Variability of Broad and Blueshifted Component of [OIII]λ\lambda5007 in IZWI

Although the existence of asymmetrical profile of [OIII]$\lambda$5007 has been discovered for ages, its filiation and physics are poorly understood. Two new spectra of I ZWI taken on Nov 16, 2001 and on Dec 3, 2002 were compared with the spectra taken by BG92. Following results are obtained. 1)The certain variations of broad [OIII] during about 10 years separating the observations are identified. The inferred length scale of broad [OIII] emitting region ranges from 0.3pc to 3pc. By assuming a Keplerian motion in emitting region, the material emitting broad [OIII] is likely to be located at transient emission line region, between BLR and NLR. 2)We find a positive relation between the FeII emission and flux of H$\beta$(or continuum). On the other hand, the parameter RFe decreases with ionizing continuum marginally. 3)We detect a low ionized NLR in I ZWI, because of the low flux ratios $\rm{[OIII]_{n}/H\beta_{n}}$($\sim1.7$).Comment: 14 pages, 3 figures, NewA in pres

A Comprehensive Study of Gamma-Ray Burst Optical Emission: I. Flares and Early Shallow Decay Component

Well-sampled optical lightcurves of 146 gamma-ray bursts (GRBs) are compiled from the literature. By empirical fitting we identify eight possible emission components and summarize the results in a "synthetic" lightcurve. Both optical flare and early shallow-decay components are likely related to long-term central engine activities. We focus on their statistical properties in this paper. Twenty-four optical flares are obtained from 19 GRBs. The isotropic R-band energy is smaller than 1% of $E_{\gamma, \rm iso}$. The relation between isotropic luminosities of the flares and gamma-rays follows $L^{\rm F}_{\rm R, iso}\propto L_{{\gamma}, \rm iso}^{1.11\pm 0.27}$. Later flares tend to be wider and dimmer, i.e., $w^{\rm F}\sim t^{\rm F}_{\rm p}/2$ and $L^{\rm F}_{\rm R, iso}\propto [t^{\rm F}_{\rm p}/(1+z)]^{-1.15\pm0.15}$. The detection probability of the optical flares is much smaller than that of X-ray flares. An optical shallow decay segment is observed in 39 GRBs. The relation between the break time and break luminosity is a power-law, with an index of $-0.78\pm 0.08$, similar to that derived from X-ray flares. The X-ray and optical breaks are usually chromatic, but a tentative correlation is found. We suggest that similar to the prompt optical emission that tracks $\gamma$-rays, the optical flares are also related to the erratic behavior of the central engine. The shallow decay component is likely related to a long-lasting spinning-down central engine or piling up of flare materials onto the blastwave. Mixing of different emission components may be the reason of the diverse chromatic afterglow behaviors.Comment: 43 pages, 13 figures, 3 tables, accepted for publication in Ap

Modeling the high-energy emission in GRB 110721A and implications on the early multiwavelength and polarimetric observations

GRB 110721A was detected by the Gamma-ray Burst Monitor and the Large Area Telescope (LAT) onboard the Fermi satellite and the Gamma-ray Burst Polarimeter onboard the IKAROS solar mission. Previous analysis done of this burst showed: i) a linear polarization signal with position angle stable ($\phi_p= 160^\circ\pm11$) and high degree of $\Pi=84^{+16}_{-28}$, ii) an extreme peak energy of a record-breaking at 15$\pm$2 MeV, and iii) a subdominant prompt thermal component observed right after the onset of this burst. In this paper, the LAT data around the reported position of GRB 110721A are analysed with the most recent software and then, the LAT light curve above 100 MeV was obtained. The LAT light curve is modelled in terms of adiabatic early-afterglow external shocks when the outflow propagates into a stellar wind. Additionally, we discuss the possible origins and also study the implications of the early-afterglow external shocks on the extreme peak energy observed at 15$\pm$2 MeV, the polarization observations and the subdominant prompt thermal component.Comment: 9 pages and one figure. Accepted for publication in Ap

