Stellar Parameters of Main Sequence Turn-off Star Candidates Observed with the LAMOST and Kepler

Main sequence turn-off (MSTO) stars have advantages as indicators of Galactic evolution since their ages could be robustly estimated from atmospheric parameters. Hundreds of thousands of MSTO stars have been selected from the LAMOST Galactic sur- vey to study the evolution of the Galaxy, and it is vital to derive accurate stellar parameters. In this work, we select 150 MSTO star candidates from the MSTO stars sample of Xiang that have asteroseismic parameters and determine accurate stellar parameters for these stars combing the asteroseismic parameters deduced from the Kepler photometry and atmospheric parameters deduced from the LAMOST spectra.With this sample, we examine the age deter- mination as well as the contamination rate of the MSTO stars sample. A comparison of age between this work and Xiang shows a mean difference of 0.53 Gyr (7%) and a dispersion of 2.71 Gyr (28%). The results show that 79 of the candidates are MSTO stars, while the others are contaminations from either main sequence or sub-giant stars. The contamination rate for the oldest stars is much higher than that for the younger stars. The main cause for the high contamination rate is found to be the relatively large systematic bias in the LAMOST surface gravity estimates.Comment: accepted by RA

Zn⁺-O⁻ dual-spin surface states formation by modification of ZnO nanoparticles with diboron compounds

ZnO semiconductor oxides are versatile functional materials that are used in photoelectronics, catalysis, sensing, etc. The Zn⁺–O⁻ surface electronic states of semiconductor oxides were formed on the ZnO surface by Zn 4s and O 2p orbital coupling with the diboron compound’s B 2p orbitals. The formation of spin-coupled surface states was based on the spin–orbit interaction on the interface, which has not been reported before. This shows that the semiconductor oxide’s spin surface states can be modulated by regulating surface orbital energy. The Zn⁺–O⁻ surface electronic states were confirmed by electron spin resonance results, which may help in expanding the fundamental research on spintronics modulation and quantum transport

High-throughput discovery of chemical structure-polarity relationships combining automation and machine learning techniques

As an essential attribute of organic compounds, polarity has a profound influence on many molecular properties such as solubility and phase transition temperature. Thin layer chromatography (TLC) represents a commonly used technique for polarity measurement. However, current TLC analysis presents several problems, including the need for a large number of attempts to obtain suitable conditions, as well as irreproducibility due to non-standardization. Herein, we describe an automated experiment system for TLC analysis. This system is designed to conduct TLC analysis automatically, facilitating high-throughput experimentation by collecting large experimental data under standardized conditions. Using these datasets, machine learning (ML) methods are employed to construct surrogate models correlating organic compounds' structures and their polarity using retardation factor (Rf). The trained ML models are able to predict the Rf value curve of organic compounds with high accuracy. Furthermore, the constitutive relationship between the compound and its polarity can also be discovered through these modeling methods, and the underlying mechanism is rationalized through adsorption theories. The trained ML models not only reduce the need for empirical optimization currently required for TLC analysis, but also provide general guidelines for the selection of conditions, making TLC an easily accessible tool for the broad scientific community

LAMOST observations in the Kepler field. Analysis of the stellar parameters measured with the LASP based on the low-resolution spectra

All of the 14 subfields of the Kepler field have been observed at least once with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST, Xinglong Observatory, China) during the 2012-2014 observation seasons. There are 88,628 reduced spectra with SNR$_g$ (signal-to-noise ratio in g band) $\geq$ 6 after the first round (2012-2014) of observations for the LAMOST-Kepler project (LK-project). By adopting the upgraded version of the LAMOST Stellar Parameter pipeline (LASP), we have determined the atmospheric parameters ($T_{\rm eff}$ , $\log g$, and $\rm [Fe/H]$) and heliocentric radial velocity $v_{\rm rad}$ for 51,406 stars with 61,226 spectra. Compared with atmospheric parameters derived from both high-resolution spectroscopy and asteroseismology method for common stars in Huber et al. (2014), an external calibration of LASP atmospheric parameters was made, leading to the determination of external errors for the giants and dwarfs, respectively. Multiple spectroscopic observations for the same objects of the LK-project were used to estimate the internal uncertainties of the atmospheric parameters as a function of SNR$_g$ with the unbiased estimation method. The LASP atmospheric parameters were calibrated based on both the external and internal uncertainties for the giants and dwarfs, respectively. A general statistical analysis of the stellar parameters leads to discovery of 106 candidate metal-poor stars, 9 candidate very metal-poor stars, and 18 candidate high-velocity stars. Fitting formulae were obtained segmentally for both the calibrated atmospheric parameters of the LK-project and the KIC parameters with the common stars. The calibrated atmospheric parameters and radial velocities of the LK-project will be useful for studying stars in the Kepler field.Comment: 53 pages, 21 figures, 5 tables, Accepted for publication by ApJ

LncRNA ADAMTS9-AS1 knockdown suppresses cell proliferation and migration in glioma through downregulating Wnt/β-catenin signaling pathway

