Academia Sinica

About: Academia Sinica is a facility organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Population & Gene. The organization has 52086 authors who have published 65998 publications receiving 1728114 citations. The organization is also known as: Central Research Academy.

Some insights into energy metabolism for osmoregulation in fish.

Abstract: A sufficient and timely energy supply is a prerequisite for the operation of iono- and osmoregulatory mechanisms in fish. Measurements of whole-fish or isolated-gill (or other organs) oxygen consumption have demonstrated regulation of the energy supply during acclimation to different osmotic environments, and such regulation is dependent on species, the situation of acclimation or acclimatization, and life habits. Carbohydrate metabolism appears to play a major role in the energy supply for iono- and osmoregulation, and the liver is the major source supplying carbohydrate metabolites to osmoregulatory organs. Compared with carbohydrates, the roles of lipids and proteins remain largely unclear. Energy metabolite translocation was recently found to occur between fish gill ionocytes and neighboring glycogen-rich (GR) cells, indicating the physiological significance of a local energy supply for gill ion regulatory mechanisms. Spatial and temporal relationships between the liver and other osmoregulatory and non-osmoregulatory organs in partitioning the energy supply for ion regulatory mechanisms during salinity challenges were also proposed. A novel glucose transporter was found to specifically be expressed and function in gill ionocytes, providing the first cue for investigating energy translocation among gill cells. Advanced molecular physiological approaches can be used to examine energy metabolism relevant to a particular cell type (e.g., gill ionocytes), and functional genomics may also provide another powerful approach to explore new metabolic pathways related to fish ion regulation.

The VIMOS Public Extragalactic Redshift Survey (VIPERS) - Galaxy clustering and redshift-space distortions at z ≃ 0.8 in the first data release

Abstract: We present in this paper the general real- and redshift-space clustering properties of galaxies as measured in the first data release of the VIPERS survey. VIPERS is a large redshift survey designed to probe the distant Universe and its large-scale structure at 0.5 < z < 1.2. We describe in this analysis the global properties of the sample and discuss the survey completeness and associated corrections. This sample allows us to measure the galaxy clustering with an unprecedented accuracy at these redshifts. From the redshift-space distortions observed in the galaxy clustering pattern we provide a first measurement of the growth rate of structure at z = 0.8: f\sigma_8 = 0.47 +/- 0.08. This is completely consistent with the predictions of standard cosmological models based on Einstein gravity, although this measurement alone does not discriminate between different gravity models.

Loss of non-coding RNA expression from the DLK1-DIO3 imprinted locus correlates with reduced neural differentiation potential in human embryonic stem cell lines

Abstract: Pluripotent stem cells are increasingly used to build therapeutic models, including the transplantation of neural progenitors derived from human embryonic stem cells (hESCs). Recently, long non-coding RNAs (lncRNAs), including delta-like homolog 1 gene and the type III iodothyronine deiodinase gene (DLK1-DIO3) imprinted locus-derived maternally expressed gene 3 (MEG3), were found to be expressed during neural development. The deregulation of these lncRNAs is associated with various neurological diseases. The imprinted locus DLK1-DIO3 encodes abundant non-coding RNAs (ncRNAs) that are regulated by differential methylation of the locus. We aim to study the correlation between the DLK1-DIO3-derived ncRNAs and the capacity of hESCs to differentiate into neural lineages. We classified hESC sublines into MEG3-ON and MEG3-OFF based on the expression levels of MEG3 and its downstream microRNAs as detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). A cDNA microarray was used to analyze the gene expression profiles of hESCs. To investigate the capacity of neural differentiation in MEG3-ON and MEG3-OFF hESCs, we performed neural lineage differentiation followed by neural lineage marker expression and neurite formation analyses via qRT-PCR and immunocytochemistry, respectively. MEG3-knockdown via small interfering RNA (siRNA) and small hairpin RNA (shRNA) was used to investigate the potential causative effect of MEG3 in regulating neural lineage-related gene expression. DLK1-DIO3-derived ncRNAs were repressed in MEG3-OFF hESCs compared with those in the MEG3-ON hESCs. The transcriptome profile indicated that many genes related to nervous system development and neural-type tumors were differentially expressed in MEG3-OFF hESCs. Three independent MEG3-knockdown assays using different siRNA and shRNA constructs consistently resulted in downregulation of some neural lineage genes. Lower expression levels of stage-specific neural lineage markers and reduced neurite formation were observed in neural lineage-like cells derived from MEG3-OFF-associated hESCs compared with those in the MEG3-ON groups at the same time points after differentiation. Repression of ncRNAs derived from the DLK1-DIO3 imprinted locus is associated with reduced neural lineage differentiation potential in hESCs.

Supernova constraints on a holographic dark energy model

Abstract: In this paper, we use the type Ia supernova data to constrain the model of holographic dark energy. For d = 1, the best fit result is Ωm0 = 0.25, the equation of the state of the holographic dark energy wΛ0 = −0.91 and the transition between the decelerating expansion and the accelerating expansion happened when the cosmological red-shift was zT = 0.72. If we set d as a free parameter, the best fit results are d = 0.21, Ωm0 = 0.46, wΛ0 = −2.67, which sounds like a phantom today, and the transition red-shift is zT = 0.28.