Infecciosa/inmunología , Virus de la Enfermedad Infecciosa de la Bolsa/inmunología , Virus de la Enfermedad de Newcastle/inmunología , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/inmunología , Infecciones por Coronavirus/virología , Ensayo de Inmunoadsorción Enzimática/veterinaria , Ensayo de Inmunoadsorción Enzimática/métodosRESUMEN
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.
Asunto(s)
Anticuerpos Antivirales , Infecciones por Coronavirus , Ensayo de Inmunoadsorción Enzimática , Enfermedades de los Porcinos , Animales , China/epidemiología , Estudios Seroepidemiológicos , Porcinos , Ensayo de Inmunoadsorción Enzimática/métodos , Anticuerpos Antivirales/sangre , Enfermedades de los Porcinos/epidemiología , Enfermedades de los Porcinos/virología , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/diagnóstico , Inmunoglobulina G/sangre , Alphacoronavirus/inmunología , Alphacoronavirus/genética , Reacciones Cruzadas , Sensibilidad y EspecificidadRESUMEN
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 100.14 TCID50/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.
Asunto(s)
Técnicas Biosensibles , Nanotubos de Carbono , Virus de la Diarrea Epidémica Porcina , Virus de la Diarrea Epidémica Porcina/aislamiento & purificación , Animales , Porcinos , Técnicas Biosensibles/métodos , Técnicas Biosensibles/instrumentación , Nanotubos de Carbono/química , Límite de Detección , Inmunoensayo/métodos , Inmunoensayo/instrumentación , Anticuerpos Monoclonales/inmunología , Transistores Electrónicos , Enfermedades de los Porcinos/diagnóstico , Enfermedades de los Porcinos/virología , Glicoproteína de la Espiga del Coronavirus/inmunología , Glicoproteína de la Espiga del Coronavirus/análisis , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/virología , Anticuerpos Antivirales/inmunología , Diseño de EquipoRESUMEN
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 (NT50 = 1384, NT80 = 384), we determined the IC50 and IC80 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.
Asunto(s)
Anticuerpos Neutralizantes , Anticuerpos Antivirales , Coronavirus del Síndrome Respiratorio de Oriente Medio , Pruebas de Neutralización , Coronavirus del Síndrome Respiratorio de Oriente Medio/inmunología , Humanos , Pruebas de Neutralización/métodos , Anticuerpos Neutralizantes/sangre , Anticuerpos Neutralizantes/inmunología , Anticuerpos Antivirales/sangre , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/inmunología , Infecciones por Coronavirus/diagnóstico , Animales , Concentración 50 Inhibidora , Sensibilidad y EspecificidadRESUMEN
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.
Asunto(s)
COVID-19 , Aprendizaje Profundo , Redes Neurales de la Computación , SARS-CoV-2 , COVID-19/diagnóstico por imagen , COVID-19/virología , COVID-19/diagnóstico , Humanos , SARS-CoV-2/aislamiento & purificación , Radiografía Torácica/métodos , Pandemias , Neumonía Viral/diagnóstico por imagen , Neumonía Viral/virología , Neumonía Viral/diagnóstico , Infecciones por Coronavirus/diagnóstico por imagen , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/virología , Betacoronavirus/aislamiento & purificación , Sensibilidad y Especificidad , Tomografía Computarizada por Rayos X/métodosRESUMEN
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.
Asunto(s)
COVID-19 , SARS-CoV-2 , Humanos , COVID-19/diagnóstico , COVID-19/orina , COVID-19/virología , SARS-CoV-2/aislamiento & purificación , Pandemias , Masculino , Neumonía Viral/diagnóstico , Neumonía Viral/orina , Neumonía Viral/virología , Persona de Mediana Edad , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/orina , Femenino , Betacoronavirus/aislamiento & purificación , Espectrometría de Masas/métodos , Adulto , Metabolómica/métodos , Anciano , Aprendizaje AutomáticoRESUMEN
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 39â within 20â¯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 100â¯%. 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.
Asunto(s)
Pollos , Infecciones por Coronavirus , Virus de la Bronquitis Infecciosa , Técnicas de Amplificación de Ácido Nucleico , Enfermedades de las Aves de Corral , Recombinasas , Sensibilidad y Especificidad , Virus de la Bronquitis Infecciosa/genética , Virus de la Bronquitis Infecciosa/aislamiento & purificación , Animales , Pollos/virología , Enfermedades de las Aves de Corral/virología , Enfermedades de las Aves de Corral/diagnóstico , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/veterinaria , Infecciones por Coronavirus/virología , Recombinasas/metabolismo , Recombinasas/genética , Reproducibilidad de los Resultados , Técnicas de Amplificación de Ácido Nucleico/métodos , Técnicas de Amplificación de Ácido Nucleico/veterinaria , Cartilla de ADN/genética , Reacción en Cadena en Tiempo Real de la Polimerasa/métodos , Reacción en Cadena en Tiempo Real de la Polimerasa/veterinaria , Fluorescencia , Técnicas de Diagnóstico Molecular/métodosRESUMEN
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.