Advances of Genetic Testing Technology in Etiology Diagnosis of Recurrent Spontaneous Abortion

Recurrent spontaneous abortion (RSA) is a complex and heterogeneous disorder with multiple etiologies. Genetic factors are thought to play an important role in the etiology of RSA. With recent advances in genetic testing technologies, there has been an increasing interest in using these tools to diagnose the etiology of RSA. This review discusses the different types of genetic testing methods, such as karyotyping, chromosomal microarray analysis, next-generation sequencing, and their applications in the diagnosis of the etiology RSA. The use of genetic testing in the diagnosis of RSA has the potential to improve the accuracy of diagnosis and the understanding of the underlying mechanisms of the disorder, which could lead to better management and treatment of affected individuals.

Development and Assessment of Two Highly Pathogenic Avian Influenza(HPAI) H5N6 Candidate Vaccine Viruses for Pandemic Preparedness

Objective In China, 24 cases of human infection with highly pathogenic avian influenza(HPAI) H5 N6 virus have been confirmed since the first confirmed case in 2014. Therefore, we developed and assessed two H5 N6 candidate vaccine viruses(CVVs).Methods In accordance with the World Health Organization(WHO) recommendations, we constructed two reassortant viruses using reverse genetics(RG) technology to match the two different epidemic H5 N6 viruses. We performed complete genome sequencing to determine the genetic stability. We assessed the growth ability of the studied viruses in MDCK cells and conducted a hemagglutination inhibition assay to analyze their antigenicity. Pathogenicity attenuation was also evaluated in vitro and in vivo.Results The results showed that no mutations occurred in hemagglutinin or neuraminidase, and both CVVs retained their original antigenicity. The replication capacity of the two CVVs reached a level similar to that of A/Puerto Rico/8/34 in MDCK cells. The two CVVs showed low pathogenicity in vitro and in vivo, which are in line with the WHO requirements for CVVs.Conclusion We obtained two genetically stable CVVs of HPAI H5N6 with high growth characteristics,which may aid in our preparedness for a potential H5N6 pandemic.

Fault self-repair strategy based on evolvable hardware and reparation balance technology

In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear easily. Circuit faults will inevitably lead to serious losses of availability or impeded mission success without self-repair over the mission duration. Traditional fault-repair methods based on redundant fault-tolerant technique are straightforward to implement, yet their area, power and weight cost can be excessive. Moreover they utilize all plug-in or component level circuits to realize redundant backup, such that their applicability is limited. Hence, a novel selfrepair technology based on evolvable hardware（EHW） and reparation balance technology（RBT） is proposed. Its cost is low, and fault self-repair of various circuits and devices can be realized through dynamic configuration. Making full use of the fault signals, correcting circuit can be found through EHW technique to realize the balance and compensation of the fault output-signals. In this paper, the self-repair model was analyzed which based on EHW and RBT technique, the specific self-repair strategy was studied, the corresponding self-repair circuit fault system was designed, and the typical faults were simulated and analyzed which combined with the actual electronic devices. Simulation results demonstrated that the proposed fault self-repair strategy was feasible. Compared to traditional techniques, fault self-repair based on EHW consumes fewer hardware resources, and the scope of fault self-repair was expanded significantly.

Simultaneous characterization of multiple properties of solid and liquid phases in crystallization processes using NIR

Near infrared spectroscopy （NIR） is now probably the most popular process analytical technology （PAT） for pharmaceutical and some other industries. However, unlike mid-IR, NIR is known to have difficulties in monitoring crystallization or precipitation processes because the existence of solids could cause distortion of the spectra. This phenomenon, seen as unfavorable previously, is however an indication that NIR spectra contain rich information about both solids and liquids, giving the possibility of using the same instrument for multiple property characterization. In this study, transflectance NIR calibration data was obtained using solutions and slurries of varied solution concentration, particle size, solid concentration and temperature. The data was used to build calibration models for prediction of the multiple properties of both phases. Predictive models were developed for this challenging application using an approach that combines genetic algorithm （GA） and support vector machine （SVM）. GA is used for wavelength selection and SVM for mode building. The new GA-SVM approach is shown to outperform other methods including GA-PLS （partial least squares） and traditional SVM. NIR is thus successfully applied to monitoring seeded and unseeded cooling crystallization processes of L-glutamic acid.