Fowl adenovirus serotype 4: Epidemiology, pathogenesis, diagnostic detection, and vaccine strategies.

Fowl adenovirus (FAdV) serotype-4 is highly pathogenic for chickens, especially for broilers aged 3 to 5 wk, and it has emerged as one of the foremost causes of economic losses to the poultry industry in the last 30 years. The liver is a major target organ of FAdV-4 infections, and virus-infected chickens usually show symptoms of hydropericardium syndrome. The virus is very contagious, and it is spread both vertically and horizontally. It can be isolated from infected liver homogenates and detected by several laboratory diagnostic methods (including an agar gel immunodiffusion test, indirect immunofluorescence assays, counterimmunoelectrophoresis, enzyme-linked immunosorbent assays, restriction endonuclease analyses, polymerase chain reaction (PCR), real-time PCR, and high-resolution melting-curve analyses). Although inactivated vaccines have been deployed widely to control the disease, attenuated live vaccines and subunit vaccines also have been developed, and they are more attractive vaccine candidates. This article provides a comprehensive review of FAdV-4, including its epidemiology, pathogenesis, diagnostic detection, and vaccine strategies.

Process of Bipolaris sorghicola invasion of host cells.

Target leaf spot is a sorghum leaf disease caused by Bipolaris sorghicola, a species of fungus with a global distribution. In this study, we investigated the process by which B. sorghicola invades cells of barley, onion, Arabidopsis thaliana species, and sorghum. The results showed that within 8 h of coming into contact with host cells, the hyphal ends of B. sorghicola expand and form a uniform infective penetration pegbolt-like structure; a primary infection mycelium can be formed inside host cells within 24 h after contact, which can infect closed cells after 48 h. A mycelium can grow within the gap between cells and form infective hyphae. The pathogen infection process was the same in different host cells. B. sorghicola can affect root cells through soil infection, indicating that it may also have characteristics of soil-borne pathogens.

Influences of high-voltage electrical burns on the pulmonary microcirculation in rabbits.

This study was performed to investigate the effects of high-voltage electrical burns (HEB) on the pulmonary microcirculation in rabbits. Total of 120 rabbits were randomly divided into control and HEB group using a random number table. HEB model was developed with a voltage regulator and experimental transformer. Laser Doppler perfusion imager was utilized to monitor and quantify the blood perfusion in pulmonary microcirculation. The microvascular morphologic changes of the lung were observed using light microscopy and transmission electron microscope (TEM). The lung wet/dry weight ratio and the PaO2 were determined. The values of blood perfusion in rabbit pulmonary microcirculation in the HEB group were decreased at 5 min, but increased at 1 h after burn (P <  0.01) and then decreased gradually. Light microscopy reveals microthrombus formation in pulmonary venules and bleeding in venous capillaries in HEB group. We found the number of microvilli in the capillary endothelial cells decreased, the rough endoplasmic reticulum expanded and severe degranulation occurred, the mitochondrial cristae fused or disappeared, and severe edema surrounded the capillary endothelial cells by TEM. The values of lung wet/dry weight ratio were higher and the PaO2 were lower than that of before burn group (P <  0.01). These results demonstrated that microcirculatory disorders play a major role in the development of progressive lung damage after high-voltage electrical burns.

Signal transduction pathways in Synechocystis sp. PCC 6803 and biotechnological implications under abiotic stress.

Cyanobacteria have developed various response mechanisms in long evolution to sense and adapt to external or internal changes under abiotic stresses. The signal transduction system of a model cyanobacterium Synechocystis sp. PCC 6803 includes mainly two-component signal transduction systems of eukaryotic-type serine/threonine kinases (STKs), on which most have been investigated at present. These two-component systems play a major role in regulating cell activities in cyanobacteria. More and more co-regulation and crosstalk regulations among signal transduction systems had been discovered due to increasing experimental data, and they are of great importance in corresponding to abiotic stresses. However, mechanisms of their functions remain unknown. Nevertheless, the two signal transduction systems function as an integral network for adaption in different abiotic stresses. This review summarizes available knowledge on the signal transduction network in Synechocystis sp. PCC 6803 and biotechnological implications under various stresses, with focuses on the co-regulation and crosstalk regulations among various stress-responding signal transduction systems.

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable.

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (ECe 4-8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.