The Age-Redshift Relationship of Old Passive Galaxies

We use 32 age measurements of passively evolving galaxies as a function of redshift to test and compare the standard model ($\Lambda$CDM) with the $R_{\rm h}=ct$ Universe. We show that the latter fits the data with a reduced $\chi^2_{\rm dof}=0.435$ for a Hubble constant $H_{0}= 67.2_{-4.0}^{+4.5}$ km $\rm s^{-1}$ $\rm Mpc^{-1}$. By comparison, the optimal flat $\Lambda$CDM model, with two free parameters (including $\Omega_{\rm m}=0.12_{-0.11}^{+0.54}$ and $H_{0}=94.3_{-35.8}^{+32.7}$ km $\rm s^{-1}$ $\rm Mpc^{-1}$), fits the age-\emph{z} data with a reduced $\chi^2_{\rm dof}=0.428$. Based solely on their $\chi^2_{\rm dof}$ values, both models appear to account for the data very well, though the optimized $\Lambda$CDM parameters are only marginally consistent with those of the concordance model ($\Omega_{\rm m}=0.27$ and $H_{0}= 70$ km $\rm s^{-1}$ $\rm Mpc^{-1}$). Fitting the age-$z$ data with the latter results in a reduced $\chi^2_{\rm dof}=0.523$. However, because of the different number of free parameters in these models, selection tools, such as the Akaike, Kullback and Bayes Information Criteria, favour $R_{\rm h}=ct$ over $\Lambda$CDM with a likelihood of $\sim 66.5\%-80.5\%$ versus $\sim 19.5\%-33.5\%$. These results are suggestive, though not yet compelling, given the current limited galaxy age-$z$ sample. We carry out Monte Carlo simulations based on these current age measurements to estimate how large the sample would have to be in order to rule out either model at a $\sim 99.7\%$ confidence level. We find that if the real cosmology is $\Lambda$CDM, a sample of $\sim 45$ galaxy ages would be sufficient to rule out $R_{\rm h}=ct$ at this level of accuracy, while $\sim 350$ galaxy ages would be required to rule out $\Lambda$CDM if the real Universe were instead $R_{\rm h}=ct$.Comment: 36 pages, 13 figures, 1 table; accepted for publication in The Astronomical Journal. arXiv admin note: text overlap with arXiv:1405.238

A Phenomenological Thermal-Mechanical Viscoelastic Constitutive Modeling for Polypropylene Wood Composites

This paper presents a phenomenological thermal-mechanical viscoelastic constitutive modeling for polypropylene wood composites. Polypropylene (PP) wood composite specimens are compressed at strain rates from 10−4 to 10−2 s−1 and at temperature of , , and , respectively. The mechanical responses are shown to be sensitive both to strain rate and to temperature. Based on the Maxwell viscoelastic model, a nonlinear thermal-mechanical viscoelastic constitutive model is developed for the PP wood composite by decoupling the effect of temperature with that of the strain rate. Corresponding viscoelastic parameters are obtained through curve fitting with experimental data. Then the model is used to simulate thermal compression of the PP wood composite. The predicted theoretical results coincide quite well with experimental data. The proposed constitutive model is then applied to the thermoforming simulation of an automobile interior part with the PP wood composites

Inhibitory effects of total saponins from Ilex pubescens Hook against hydrogen peroxide-induced cardiomyocyte apoptosis

Purpose: To study the protective effects of total saponins from Ilex pubescens Hook (IPTS) against cardiomyocyte apoptosis.Methods: Response surface methodology (RSM) based on Box-Benhnken Design (BBD) was carried out to optimize the extraction of IPTS. Thereafter, H9c2 cell model prepared by hydrogen peroxide (H2O2) treatment was used to investigate the effects of IPTS on cardiomyocyte apoptosis. Cell viability was determined using MTT assay, while the levels of lactate dehydrogenase (LDH), malondialdehyde (MDA), superoxide dismutase (SOD), creatine kinase (CK) and catalase (CAT) were measured as indices of oxidative stress. Expressions of proteins related to apoptosis (caspase-3, Bax and Bcl-2) were measured using Western blot assay.Results: Optimal IPTS extraction was achieved with extraction temperature of 86.6 °C, extraction time of 2.23 h and water: raw material ratio of 10.8 mL/g. IPTS extract, at doses of 200, 400, 600 and 800 μg/mL, significantly increased the viability of H2O2-treated H9c2 cells (p < 0.05), but significantly decreased LDH and CK activities (p < 0.01). It also led to significant increases in SOD and CAT activities, and significant decreases in the levels of MDA in these cells (p < 0.01). There were significant down-regulation of the protein expressions of caspase-3 and Bax (p < 0.01) in IPTS-treated H9c2 cells, as well as significant up-regulation of Bcl-2 protein expression (p < 0.01).Conclusion: These results suggest that IPTS can protect cardiomyocytes against apoptosis via the inhibition of oxidative stress and mitochondria-induced intrinsic apoptosis.Keywords: Ilex pubescens, Total saponins, Cardiomyocytes, Apoptosis, H9c2 cell

