Respiratory Infectious Diseases Research Articles

Thiolated chitosan encapsulation constituted mucoadhesive nanovaccine confers broad protection against divergent influenza A viruses

Influenza A virus (IAV) poses a significant threat to human and animal health, necessitating the development of universal influenza vaccines that can effectively activate mucosal immunity. Intranasal immunization has attracted significant attention due to its capacity to induce triple immune responses, including mucosal secretory IgA. However, inducing mucosal immunity through vaccination is challenging due to the self-cleansing nature of the mucosal surface. Thiolated chitosan (TCS) were explored for mucosal vaccine delivery, capitalizing on biocompatibility and bioadhesive properties of chitosan, with thiol modification enhancing mucoadhesive capability. The focus was on developing a universal nanovaccine by utilizing TCS-encapsulated virus-like particles displaying conserved B-cell and T-cell epitopes from M2e and NP proteins of IAV. The optimal conditions for nanoparticle formation were investigated by adjusting the thiol groups content of TCS and the amount of sodium tripolyphosphate. The nanovaccine induced robust immune responses and provided complete protection against IAVs from different species following intranasal immunization. The broad protective effect of nanovaccines can be attributed to the synergistic effect of antibodies and T cells. This study developed a universal intranasal nanovaccine and demonstrated the potential of TCS in the development of mucosal vaccines for respiratory infectious diseases.

Does a prior diagnosis of infectious disease confer an increased risk of latent autoimmune diabetes in adults?

Infections are proposed risk factors for type 1 diabetes in children. We examined whether a diagnosis of infectious disease also confers an increased risk of latent autoimmune diabetes in adults (LADA). We used data from a population-based Swedish case-control study with incident cases of LADA (n=597) and matched controls (n=2386). The history of infectious disease was ascertained through national and regional patient registers. We estimated adjusted odds ratios (OR) with 95% confidence intervals for ≥1 respiratory (any/upper/lower), gastrointestinal, herpetic, other or any infectious disease episode, or separately, for 1 and ≥2 infectious disease episodes, within 0-1, 1-3, 3-5 and 5-10years before LADA diagnosis/matching. Stratified analyses were performed on the basis of HLA risk genotypes and Glutamic acid decarboxylase antibodies (GADA) levels. Individuals who developed LADA did not have a higher prevalence of infectious disease 1-10years before diabetes diagnosis. For example, OR was estimated at 0.87 (0.66, 1.14) for any versus no respiratory infectious disease within 1-3years. Similar results were seen for LADA with high-risk HLA genotypes (OR 0.95 [0.64, 1.42]) or high GADA levels (OR 1.10 [0.79, 1.55]), ≥2 episodes (OR 0.89 [0.56, 1.40]), and in infections treated using antibiotics (OR 1.03 [0.73, 1.45]). The only significant association was observed with lower respiratory disease the year preceding LADA diagnosis (OR 1.67 [1.06, 2.64]). Our findings do not support the idea that exposure to infections increases the risk of LADA. A higher prevalence of respiratory infection in the year before LADA diagnosis could reflect increased susceptibility to infections due to hyperglycemia.

Assessment of mask associated dry eye among doctors and medical students at a tertiary care centre

When faced with outbreaks of infectious respiratory diseases in the past, the use of face masks has often been mandated. The world collectively experienced the devastating COVID-19 pandemic, which originated in Wuhan, China, in October 2019 and rapidly spread across the globe. Wearing face masks became the primary defense against infection. However, during this period, many individuals reported experiencing symptoms of dry eye. This study aimed to investigate the correlation between mask usage and dryness among healthcare workers.A hospital-based cross-sectional study was conducted using an online survey, which included a modified version of the Ocular Surface Disease Index (OSDI) questionnaire. Electronic consent was obtained to gather information about the occurrence of dryness while wearing masks.Among the 284 participants, females exhibited a higher OSDI score (12.5) compared to males. Notably, individuals with pre-existing dry eye conditions had a significantly higher OSDI score (23.96) when wearing face masks. Across different age groups, no significant variations were observed. In terms of the duration of face mask use, those who wore masks for less than 4 hours and more than 6 hours had an OSDI score of 12.5, whereas individuals wearing masks for 4 to 6 hours had a score of 8.3.Wearing face masks may pose a risk for dryness, particularly among females, and can exacerbate dryness symptoms in individuals with pre-existing dry eye conditions.

