Detection of differentially expressed genes between Erhualian and Large White placentas on day 75 and 90 of gestation

<p>Abstract</p> <p>Background</p> <p>Placental efficiency is strongly associated with litter size, fetal weight and prenatal mortality. Together with its rapid growth during late gestation, the Large White pig breed shows a significant increase in placental size and weight, but this does not occur in the highly prolific Chinese pig breeds. To understand the molecular basis of placental development during late gestation in Chinese indigenous and Western breeds with different placental efficiency, female placental samples were collected from six pregnant Erhualian gilts at gestation day 75 (E75) and day 90 (E90) and from six pregnant Large White gilts at gestation day 75 (L75) and day 90 (L90). Two female placentas from one sow were used to extract RNA and then pooled in equal volumes. Twelve pooled samples were hybridized to the porcine Affymetrix GeneChip.</p> <p>Results</p> <p>A total of 226 and 577 transcripts were detected that were differentially expressed between E75 and L75 and between E90 and L90 (p < 0.01, q < 0.2), respectively. Gene Ontology (GO) analysis revealed that these genes belong to the class of genes that participate in angiogenesis and development. Real-time RT-PCR confirmed the differential expression of eight selected genes. Significant differential expression of five genes in the <it>VEGF </it>pathway was also detected between the breeds. A search of chromosomal location revealed that 44 differentially expressed genes located to QTL regions related to reproduction. Differential expression of six candidate imprinted genes was also confirmed. Three of the six genes (<it>PLAGL1</it>, <it>DIRAS3</it>, and <it>SLC38A4</it>) showed monoallelic expression in the porcine placenta.</p> <p>Conclusion</p> <p>Our study detected many genes that showed differential expression between placentas of two divergent breed of pigs, and confirmed the imprinting of three genes. These findings help to elucidate the genetic control of placental efficiency and improve the understanding of placental development.</p

One-step fabrication of biocompatible chitosan-coated ZnS and ZnS:Mn2+ quantum dots via a γ-radiation route

Biocompatible chitosan-coated ZnS quantum dots [CS-ZnS QDs] and chitosan-coated ZnS:Mn2+ quantum dots [CS-ZnS:Mn2+ QDs] were successfully fabricated via a convenient one-step γ-radiation route. The as-obtained QDs were around 5 nm in diameter with excellent water-solubility. These QDs emitting strong visible blue or orange light under UV excitation were successfully used as labels for PANC-1 cells. The cell experiments revealed that CS-ZnS and CS-ZnS:Mn2+ QDs showed low cytotoxicity and good biocompatibility, which offered possibilities for further biomedical applications. Moreover, this convenient synthesis strategy could be extended to fabricate other nanoparticles coated with chitosan

Match-Fixing en tenis : análisis sobre el amaño de partidos en el mundo del tenis

El presente artículo expone, a partir de un hipotético caso práctico, la situación de los amaños deportivos o match-fixing en el ámbito del tenis profesional y cuáles son, a nivel jurídico, la normativa y sanciones que se establecen para los supuestos casos de amaños deportivos

Highlights from the 2019 International Myopia Summit on 'controversies in myopia'.

Myopia is an emerging public health issue with potentially significant economic and social impact, especially in East Asia. However, many uncertainties about myopia and its clinical management remain. The International Myopia Summit workgroup was convened by the Singapore Eye Research Institute, the WHO Regional Office for the Western Pacific and the International Agency for the Prevention of Blindness in 2019. The aim of this workgroup was to summarise available evidence, identify gaps or unmet needs and provide consensus on future directions for clinical research in myopia. In this review, among the many 'controversies in myopia' discussed, we highlight three main areas of consensus. First, development of interventions for the prevention of axial elongation and pathologic myopia is needed, which may require a multifaceted approach targeting the Bruch's membrane, choroid and/or sclera. Second, clinical myopia management requires co-operation between optometrists and ophthalmologists to provide patients with holistic care and a tailored approach that balances risks and benefits of treatment by using optical and pharmacological interventions. Third, current diagnostic technologies to detect myopic complications may be improved through collaboration between clinicians, researchers and industry. There is an unmet need to develop new imaging modalities for both structural and functional analyses and to establish normative databases for myopic eyes. In conclusion, the workgroup's call to action advocated for a paradigm shift towards a collaborative approach in the holistic clinical management of myopia

Comparison of Rx-defined morbidity groups and diagnosis- based risk adjusters for predicting healthcare costs in Taiwan

<p>Abstract</p> <p>Background</p> <p>Medication claims are commonly used to calculate the risk adjustment for measuring healthcare cost. The Rx-defined Morbidity Groups (Rx-MG) which combine the use of medication to indicate morbidity have been incorporated into the Adjusted Clinical Groups (ACG) Case Mix System, developed by the Johns Hopkins University. This study aims to verify that the Rx-MG can be used for adjusting risk and for explaining the variations in the healthcare cost in Taiwan.</p> <p>Methods</p> <p>The Longitudinal Health Insurance Database 2005 (LHID2005) was used in this study. The year 2006 was chosen as the baseline to predict healthcare cost (medication and total cost) in 2007. The final sample size amounted to 793 239 (81%) enrolees, and excluded any cases with discontinued enrolment. Two different kinds of models were built to predict cost: the concurrent model and the prospective model. The predictors used in the predictive models included age, gender, Aggregated Diagnosis Groups (ADG, diagnosis- defined morbidity groups), and Rx-defined Morbidity Groups. Multivariate OLS regression was used in the cost prediction modelling.</p> <p>Results</p> <p>The concurrent model adjusted for Rx-defined Morbidity Groups for total cost, and controlled for age and gender had a better predictive R-square = 0.618, compared to the model adjusted for ADGs (R²= 0.411). The model combined with Rx-MGs and ADGs performed the best for concurrently predicting total cost (R²= 0.650). For prospectively predicting total cost, the model combined Rx-MGs and ADGs (R²= 0.382) performed better than the models adjusted by Rx-MGs (R²= 0.360) or ADGs (R²= 0.252) only. Similarly, the concurrent model adjusted for Rx-MGs predicting pharmacy cost had a better performance (R-square = 0.615), than the model adjusted for ADGs (R²= 0.431). The model combined with Rx-MGs and ADGs performed the best in concurrently as well as prospectively predicting pharmacy cost (R²= 0.638 and 0.505, respectively). The prospective models showed a remarkable improvement when adjusted by prior cost.</p> <p>Conclusions</p> <p>The medication-based Rx-Defined Morbidity Groups was useful in predicting pharmacy cost as well as total cost in Taiwan. Combining the information on medication and diagnosis as adjusters could arguably be the best method for explaining variations in healthcare cost.</p

6G Network AI Architecture for Everyone-Centric Customized Services

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions

The diploid genome sequence of an Asian individual

Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics