Examining the Mediating Role of Strategic Integration of Purchasing, And Advance Purchasing Practices in the Relationship between Purchasing Operational Performance and IT Investment in Purchasing

The main purpose of the current study is to investigate the mediating role of strategic integration of purchasing, and advance purchasing practices in the relationship between purchasing operational performance and IT investment in purchasing. In this research, some other practices have been considered including involvement of suppliers, evaluation and assessment of suppliers and integration of logistics. Strategic integration of purchasing is referred as the degree to which the strategic relevance of purchasing function is recognized by a company. This has been regarded as an important antecedent of supply management practices and advanced purchasing. In the relation of performance, supply and purchasing practices and IT investments, one of the important factors is strategic integration of purchasing. The study has used survey-based method and data is collected by the aid of questionnaire. The collected data is analyzed with the SEM-PLS. The findings of the study have shown agreement with the proposed results. In author knowledge it is among the pioneering studies on the issues related to strategic integration of purchasing, advance purchasing practices, purchasing operational performance and IT investment in purchasing. This study will provide guidelines to policymakers, researchers and corporate personnel in understanding the relationship between strategic integration of purchasing, advance purchasing practices, purchasing operational performance and IT investment in purchasing

The behaviour of e-commerce users: An empirical investigation of online shopping

This paper investigates the relationship between information and communication used by users on electronic commerce platforms. This study is underpinned by the Theory of Reasoned Action (TRA) to understand the factors contributing to electronic users' intention to use online shopping platforms. The primary data was collected using a self-administrated online survey from 422 respondents of online electronic commerce shopping users and analyzed using Statistical Packages for Social Science (SPSS) version 28. Empirically, this study shows that trust between e-commerce users in the digital platform as a medium, consumers’ intention to use the digital platform to make purchases  and consumers’ behavioural attitudes significantly influence consumers’ intention to use online shopping platforms. The study's premises on user trust are beneficial for regulators, online business owners and the government because they help them identify the traits that give customers more confidence to use electronic commerce transactions. This study suggests that users’ trust in the information provided when dealing through electronic commerce transactions is vital for the parties involved. This study provides a theoretical framework for future research to examine the effect of these factors and determine the influence of  diversification on electronic commerce behaviour

Neural networks for genetic epidemiology: past, present, and future

During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN) are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes

Possible Associations of NTRK2 Polymorphisms with Antidepressant Treatment Outcome: Findings from an Extended Tag SNP Approach

Background: Data from clinical studies and results from animal models suggest an involvement of the neurotrophin system in the pathology of depression and antidepressant treatment response. Genetic variations within the genes coding for the brain-derived neurotrophic factor (BDNF) and its key receptor Trkb (NTRK2) may therefore influence the response to antidepressant treatment. Methods: We performed a single and multi-marker association study with antidepressant treatment outcome in 398 depressed Caucasian inpatients participating in the Munich Antidepressant Response Signature (MARS) project. Two Caucasian replication samples (N = 249 and N = 247) were investigated, resulting in a total number of 894 patients. 18 tagging SNPs in the BDNF gene region and 64 tagging SNPs in the NTRK2 gene region were genotyped in the discovery sample; 16 nominally associated SNPs were tested in two replication samples. Results: In the discovery analysis, 7 BDNF SNPs and 9 NTRK2 SNPs were nominally associated with treatment response. Three NTRK2 SNPs (rs10868223, rs1659412 and rs11140778) also showed associations in at least one replication sample and in the combined sample with the same direction of effects ($P_{corr}$ = .018, $P_{corr}$ = .015 and $P_{corr}$ = .004, respectively). We observed an across-gene BDNF-NTRK2 SNP interaction for rs4923468 and rs1387926. No robust interaction of associated SNPs was found in an analysis of BDNF serum protein levels as a predictor for treatment outcome in a subset of 93 patients. Conclusions/Limitations: Although not all associations in the discovery analysis could be unambiguously replicated, the findings of the present study identified single nucleotide variations in the BDNF and NTRK2 genes that might be involved in antidepressant treatment outcome and that have not been previously reported in this context. These new variants need further validation in future association studies

Comparative Linkage Meta-Analysis Reveals Regionally-Distinct, Disparate Genetic Architectures: Application to Bipolar Disorder and Schizophrenia

New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for ”missing heritability.” However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP-based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1–5% MAF) and rare (<1%) variants are of great importance. Of direct relevance, we have available an accumulated wealth of linkage data collected through traditional genetic methods over several decades, the full value of which has not been exhausted. To that end, we compare results from two different linkage meta-analysis methods—GSMA and MSP—applied to the same set of 13 bipolar disorder and 16 schizophrenia GWLS datasets. Interestingly, we find that the two methods implicate distinct, largely non-overlapping, genomic regions. Furthermore, based on the statistical methods themselves and our contextualization of these results within the larger genetic literatures, our findings suggest, for each disorder, distinct genetic architectures may reside within disparate genomic regions. Thus, comparative linkage meta-analysis (CLMA) may be used to optimize low-frequency and rare variant discovery in the modern genomic era