Development of a Large-Scale Pathogen Screening Test for the Biosafety Evaluation of Canine Mesenchymal Stem Cells

BackgroundThe action of mesenchymal stem cells (MSCs) is the subject of intense research in the field of regenerative medicine, including their potential use in companion animals, such as dogs. To ensure the safety of canine MSC batches for their application in regenerative medicine, a quality control test must be conducted in accordance with Good Manufacturing Practices (GMP). Based on guidance provided by the European Medicines Agency, this study aimed to develop and validate a highly sensitive and robust, nucleic acid-based test panel for the detection of various canine pathogens. Analytical sensitivity, specificity, amplification efficiency, and linearity were evaluated to ensure robust assessment. Additionally, viable spike-in controls were used to control for optimal nucleic acid extraction. The conventional PCR-based and real-time PCR-based pathogen assays were evaluated in a real-life setting, by direct testing MSC batches.ResultsThe established nucleic acid-based assays displayed remarkable sensitivity, detecting 100–1 copies/reaction of template DNA. They also exhibited high specificity and efficiency. Moreover, highly effective nucleic acid isolation was confirmed by the sensitive detection of spike-in controls. The detection capacity of our optimized and validated methods was determined by direct pathogen testing of nine MSC batches that displayed unusual phenotypes, such as reduced cell division or other deviating characteristics. Among these MCS batches of uncertain purity, only one tested negative for all pathogens. The direct testing of these samples yielded positive results for important canine pathogens, including tick-borne disease-associated species and viral members of the canine infectious respiratory disease complex (CIRDC). Notably, samples positive for the etiological agents responsible for enteritis (CPV), leptospirosis (Leptospira interrogans), and neosporosis (Neospora caninum) were also identified. Furthermore, we conducted biosafety evaluation of 12 MSC batches intended for therapeutic application. Eleven MSC batches were found to be free of extraneous agents, and only one tested positive for a specific pathogen, namely, canine parvovirus.ConclusionIn this study, we established and validated reliable, highly sensitive, and accurate nucleic acid-based testing methods for a broad spectrum of canine pathogens.

Development of a one-step multiplex (RT)-PCR for simultaneous detection of virus-induced respiratory disease complex in dogs in Vietnam

Canine infectious respiratory disease (CIRD) viruses, particularly canine distemper virus (CDV), canine adenovirus type 2 (CAV-2), and canine parainfluenza virus (CPIV), are the primary agents responsible for respiratory diseases in dogs. A dog can be infected with a single or multiple viruses with similar clinical signs. Although CIRD is globally prevalent in dogs, investigation into the causative viruses in Vietnam remains limited. This study aims to identify the presence of CIRD virus(es) in dogs via molecular detection. Three primer sets were newly designed and applied into (RT)-PCR reaction to detect viral genes of CDV, CAV-2, and CPIV in a commercial vaccine (Vanguard® Plus 5/L, Zoetis, USA). Both simplex and multiplex (RT)-PCR reactions using the three primer sets could detect the presence of CAV-2, CDV, and CPIV in the vaccine sample. Subsequently, the applicability of the one-step multiplex (RT)-PCR was demonstrated to test for 27 clinical nasal swab samples collected from dogs suspected of having CIRD. The results showed that our (RT)-PCR could detect CIRD virus(es) in all tested clinical samples. PCR amplicons for each representative CAV-2, CDV, and CPIV were selected for sequencing and showed high genetic similarity to respective field viruses. In conclusion, this study successfully developed a one-step multiplex (RT)-PCR reaction to detect and differentiate causative viruses of CIRD in dogs.

Inhaled SARS-CoV-2 vaccine for single-dose dry powder aerosol immunization.

