A minimal model for excitons within time-dependent density-functional theory

The accurate description of the optical spectra of insulators and semiconductors remains an important challenge for time-dependent density-functional theory (TDDFT). Evidence has been given in the literature that TDDFT can produce bound as well as continuum excitons for specific systems, but there are still many unresolved basic questions concerning the role of dynamical exchange and correlation (xc). In particular, the role of the long spatial range and the frequency dependence of the xc kernel $f_{\rm xc}$ for excitonic binding are still not very well explored. We present a minimal model for excitons in TDDFT, consisting of two bands from a one-dimensional Kronig-Penney model and simple approximate xc kernels, which allows us to address these questions in a transparent manner. Depending on the system, it is found that adiabatic xc kernels can produce a single bound exciton, and sometimes two bound excitons, where the long spatial range of $f_{\rm xc}$ is not a necessary condition. It is shown how the Wannier model, featuring an effective electron-hole interaction, emerges from TDDFT. The collective, many-body nature of excitons is explicitly demonstrated.Comment: 12 pages, 11 figure

Mapping the Milky Way with LAMOST II: the stellar halo

The radial number density and flattening of the Milky Way's stellar halo is measured with $\mathrm{5351}$ metal-poor ([Fe/H]$<-1$) K giants from LAMOST DR3, using a nonparametric method which is model independent and largely avoids the influence of halo substucture. The number density profile is well described by a single power law with index $5.03^{+0.64}_{-0.64}$, and flattening that varies with radius. The stellar halo traced by LAMOST K giants is more flattened at smaller radii, and becomes nearly spherical at larger radii. The flattening, $q$, is about 0.64, 0.8, 0.96 at $r=15$, 20 and 30 kpc (where $r=\sqrt{R^2+\left[Z/q\left(r\right)\right]^2}$), respectively. Moreover, the leading arm of the Sagittarius dwarf galaxy tidal stream in the north, and the trailing arm in the south, are significant in the residual map of density distribution. In addition, an unknown overdensity is identified in the residual map at (R,Z)=(30,15) kpc.Comment: 16 pages, 24 figures, accepted by MNRA

Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions

IMPORTANCE Current approaches to identifying individuals at high risk for opioid overdose target many patients who are not truly at high risk. OBJECTIVE To develop and validate a machine-learning algorithm to predict opioid overdose risk among Medicare beneficiaries with at least 1 opioid prescription. DESIGN, SETTING, AND PARTICIPANTS A prognostic study was conducted between September 1, 2017, and December 31, 2018. Participants (n = 560 057) included fee-for-service Medicare beneficiaries without cancer who filled 1 or more opioid prescriptions from January 1, 2011, to December 31, 2015. Beneficiaries were randomly and equally divided into training, testing, and validation samples. EXPOSURES Potential predictors (n = 268), including sociodemographics, health status, patterns of opioid use, and practitioner-level and regional-level factors, were measured in 3-month windows, starting 3 months before initiating opioids until loss of follow-up or the end of observation. MAIN OUTCOMES AND MEASURES Opioid overdose episodes from inpatient and emergency department claims were identified. Multivariate logistic regression (MLR), least absolute shrinkage and selection operator-type regression (LASSO), random forest (RF), gradient boosting machine (GBM), and deep neural network (DNN) were applied to predict overdose risk in the subsequent 3 months after initiation of treatment with prescription opioids. Prediction performance was assessed using the C statistic and other metrics (eg, sensitivity, specificity, and number needed to evaluate [NNE] to identify one overdose). The Youden index was used to identify the optimized threshold of predicted score that balanced sensitivity and specificity. RESULTS Beneficiaries in the training (n = 186 686), testing (n = 186 685), and validation (n = 186 686) samples had similar characteristics (mean [SD] age of 68.0 [14.5] years, and approximately 63% were female, 82% were white, 35% had disabilities, 41% were dual eligible, and 0.60% had at least 1 overdose episode). In the validation sample, the DNN (C statistic = 0.91; 95% CI, 0.88-0.93) and GBM (C statistic = 0.90; 95% CI, 0.87-0.94) algorithms outperformed the LASSO (C statistic = 0.84; 95% CI, 0.80-0.89), RF (C statistic = 0.80; 95% CI, 0.75-0.84), and MLR (C statistic = 0.75; 95% CI, 0.69-0.80) methods for predicting opioid overdose. At the optimized sensitivity and specificity, DNN had a sensitivity of 92.3%, specificity of 75.7%, NNE of 542, positive predictive value of 0.18%, and negative predictive value of 99.9%. The DNN classified patients into low-risk (76.2%[142 180] of the cohort), medium-risk (18.6%[34 579] of the cohort), and high-risk (5.2%[9747] of the cohort) subgroups, with only 1 in 10 000 in the low-risk subgroup having an overdose episode. More than 90% of overdose episodes occurred in the high-risk and medium-risk subgroups, although positive predictive values were low, given the rare overdose outcome. CONCLUSIONS AND RELEVANCE Machine-learning algorithms appear to perform well for risk prediction and stratification of opioid overdose, especially in identifying low-risk subgroups that have minimal risk of overdose.NIH/National Institute on Drug Abuse [R01DA044985]; Pharmaceutical Research and Manufacturers of America Foundation Research Starter AwardOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