The long non‐coding RNA antisense 1 ADAMTS9-AS1 has been reported to serve as an oncogene or tumor suppressor in several tumors, including colorectal cancer and hepatocellular carcinoma. Nevertheless, the clinical significance and biological behaviors of ADAMTS9-AS1 in glioma still remain unclear. Therefore, the goal of this study was to evaluate the functional roles and potential mechanisms of ADAMTS9-AS1 in glioma cells. Using quantitative real-time PCR analysis, we found that ADAMTS9-AS1 was upregulated in glioma tissues and cells in comparison to corresponding controls. ADAMTS9-AS1 expression level was correlated to tumor size (p=0.005) and WHO grade (p=0.002). Kaplan-Meier analysis and Cox multivariate analysis showed that ADAMTS9-AS1 could serve as an independent prognostic factor affecting the overall survival of glioma patients. Functionally, depletion of ADAMTS9-AS1 significantly suppressed the proliferation, migration and invasion in glioma cell lines (U251 and U87), as shown via CCK-8 assay, Edu corporation assay, wound healing assay and transwell assay. Furthermore, we demonstrated that knockdown of ADAMTS9-AS1 suppressed Wnt1, β-catenin, c-myc and PCNA, while upregulating E-cadherin expression. In conclusion, our data revealed that ADAMTS9-AS1 confers oncogenic function in the progression of glioma, thus targeting ADAMTS9-AS1 might be a promising therapeutic strategy for this disease

Development and validation of a dynamic online nomogram for predicting acute kidney injury in cirrhotic patients upon ICU admission

BackgroundAcute kidney injury (AKI) is one of the most common and deadly complications among cirrhotic patients at intensive care unit (ICU) admission. We aimed to develop and validate a simple and clinically useful dynamic nomogram for predicting AKI in cirrhotic patients upon ICU admission.MethodsWe analyzed the admission data of 4,375 patients with liver cirrhosis in ICU from 2008 to 2019 in the intensive care unit IV (MIMIC-IV) database. The eligible cirrhotic patients were non-randomly divided into derivation (n = 2,188) and validation (n = 2,187) cohorts at a ratio of 1:1, according to the order of admission. The least absolute shrinkage and selection operator regression model was used to identify independent predictors of AKI in the derivation cohort. A dynamic online nomogram was built using multivariate logistic regression analysis in the derivation cohort and then validated in the validation cohort. The C-index, calibration curve, and decision curve analysis were used to assess the nomogram’s discrimination, calibration, and clinical usefulness, respectively.ResultsThe incidence of AKI in 4,375 patients was 71.3%. Ascites, chronic kidney disease, shock, sepsis, diuretic drugs, hepatic encephalopathy, bacterial infections, vasoactive drugs, admission age, total bilirubin, and blood urea nitrogen were identified using the multivariate logistic regression analysis as significant predictors of AKI upon ICU admission. In the derivation cohort, the model showed good discrimination (C-index, 0.786; 95% CI, 0.765–0.806) and good calibration. The model in the validation cohort yielded good discrimination (C-index, 0.774; 95% CI, 0.753–0.795) and good calibration. Decision curve analysis demonstrated that the dynamic online nomogram was clinically useful.ConclusionOur study presents a dynamic online nomogram that incorporates clinical predictors and can be conveniently used to facilitate the individualized prediction of AKI in cirrhotic patients upon ICU admission

Experimental study on wear failure of spindle hook teeth of cotton picker

Introduction: The wear failure of spindle will lead to a decrease in cotton harvesting rate of the cotton picker during field operation and serious wastage.Method: Three types of spindle samples at different installation positions and working areas were obtained through field experiments to explore the wear failure law of spindle hook teeth of cotton picker during field operation. Hardness of hook tooth coating and substrate of spindles were tested, surface and cross-section microstructure of the spindle hook teeth were characterized, and wear area and width of the spindle hook teeth were extracted.Results: Results showed that the hardness of the hook tooth coating is evidently higher than that of the substrate; the average coating hardness of the No. 3 spindle hook teeth reaches the maximum at 1033.6 HV0.1; defects, such as microcracks and micropores, exist in the coating of the three types of spindle hook teeth; and the thickness of the coating is between 70 and 130 μm. The wear area of spindle hook tooth changes exponentially and the wear width changes linearly with the increase of field operation area at the same installation position. The wear area and width of the spindle hook teeth gradually increase with the decrease of the installation height and the wear change of the hook teeth is negatively correlated with the installation height in the same field operation area.Discussion: The wear failure of spindle hook tooth is mainly caused by abrasive, fatigue, and oxidation wear. The results of this study can provide a reference for improving the wear resistance of spindle hook teeth

Effects of Transplanting Bone Marrow Stromal Cells Transfected with CXCL13 on Fracture Healing of Diabetic Rats

Background/Aims: Diabetic fracture have poor treatment and serious complications. Therefore, how to treat diabetic fracture is receiving increasing attention. This study aimed to investigate the effects of transplanting CXCL13-stimulated bone marrow stromal cells (BMSCs) on the fracture healing in diabetic rats. Methods: In vitro, RT-PCR was employed to examine the expression of CXCL13 in BMSCs in high glucose environment. MTT assay and apoptosis assay were utilized to determine the effects of CXCL13 overexpression on the proliferation and apoptosis of BMSCs respectively. ALP staining was applied to detect the ALP activity. In vivo, CXCL13-stimulated BMSCs were transplanted into the fracture sites of diabetic rats. At the 1st week, 2nd weeks, 4th week and 6th week after the operation, bone mineral density (BMD) and callus area measurement, ELISA detection, and HE staining were performed to evaluate the fracture healing. Results: Low BMD and less area of callus in diabetic rats showed that the recovery after fracture was worse in diabetic rats than in non-diabetic rats. Meanwhile, the expression of CXCL13 in serum was lower in diabetic rats than in non-diabetic rats. Overexpression of CXCL13 promoted the proliferation of BMSCs in vitro high glucose environment. After BMSCs transfected with CXCL13 being transplanted into the fracture sites of diabetic rats, it was found that the fracture healing was enhanced and ALP expression in serum became higher. HE staining results further verified the effects of transplantation of BMSCs transfected with CXCL13 on fracture healing in diabetic rats. Conclusion: These finding indicated that CXCL13 may play a critical role in the process of fracture healing, which could provide a deeper insight into molecular targets for the fracture healing in diabetic people