Identification of domestic cat hepadnavirus from a cat blood sample in Japan

The hepatitis B virus (Hepadnaviridae) induces chronic hepatitis and hepatic cancer in humans. A novel domestic cat hepadnavirus (DCH) was recently identified in several countries, however, the DCH infection status of cats in Japan is unknown. Therefore, we investigated the DCH infection rate of 139 cat samples collected in Japan. We identified one positive blood sample (0.78%) from a 17-year-old female cat with chronically elevated alanine aminotransferase. Phylogenetic analysis demonstrated that the DCH strain identified in this study is genetically distinct from strains in other countries. Further investigations are required to elucidate the evolution of DCH and the impact of DCH infection on hepatic diseases in domestic cats.

Low Positive Rates for HBeAg and HBV DNA in Rheumatoid Arthritis Patients—A Case-Control Study

Background The rates of hepatitis B virus (HBV) infection in rheumatoid arthritis (RA) patients were controversial when considering the reported outcomes. It was speculated that HBV infection status altered after suffering from RA, and variations over HBV infection rates became apparent. Methods To compare the positive proportions of hepatitis B e antigen (HBeAg) and HBV DNA, a case-control study was performed between the 27 chronic hepatitis B (CHB) patients with RA and the 108 age-and gender-matched CHB patients. In addition, the positive rates of hepatitis B surface antigen (HBsAg) and hepatitis B core antibody (anti-HBc) were surveyed among the 892 RA patients. Results Compared to the CHB patients, the CHB patients with RA exhibited lower rates of HBeAg positivity (11.1% vs. 35.2%, P = 0.003), HBV DNA positivity (37.0% vs. 63.9%, P = 0.007) and ALT elevation (11.1% vs. 35.2%, P = 0.024). In the 892 RA patients, the prevalence of HBsAg (3.0%) was lower than that of China national data (7.2%), whereas the anti-HBc positive rate of 44.6% was higher than that of 34.1%. Conclusion HBV infection status altered after suffering from RA. Compared to the matched CHB patients, low positive proportions of HBeAg and HBV DNA were observed for CHB patients with RA.

Effect of Helicobacter pylori infection on malignancy of undifferentiated-type gastric cancer

Background Although almost all cases of gastric cancer are caused by Helicobacter pylori (HP) infection, there are some rare exceptions. Furthermore, the clinicopathological characteristics of gastric cancer may differ depending on HP infection status. This study aimed to determine the clinicopathological characteristics of undifferentiated-type gastric cancer (UD-GC) according to HP status. Methods The study involved 83 patients with UD-GC who were selected from 1559 patients with gastric cancer who underwent endoscopic resection at our hospital and whose HP infection status was confirmed. Clinicopathological characteristics were evaluated according to HP status (eradicated, n = 28; infected, n = 32; not infected, n = 23). Results In patients without HP infection, UD-GCs were < 20 mm and intramucosal with no vascular invasion. In patients with eradicated HP, there was no correlation between development of UD-GC and time since eradication. Nine of twelve patients with a tumor detected ≥ 5 years after eradication had undergone yearly endoscopy. Submucosal invasion was observed in two of four patients and lymphovascular invasion in three of four patients whose UD-GC was detected ≥ 10 years after eradication. There was no significant between-group difference in the frequency of lesions with invasion into the submucosal layer or deeper (14.3%, 10.5%, and 0% in the UD-E, UD-I, and UD-U groups, respectively). Conclusion The clinicopathological characteristics of UD-GC were similar between HP-infected patients and HP-eradicated patients. Three of four patients with eradicated HP whose UD-GC developed ≥ 10 years after eradication were not eligible for endoscopic treatment and required additional surgery resection. In contrast, UD-GC was curable by endoscopic resection in all patients without HP infection.

Serological Study of SARS-CoV-2 Antibodies in Japanese Cats: Analysis of Risk Factors Among Cat Lifestyles

Background Little is known about the epidemic status of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in cats living in Japan, and about the influence of cat lifestyles on the SARS-CoV-2 infection epidemic in cats. Results We developed protein A/G-based ELISA, which was standardized using positive rabbit antibodies. The measured values of this ELISA were consistent with those of conventional anti-feline IgG-based ELISA. We then collected blood samples from 1,969 cats that visited veterinary clinics in Japan from June to July 2020 and examined for the presence of anti-SARS-CoV-2 antibodies. Using protein A/G-based ELISA, nine cats were found to have SARS-CoV-2 S1-specific IgG, among which four had RBD-specific IgG. Among those nine samples, one showed neutralizing activity. Based on these, we estimated that the prevalence of SARS-CoV-2 neutralizing antibodies in cats living in Japan was 0.05% (1/1,969 samples). This prevalence did not differ much from the prevalence of neutralizing antibodies for SARS-CoV-2 in humans conducted in Japan at that time. Furthermore, we searched for factors associated with the prevalence of neutralizing antibodies in cats using our data and information from five countries (China, Croatia, France, Germany, and Italy). The prevalence of SARS-CoV-2 in cats was correlated with the rate of keeping indoor-only. Conclusions Protein A/G-based ELISA has the potential to be a standardized method to measure anti-SARS-CoV-2 antibodies in cats. The infection status of SARS-CoV-2 in cats in Japan is linked to that in humans, and the epidemic of SARS-CoV-2 infection in cats may be controlled by their living environment.

