Mirror protected Dirac fermions on a Weyl semimetal NbP surface

The first Weyl semimetal was recently discovered in the NbP class of compounds. Although the topology of these novel materials has been identified, the surface properties are not yet fully understood. By means of scanning tunneling spectroscopy, we find that NbPs (001) surface hosts a pair of Dirac cones protected by mirror symmetry. Through our high resolution spectroscopic measurements, we resolve the quantum interference patterns arising from these novel Dirac fermions, and reveal their electronic structure, including the linear dispersions. Our data, in agreement with our theoretical calculations, uncover further interesting features of the Weyl semimetal NbPs already exotic surface. Moreover, we discuss the similarities and distinctions between the Dirac fermions here and those in topological crystalline insulators in terms of symmetry protection and topology

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Chemical Characteristics-Based Evolution of Groundwater in Tailan River Basin, Xinjiang, China

Groundwater plays an important role in ecological environment protection in arid and semi-arid areas. Therefore, understanding the characteristics of hydrochemical evolution is of great significance for the sustainable use of groundwater in the area of the Tailan River Basin. The Tailan River Basin is located in an arid, ecologically sensitive area in western China. In this study, we collected 42 groups of representative water samples from the Tailan River Basin and analyzed the chemical distribution in the groundwater using mathematical statistics, Piper and Gibbs diagrams, ion ratio analysis, and hydrogeochemical simulation methods. We also discussed the water–rock interactions in the groundwater hydrochemical evolutionary process. The results were as follows: (1) The chemical types of groundwater changed from HCO3·SO4-Ca·Na to SO4·Cl-Na·Ca, Cl·SO4-Na, and Cl-Na, and the total dissolved solids content increased from less than 1 g/L to more than 40 g/L from the gravel plain to the fine soil plain. (2) The Gibbs diagram, the ion ratio analysis, and the saturation index showed that the groundwater chemical characteristics in the study area were mainly controlled by water–rock interactions, as well as evaporation and concentration. Along the runoff of groundwater, halite and gypsum were dissolved. Nevertheless, dolomite and calcite precipitated. The relationship between the chlor-alkali index and [(Na+ + K+)-Cl−] and [(Ca2+ + Mg2+)-(HCO3− + SO42−)] indicated that cation exchange also affects the chemical composition of groundwater in the area. (3) Through reverse hydrogeochemical simulation, the main water–rock effect of the groundwater runoff process revealed by qualitative analysis was quantitatively verified

Attention-Embedded Triple-Fusion Branch CNN for Hyperspectral Image Classification

Hyperspectral imaging (HSI) is widely used in various fields owing to its rich spectral information. Nonetheless, the high dimensionality of HSI and the limited number of labeled data remain significant obstacles to HSI classification technology. To alleviate the above problems, we propose an attention-embedded triple-branch fusion convolutional neural network (AETF-Net) for an HSI classification. The network consists of a spectral attention branch, a spatial attention branch, and a multi-attention fusion branch (MAFB). The spectral branch introduces the cross-channel attention to alleviate the band redundancy problem in high dimensions, while the spatial branch preserves the location information of features and eliminates interfering image elements by a bi-directional spatial attention module. These pre-extracted spectral and spatial attention features are then embedded into a novel MAFB with large kernel decomposition technique. The proposed AETF-Net achieves multi-attention features reuse and extracts more representative and discriminative features. Experimental results on three well-known datasets demonstrate the superiority of the method AETF-Net

Chiral Majorana Fermion Modes on the Surface of Superconducting Topological Insulators

The surface of superconducting topological insulators (STIs) has been recognized as an effective $p\pm ip$ superconductivity platform for realizing elusive Majorana fermions. Chiral Majorana modes (CMMs), which are different from Majorana bound states localized at points, can be achieved readily in experiments by depositing a ferromagnetic overlayer on top of the STI surface. Here we simulate this heterostructure by employing a realistic tight-binding model and show that the CMM appears on the edge of the ferromagnetic islands only after the superconducting gap is inverted by the exchange coupling between the ferromagnet and the STI. In addition, multiple CMMs can be generated by tuning the chemical potential of the topological insulator. These results can be applied to both proximity-effect induced superconductivity in topological insulators and intrinsic STI compounds such as PbTaSe$_2$, BiPd and their chemical analogues, providing a route to engineering CMMs in those materials

Involvement of endothelial CK2 in the radiation induced perivascular resistant niche (PVRN) and the induction of radioresistance for non-small cell lung cancer (NSCLC) cells

