511 keV galactic line from first-order phase transitions and primordial black holes

Hawking evaporation of primordial black hole (PBH), with mass $3\times 10^{-17} \lesssim M_{\rm PBH}/M_\odot \lesssim 7\times 10^{-17}$ and fractional abundance $0.01 \lesssim f_{\rm PBH} \lesssim 0.5$, well reproduces 511 keV gamma-ray excess from galaxy center. In this work, we investigated the production mechanism of PBHs base on the first-order phase transition induced by quartic effective thermal potential of a scalar field in dark sector. We found the phase transition with vacuum energy, $\mathcal{O}(1)\lesssim B^{1/4}/{\rm MeV} \lesssim \mathcal{O}(100)$, produces the desired PBH mass and abundance fraction. Correlated signatures of gravitational wave and extragalactic gamma-ray from phase transition and black hole evaporation, respectively, are within $\mu$Ares and AMEGO/e-ASTROGAM projected sensitivities

LD2SNPing: linkage disequilibrium plotter and RFLP enzyme mining for tag SNPs

<p>Abstract</p> <p>Background</p> <p>Linkage disequilibrium (LD) mapping is commonly used to evaluate markers for genome-wide association studies. Most types of LD software focus strictly on LD analysis and visualization, but lack supporting services for genotyping.</p> <p>Results</p> <p>We developed a freeware called LD₂SNPing, which provides a complete package of mining tools for genotyping and LD analysis environments. The software provides SNP ID- and gene-centric online retrievals for SNP information and tag SNP selection from dbSNP/NCBI and HapMap, respectively. Restriction fragment length polymorphism (RFLP) enzyme information for SNP genotype is available to all SNP IDs and tag SNPs. Single and multiple SNP inputs are possible in order to perform LD analysis by online retrieval from HapMap and NCBI. An LD statistics section provides <it>D</it>, <it>D'</it>, <it>r</it>², <it>δ</it>_<it>Q</it>, <it>ρ</it>, and the <it>P </it>values of the Hardy-Weinberg Equilibrium for each SNP marker, and Chi-square and likelihood-ratio tests for the pair-wise association of two SNPs in LD calculation. Finally, 2D and 3D plots, as well as plain-text output of the results, can be selected.</p> <p>Conclusion</p> <p>LD₂SNPing thus provides a novel visualization environment for multiple SNP input, which facilitates SNP association studies. The software, user manual, and tutorial are freely available at <url>http://bio.kuas.edu.tw/LD2NPing</url>.</p

Tuning the Photocycle Kinetics of Bacteriorhodopsin in Lipid Nanodiscs

AbstractMonodisperse lipid nanodiscs are particularly suitable for characterizing membrane protein in near-native environment. To study the lipid-composition dependence of photocycle kinetics of bacteriorhodopsin (bR), transient absorption spectroscopy was utilized to monitor the evolution of the photocycle intermediates of bR reconstituted in nanodiscs composed of different ratios of the zwitterionic lipid (DMPC, dimyristoyl phosphatidylcholine; DOPC, dioleoyl phosphatidylcholine) to the negatively charged lipid (DOPG, dioleoyl phosphatidylglycerol; DMPG, dimyristoyl phosphatidylglycerol). The characterization of ion-exchange chromatography showed that the negative surface charge of nanodiscs increased as the content of DOPG or DMPG was increased. The steady-state absorption contours of the light-adapted monomeric bR in nanodiscs composed of different lipid ratios exhibited highly similar absorption features of the retinal moiety at 560 nm, referring to the conservation of the tertiary structure of bR in nanodiscs of different lipid compositions. In addition, transient absorption contours showed that the photocycle kinetics of bR was significantly retarded and the transient populations of intermediates N and O were decreased as the content of DMPG or DOPG was reduced. This observation could be attributed to the negatively charged lipid heads of DMPG and DOPG, exhibiting similar proton relay capability as the native phosphatidylglycerol (PG) analog lipids in the purple membrane. In this work, we not only demonstrated the usefulness of nanodiscs as a membrane-mimicking system, but also showed that the surrounding lipids play a crucial role in altering the biological functions, e.g., the ion translocation kinetics of the transmembrane proteins

New Ventures, Internationalization, and Asymmetric Grin Curve: Analysis of Taiwan’s Big Data

Under globalization, small and medium enterprises (SMEs) that predominate Taiwan’s economy have been primarily original equipment manufacturers (OEMs) continuing to adjust operating strategies in order to extend supply chains and enhance competitiveness. This paper adopts the big data composed of 104,377 Taiwanese manufacturers from the 2011 Industry, Commerce, and Service Census to assess impact of the business life cycle, brand revenue, R&amp;D spending, and internationalization on value creation. Major findings are as follows. First, the link of the firm’s operating years with value creation is characterized by a quadratic U-shaped curve where the minimum point corresponds to 15 years of operation, suggesting a cost of lower value added for new ventures at the early stage of development. Second, a reversed U-shaped curve of value creation is found as regards brand revenue and R&amp;D spending, with the greater impact of the latter. Third, the impact of overseas investment and export expansion is also captured by a reversed U-shaped curve, with greater impact for the former. Fourth, an asymmetric grin curve rather than a smile curve is found in Taiwan’s manufacturers, whose value creation can be strengthened by strategies that focus on the learning curve, internationalization, internet, operating scale, and capital intensity

New Ventures, Internationalization, and Asymmetric Grin Curve: Analysis of Taiwan’s Big Data