The COVID-19 pandemic has fostered major advances in vaccination technologies1-4; however, there are urgent needs for vaccines that induce mucosal immune responses and for single-dose, non-invasive administration4-6. Here we develop an inhalable, single-dose, dry powder aerosol SARS-CoV-2 vaccine that induces potent systemic and mucosal immune responses. The vaccine encapsulates assembled nanoparticles comprising proteinaceous cholera toxin B subunits displaying the SARS-CoV-2 RBD antigen within microcapsules of optimal aerodynamic size, and this unique nano-micro coupled structure supports efficient alveoli delivery, sustained antigen release and antigen-presenting cell uptake, which are favourable features for the induction of immune responses. Moreover, this vaccine induces strong production of IgG and IgA, as well as a local T cell response, collectively conferring effective protection against SARS-CoV-2 in mice, hamsters and nonhuman primates. Finally, we also demonstrate a mosaic iteration of the vaccine that co-displays ancestral and Omicron antigens, extending the breadth of antibody response against co-circulating strains and transmission of the Omicron variant. These findings support the use of this inhaled vaccine as a promising multivalent platform for fighting COVID-19 and other respiratory infectious diseases.

Association between COVID-19 and outstanding academic performance at a Spanish university

BackgroundSARS-CoV-2 is the causative agent of COVID-19 identified in December 2019, an acute infectious respiratory disease that can cause persistent neurological and musculoskeletal symptoms such as headache, fatigue, myalgias difficulty concentrating, among others including acute cerebrovascular disease with a prevalence of 1–35%. The aim of this study is to evaluate the impact of COVID-19 in undergraduate students on their academic performance as an indicator of their intellectual ability and performance in a university that maintained 100% face-to-face teaching during the 2020–2021 academic year.MethodsA total of 7,039 undergraduate students were analyzed in a prospective cohort study at the University of Navarra. A questionnaire including sociodemographic and behavioral questions was sent. PCRs were performed throughout the academic year for the diagnosis of SARS-CoV-2 infection and students’ academic results were provided by the academic center, adjusted descriptive and multivariate models were performed to assess the association.ResultsA total of 658 (9.3%) participants were diagnosed with COVID-19, almost 4.0% of them achieved outstanding academic results, while uninfected students did so in 7.3%. SARS-CoV-2 infection was associated with a significant decrease in having outstanding academic results (OR = 0.57; 95% CI: 0.38–0.86).ConclusionHaving COVID-19 disease, decreased academic performance in undergraduate students. Therefore, it is necessary to prevent infection even in the youngest sections of the population.

A noval pulmonary function evaluation method based on ResNet50 + SVR model and cough

Traditionally, the clinical evaluation of respiratory diseases was pulmonary function testing, which can be used for the detection of severity and prognosis through pulmonary function parameters. However, this method is limited by the complex process, which is impossible for patients to monitor daily. In order to evaluate pulmonary function parameters conveniently with less time and location restrictions, cough sound is the substitute parameter. In this paper, 371 cough sounds segments from 150 individuals were separated into 309 and 62 as the training and test samples. Short-time Fourier transform (STFT) was applied to transform cough sound into spectrogram, and ResNet50 model was used to extract 2048-dimensional features. Through support vector regression (SVR) model with biological attributes, the data were regressed with pulmonary function parameters, FEV1, FEV1%, FEV1/FVC, FVC, FVC%, and the performance of this models was evaluated with fivefold cross-validation. Combines with deep learning and machine learning technologies, the better results in the case of small samples were achieved. Using the coefficient of determination (R2), the ResNet50 + SVR model shows best performance in five basic pulmonary function parameters evaluation as FEV1(0.94), FEV1%(0.84), FEV1/FVC(0.68), FVC(0.92), and FVC%(0.72). This ResNet50 + SVR hybrid model shows excellent evaluation of pulmonary function parameters during coughing, making it possible to realize a simple and rapid evaluation for pneumonia patients. The technology implemented in this paper is beneficial in judge the patient's condition, realize early screening of respiratory diseases, evaluate postoperative disease changes and detect respiratory infectious diseases without time and location restrictions.

