Does culture matter? Cultural influences and IT governance integration mechanism

This paper aims to contribute to the conceptualization and contextualization of IT governance (ITG) by exploring the potential influences of national culture on ITG integration mechanisms. We address the lack of understanding towards the influences that culture may have on ITG in previous literature and present a framework to examine whether and how cultural intervention effects ITG performance. Conventional themes in ITG studies pay more attention to the structure of decision-making authorities. This paper focuses on the paradigm of integrative coordination. Through the lens of the resource-based view (RBV), we conceptualize ITG as a systemic set of firm-specific resources in IT value creation; whereas the complementarity of national culture to ITG is conceptualized as a type of country-specific resource. The propositions presented are expected to enrich the understanding of ITG integration mechanisms and IT value creation and benefit the cross-country transfer of ITG concepts and practice

Demographics and Medication Use of Patients with Late-Onset Alzheimer's Disease in Hong Kong

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly population. However, epidemiological studies on the demographics of AD in Hong Kong population are lacking. OBJECTIVE: We investigated the demographics, comorbidities, mortality rates, and medication use of patients with AD in Hong Kong to understand how the disease has been managed locally. METHODS: This was a collaborative study of The Hong Kong University of Science and Technology and the Hospital Authority Data Collaboration Lab. We analyzed the demographic data, clinical records, diagnoses, and medication records of patients with AD under the care of the Hospital Authority between January 1, 2007 and December 31, 2017. RESULTS: We identified 23,467 patients diagnosed with AD. The median age at diagnosis was 84 years old, and 71% of patients were female. The most common comorbidity was hypertension (52.6%). 39.9% of patients received medications for dementia; of those, 68.4% had taken those medications for >  1 year. Compared to nonusers, long-term AD medication users had a significantly younger age of AD onset and were taking more lipid-regulating medication, diabetes medication, or antidepressants. Surprisingly, the use of antipsychotics in patients with AD was quite common; 50.7% of patients had received any type of antipsychotic during disease progression. CONCLUSION: This study provides detailed information on the demographics and medication use of patients with AD in Hong Kong. The data from this AD cohort will aid our future research aiming to identify potential AD risk factors and associations between AD and other diseases

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction

BACKGROUND: The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. RESULTS: The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. CONCLUSION: Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

High-level expression of Rad51 is an independent prognostic marker of survival in non-small-cell lung cancer patients

High-level expression of Rad51, a key factor in homologous recombination, has been observed in a variety of human malignancies. This study was aimed to evaluate Rad51 expression to serve as prognostic marker in non-small-cell lung cancer (NSCLC). A total of 383 non-small-cell lung tumours were analysed immunohistochemically on NSCLC tissue microarrays. High-level Rad51 expression was observed in 29.4% (100 out of 340) of cases. Patients whose tumours displayed high-level Rad51 expression showed a significantly shorter median survival time of 19 vs 68 months (P<0.0001, log-rank test). Similarly T status, N status, M status, clinical stage and histological tumour grade were significant prognostic markers in univariate Cox survival analysis. Importantly, Rad51 expression (P<0.0001) together with tumour differentiation (P<0.009), clinical stage (P=0.004) and N status (P=0.0001) proved to be independent prognostic parameters in multivariate analysis. Rad51 expression predicted the outcome of squamous cell cancer as well as adenocarcinoma of the lung. Our results suggest that Rad51 expression provides additional prognostic information for surgically treated NSCLC patients. We hypothesise that the decreased survival of NSCLC patients with high-level expression of Rad51 is related to an enhanced propensity of tumour cells for survival, antiapoptosis and chemo-/radioresistance

An abrupt weakening of the subpolar gyre as trigger of Little Ice Age-type episodes

