Empirical extinction coefficients for the GALEX, SDSS, 2MASS and WISE passbands

Using the "standard pair" technique of paring stars of almost nil and high extinction but otherwise of almost identical stellar parameters from the SDSS, and combing the SDSS, GALEX, 2MASS and WISE photometry ranging from the far UV to the mid-IR, we have measured dust reddening in the FUV-NUV, NUV-u, u-g, g-r, r-i, i-z, z-J, J-H, H-Ks, Ks-W1 and W1-W2 colors for thousands of Galactic stars. The measurements, together with the E(B-V) values given by Schlegel et al. (1998), allow us to derive the observed, model-free reddening coefficients for those colors. The results are compared with previous measurements and the predictions of a variety of Galactic reddening laws. We find that 1) The dust reddening map of Schlegel et al. (1998) over-estimates E(B-V) by about 14 per cent, consistent with the recent work of Schlafly et al. (2010) and Schlafly & Finkbeiner (2011); 2) All the new reddening coefficients, except those for NUV-u and u-g, prefer the R(V) = 3.1 Fitzpatrick reddening law rather than the R(V) = 3.1 CCM and O'Donnell (O'Donnell 1994) reddening laws. Using the Ks-band extinction coefficient predicted by the R(V) = 3.1 Fitzpatrick law and the observed reddening coefficients, we have deduced new extinction coefficients for the FUV, NUV, u, g, r, i, z, J, H, W1 and W2 passbands. We recommend that the new reddening and extinction coefficients should be used in the future and an update of the Fitzpatrick reddening law in the UV is probably necessary. We stress however that the FUV- and NUV-band coefficients should be used with caution given their relatively large measurement uncertainties. Finally, potential applications of the "standard pair" technique with the LAMOST Galactic surveys are discussed.Comment: 13 pages, 9 figures, accepted to MNRA

Drug Repurposing in Neurological Diseases: Opportunities and Challenges

Drug repurposing or repositioning refers to “studying of clinically approved drugs in one disease to see if they have therapeutic value and do not trigger side effects in other diseases.” Nowadays, it is a vital drug discovery approach to explore new therapeutic benefits of existing drugs or drug candidates in various human diseases including neurological disorders. This approach overcomes the shortage faced during traditional drug development in grounds of financial support and timeline. It is especially hopeful in some refractory diseases including neurological diseases. The feature that structure complexity of the nervous system and influence of blood–brain barrier permeability often becomes more difficult to develop new drugs in neuropathological conditions than diseases in other organs; therefore, drug repurposing is particularly of utmost importance. In this chapter, we discuss the role of drug repurposing in neurological diseases and make a summarization of repurposing candidates currently in clinical trials for neurological diseases and potential mechanisms as well as preliminary results. Subsequently we also outline drug repurposing approaches and limitations and challenges in the future investigations

Competitive Lotka-Volterra Population Dynamics with Jumps

This paper considers competitive Lotka-Volterra population dynamics with jumps. The contributions of this paper are as follows. (a) We show stochastic differential equation (SDE) with jumps associated with the model has a unique global positive solution; (b) We discuss the uniform boundedness of $p$th moment with $p>0$ and reveal the sample Lyapunov exponents; (c) Using a variation-of-constants formula for a class of SDEs with jumps, we provide explicit solution for 1-dimensional competitive Lotka-Volterra population dynamics with jumps, and investigate the sample Lyapunov exponent for each component and the extinction of our $n$-dimensional model.Comment: 25 page

Empirical metallicity-dependent calibrations of effective temperature against colours for dwarfs and giants based on interferometric data

We present empirical metallicity-dependent calibrations of effective temperature against colours for dwarfs of luminosity classes IV and V and for giants of luminosity classes II and III, based on a collection from the literature of about two hundred nearby stars with direct effective temperature measurements of better than 2.5 per cent. The calibrations are valid for an effective temperature range 3,100 - 10,000 K for dwarfs of spectral types M5 to A0 and 3,100 - 5,700 K for giants of spectral types K5 to G5. A total of twenty-one colours for dwarfs and eighteen colours for giants of bands of four photometric systems, i.e. the Johnson ($UBVR_{\rm J}I_{\rm J}JHK$), the Cousins ($R_{\rm C}I_{\rm C}$), the Sloan Digital Sky Survey (SDSS, $gr$) and the Two Micron All Sky Survey (2MASS, $JHK_{\rm s}$), have been calibrated. Restricted by the metallicity range of the current sample, the calibrations are mainly applicable for disk stars ([Fe/H]$\,\gtrsim\,-1.0$). The normalized percentage residuals of the calibrations are typically 2.0 and 1.5 per cent for dwarfs and giants, respectively. Some systematic discrepancies at various levels are found between the current scales and those available in the literature (e.g. those based on the infrared flux method IRFM or spectroscopy). Based on the current calibrations, we have re-determined the colours of the Sun. We have also investigated the systematic errors in effective temperatures yielded by the current on-going large scale low- to intermediate-resolution stellar spectroscopic surveys. We show that the calibration of colour ($g-K_{\rm s}$) presented in the current work provides an invaluable tool for the estimation of stellar effective temperature for those on-going or upcoming surveys.Comment: 28 pages, 19 figures, 8 tables, accepted for publication in MNRA

Long-range and short-range tumor-stroma networks synergistically contribute to tumor-associated epilepsy

