Transport of IgG across the blood-luminal barrier of the male reproductive tract of the rat and the effect of estradiol administration on reabsorption of fluid and IgG by the epididymal ducts

In rats immunized systemically with tetanus toxoid the concentration of specific anti-tetanus-toxoid-specific IgG in fluid from the rete testis and cauda epididymidis were respectively 0.6% and 1.4% the concentration in blood serum. The extratesticular duct system reabsorbed 97% of the IgG and 99% of the fluid leaving the rete, but estradiol administration affected the site of reabsorption. In untreated rats, the ductuli efferentes reabsorbed 94% of the IgG and 96% of the fluid leaving the rete, whereas estradiol-treated rats reabsorbed 83% of the IgG and 86% of the fluid, and the ductus epididymidis fully compensated for these different effects of estradiol on the ductuli efferentes. The concentrations of IgG in secretions of the seminal vesicles and prostate gland were lower (0.1% and 0.3% respectively of the titers in blood serum) than in fluids from the extratesticular ducts, and were not affected by the administration of estradiol. RT-PCR showed that Fcgrt (neonatal Fc receptor, also known as FcRn) is expressed in the reproductive ducts, where IgG is probably transported across epithelium, being particularly strong in the ductuli efferentes (where most IgG was reabsorbed) and distal caput epididymidis. It is concluded that IgG enters the rete testis and is concentrated only 2.5-fold along the extratesticular duct system, unlike spermatozoa, which are concentrated 95-fold. Further, the ductus epididymidis can recognize and compensate for changes in function of the ductuli efferentes.

Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm

In cloud computing, resource allocation and scheduling of multiple composite web services is an important and challenging problem. This is especially so in a hybrid cloud where there may be some low-cost resources available from private clouds and some high-cost resources from public clouds. Meeting this challenge involves two classical computational problems: one is assigning resources to each of the tasks in the composite web services; the other is scheduling the allocated resources when each resource may be used by multiple tasks at different points of time. In addition, Quality-of-Service (QoS) issues, such as execution time and running costs, must be considered in the resource allocation and scheduling problem. Here we present a Cooperative Coevolutionary Genetic Algorithm (CCGA) to solve the deadline-constrained resource allocation and scheduling problem for multiple composite web services. Experimental results show that our CCGA is both efficient and scalable.