We investigate the mechanism of a decadal-scale weakening shift in the strength of the subpolar gyre (SPG) that is found in one among three last millennium simulations with a state-of-the-art Earth system model. The SPG shift triggers multicentennial anomalies in the North Atlantic climate driven by long-lasting internal feedbacks relating anomalous oceanic and atmospheric circulation, sea ice extent, and upper-ocean salinity in the Labrador Sea. Yet changes throughout or after the shift are not associated with a persistent weakening of the Atlantic Meridional Overturning Circulation or shifts in the North Atlantic Oscillation. The anomalous climate state of the North Atlantic simulated after the shift agrees well with climate reconstructions from within the area, which describe a transition between a stronger and weaker SPG during the relatively warm medieval climate and the cold Little Ice Age respectively. However, model and data differ in the timing of the onset. The simulated SPG shift is caused by a rapid increase in the freshwater export from the Arctic and associated freshening in the upper Labrador Sea. Such freshwater anomaly relates to prominent thickening of the Arctic sea ice, following the cluster of relatively small-magnitude volcanic eruptions by 1600 CE. Sensitivity experiments without volcanic forcing can nonetheless produce similar abrupt events; a necessary causal link between the volcanic cluster and the SPG shift can therefore be excluded. Instead, preconditioning by internal variability explains discrepancies in the timing between the simulated SPG shift and the reconstructed estimates for the Little Ice Age onset

RNA Methylation by the MIS Complex Regulates a Cell Fate Decision in Yeast

For the yeast Saccharomyces cerevisiae, nutrient limitation is a key developmental signal causing diploid cells to switch from yeast-form budding to either foraging pseudohyphal (PH) growth or meiosis and sporulation. Prolonged starvation leads to lineage restriction, such that cells exiting meiotic prophase are committed to complete sporulation even if nutrients are restored. Here, we have identified an earlier commitment point in the starvation program. After this point, cells, returned to nutrient-rich medium, entered a form of synchronous PH development that was morphologically and genetically indistinguishable from starvation-induced PH growth. We show that lineage restriction during this time was, in part, dependent on the mRNA methyltransferase activity of Ime4, which played separable roles in meiotic induction and suppression of the PH program. Normal levels of meiotic mRNA methylation required the catalytic domain of Ime4, as well as two meiotic proteins, Mum2 and Slz1, which interacted and co-immunoprecipitated with Ime4. This MIS complex (Mum2, Ime4, and Slz1) functioned in both starvation pathways. Together, our results support the notion that the yeast starvation response is an extended process that progressively restricts cell fate and reveal a broad role of post-transcriptional RNA methylation in these decisions

M-CSF Induces Monocyte Survival by Activating NF-κB p65 Phosphorylation at Ser276 via Protein Kinase C

Macrophage colony-stimulating factor (M-CSF) promotes mononuclear phagocyte survival and proliferation. The transcription factor Nuclear Factor-kappaB (NF-κB) is a key regulator of genes involved in M-CSF-induced mononuclear phagocyte survival and this study focused at identifying the mechanism of NF-κB transcriptional activation. Here, we demonstrate that M-CSF stimulated NF-κB transcriptional activity in human monocyte-derived macrophages (MDMs) and the murine macrophage cell line RAW 264.7. The general protein kinase C (PKC) inhibitor Ro-31-8220, the conventional PKCα/β inhibitor Gö-6976, overexpression of dominant negative PKCα constructs and PKCα siRNA reduced NF-κB activity in response to M-CSF. Interestingly, Ro-31-8220 reduced Ser276 phosphorylation of NF-κBp65 leading to decreased M-CSF-induced monocyte survival. In this report, we identify conventional PKCs, including PKCα as important upstream kinases for M-CSF-induced NF-κB transcriptional activation, NF-κB-regulated gene expression, NF-κB p65 Ser276 phosphorylation, and macrophage survival. Lastly, we find that NF-κB p65 Ser276 plays an important role in basal and M-CSF-stimulated NF-κB activation in human mononuclear phagocytes

Search for the neutral Higgs bosons of the minimal supersymmetric standard model in pp collisions at root s=7 TeV with the ATLAS detector

A search for neutral Higgs bosons of the Minimal Supersymmetric Standard Model (MSSM) is reported. The analysis is based on a sample of proton-proton collisions at a centre-of-mass energy of 7TeV recorded with the ATLAS detector at the Large Hadron Collider. The data were recorded in 2011 and correspond to an integrated luminosity of 4.7 fb-1 to 4.8 fb-1. Higgs boson decays into oppositely-charged muon or τ lepton pairs are considered for final states requiring either the presence or absence of b-jets. No statistically significant excess over the expected background is observed and exclusion limits at the 95% confidence level are derived. The exclusion limits are for the production cross-section of a generic neutral Higgs boson, φ, as a function of the Higgs boson mass and for h/A/H production in the MSSM as a function of the parameters mA and tan β in the mhmax scenario for mA in the range of 90GeV to 500 GeV. Copyright CERN