Nitric oxide-assisted mucus-walking zwitterionic nanocomplexes for synergistic treatment of severe respiratory infectious disease

Among patients who suffer from lung-related disability, acute respiratory distress syndrome (ARDS) is one of the diseases with the significant mortality rate and the main cause is the interference in pulmonary drug delivery by accumulated bronchoalveolar lavage fluid (BALF) in the alveolar region. Here, a zwitterion-functionalized multi-drug nanocomplex (ZnC) capable of anti-mucociliary clearance was synthesized. Additionally, nitric oxide (NO) was functionalized with ZnC to fuel the mobility in the BALF through its role as a nanomotor as well as anti-inflammation. Subsequently, dexamethasone (Dex) was loaded and final product of anti-inflammatory mucus permeator (AIM) was introduced. By in situ tracking the AIM within the mucus-rich environment, the fueled mobility by NO and zwitterion was demonstrated. Notably, when AIM was inhaled by the in vivo ARDS model, there was an increase in the anti-inflammation effect due to the presence of ZnC as well as the synergy between NO and Dex, which recovered the pulmonary function of the model and increased survival rate.

Ambient atmospheric PM worsens mouse lung injury induced by influenza A virus through lysosomal dysfunction

BackgroundParticulate matter (PM) air pollution poses a significant risk to respiratory health and is especially linked with various infectious respiratory diseases such as influenza. Our previous studies have shown that H5N1 virus infection could induce alveolar epithelial A549 cell death by enhancing lysosomal dysfunction. This study aims to investigate the mechanisms underlying the effects of PM on influenza virus infections, with a particular focus on lysosomal dysfunction.ResultsHere, we showed that PM nanoparticles such as silica and alumina could induce A549 cell death and lysosomal dysfunction, and degradation of lysosomal-associated membrane proteins (LAMPs), which are the most abundant lysosomal membrane proteins. The knockdown of LAMPs with siRNA facilitated cellular entry of both H1N1 and H5N1 influenza viruses. Furthermore, we demonstrated that silica and alumina synergistically increased alveolar epithelial cell death induced by H1N1 and H5N1 influenza viruses by enhancing lysosomal dysfunction via LAMP degradation and promoting viral entry. In vivo, lung injury in the H5N1 virus infection-induced model was exacerbated by pre-exposure to silica, resulting in an increase in the wet/dry ratio and histopathological score.ConclusionsOur findings reveal the mechanism underlying the synergistic effect of nanoparticles in the early stage of the influenza virus life cycle and may explain the increased number of respiratory patients during periods of air pollution.

Impact of Media Awareness and Use of Face-Masks on Infectious Respiratory Disease

Infectious respiratory diseases have been a threat to our lives and livelihoods. Communities with a higher population density ultimately are at a higher risk of a rapid spread of infectious disease once they occur. Mathematical models have extensively been used to analyse the impact of several mitigation measures to the transmission of infectious diseases. The focus of this study is to determine the impact of media awareness, use of face-masks alongside quarantine and isolation on the transmission dynamics of a respiratory infection where there is no available vaccination or treatment plan. The model is based on a system of deterministic ordinary differential equations (ODE’s). By the use of the next generation matrix (NGM), the basic reproduction is determined. The local stability analysis analysis of the disease free equilibrium (DFE) is obtained by the trace-determinant approach while it’s global stability was determined by the use of the Lyapunov-Krasovskii method. It was established that the local DFE was asymptotically stable while it was unstable globally implying that with application of this intended strategies, the transmission of the disease could be lowered but not eradicated. The importance of media awareness to any campaign towards reduction of transmission is paramount. Effort should be geared towards the public having correct information on a given disease. The impact of face mask is dependent on the efficacy of the face - mask and its compliant and consistent use, these two factors are multiplicative. Numerical simulations were done by the use of Python software and it was established that if quarantine rate and the isolation rate was to be maximised then the disease would be curtailed. The results of this study gives valuable information on the intervention strategies to be applied by the public heath officials.

Incidence Among Infants in Moscow Including the COVID-19 Statistics

The study presents the data on incidence among infants in Moscow. The author analyzed the indicators of overall incidence, the characteristics of disease distribution, and the level of follow-up care in children of the given age group. The data was obtained from the open sources of Federal State Statistics Service of the Russian Federation (Rosstat) and from the Federal Statistical Observation Form No. 12 “On the number of diseases registered in patients residing in the service area of a medical organization” from 2016 to 2022.
 The author evaluated the impact of COVID-19 pandemic on the pre-COVID incidence trends in general and by specific disease categories, as well as on the distribution of diseases common to infants. The results show a decrease in overall incidence and specifically of infectious diseases, respiratory diseases, injuries, poisonings, and other external causes in all age groups. While overall incidence was decreasing between 2020 and 2022, the number of cases requiring the follow-up care was constantly growing. The absence of herd immunity and newborn vaccination due to the age characteristics of the group has led to an explosion of COVID-19 cases in the last three years. The study also revealed the variation in indicators for certain diseases, which warrants further investigation of the dynamics in these nosological groups.

