We present light curves and spectra of the tidal disruption event (TDE) ASASSN-18pg/AT 2018dyb spanning a period of one year. The event shows a plethora of strong emission lines, including the Balmer ...series, He ii, He i, and metal lines of O iii λ3760 and N iii λλ4100, 4640 (blended with He ii). The latter lines are consistent with originating from the Bowen fluorescence mechanism. By analyzing literature spectra of past events, we conclude that these lines are common in TDEs. The spectral diversity of optical TDEs is thus larger than previously thought and includes N-rich events besides H- and He-rich events. We study how the spectral lines evolve with time, by means of their width, relative strength, and velocity offsets. The velocity width of the lines starts at ∼13,000 km s−1 and decreases with time. The ratio of He ii to N iii increases with time. The same is true for ASASSN-14li, which has a very similar spectrum to AT 2018dyb but its lines are narrower by a factor of >2. We estimate a black hole mass of MBH = 3.3 − 2.0 + 5.0 × 10 6 M by using the M- relation. This is consistent with the black hole mass derived using the MOSFiT transient fitting code. The detection of strong Bowen lines in the optical spectrum is an indirect proof for extreme ultraviolet and (reprocessed) X-ray radiation and favors an accretion origin for the TDE optical luminosity. A model where photons escape after multiple scatterings through a super-Eddington thick disk and its optically thick wind, viewed at an angle close to the disk plane, is consistent with the observations.
ABSTRACT
Low-luminosity Type II supernovae (LL SNe II) make up the low explosion energy end of core-collapse SNe, but their study and physical understanding remain limited. We present SN 2016aqf, an ...LL SN II with extensive spectral and photometric coverage. We measure a V-band peak magnitude of −14.58 mag, a plateau duration of ∼100 d, and an inferred 56Ni mass of 0.008 ± 0.002 M⊙. The peak bolometric luminosity, Lbol ≈ 1041.4 erg s−1, and its spectral evolution are typical of other SNe in the class. Using our late-time spectra, we measure the O i λλ6300, 6364 lines, which we compare against SN II spectral synthesis models to constrain the progenitor zero-age main-sequence mass. We find this to be 12 ± 3 M⊙. Our extensive late-time spectral coverage of the Fe ii λ7155 and Ni ii λ7378 lines permits a measurement of the Ni/Fe abundance ratio, a parameter sensitive to the inner progenitor structure and explosion mechanism dynamics. We measure a constant abundance ratio evolution of $0.081^{+0.009}_{-0.010}$ and argue that the best epochs to measure the ratio are at ∼200–300 d after explosion. We place this measurement in the context of a large sample of SNe II and compare against various physical, light-curve, and spectral parameters, in search of trends that might allow indirect ways of constraining this ratio. We do not find correlations predicted by theoretical models; however, this may be the result of the exact choice of parameters and explosion mechanism in the models, the simplicity of them, and/or primordial contamination in the measured abundance ratio.
Abstract
Large modern surveys require efficient review of data in order to find transient sources such as supernovae, and to distinguish such sources from artefacts and noise. Much effort has been ...put into the development of automatic algorithms, but surveys still rely on human review of targets. This paper presents an integrated system for the identification of supernovae in data from Pan-STARRS1, combining classifications from volunteers participating in a citizen science project with those from a convolutional neural network. The unique aspect of this work is the deployment, in combination, of both human and machine classifications for near real-time discovery in an astronomical project. We show that the combination of the two methods outperforms either one used individually. This result has important implications for the future development of transient searches, especially in the era of Large Synoptic Survey Telescope and other large-throughput surveys.
BACKGROUND AND PURPOSE—Resveratrol, at least in part via SIRT1 (silent information regulator 2 homologue 1) activation, protects against cerebral ischemia when administered 2 days before injury. ...However, it remains unclear if SIRT1 activation must occur, and in which brain cell types, for the induction of neuroprotection. We hypothesized that neuronal SIRT1 is essential for resveratrol-induced ischemic tolerance and sought to characterize the metabolic pathways regulated by neuronal Sirt1 at the cellular level in the brain.
METHODS—We assessed infarct size and functional outcome after transient 60 minute middle cerebral artery occlusion in control and inducible, neuronal-specific SIRT1 knockout mice. Nontargeted primary metabolomics analysis identified putative SIRT1-regulated pathways in brain. Glycolytic function was evaluated in acute brain slices from adult mice and primary neuronal-enriched cultures under ischemic penumbra-like conditions.
RESULTS—Resveratrol-induced neuroprotection from stroke was lost in neuronal Sirt1 knockout mice. Metabolomics analysis revealed alterations in glucose metabolism on deletion of neuronal Sirt1, accompanied by transcriptional changes in glucose metabolism machinery. Furthermore, glycolytic ATP production was impaired in acute brain slices from neuronal Sirt1 knockout mice. Conversely, resveratrol increased glycolytic rate in a SIRT1-dependent manner and under ischemic penumbra-like conditions in vitro.
