Detection of Hepatitis B virus in serum and liver of chickens

Hepatitis B virus (HBV) is one of the most important human pathogens. Its existence in food animals could present a significant threat to public health. The objective of this study was to determine if HBV is present in serum and liver of chickens. A total of 129 serum samples from broiler chickens were collected for the detection of HBV antigens and antibodies, and 193 liver samples were tested for HBV DNA sequence by PCR and for the existence of HBV antigens by immunohistochemistry. The overall prevalence of HBsAg, anti-HBs, anti-HBc was 28.68%, 53.49%, 17.05%, respectively, whereas HBeAg, anti-HBe were barely detectable. Three serum samples were found to be positive for both HBsAg and HBeAg. Further analysis of these samples with transmission electron microscopy (TEM) revealed two morphologic particles with 20 nm and 40 nm in diameter, which were similar to small spherical and Danes particles of HBV. The viral DNA sequence identified in two of the chicken livers shared 92.2% of one known HBV strain and 97.9% nucleotide sequence of another HBV strain. Our results showed the existence of HBV in chickens. This would present a significant risk to people who work with live chickens or chicken products if HBV found in chicken could be confirmed to be the same as human HBV

Predicted Mean Vote of Subway Car Environment Based on Machine Learning

The thermal comfort of passengers in the carriage cannot be ignored. Thus, this research aims to establish a prediction model for the thermal comfort of the internal environment of a subway car and find the optimal input combination in establishing the prediction model of the predicted mean vote (PMV) index. Data-driven modeling utilizes data from experiments and questionnaires conducted in Nanjing Metro. Support vector machine (SVM), decision tree (DT), random forest (RF), and logistic regression (LR) were used to build four models. This research aims to select the most appropriate input variables for the predictive model. All possible combinations of 11 input variables were used to determine the most accurate model, with variable selection for each model comprising 102 350 iterations. In the PMV prediction, the RF model was the best when using the correlation coefficients square (R2) as the evaluation indicator (R2: 0.7680, mean squared error (MSE): 0.2868). The variables include clothing temperature (CT), convective heat transfer coefficient between the surface of the human body and the environment (CHTC), black bulb temperature (BBT), and thermal resistance of clothes (TROC). The RF model with MSE as the evaluation index also had the highest accuracy (R2: 0.7676, MSE: 0.2836). The variables include clothing surface area coefficient (CSAC), CT, BBT, and air velocity (AV). The results show that the RF model can efficiently predict the PMV of the subway car environment

BmILF and I-motif Structure Are Involved in Transcriptional Regulation of \u3cem\u3eBmPOUM2\u3c/em\u3e in \u3cem\u3eBombyx mori\u3c/em\u3e

Guanine-rich and cytosine-rich DNA can form four-stranded DNA secondary structures called G-quadruplex (G4) and i-motif, respectively. These structures widely exist in genomes and play important roles in transcription, replication, translation and protection of telomeres. In this study, G4 and i-motif structures were identified in the promoter of the transcription factor gene BmPOUM2, which regulates the expression of the wing disc cuticle protein gene (BmWCP4) during metamorphosis. Disruption of the i-motif structure by base mutation, anti-sense oligonucleotides (ASOs) or inhibitory ligands resulted in significant decrease in the activity of the BmPOUM2 promoter. A novel i-motif binding protein (BmILF) was identified by pull-down experiment. BmILF specifically bound to the i-motif and activated the transcription of BmPOUM2. The promoter activity of BmPOUM2 was enhanced when BmILF was over-expressed and decreased when BmILF was knocked-down by RNA interference. This study for the first time demonstrated that BmILF and the i-motif structure participated in the regulation of gene transcription in insect metamorphosis and provides new insights into the molecular mechanism of the secondary structures in epigenetic regulation of gene transcription

Developing a time series predictive model for dengue in Zhongshan, China based on weather and Guangzhou dengue surveillance data

Dengue is a re-emerging infectious disease of humans, rapidly growing from endemic areas to dengue-free regions due to favorable conditions. In recent decades, Guangzhou has again suffered from several big outbreaks of dengue; as have its neighboring cities. This study aims to examine the impact of dengue epidemics in Guangzhou, China, and to develop a predictive model for Zhongshan based on local weather conditions and Guangzhou dengue surveillance information. Methods We obtained weekly dengue case data from 1st January, 2005 to 31st December, 2014 for Guangzhou and Zhongshan city from the Chinese National Disease Surveillance Reporting System. Meteorological data was collected from the Zhongshan Weather Bureau and demographic data was collected from the Zhongshan Statistical Bureau. A negative binomial regression model with a log link function was used to analyze the relationship between weekly dengue cases in Guangzhou and Zhongshan, controlling for meteorological factors. Cross-correlation functions were applied to identify the time lags of the effect of each weather factor on weekly dengue cases. Models were validated using receiver operating characteristic (ROC) curves and k-fold cross-validation. Results Our results showed that weekly dengue cases in Zhongshan were significantly associated with dengue cases in Guangzhou after the treatment of a 5 weeks prior moving average (Relative Risk (RR) = 2.016, 95% Confidence Interval (CI): 1.845–2.203), controlling for weather factors including minimum temperature, relative humidity, and rainfall. ROC curve analysis indicated our forecasting model performed well at different prediction thresholds, with 0.969 area under the receiver operating characteristic curve (AUC) for a threshold of 3 cases per week, 0.957 AUC for a threshold of 2 cases per week, and 0.938 AUC for a threshold of 1 case per week. Models established during k-fold cross-validation also had considerable AUC (average 0.938–0.967). The sensitivity and specificity obtained from k-fold cross-validation was 78.83% and 92.48% respectively, with a forecasting threshold of 3 cases per week; 91.17% and 91.39%, with a threshold of 2 cases; and 85.16% and 87.25% with a threshold of 1 case. The out-of-sample prediction for the epidemics in 2014 also showed satisfactory performance. Conclusion Our study findings suggest that the occurrence of dengue outbreaks in Guangzhou could impact dengue outbreaks in Zhongshan under suitable weather conditions. Future studies should focus on developing integrated early warning systems for dengue transmission including local weather and human movement