New Views on Strand Asymmetry in Insect Mitochondrial Genomes

Strand asymmetry in nucleotide composition is a remarkable feature of animal mitochondrial genomes. Understanding the mutation processes that shape strand asymmetry is essential for comprehensive knowledge of genome evolution, demographical population history and accurate phylogenetic inference. Previous studies found that the relative contributions of different substitution types to strand asymmetry are associated with replication alone or both replication and transcription. However, the relative contributions of replication and transcription to strand asymmetry remain unclear. Here we conducted a broad survey of strand asymmetry across 120 insect mitochondrial genomes, with special reference to the correlation between the signs of skew values and replication orientation/gene direction. The results show that the sign of GC skew on entire mitochondrial genomes is reversed in all species of three distantly related families of insects, Philopteridae (Phthiraptera), Aleyrodidae (Hemiptera) and Braconidae (Hymenoptera); the replication-related elements in the A+T-rich regions of these species are inverted, confirming that reversal of strand asymmetry (GC skew) was caused by inversion of replication origin; and finally, the sign of GC skew value is associated with replication orientation but not with gene direction, while that of AT skew value varies with gene direction, replication and codon positions used in analyses. These findings show that deaminations during replication and other mutations contribute more than selection on amino acid sequences to strand compositions of G and C, and that the replication process has a stronger affect on A and T content than does transcription. Our results may contribute to genome-wide studies of replication and transcription mechanisms

Explainable machine learning-based prediction model for diabetic nephropathy

The aim of this study is to analyze the effect of serum metabolites on diabetic nephropathy (DN) and predict the prevalence of DN through a machine learning approach. The dataset consists of 548 patients from April 2018 to April 2019 in Second Affiliated Hospital of Dalian Medical University (SAHDMU). We select the optimal 38 features through a Least absolute shrinkage and selection operator (LASSO) regression model and a 10-fold cross-validation. We compare four machine learning algorithms, including eXtreme Gradient Boosting (XGB), random forest, decision tree and logistic regression, by AUC-ROC curves, decision curves, calibration curves. We quantify feature importance and interaction effects in the optimal predictive model by Shapley Additive exPlanations (SHAP) method. The XGB model has the best performance to screen for DN with the highest AUC value of 0.966. The XGB model also gains more clinical net benefits than others and the fitting degree is better. In addition, there are significant interactions between serum metabolites and duration of diabetes. We develop a predictive model by XGB algorithm to screen for DN. C2, C5DC, Tyr, Ser, Met, C24, C4DC, and Cys have great contribution in the model, and can possibly be biomarkers for DN

An ortho­rhom­bic polymorph of 1-benzyl-1H-benzimidazole

The title compound, C14H12N2, in contrast to the previously reported monoclinic polymorph [Lei et al. (2009 ▶). Acta Cryst. E65, o2613], crystallizes in the ortho­rhom­bic crystal system. The dihedral angle between the imidazole ring system and the phenyl ring is 76.78 (16)°. Weak C—H⋯N and C—H⋯π inter­actions are observed in the crystal structure

Increased Methylation of the MOR Gene Proximal Promoter in Primary Sensory Neurons Plays a Crucial Role in the Decreased Analgesic Effect of Opioids in Neuropathic Pain

BACKGROUND: The analgesic potency of opioids is reduced in neuropathic pain. However, the molecular mechanism is not well understood. RESULTS: The present study demonstrated that increased methylation of the Mu opioid receptor (MOR) gene proximal promoter (PP) in dorsal root ganglion (DRG) plays a crucial role in the decreased morphine analgesia. Subcutaneous (s.c.), intrathecal (i.t.) and intraplantar (i.pl.), not intracerebroventricular (i.c.v.) injection of morphine, the potency of morphine analgesia was significantly reduced in nerve-injured mice compared with control sham-operated mice. After peripheral nerve injury, we observed a decreased expression of MOR protein and mRNA, accompanied by an increased methylation status of MOR gene PP, in DRG. However, peripheral nerve injury could not induce a decreased expression of MOR mRNA in the spinal cord. Treatment with 5-aza-2′-deoxycytidine (5-aza-dC), inhibited the increased methylation of MOR gene PP and prevented the decreased expression of MOR in DRG, thereby improved systemic, spinal and periphery morphine analgesia. CONCLUSIONS: Altogether, our results demonstrate that increased methylation of the MOR gene PP in DRG is required for the decreased morphine analgesia in neuropathic pain