Why Pleiotropic Interventions are Needed for Alzheimer's Disease

Alzheimer's disease (AD) involves a complex pathological cascade thought to be initially triggered by the accumulation of β-amyloid (Aβ) peptide aggregates or aberrant amyloid precursor protein (APP) processing. Much is known of the factors initiating the disease process decades prior to the onset of cognitive deficits, but an unclear understanding of events immediately preceding and precipitating cognitive decline is a major factor limiting the rapid development of adequate prevention and treatment strategies. Multiple pathways are known to contribute to cognitive deficits by disruption of neuronal signal transduction pathways involved in memory. These pathways are altered by aberrant signaling, inflammation, oxidative damage, tau pathology, neuron loss, and synapse loss. We need to develop stage-specific interventions that not only block causal events in pathogenesis (aberrant tau phosphorylation, Aβ production and accumulation, and oxidative damage), but also address damage from these pathways that will not be reversed by targeting prodromal pathways. This approach would not only focus on blocking early events in pathogenesis, but also adequately correct for loss of synapses, substrates for neuroprotective pathways (e.g., docosahexaenoic acid), defects in energy metabolism, and adverse consequences of inappropriate compensatory responses (aberrant sprouting). Monotherapy targeting early single steps in this complicated cascade may explain disappointments in trials with agents inhibiting production, clearance, or aggregation of the initiating Aβ peptide or its aggregates. Both plaque and tangle pathogenesis have already reached AD levels in the more vulnerable brain regions during the “prodromal” period prior to conversion to “mild cognitive impairment (MCI).” Furthermore, many of the pathological events are no longer proceeding in series, but are going on in parallel. By the MCI stage, we stand a greater chance of success by considering pleiotropic drugs or cocktails that can independently limit the parallel steps of the AD cascade at all stages, but that do not completely inhibit the constitutive normal functions of these pathways. Based on this hypothesis, efforts in our laboratories have focused on the pleiotropic activities of omega-3 fatty acids and the anti-inflammatory, antioxidant, and anti-amyloid activity of curcumin in multiple models that cover many steps of the AD pathogenic cascade (Cole and Frautschy, Alzheimers Dement 2:284–286, 2006)

Eosinophils in glioblastoma biology

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. The development of this malignant glial lesion involves a multi-faceted process that results in a loss of genetic or epigenetic gene control, un-regulated cell growth, and immune tolerance. Of interest, atopic diseases are characterized by a lack of immune tolerance and are inversely associated with glioma risk. One cell type that is an established effector cell in the pathobiology of atopic disease is the eosinophil. In response to various stimuli, the eosinophil is able to produce cytotoxic granules, neuromediators, and pro-inflammatory cytokines as well as pro-fibrotic and angiogenic factors involved in pathogen clearance and tissue remodeling and repair. These various biological properties reveal that the eosinophil is a key immunoregulatory cell capable of influencing the activity of both innate and adaptive immune responses. Of central importance to this report is the observation that eosinophil migration to the brain occurs in response to traumatic brain injury and following certain immunotherapeutic treatments for GBM. Although eosinophils have been identified in various central nervous system pathologies, and are known to operate in wound/repair and tumorstatic models, the potential roles of eosinophils in GBM development and the tumor immunological response are only beginning to be recognized and are therefore the subject of the present review

Convergent functional genomic studies of omega-3 fatty acids in stress reactivity, bipolar disorder and alcoholism

Omega-3 fatty acids have been proposed as an adjuvant treatment option in psychiatric disorders. Given their other health benefits and their relative lack of toxicity, teratogenicity and side effects, they may be particularly useful in children and in females of child-bearing age, especially during pregnancy and postpartum. A comprehensive mechanistic understanding of their effects is needed. Here we report translational studies demonstrating the phenotypic normalization and gene expression effects of dietary omega-3 fatty acids, specifically docosahexaenoic acid (DHA), in a stress-reactive knockout mouse model of bipolar disorder and co-morbid alcoholism, using a bioinformatic convergent functional genomics approach integrating animal model and human data to prioritize disease-relevant genes. Additionally, to validate at a behavioral level the novel observed effects on decreasing alcohol consumption, we also tested the effects of DHA in an independent animal model, alcohol-preferring (P) rats, a well-established animal model of alcoholism. Our studies uncover sex differences, brain region-specific effects and blood biomarkers that may underpin the effects of DHA. Of note, DHA modulates some of the same genes targeted by current psychotropic medications, as well as increases myelin-related gene expression. Myelin-related gene expression decrease is a common, if nonspecific, denominator of neuropsychiatric disorders. In conclusion, our work supports the potential utility of omega-3 fatty acids, specifically DHA, for a spectrum of psychiatric disorders such as stress disorders, bipolar disorder, alcoholism and beyond