Genome sequencing reveals molecular epidemiological characteristics and new recombinations of adenovirus in Beijing, China, 2014-2019.

To investigate the molecular epidemiological characteristics and genetic variations of human adenovirus (HAdV) in acute respiratory tract infections in Beijing. Whole-genome sequencing and phylogenetic analyses were performed for 83 strains of HAdV with different types in Beijing from 2014 to 2019. The clinical characteristics of HAdV infection were analyzed statistically. HAdV-B was divided into four genotypes, including B3 (n = 11), B7 (n = 13), B14 (n = 4), and B55 (n = 2). HAdV-C was divided into three genotypes, including C1 (n = 14), C2 (n = 13), and C5 (n = 10). In HAdV-C, nine recombinant adenovirus strains were identified in type 1, and seven recombinant strains were found in type 2. In type 1, we found three newly emerged intraspecific recombinant strains (A47, A48, and A52) collected in 2017, 2018, and 2019, respectively. In addition, the previously reported recombinant strains of HAdV-C1 showed more severe disease than other strains of HAdV-C, causing severe community-acquired pneumonia in both the elderly and children. Continuous population-wide molecular epidemiological surveillance of HAdV is essential for the prevention and control of respiratory infectious diseases.

Geographical characteristics and influencing factors of the influenza epidemic in Hubei, China, from 2009 to 2019.

Influenza is an acute respiratory infectious disease that commonly affects people and has an important impact on public health. Based on influenza incidence data from 103 counties in Hubei Province from 2009 to 2019, this study used time series analysis and geospatial analysis to analyze the spatial and temporal distribution characteristics of the influenza epidemic and its influencing factors. The results reveal significant spatial-temporal clustering of the influenza epidemic in Hubei Province. Influenza mainly occurs in winter and spring of each year (from December to March of the next year), with the highest incidence rate observed in 2019 and an overall upward trend in recent years. There were significant spatial and urban-rural differences in influenza prevalence in Hubei Province, with the eastern region being more seriously affected than the central and western regions, and the urban regions more seriously affected than the rural region. Hubei's influenza epidemic showed an obvious spatial agglomeration distribution from 2009 to 2019, with the strongest clustering in winter. The hot spot areas of interannual variation in influenza were mainly distributed in eastern and western Hubei, and the cold spot areas were distributed in north-central Hubei. In addition, the cold hot spot areas of influenza epidemics varied from season to season. The seasonal changes in influenza prevalence in Hubei Province are mainly governed by meteorological factors, such as temperature, sunshine, precipitation, humidity, and wind speed. Low temperature, less rain, less sunshine, low wind speed and humid weather will increase the risk of contracting influenza; the interannual changes and spatial differentiation of influenza are mainly influenced by socioeconomic factors, such as road density, number of health technicians per 1,000 population, urbanization rate and population density. The strength of influenza's influencing factors in Hubei Province exhibits significant spatial variation, but in general, the formation of spatial variation of influenza in Hubei Province is still the result of the joint action of socioeconomic factors and natural meteorological factors. Understanding the temporal and spatial distribution characteristics of influenza in Hubei Province and its influencing factors can provide a reasonable decision-making basis for influenza prevention and control and public health development in Hubei Province and can also effectively improve the scientific understanding of the public with respect to influenza and other respiratory infectious diseases to reduce the influenza incidence, which also has reference significance for the prevention and control of influenza and other respiratory infectious diseases in other countries or regions.