Empirical Study on Classifiers for Earlier Prediction of COVID-19 Infection Cure and Death Rate in the Indian States

Machine Learning methods can play a key role in predicting the spread of respiratory infection with the help of predictive analytics. Machine Learning techniques help mine data to better estimate and predict the COVID-19 infection status. A Fine-tuned Ensemble Classification approach for predicting the death and cure rates of patients from infection using Machine Learning techniques has been proposed for different states of India. The proposed classification model is applied to the recent COVID-19 dataset for India, and a performance evaluation of various state-of-the-art classifiers to the proposed model is performed. The classifiers forecasted the patients’ infection status in different regions to better plan resources and response care systems. The appropriate classification of the output class based on the extracted input features is essential to achieve accurate results of classifiers. The experimental outcome exhibits that the proposed Hybrid Model reached a maximum F1-score of 94% compared to Ensembles and other classifiers like Support Vector Machine, Decision Trees, and Gaussian Naïve Bayes on a dataset of 5004 instances through 10-fold cross-validation for predicting the right class. The feasibility of automated prediction for COVID-19 infection cure and death rates in the Indian states was demonstrated.

Epidemiological and ecological consequences of virus manipulation of host and vector in plant virus transmission

Many plant viruses are transmitted by insect vectors. Transmission can be described as persistent or non-persistent depending on rates of acquisition, retention, and inoculation of virus. Much experimental evidence has accumulated indicating vectors can prefer to settle and/or feed on infected versus noninfected host plants. For persistent transmission, vector preference can also be conditional, depending on the vector’s own infection status. Since viruses can alter host plant quality as a resource for feeding, infection potentially also affects vector population dynamics. Here we use mathematical modelling to develop a theoretical framework addressing the effects of vector preferences for landing, settling and feeding–as well as potential effects of infection on vector population density–on plant virus epidemics. We explore the consequences of preferences that depend on the host (infected or healthy) and vector (viruliferous or nonviruliferous) phenotypes, and how this is affected by the form of transmission, persistent or non-persistent. We show how different components of vector preference have characteristic effects on both the basic reproduction number and the final incidence of disease. We also show how vector preference can induce bistability, in which the virus is able to persist even when it cannot invade from very low densities. Feedbacks between plant infection status, vector population dynamics and virus transmission potentially lead to very complex dynamics, including sustained oscillations. Our work is supported by an interactive interface https://plantdiseasevectorpreference.herokuapp.com/. Our model reiterates the importance of coupling virus infection to vector behaviour, life history and population dynamics to fully understand plant virus epidemics.

Analysis of cutoff point estimation for determining seropositivity in the context of SARS-CoV-2 infections

In this work will apply mixture models based on distributions from the SMSN family to antibody data against four SARS-CoV-2 virus antigens. Furthermore, since the true infection status of individuals is known a priori, performance measures will be calculated for the methods proposed for cutoff point estimation such as sensitivity, specificity and accuracy. The results of a simulation study will also be presented.

Pretreatment C-Reactive Protein/Albumin Ratio is Associated With Poor Survival in Patients With 2018 FIGO Stage IB-IIA HPV-Positive Cervical Cancer

Objectives: The present study aimed to identify the predictive value of inflammatory indexes stratified according to human papillomavirus (HPV) infection status in women with FIGO 2018 stage IB∼IIA cervical cancer. We also explored the influences of HPV infection status on the survival of cervical cancer patients.Methods: We collected data for 583 women with stage IB∼IIA cervical cancer in Sun Yat-sen University Cancer Center between 2009 and 2017. The t-test, chi-squared (χ2) test and Fisher’s exact test were applied to compare the differences of inflammatory indexes and clinicopathological features between HPV-positive and HPV-negative groups. Univariate and multivariate analyses were used to identify clinicopathological factors that were associated with the prognosis of cervical cancer patients.Results: There were no differences in overall survival (OS) and progression-free survival (PFS) between HPV-positive and HPV-negative groups. In HPV-positive group, the maximum tumor size, neoadjuvant chemotherapy and the body mass index (BMI) correlated significantly with C-reactive protein/albumin ratio (CAR). The maximum tumor size and the prognostic nutritional index (PNI) correlated significantly with the platelet-lymphocyte ratio (PLR). The maximum tumor size, neoadjuvant chemotherapy and PLR correlated significantly with PNI. Univariate and multivariate analyses showed that the depth of tumor invasion (HR: 3.651, 95% CI: 1.464–9.103, p = 0.005; HR: 2.478, 95% CI: 1.218–5.043, p = 0.012) and CAR (HR: 5.201, 95% CI: 2.080–13.004, p &lt; 0.0001; HR: 2.769, 95% CI: 1.406–5.455, p = 0.003) were independent predictors of poor OS and PFS. PNI was an independent protective factor of OS (HR: 0.341, 95% CI: 0.156–0.745, p = 0.007). PLR was an independent factor of PFS (HR: 1.991, 95% CI: 1.018–3.894, p = 0.044). In HPV-negative group, BMI correlated significantly with CAR. Only depth of invasion (HR: 9.192, 95% CI: 1.016–83.173, p = 0.048) was the independent predictor of poor OS, and no inflammation indexes were independent predictors of prognosis.Conclusion: In patients with HPV-positive cervical cancer, depth of invasion, PNI and CAR are independent factors of OS, and depth of invasion, PLR and CAR are independent factors for PFS. For patients with HPV-negative disease, no inflammation indexes had predictive value for prognosis. The predictive value of inflammation indexes on prognosis is more significant in patients with HPV-positive cervical cancer. Stratification of HPV infection status promotes a more precise clinical application of inflammation indexes, thus improving their accuracy and feasibility.