The effect of microgravity on tissue structure and function of rat testis

To explore whether an environment of weightlessness will cause damage to the reproductive system of animals, we used the tail-suspension model to simulate microgravity, and investigated the effect of microgravity on the tissue structure and function of the testis in sexually mature male rats. Forty-eight male Wistar rats weighing 200-250 g were randomly assigned to three groups (N = 16 each): control, tail traction, and tail suspension. After the rats were suspended for 7 or 14 days, morphological changes of testis were evaluated by histological and electron microscopic methods. The expression of HSP70, bax/bcl-2 and AR (androgen receptor) in testis was measured by immunohistochemistry. Obvious pathological lesions were present in the testis after the rats were suspended for 7 or 14 days. We detected overexpression of HSP70 and an increase of apoptotic cells, which may have contributed to the injury to the testis. The expression of AR, as an effector molecule in the testis, was significantly decreased in the suspended groups compared to control (P < 0.01). We also observed that, with a longer time of suspension, the aforementioned pathological damage became more serious and some pathological injury to the testis was irreversible. The results demonstrated that a short- or medium-term microgravity environment could lead to severe irreversible damage to the structure of rat testis

Dynamic spatiotemporal analysis of indigenous dengue fever at street-level in Guangzhou city, China

Background This study aimed to investigate the spatiotemporal clustering and socio-environmental factors associated with dengue fever (DF) incidence rates at street level in Guangzhou city, China. Methods Spatiotemporal scan technique was applied to identify the high risk region of DF. Multiple regression model was used to identify the socio-environmental factors associated with DF infection. A Poisson regression model was employed to examine the spatiotemporal patterns in the spread of DF. Results Spatial clusters of DF were primarily concentrated at the southwest part of Guangzhou city. Age group (65+ years) (Odd Ratio (OR) = 1.49, 95% Confidence Interval (CI) = 1.13 to 2.03), floating population (OR = 1.09, 95% CI = 1.05 to 1.15), low-education (OR = 1.08, 95% CI = 1.01 to 1.16) and non-agriculture (OR = 1.07, 95% CI = 1.03 to 1.11) were associated with DF transmission. Poisson regression results indicated that changes in DF incidence rates were significantly associated with longitude (β = -5.08, P<0.01) and latitude (β = -1.99, P<0.01). Conclusions The study demonstrated that social-environmental factors may play an important role in DF transmission in Guangzhou. As geographic range of notified DF has significantly expanded over recent years, an early warning systems based on spatiotemporal model with socio-environmental is urgently needed to improve the effectiveness and efficiency of dengue control and prevention

Genome-wide methylation profiling identify hypermethylated HOXL subclass genes as potential markers for esophageal squamous cell carcinoma detection

Abstract Background Numerous studies have revealed aberrant DNA methylation in esophageal squamous cell carcinoma (ESCC). However, they often focused on the partial genome, which resulted in an inadequate understanding of the shaped methylation features and the lack of available methylation markers for this disease. Methods The current study investigated the methylation profiles between ESCC and paired normal samples using whole-genome bisulfite sequencing (WGBS) data and obtained a group of differentially methylated CpGs (DMC), differentially methylated regions (DMR), and differentially methylated genes (DMG). The DMGs were then verified in independent datasets and Sanger sequencing in our custom samples. Finally, we attempted to evaluate the performance of these genes as methylation markers for the classification of ESCC. Results We obtained 438,558 DMCs, 15,462 DMRs, and 1568 DMGs. The four significantly enriched gene families of DMGs were CD molecules, NKL subclass, HOXL subclass, and Zinc finger C2H2-type. The HOXL subclass homeobox genes were observed extensively hypermethylated in ESCC. The HOXL-score estimated by HOXC10 and HOXD1 methylation, whose methylation status were then confirmed by sanger sequencing in our custom ESCC samples, showed good ability in discriminating ESCC from normal samples. Conclusions We observed widespread hypomethylation events in ESCC, and the hypermethylated HOXL subclass homeobox genes presented promising applications for the early detection of esophageal squamous cell carcinoma