The risk of aerosol transmission of respiratory infectious diseases in the isolation ward

The risk of aerosol transmission of respiratory infectious diseases in the isolation ward

Risk evaluation of venue types and human behaviors of COVID-19 outbreaks in public indoor environments: A systematic review and meta-analysis

Despite increasing vaccination rates, the incidence of breakthrough infections with COVID-19 has increased due to the continued emergence of new variants of the SARS-CoV-2 coronavirus. Therefore, Non-pharmaceutical interventions remain the most effective measures for coping with the ever-changing pandemic. The lifting of compulsory interventions has made individuals primary responsibility for their own health, which highlights the importance of increasing awareness of the infection risk from the environment in which they live and their individual behaviors. We systematically searched PubMed, Web of Science, ScienceDirect, and Scopus on April 17, 2023, for all studies reporting COVID-19 outbreaks in public indoor venues. The study outcome was the attack rate. A total of 42 studies, which included cross-sectional studies, cohort studies, and case studies, reporting data on 1951 confirmed cases in 64 COVID-19 outbreaks satisfied the meta-analysis and were included in the review. A random-effect model was used in the meta-analysis, and subgroup analyses were conducted to investigate factors affecting attack rates. We found a strong level of evidence (p < 0.01) supporting a higher pooled attack rate in recreation-related venues (0.44, 95% CI: 0.30 to 0.60) than in work-related venues (0.21, 95% CI: 0.16 to 0.27). Compared to those outbreaks without that, outbreaks with high-intensity exercise, vocalization, contact behavior, or close body proximity had a higher attack rate of 0.51, 0.55, 0.33, and 0.39, respectively. Further studies suggest that different attack rates across different types of settings may be the result of heterogeneity in exposed people's behaviors. There were significant heterogeneities that may limit the interpretation of connections between influencing factors and outbreak outcomes. The identification of key behaviors that may contribute to transmission risk, and their correlation with venue type, has important implications for the development of future public health interventions and individual prevention strategies for respiratory infectious diseases such as COVID-19.

Predicting the transmission trend of respiratory viruses in new regions via geospatial similarity learning

The outbreak and spread of COVID-19 remind us again of the devastating attack that human-to-human transmitted respiratory infectious diseases (H-HRIDs) bring to global economics and public health. Predicting the trend of H-HRIDs yields important suggestions for making response strategies. Existing methods predict the future trend of H-HRIDs based on the prophase epidemiological data. However, it is also crucial to predict the potential outbreak trend of H-HRIDs in regions without prophase epidemiological data based on those with epidemiological data available. This prediction can provide constructive pharmaceutical strategies and non-pharmaceutical interventions such as pre-allocating the limited preventions to regions with different potential trends, especially at the early stage of an H-HRID. In this paper, transform the problem of predicting the early-stage trend of an H-HRID in new regions without prophase epidemiological data into the problem of learning regions’ geospatial features via a Contrastive learning-based Hierarchical Graph Convolutional Neural Network (CHGCN). Specifically, CHGCN first generates training data from regions with epidemiological data available via a Relaxed Graph Edit Distance (RGED) algorithm. CHGCN then uses a constructive learning schema to learn region embeddings, where regions with similar geospatial features and H-HRID trends exhibit similar embeddings. Once trained, CHGCN searches for the region with epidemiological data available that has the highest embedding similarity to the given query region without prophase epidemiological data, so as to achieve early-stage H-HRID trend prediction for the query region. Experimental results on COVID-19 demonstrate that the proposed CHGCN achieves state-of-the-art performance in predicting the early-stage trend of H-HRIDs, compared with the baselines.

Epidemiologic investigation and genetic characterization of canine respiratory coronavirus in the Southeastern United States.

Canine respiratory coronavirus (CRCoV) is one of the main causative agents of canine infectious respiratory disease (CIRD), an illness whose epidemiology is poorly understood. We assessed the prevalence, risk factors, and genetic characterization of CRCoV in privately owned dogs in the Southeastern United States. We PCR-screened 189 nasal swabs from dogs with and without CIRD clinical signs for 9 CIRD-related pathogens, including CRCoV; 14% of dogs, all diagnosed with CIRD, were positive for CRCoV, with a significantly higher rate of cases in younger dogs and during warmer weather. Notably, the presence of CRCoV, alone or in coinfection with other CIRD pathogens, was statistically associated with a worse prognosis. We estimated a CRCoV seroprevalence of 23.7% retrospectively from 540 serum samples, with no statistical association to dog age, sex, or season, but with a significantly higher presence in urban counties. Additionally, the genomes of 6 CRCoVs were obtained from positive samples using an in-house developed targeted amplicon-based approach specific to CRCoV. Subsequent phylogeny clustered their genomes in 2 distinct genomic groups, with most isolates sharing a higher similarity with CRCoVs from Sweden and only 1 more closely related to CRCoVs from Asia. We provide new insights into CIRD and CRCoV epidemiology in the Southeastern United States and further support the association of CRCoV with more severe cases of CIRD. Additionally, we developed and successfully tested a new amplicon-based approach for whole-genome sequencing of CRCoV that can be used to further investigate the genetic diversity within CRCoVs.