CONCLUSIONS—Our data demonstrate that resveratrol requires neuronal SIRT1 to elicit ischemic tolerance and identify a novel role for SIRT1 in the regulation of glycolytic function in brain. Identification of robust neuroprotective mechanisms that underlie ischemia tolerance and the metabolic adaptations mediated by SIRT1 in brain are crucial for the translation of therapies in cerebral ischemia and other neurological disorders.
Importance The ability of computed tomography (CT) to distinguish between benign congenital lung malformations and malignant cystic pleuropulmonary blastomas (PPBs) is unclear. Objective To assess ...whether chest CT can detect malignant tumors among postnatally detected lung lesions in children. Design, Setting, and Participants This retrospective multicenter case-control study used a consortium database of 521 pathologically confirmed primary lung lesions from January 1, 2009, through December 31, 2015, to assess diagnostic accuracy. Preoperative CT scans of children with cystic PPB (cases) were selected and age-matched with CT scans from patients with postnatally detected congenital lung malformations (controls). Statistical analysis was performed from January 18 to September 6, 2020. Preoperative CT scans were interpreted independently by 9 experienced pediatric radiologists in a blinded fashion and analyzed from January 24, 2019, to September 6, 2020. Main Outcomes and Measures Accuracy, sensitivity, and specificity of CT in correctly identifying children with malignant tumors. Results Among 477 CT scans identified (282 boys 59%; median age at CT, 3.6 months IQR, 1.2-7.2 months; median age at resection, 6.9 months IQR, 4.2-12.8 months), 40 cases were extensively reviewed; 9 cases (23%) had pathologically confirmed cystic PPB. The median age at CT was 7.3 months (IQR, 2.9-22.4 months), and median age at resection was 8.7 months (IQR, 5.0-24.4 months). The sensitivity of CT for detecting PPB was 58%, and the specificity was 83%. High suspicion for malignancy correlated with PPB pathology (odds ratio, 13.5; 95% CI, 2.7-67.3;P = .002). There was poor interrater reliability (κ = 0.36 range, 0.06-0.64;P < .001) and no significant difference in specific imaging characteristics between PPB and benign cystic lesions. The overall accuracy rate for distinguishing benign vs malignant lesions was 81%. Conclusions and Relevance This study suggests that chest CT, the current criterion standard imaging modality to assess the lung parenchyma, may not accurately and reliably distinguish PPB from benign congenital lung malformations in children. In any cystic lung lesion without a prenatal diagnosis, operative management to confirm pathologic diagnosis is warranted.
A major concern for cardiac arrest (CA) survivors is the manifestation of long-term cognitive impairments. Physical exercise (PE) is a well-established approach to improve cognitive functions under ...certain pathological conditions. We previously showed that PE post-CA mitigates cognitive deficits, but the underlying mechanisms remain unknown. To define neuroprotective mechanisms, we analyzed whether PE post-CA protects neurons involved in memory. We first performed a contextual fear conditioning (CFC) test to confirm that PE post-CA preserves memory in rats. We then conducted a cell-count analysis and determined the number of live cells in the hippocampus, and septal and thalamic nuclei, all areas involved in cognitive functions. Lastly, we performed RNA-seq to determine PE post-CA effect on gene expression. Following CA, exercised rats had preserved CFC memory than sham PE animals. Despite this outcome, PE post-CA did not protect hippocampal cells from dying. However, PE ameliorated cell death in septal and thalamic nuclei compared to sham PE animals, suggesting that these nuclei are crucial in mitigating cognitive decline post-CA. Interestingly, PE affected regulation of genes related to neuroinflammation, plasticity, and cell death. These findings reveal potential mechanisms whereby PE post-CA preserves cognitive functions by protecting septal and thalamic cells via gene regulation.
Full text
Available for:
NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Ischemic preconditioning is an innate neuroprotective mechanism in which a sub-injurious ischemic exposure increases the brain’s ability to withstand a subsequent, normally injurious ischemic insult. ...Part of ischemic preconditioning neuroprotection stems from an epigenetic reprogramming of the brain to a phenotype of ischemic tolerance, which results in a gene expression profile different from that observed in the non-injured and ischemia-injured brains. Such neuroprotective reprograming, activated by ischemic preconditioning, requires specific changes in DNA accessibility coordinated with activation of transcriptional activator and repressor proteins, which allows for expression of specific neuroprotective proteins despite a general repression of gene expression. In this review we examine the effects of injurious ischemia and ischemic preconditioning on the regulation of DNA methylation, histone post-translational modifications, and non-coding RNA expression. There is increasing interest in the role of epigenetics in disease pathobiology, and whether and how pharmacological manipulation of epigenetic processes may allow for ischemic neuroprotection. Therefore, a better understanding of the epigenomic determinants underlying the modulation of gene expression that lead to ischemic tolerance or cell death offers the promise of novel neuroprotective therapies that target global reprograming of genomic activity versus individual cellular signaling pathways.