Abstract Background Tumor microenvironment (TME) plays a vital role in determining the outcomes of radiotherapy. As an important component of TME, vascular endothelial cells are involved in the perivascular resistance niche (PVRN), which is formed by inflammation or cytokine production induced by ionizing radiation (IR). Protein kinase CK2 is a constitutively active serine/threonine kinase which plays a vital role in cell proliferation and inflammation. In this study, we investigated the potential role of CK2 in PVRN after IR exposure. Result Specific CK2 inhibitors, Quinalizarin and CX-4945, were employed to effectively suppressed the kinase activity of CK2 in human umbilical vein endothelial cells (HUVECs) without affecting their viability. Results showing that conditioned medium from IR-exposed HUVECs increased cell viability of A549 and H460 cells, and the pretreatment of CK2 inhibitors slowed down such increment. The secretion of IL-8 and IL-6 in HUVECs was induced after exposure with IR, but significantly inhibited by the addition of CK2 inhibitors. Furthermore, IR exposure elevated the nuclear phosphorylated factor-κB (NF-κB) p65 expression in HUVECs, which was a master factor regulating cytokine production. But when pretreated with CK2 inhibitors, such elevation was significantly suppressed. Conclusion This study indicated that protein kinase CK2 is involved in the key process of the IR induced perivascular resistant niche, namely cytokine production, by endothelial cells, which finally led to radioresistance of non-small cell lung cancer cells. Thus, the inhibition of CK2 may be a promising way to improve the outcomes of radiation in non-small cell lung cancer cells

Table_1_Alterations and correlations of gut microbiota, fecal, and serum metabolome characteristics in a rat model of alcohol use disorder.XLSX

BackgroundGrowing evidence suggests the gut microbiota and metabolites in serum or fecal may play a key role in the process of alcohol use disorder (AUD). However, the correlations of gut microbiota and metabolites in both feces and serum in AUD subjects are not well understood.MethodsWe established a rat model of AUD by a chronic intermittent ethanol voluntary drinking procedure, then the AUD syndromes, the gut microbiota, metabolomic profiling in feces and serum of the rats were examined, and correlations between gut microbiota and metabolites were analyzed.ResultsEthanol intake preference increased and maintained at a high level in experimental rats. Anxiety-like behaviors was observed by open field test and elevated plus maze test after ethanol withdraw, indicating that the AUD rat model was successfully developed. The full length 16S rRNA gene sequencing showed AUD significantly changed the β-diversity of gut microbial communities, and significantly decreased the microbial diversity but did not distinctly impact the microbial richness. Microbiota composition significantly changed in AUD rats, such as the abundance of Romboutsia and Turicibacter were significantly increased, whereas uncultured_bacterium_o_Mollicutes_RF39 was decreased. In addition, the untargeted metabolome analysis revealed that many metabolites in both feces and serum were altered in the AUD rats, especially involved in sphingolipid metabolism and glycerophospholipid metabolism pathways. Finally, multiple correlations among AUD behavior, gut microbiota and co-changed metabolites were identified, and the metabolites were directly correlated with the gut microbiota and alcohol preference.ConclusionThe altered metabolites in feces and serum are important links between the gut microbiota dysbiosis and alcohol preference in AUD rats, and the altered gut microbiota and metabolites can be potentially new targets for treating AUD.</p

Data_Sheet_1_Alterations and correlations of gut microbiota, fecal, and serum metabolome characteristics in a rat model of alcohol use disorder.PDF

BackgroundGrowing evidence suggests the gut microbiota and metabolites in serum or fecal may play a key role in the process of alcohol use disorder (AUD). However, the correlations of gut microbiota and metabolites in both feces and serum in AUD subjects are not well understood.MethodsWe established a rat model of AUD by a chronic intermittent ethanol voluntary drinking procedure, then the AUD syndromes, the gut microbiota, metabolomic profiling in feces and serum of the rats were examined, and correlations between gut microbiota and metabolites were analyzed.ResultsEthanol intake preference increased and maintained at a high level in experimental rats. Anxiety-like behaviors was observed by open field test and elevated plus maze test after ethanol withdraw, indicating that the AUD rat model was successfully developed. The full length 16S rRNA gene sequencing showed AUD significantly changed the β-diversity of gut microbial communities, and significantly decreased the microbial diversity but did not distinctly impact the microbial richness. Microbiota composition significantly changed in AUD rats, such as the abundance of Romboutsia and Turicibacter were significantly increased, whereas uncultured_bacterium_o_Mollicutes_RF39 was decreased. In addition, the untargeted metabolome analysis revealed that many metabolites in both feces and serum were altered in the AUD rats, especially involved in sphingolipid metabolism and glycerophospholipid metabolism pathways. Finally, multiple correlations among AUD behavior, gut microbiota and co-changed metabolites were identified, and the metabolites were directly correlated with the gut microbiota and alcohol preference.ConclusionThe altered metabolites in feces and serum are important links between the gut microbiota dysbiosis and alcohol preference in AUD rats, and the altered gut microbiota and metabolites can be potentially new targets for treating AUD.</p