Meta-Analysis for Genome-Wide Association Study Identifies Multiple Variants at the BIN1 Locus Associated with Late-Onset Alzheimer's Disease

Recent GWAS studies focused on uncovering novel genetic loci related to AD have revealed associations with variants near CLU, CR1, PICALM and BIN1. In this study, we conducted a genome-wide association study in an independent set of 1034 cases and 1186 controls using the Illumina genotyping platforms. By coupling our data with available GWAS datasets from the ADNI and GenADA, we replicated the original associations in both PICALM (rs3851179) and CR1 (rs3818361). The PICALM variant seems to be non-significant after we adjusted for APOE e4 status. We further tested our top markers in 751 independent cases and 751 matched controls. Besides the markers close to the APOE locus, a marker (rs12989701) upstream of BIN1 locus was replicated and the combined analysis reached genome-wide significance level (p = 5E-08). We combined our data with the published Harold et al. study and meta-analysis with all available 6521 cases and 10360 controls at the BIN1 locus revealed two significant variants (rs12989701, p = 1.32E-10 and rs744373, p = 3.16E-10) in limited linkage disequilibrium (r2 = 0.05) with each other. The independent contribution of both SNPs was supported by haplotype conditional analysis. We also conducted multivariate analysis in canonical pathways and identified a consistent signal in the downstream pathways targeted by Gleevec (P = 0.004 in Pfizer; P = 0.028 in ADNI and P = 0.04 in GenADA). We further tested variants in CLU, PICALM, BIN1 and CR1 for association with disease progression in 597 AD patients where longitudinal cognitive measures are sufficient. Both the PICALM and CLU variants showed nominal significant association with cognitive decline as measured by change in Clinical Dementia Rating-sum of boxes (CDR-SB) score from the baseline but did not pass multiple-test correction. Future experiments will help us better understand potential roles of these genetic loci in AD pathology

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p

Using hippocampal microRNA expression differences between mouse inbred strains to characterise miRNA function

Micro-RNAs (miRNAs) are short, single-stranded, noncoding RNAs that are involved in the regulation of protein-coding genes at the level of messenger RNA (mRNA). They are involved in the regulation of numerous traits, including developmental timing, apoptosis, immune function, and neuronal development. To better understand how the expression of the miRNAs themselves is regulated, we looked for miRNA expression differences among four mouse inbred strains, A/J, BALB/cJ, C57BL/6J, and DBA/2J, in one tissue, the hippocampus. A total of 166 miRNA RT-PCR assays were used to screen RNA pools for each strain. Twenty miRNA species that were markedly different between strains were further investigated using eight individual samples per strain, and 11 miRNAs showed significant differences across strains (p < 0.05). This is the first observation of miRNA expression differences across inbred mice strains. We conducted an in silico correlation analysis of the expression of these differentially expressed miRNAs with phenotype data and mRNA expression to better characterise the effects of these miRNAs on both phenotype and the regulation of mRNA expression. This approach has allowed us to nominate miRNAs that have potential roles in anxiety, exploration, and learning and memory

Diagenesis of archaeological bone and tooth

An understanding of the structural complexity of mineralised tissues is fundamental for exploration into the field of diagenesis. Here we review aspects of current and past research on bone and tooth diagenesis using the most comprehensive collection of literature on diagenesis to date. Environmental factors such as soil pH, soil hydrology and ambient temperature, which influence the preservation of skeletal tissues are assessed, while the different diagenetic pathways such as microbial degradation, loss of organics, mineral changes, and DNA degradation are surveyed. Fluctuating water levels in and around the bone is the most harmful for preservation and lead to rapid skeletal destruction. Diagenetic mechanisms are found to work in conjunction with each other, altering the biogenic composition of skeletal material. This illustrates that researchers must examine multiple diagenetic pathways to fully understand the post-mortem interactions of archaeological skeletal material and the burial environment