Full text
Available for:
EMUNI, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UL, UM, UPCLJ, UPUK, VSZLJ, ZAGLJ, ZRSKP
Neuroprotective agents administered post-cerebral ischemia have failed so far in the clinic to promote significant recovery. Thus, numerous efforts were redirected toward prophylactic approaches such ...as preconditioning as an alternative therapeutic strategy. Our laboratory has revealed a novel long-term window of cerebral ischemic tolerance mediated by resveratrol preconditioning (RPC) that lasts for 2 weeks in mice. To identify its mediators, we conducted an RNA-seq experiment on the cortex of mice 2 weeks post-RPC, which revealed 136 differentially expressed genes. The majority of genes (116/136) were downregulated upon RPC and clustered into biological processes involved in transcription, synaptic signaling, and neurotransmission. The downregulation in these processes was reminiscent of metabolic depression, an adaptation used by hibernating animals to survive severe ischemic states by downregulating energy-consuming pathways. Thus, to assess metabolism, we used a neuronal-astrocytic co-culture model and measured the cellular respiration rate at the long-term window post-RPC. Remarkably, we observed an increase in glycolysis and mitochondrial respiration efficiency upon RPC. We also observed an increase in the expression of genes involved in pyruvate uptake, TCA cycle, and oxidative phosphorylation, all of which indicated an increased reliance on energy-producing pathways. We then revealed that these nuclear and mitochondrial adaptations, which reduce the reliance on energy-consuming pathways and increase the reliance on energy-producing pathways, are epigenetically coupled through acetyl-CoA metabolism and ultimately increase baseline ATP levels. This increase in ATP would then allow the brain, a highly metabolic organ, to endure prolonged durations of energy deprivation encountered during cerebral ischemia.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
BACKGROUND AND PURPOSE—Prophylactic treatments that afford neuroprotection against stroke may emerge from the field of preconditioning. Resveratrol mimics ischemic preconditioning, reducing ischemic ...brain injury when administered 2 days before global ischemia in rats. This protection is linked to silent information regulator 2 homologue 1 (Sirt1) and enhanced mitochondrial function possibly through its repression of uncoupling protein 2. Brain-derived neurotrophic factor (BDNF) is another neuroprotective protein associated with Sirt1. In this study, we sought to identify the conditions of resveratrol preconditioning (RPC) that most robustly induce neuroprotection against focal ischemia in mice.
METHODS—We tested 4 different RPC paradigms against a middle cerebral artery occlusion model of stroke. Infarct volume and neurological score were calculated 24 hours after middle cerebral artery occlusion. Sirt1-chromatin binding was evaluated by ChIP-qPCR. Percoll gradients were used to isolate synaptic fractions, and changes in protein expression were determined via Western blot analysis. BDNF concentration was measured using a BDNF-specific ELISA assay.
RESULTS—Although repetitive RPC induced neuroprotection from middle cerebral artery occlusion, strikingly one application of RPC 14 days before middle cerebral artery occlusion showed the most robust protection, reducing infarct volume by 33% and improving neurological score by 28%. Fourteen days after RPC, Sirt1 protein was increased 1.5-fold and differentially bound to the uncoupling protein 2 and BDNF promoter regions. Accordingly, synaptic uncoupling protein 2 level decreased by 23% and cortical BDNF concentration increased 26%.
CONCLUSIONS—RPC induces a novel extended window of ischemic tolerance in the brain that lasts for at least 14 days. Our data suggest that this tolerance may be mediated by Sirt1 through upregulation of BDNF and downregulation of uncoupling protein 2.
Display omitted
•Glucose production of the thermochemical WT of five types of biomass is predicted.•The statistical evaluations of ANOVA and RSM are applied.•AI analysis of NN, MARS, and DT models ...are successfully utilized in the bioenergy field.•The predicted highest glucose concentration is 15.216 g·L-1.•The relative error between the prediction and the experiment by the NN model is 5.55%.
Artificial intelligence (AI) has become the future trend for prediction after the data is provided to machine learning. This study uses data analysis to optimize the experiment, find the best-operating conditions, and obtain the maximum glucose concentration for bioethanol production where wet torrefaction (WT) is used to perform biomass pretreatment. Forty-nine (49) sets of data are split into training and test data in the ratio of 7:4. Glucose concentrations from five different feedstocks are trained and predicted using a neural network (NN) and multivariate adaptive regression splines (MARS), followed by a decision tree (DT) to predict the classification of the materials. The predicted NN results are better than MARS, so the NN training is used for the glucose prediction along with the Box-Behnken design (BBD) experiment. The BBD experiment is performed with the parameters of temperature (170, 175, and 180 °C), reaction time (10, 20, and 30 min), and sulfuric acid concentration (0, 0.01, and 0.02 M) for the WT of sorghum distillery residue. By adding the BBD experimental data in NN training, the fit quality of the model is improved to 99.78 %. The NN model predicts that the highest glucose concentration occurring at the optimal conditions (i.e., 173 °C, 10.5 min, and 0.02 M sulfuric acid) is 15.216 g/L with a relative error of 5.55 % between the prediction and experiment. These resuts indicate that NN is an appropriate approach to predicting glucose production from biomass WT for bioethanol production. Additionally, the analysis of variance (ANOVA) evaluation shows that the order of the vital parameter for glucose concentration is sulfuric acid, followed by reaction time and temperature.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
PDF