Predominance of Canine Parainfluenza Virus and Mycoplasma in Canine Infectious Respiratory Disease Complex in Dogs.

Canine infectious respiratory disease complex (CIRDC) is caused by different viruses and bacteria. Viruses associated with CIRDC include canine adenovirus type 2 (CAV-2), canine distemper virus (CDV), canine influenza virus (CIV), canine herpesvirus type 1 (CHV-1), canine respiratory coronavirus (CRCoV), and canine parainfluenza virus (CPIV). Bacteria associated with CIRDC include Bordetella bronchiseptica, Streptococcus equi subspecies zooepidemicus (S. zooepidemicus), and Mycoplasma spp. The present study examined the prevalence of CIRDC pathogens in specimens received by a Veterinary Diagnostic Laboratory in Georgia, USA., from 2018 to 2022. Out of 459 cases, viral agents were detected in 34% of cases and bacterial agents were detected in 58% of cases. A single pathogen was detected in 31% of cases, while two or more pathogens were identified in 24% of cases. The percentages of viral agents identified were CAV-2 (4%), CDV (3%), CPIV (16%), CRCoV (7%), and CIV (2%). The percentages of bacterial agents were B. bronchiseptica (10%), Mycoplasma canis (24%), Mycoplasma cynos (21%), and S. zooepidemicus (2%). Over the five-year period, the positive cases ranged from 2-4% for CAV-2, 1-7% for CDV, 1-4% for CHV-1, 9-22% for CPIV, 4-13% for CRCoV, and 1-4% for CIV. Overall, the most prevalent pathogens associated with CIRDC were CPIV, M. canis, and M. cynos.

Genomic surveillance of SARS-CoV-2 in Weihai, China, march 2022 to march 2023.

COVID-19 is an acute respiratory infectious disease caused by SARS-CoV-2. It was first reported in Wuhan, China in December 2019 and rapidly spread globally in early 2020, triggering a global pandemic. In December 2022, China adjusted the dynamic COVID-zero strategy that lasted for three years. The number of positive cases in China increased rapidly in the short term. Weihai was also affected during this period. We conducted genomic surveillance of SARS-CoV-2 variants in Weihai during this period, hoping to understand the changes in the genomic characteristics of SARS-CoV-2 before and after the adjustment of the epidemic policy. In this study,we collected SARS-CoV-2 positive samples from March 2022 to March 2023 in Weihai and performed SARS-CoV-2 whole genome sequencing on these samples using next-generation sequencing technology. we obtained a total of 704 SARS-CoV-2 whole genome sequences, and selected 581 high-quality sequences for further analysis. The analysis results showed that from March 2022 to November 2022, before the adjustment of epidemic policy, the COVID-19 cases in Weihai were mainly from four local clusters,which were caused by four variants, including BA.2,BA.1.1,P.1.15 and BA.5.2.1. Phylogenetic analysis showed that: In the same cluster,the sequences between each other were highly homologous, and the whole genome sequence were almost identical. After December 2022, the epidemic policy was adjusted, BF.7 and BA.5.2 became the dominant variants in Weihai, consistent with the main domestic strains in China during the same period. Phylodynamic analysis showed that BF.7 and BA.5.2 had a large amount of genetic diversities in December, and the effective population size of BF.7 and BA.5.2 also showed explosive growth in December. In conclusion, we reported the composition and dynamic trend of SARS-CoV-2 variants in Weihai from March 2022 to March 2023. We found that there have been significant changes in the variants and expansion patterns of SARS-CoV-2 before and after the adjustment of epidemic policies. But the dominant variants in Weihai were the same as the SARS-CoV-2 variants circulating globally at the same time and we found no persistently dominant variants or new lineages during this period.