Epileptic seizures are frequently caused by brain tumors. Traditional anti-epileptic treatments do not acquire satisfactory responses. Preoperative and postoperative seizures seriously influence the quality of life of patients. Thus, tumor-associated epilepsy (TAE) is an important subject of the current research. The delineation of the etiology of epileptogenesis in patients with primary brain tumor may help to find the novel and effective drug targets for treating this disease. In this review, we describe the current status of treatment of TAE. More importantly, we focus on the factors that are involved in the functional connectivity between tumors and stromal cells. We propose that there exist two modes, namely, long-range and short-range modes, which likely trigger neuronal hyperexcitation and subsequent epileptic seizures. The long-range mode is referred to as factors released by tumors including glutamate and GABA, binding to the corresponding receptor on the cellular membrane and causing neuronal hyperactivity, while the short-range mode is considered to involve direct intracellular communication between tumor cells and stromas. Gap junctions and tunneling nanotube network are involved in cellular interconnections. Future investigations focused on those two modes may find a potential novel therapeutic target for treating TAE

1-[(2S)-1-Chloro-3-phenyl­propan-2-yl]-2,4,5-triphenyl-1H-imidazole

In the title compound, C30H25ClN2, the chiral center maintains the S configuration of the stating l-phenyl­alaninol. The two phenyl groups closest to the substituted N atom adopt an almost perpendicular orientation relative to the central imidazole ring, with dihedral angles of 88.9 (4) and 84.7 (3)°. The third phenyl group is nearly coplanar with it, making a dihedral angle of 11.0 (5)°

Cotton plants expressing CYP6AE14 double-stranded RNA show enhanced resistance to bollworms

RNA interference (RNAi) plays an important role in regulating gene expression in eukaryotes. Previously, we generated Arabidopsis and tobacco plants expressing double-stranded RNA (dsRNA) targeting a cotton bollworm (Helicoverpa armigera) P450 gene, CYP6AE14. Bollworms fed on transgenic dsCYP6AE14 plants showed suppressed CYP6AE14 expression and reduced growth on gossypol-containing diet (Mao et al., in Nat Biotechnol 25: 1307–1313, 2007). Here we report generation and analysis of dsRNA-expressing cotton (Gossypium hirsutum) plants. Bollworm larvae reared on T2 plants of the ds6-3 line exhibited drastically retarded growth, and the transgenic plants were less damaged by bollworms than the control. Quantitative reverse-transcription polymerase chain reaction (RT-PCR) showed that the CYP6AE14 expression level was reduced in the larvae as early as 4 h after feeding on the transgenic plants; accordingly, the CYP6AE14 protein level dropped. These results demonstrated that transgenic cotton plants expressing dsCYP6AE14 acquired enhanced resistance to cotton bollworms, and that RNAi technology can be used for engineering insect-proof cotton cultivar

ALEX: Towards Effective Graph Transfer Learning with Noisy Labels

Graph Neural Networks (GNNs) have garnered considerable interest due to their exceptional performance in a wide range of graph machine learning tasks. Nevertheless, the majority of GNN-based approaches have been examined using well-annotated benchmark datasets, leading to suboptimal performance in real-world graph learning scenarios. To bridge this gap, the present paper investigates the problem of graph transfer learning in the presence of label noise, which transfers knowledge from a noisy source graph to an unlabeled target graph. We introduce a novel technique termed Balance Alignment and Information-aware Examination (ALEX) to address this challenge. ALEX first employs singular value decomposition to generate different views with crucial structural semantics, which help provide robust node representations using graph contrastive learning. To mitigate both label shift and domain shift, we estimate a prior distribution to build subgraphs with balanced label distributions. Building on this foundation, an adversarial domain discriminator is incorporated for the implicit domain alignment of complex multi-modal distributions. Furthermore, we project node representations into a different space, optimizing the mutual information between the projected features and labels. Subsequently, the inconsistency of similarity structures is evaluated to identify noisy samples with potential overfitting. Comprehensive experiments on various benchmark datasets substantiate the outstanding superiority of the proposed ALEX in different settings.Comment: Accepted by the ACM International Conference on Multimedia (MM) 202

Rare Gingival Metastasis by Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) uncommonly metastasizes to the gingiva, which always means a poor outcome. We reported a rare HCC case with multiple metastases to gingiva, lungs, and brain. A 60-year-old man was initially diagnosed as HCC with metastases to double lungs. He was subjected to a transarterial chemoembolization (TACE) (5-fluorouracil, 750 mg) and two cycles of intravenous chemotherapy (gemcitabine 1.8 g at days 1 and 8, oxaliplatin 200 mg at day 2, every 4 weeks). However, the volume of liver tumor still increased. A bean-size gingival nodule growing with occasional bleeding was also found. TACE (5-fluorouracil 750 mg, perarubicin 40 mg, cisplatin 20 mg) was performed again and an oral sorafenib therapy (400 mg, twice per day) was adopted. The disease maintained relatively stable for about 6 months until a second obvious progress. The gingival nodule was then palliatively excised and identified as a poorly differentiated metastatic HCC by histopathological examination. Best supportive treatments were made since the performance score was too bad. Finally, cerebral metastases occurred and the patient died of systemic failure. Upon review of previous reports, we discussed risk factors, clinical and pathological characteristics, treatments, and prognosis of gingival metastasis by HCC