Under globalization, small and medium enterprises (SMEs) that predominate Taiwan’s economy have been primarily original equipment manufacturers (OEMs) continuing to adjust operating strategies in order to extend supply chains and enhance competitiveness. This paper adopts the big data composed of 104,377 Taiwanese manufacturers from the 2011 Industry, Commerce, and Service Census to assess impact of the business life cycle, brand revenue, R&D spending, and internationalization on value creation. Major findings are as follows. First, the link of the firm’s operating years with value creation is characterized by a quadratic U-shaped curve where the minimum point corresponds to 15 years of operation, suggesting a cost of lower value added for new ventures at the early stage of development. Second, a reversed U-shaped curve of value creation is found as regards brand revenue and R&D spending, with the greater impact of the latter. Third, the impact of overseas investment and export expansion is also captured by a reversed U-shaped curve, with greater impact for the former. Fourth, an asymmetric grin curve rather than a smile curve is found in Taiwan’s manufacturers, whose value creation can be strengthened by strategies that focus on the learning curve, internationalization, internet, operating scale, and capital intensity

Text-Guided Neural Image Inpainting

Image inpainting task requires filling the corrupted image with contents coherent with the context. This research field has achieved promising progress by using neural image inpainting methods. Nevertheless, there is still a critical challenge in guessing the missed content with only the context pixels. The goal of this paper is to fill the semantic information in corrupted images according to the provided descriptive text. Unique from existing text-guided image generation works, the inpainting models are required to compare the semantic content of the given text and the remaining part of the image, then find out the semantic content that should be filled for missing part. To fulfill such a task, we propose a novel inpainting model named Text-Guided Dual Attention Inpainting Network (TDANet). Firstly, a dual multimodal attention mechanism is designed to extract the explicit semantic information about the corrupted regions, which is done by comparing the descriptive text and complementary image areas through reciprocal attention. Secondly, an image-text matching loss is applied to maximize the semantic similarity of the generated image and the text. Experiments are conducted on two open datasets. Results show that the proposed TDANet model reaches new state-of-the-art on both quantitative and qualitative measures. Result analysis suggests that the generated images are consistent with the guidance text, enabling the generation of various results by providing different descriptions. Codes are available at https://github.com/idealwhite/TDANetComment: ACM MM'2020 (Oral). 9 pages, 4 tables, 7 figure

Neuropeptides Modulate Local Astrocytes to Regulate Adult Hippocampal Neural Stem Cells

Neural stem cells (NSCs) in the dentate gyrus (DG) reside in a specialized local niche that supports their neurogenic proliferation to produce adult-born neurons throughout life. How local niche cells interact at the circuit level to ensure continuous neurogenesis from NSCs remains unknown. Here we report the role of endogenous neuropeptide cholecystokinin (CCK), released from dentate CCK interneurons, in regulating neurogenic niche cells and NSCs. Specifically, stimulating CCK release supports neurogenic proliferation of NSCs through a dominant astrocyte-mediated glutamatergic signaling cascade. In contrast, reducing dentate CCK induces reactive astrocytes, which correlates with decreased neurogenic proliferation of NSCs and upregulation of genes involved in immune processes. Our findings provide novel circuit-based information on how CCK acts on local astrocytes to regulate the key behavior of adult NSCs

Is the level of serum lactate dehydrogenase a potential biomarker for glucose monitoring with type 2 diabetes mellitus?

IntroductionType 2 diabetes mellitus (T2DM) is a metabolic disorder due to defects in insulin secretion or insulin resistance leading to the dysfunction and damage of various organs. To improve the clinical evaluation of short-term blood glycemic variability monitoring, it is critical to identify another blood cell status and nutritional status biomarker that is less susceptible to interference. This study identifies the significance of serum lactate dehydrogenase (LDH) level among T2DM patients treated in outpatient clinics and investigates the relationship of LDH level with other variables.MethodsThis study comprised 72 outpatients with T2DM over 20 years of age. Blood samples were collected followed by a hematological analysis of serum glycated albumin (GA), LDH, fasting blood glucose, glycosylated hemoglobin, C-peptide, and insulin antibodies (insulin Ab).ResultsSerum LDH level was significantly correlated with GA (p &lt; 0.001), C-peptide (p = 0.04), insulin Ab (p = 0.03), and thyroid-stimulating hormone (TSH) levels (p = 0.04). Hence, we performed a linear regression analysis of hematological markers. GA (p &lt; 0.001, r2 = 0.45) and insulin Ab (p &lt; 0.001, r2 = 0.40) were significantly associated with LDH level. Then, we classified patients into low (&lt;200 U/L) and high (≥200 U/L) serum LDH level groups, respectively. GA (p &lt; 0.001), C-peptide (p = 0.001), and TSH (p = 0.03) showed significant differences in patients with high LDH levels compared with those in patients with low LDH levels.ConclusionIn conclusion, we suggested that LDH level was independent of long-term but associated with short-term blood glucose monitoring. The results indicated that changes in serum GA induced cell damage and the abnormal elevation of the serum level of LDH may occur simultaneously with glycemic variability. It has been reported that many biomarkers are being used to observe glucose variability in T2DM. However, LDH could provide a more convenient and faster evaluation of glycemic variability in T2DM

Nanostructured luminescently labeled nucleic acids

Important and emerging trends at the interface of luminescence, nucleic acids and nanotechnology are: (i) the conventional luminescence labeling of nucleic acid nanostructures (e.g. DNA tetrahedron); (ii) the labeling of bulk nucleic acids (e.g. single‐stranded DNA, double‐stranded DNA) with nanostructured luminescent labels (e.g. copper nanoclusters); and (iii) the labeling of nucleic acid nanostructures (e.g. origami DNA) with nanostructured luminescent labels (e.g. silver nanoclusters). This review surveys recent advances in these three different approaches to the generation of nanostructured luminescently labeled nucleic acids, and includes both direct and indirect labeling methods