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3 results

  • Dissecting the association between psychiatric disorders and neurological proteins: a genetic correlation and two-sample bidirectional Mendelian randomization study

  • Huimei Huang, Shiqiang Cheng, Chun’e Li, Bolun Cheng, Li Liu, Xuena Yang, Peilin Meng, Yao Yao, Chuyu Pan, Jingxi Zhang, Huijie Zhang, Yujing Chen, Zhen Zhang, Yan Wen, Yumeng Jia, Feng Zhang
  • Journal:
    Acta Neuropsychiatrica / Volume 34 / Issue 6 / December 2022
    Published online by Cambridge University Press:
    28 March 2022, pp. 311-317
  • Objectives:

    The role of neurological proteins in the development of bipolar disorder (BD) and schizophrenia (SCZ) remains elusive now. The current study aims to explore the potential genetic correlations of plasma neurological proteins with BD and SCZ.

    Methods:

    By using the latest genome-wide association study (GWAS) summary data of BD and SCZ (including 41,917 BD cases, 11,260 SCZ cases, and 396,091 controls) derived from the Psychiatric GWAS Consortium website (PGC) and a recently released GWAS of neurological proteins (including 750 individuals), we performed a linkage disequilibrium score regression (LDSC) analysis to detect the potential genetic correlations between the two common psychiatric disorders and each of the 92 neurological proteins. Two-sample Mendelian randomisation (MR) analysis was then applied to assess the bidirectional causal relationship between the neurological proteins identified by LDSC, BD and SCZ.

    Results:

    LDSC analysis identified one neurological protein, NEP, which shows suggestive genetic correlation signals for both BD (coefficient = −0.165, p value = 0.035) and SCZ (coefficient = −0.235, p value = 0.020). However, those association did not remain significant after strict Bonferroni correction. Two sample MR analysis found that there was an association between genetically predicted level of NEP protein, BD (odd ratio [OR] = 0.87, p value = 1.61 × 10−6) and SCZ (OR = 0.90, p value = 4.04 × 10−6). However, in the opposite direction, there is no genetically predicted association between BD, SCZ, and NEP protein level.

    Conclusion:

    This study provided novel clues for understanding the genetic effects of neurological proteins on BD and SCZ.

  • The Nature and Impact of ZnO Buffer Layers on the Initial Stages of the Hydride Vapor Phase Epitaxy of GAN

  • Shulin Gu, Rong Zhang, Jingxi Sun, Ling Zhang, T. F. Kuech
  • Journal:
    Materials Research Society Internet Journal of Nitride Semiconductor Research / Volume 5 / Issue S1 / 2000
    Published online by Cambridge University Press:
    13 June 2014, pp. 138-144
    Print publication:
    2000
    • Article
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  • The nature and impact of ZnO buffer layers on the initial stages of the hydride vapor phase epitaxy (HVPE) of GaN have been studied by x-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), x-ray diffraction (XRD) and photoluminescence (PL). During pre-growth heating, the surface ZnO layer was found to both desorb from ZnO-coated sapphire and react with the underlying sapphire surface forming a thin ZnAl2O4 alloy layer between ZnO and sapphire surface. This ZnO-derived surface promotes the initial nucleation of the GaN and markedly improves material surface morphology, quality and growth reproducibility.

  • The Chemistry of GaN Growth

  • T.F. Kuech, Shulin Gu, Ramchandra Wate, Ling Zhang, Jingxi Sun, J.A. Dumesic, J.M. Redwing
  • Journal:
    MRS Online Proceedings Library Archive / Volume 639 / 2000
    Published online by Cambridge University Press:
    17 March 2011, G1.1
    Print publication:
    2000

  • The development of new chemically based growth techniques has opened the range of possible GaN applications. This paper reviews some of the challenges in the chemically based growth of GaN and related materials. Ammonothermal-based growth, hydride vapor phase epitaxy and metal organic vapor phase epitaxy (MOVPE) are chemically complex systems wherein the underlying mechanisms of growth are not well understood at present. All these systems require substantial experimental and theoretical efforts to determine the nature and kinetics of GaN growth. In the case of metal organic vapor phase epitaxy, the application of computational techniques based on density functional theory have augmented the more conventional experimental approaches to determining the growth chemistry. These chemical reaction schemes, when combined with computational thermal-fluid models of the reactor environment, provide the opportunity to predict growth rates, uniformity and eve ntually materials properties.