BMP-12 Treatment of Adult Mesenchymal Stem Cells In Vitro Augments Tendon-Like Tissue Formation and Defect Repair In Vivo

We characterized the differentiation of rat bone marrow-derived mesenchymal stem cells (BM-MSCs) into tenocyte-like cells in response to bone morphogenetic protein-12 (BMP-12). BM-MSCs were prepared from Sprague-Dawley rats and cultured as monolayers. Recombinant BMP-12 treatment (10 ng/ml) of BM-MSCs for 12 hours in vitro markedly increased expression of the tenocyte lineage markers scleraxis (Scx) and tenomodulin (Tnmd) over 14 days. Treatment with BMP-12 for a further 12-hour period had no additional effect. Colony formation assays revealed that ∼80% of treated cells and their progeny were Scx- and Tnmd-positive. BM-MSCs seeded in collagen scaffolds and similarly treated with a single dose of BMP-12 also expressed high levels of Scx and Tnmd, as well as type I collagen and tenascin-c. Furthermore, when the treated BM-MSC-seeded scaffolds were implanted into surgically created tendon defects in vivo, robust formation of tendon-like tissue was observed after 21 days as evidenced by increased cell number, elongation and alignment along the tensile axis, greater matrix deposition and the elevated expression of tendon markers. These results indicate that brief stimulation with BMP-12 in vitro is sufficient to induce BM-MSC differentiation into tenocytes, and that this phenotype is sustained in vivo. This strategy of pretreating BM-MSCs with BMP-12 prior to in vivo transplantation may be useful in MSC-based tendon reconstruction or tissue engineering

A TRPV4-dependent neuroimmune axis in the spinal cord promotes neuropathic pain

Microglia, resident macrophages of the CNS, are essential to brain development, homeostasis, and disease. Microglial activation and proliferation are hallmarks of many CNS diseases, including neuropathic pain. However, molecular mechanisms that govern the spinal neuroimmune axis in the setting of neuropathic pain remain incompletely understood. Here, we show that genetic ablation or pharmacological blockade of transient receptor potential vanilloid type 4 (TRPV4) markedly attenuated neuropathic pain-like behaviors in a mouse model of spared nerve injury. Mechanistically, microglia-expressed TRPV4 mediated microglial activation and proliferation and promoted functional and structural plasticity of excitatory spinal neurons through release of lipocalin-2. Our results suggest that microglial TRPV4 channels reside at the center of the neuroimmune axis in the spinal cord, which transforms peripheral nerve injury into central sensitization and neuropathic pain, thereby identifying TRPV4 as a potential new target for the treatment of chronic pain

Dichotomy in the Impact of Elevated Maternal Glucose Levels on Neonatal Epigenome

Context Antenatal hyperglycemia is associated with increased risk of future adverse health outcomes in both mother and child. Variations in offspring's epigenome can reflect the impact and response to in utero glycemic exposure, and may have different consequences for the child. Objective We examined possible differences in associations of basal glucose status and glucose handling during pregnancy with both clinical covariates and offspring cord tissue DNA methylation. Research Design and Methods This study included 830 mother-offspring dyads from the Growing Up in Singapore Towards Healthy Outcomes cohort. The fetal epigenome of umbilical cord tissue was profiled using Illumina HumanMethylation450 arrays. Associations of maternal mid-pregnancy fasting (fasting plasma glucose [FPG]) and 2-hour plasma glucose (2hPG) after a 75-g oral glucose challenge with both maternal clinical phenotypes and offspring epigenome at delivery were investigated separately. Results Maternal age, prepregnancy body mass index, and blood pressure measures were associated with both FPG and 2hPG, whereas Chinese ethnicity (P = 1.9 x 10(-4)), maternal height (P = 1.1 x 10(-4)), pregnancy weight gain (P = 2.2 x 10(-3)), prepregnancy alcohol consumption (P = 4.6 x 10(-4)), and tobacco exposure (P = 1.9 x 10(-3)) showed significantly opposite associations between the 2 glucose measures. Most importantly, we observed a dichotomy in the effects of these glycemic indices on the offspring epigenome. Offspring born to mothers with elevated 2hPG showed global hypomethylation. CpGs most associated with the 2 measures also reflected differences in gene ontologies and had different associations with offspring birthweight. Conclusions Our findings suggest that 2 traditionally used glycemic indices for diagnosing gestational diabetes may reflect distinctive pathophysiologies in pregnancy, and have differential impacts on the offspring's DNA methylome.Peer reviewe

Dichotomy in the Impact of Elevated Maternal Glucose Levels on Neonatal Epigenome

Context Antenatal hyperglycemia is associated with increased risk of future adverse health outcomes in both mother and child. Variations in offspring's epigenome can reflect the impact and response to in utero glycemic exposure, and may have different consequences for the child. Objective We examined possible differences in associations of basal glucose status and glucose handling during pregnancy with both clinical covariates and offspring cord tissue DNA methylation. Research Design and Methods This study included 830 mother-offspring dyads from the Growing Up in Singapore Towards Healthy Outcomes cohort. The fetal epigenome of umbilical cord tissue was profiled using Illumina HumanMethylation450 arrays. Associations of maternal mid-pregnancy fasting (fasting plasma glucose [FPG]) and 2-hour plasma glucose (2hPG) after a 75-g oral glucose challenge with both maternal clinical phenotypes and offspring epigenome at delivery were investigated separately. Results Maternal age, prepregnancy body mass index, and blood pressure measures were associated with both FPG and 2hPG, whereas Chinese ethnicity (P = 1.9 x 10(-4)), maternal height (P = 1.1 x 10(-4)), pregnancy weight gain (P = 2.2 x 10(-3)), prepregnancy alcohol consumption (P = 4.6 x 10(-4)), and tobacco exposure (P = 1.9 x 10(-3)) showed significantly opposite associations between the 2 glucose measures. Most importantly, we observed a dichotomy in the effects of these glycemic indices on the offspring epigenome. Offspring born to mothers with elevated 2hPG showed global hypomethylation. CpGs most associated with the 2 measures also reflected differences in gene ontologies and had different associations with offspring birthweight. Conclusions Our findings suggest that 2 traditionally used glycemic indices for diagnosing gestational diabetes may reflect distinctive pathophysiologies in pregnancy, and have differential impacts on the offspring's DNA methylome.Peer reviewe

E3 Ligase Activity of XIAP RING Domain Is Required for XIAP-Mediated Cancer Cell Migration, but Not for Its RhoGDI Binding Activity

Although an increased expression level of XIAP is associated with cancer cell metastasis, the underlying molecular mechanisms remain largely unexplored. To verify the specific structural basis of XIAP for regulation of cancer cell migration, we introduced different XIAP domains into XIAP−/− HCT116 cells, and found that reconstitutive expression of full length HA-XIAP and HA-XIAP ΔBIR, both of which have intact RING domain, restored β-Actin expression, actin polymerization and cancer cell motility. Whereas introduction of HA-XIAP ΔRING or H467A mutant, which abolished its E3 ligase function, did not show obvious restoration, demonstrating that E3 ligase activity of XIAP RING domain played a crucial role of XIAP in regulation of cancer cell motility. Moreover, RING domain rather than BIR domain was required for interaction with RhoGDI independent on its E3 ligase activity. To sum up, our present studies found that role of XIAP in regulating cellular motility was uncoupled from its caspase-inhibitory properties, but related to physical interaction between RhoGDI and its RING domain. Although E3 ligase activity of RING domain contributed to cell migration, it was not involved in RhoGDI binding nor its ubiquitinational modification