From time series analysis to a modified ordinary differential equation

In understanding Big Data, people are interested to obtain the trend and dynamics of a given set of temporal data, which in turn can be used to predict possible futures. This paper examines a time series analysis method and an ordinary differential equation approach in modeling the price movements of petroleum price and of three different bank stock prices over a time frame of three years. Computational tests consist of a range of data fitting models in order to understand the advantages and disadvantages of these two approaches. A modified ordinary differential equation model, with different forms of polynomials and periodic functions, is proposed. Numerical tests demonstrated the advantage of the modified ordinary differential equation approach. Computational properties of the modified ordinary differential equation are studied

Research on accurate stereo portrait generation algorithm of scientific research team

In order to smoothly promote the establishment of scientific research projects, accurately identify the excellent scientific research team, and intuitively and comprehensively describe the scientific research team, it is of great significance for the scientific research management department to comprehensively understand and objectively evaluate the scientific research team. At present, the research work on the construction of accurate three-dimensional portrait of scientific research team is relatively less. In view of the practical demand of scientific research management department, this paper proposes an accurate stereo portrait generation algorithm of scientific research team. The algorithm includes three modules: research team identification, research topic extraction and research team portrait generation. Firstly, the leader of the scientific research team is identified based on the iterative middle centrality ranking method, and the members of the scientific research team are identified through the 2-faction and snowball methods, so as to realize the identification of the scientific research team. Then, considering the statistical information of words and the co-occurrence features of words in the research team, the research topics of the research team are extracted to improve the accuracy of research topic extraction. Finally, the research team portrait generation module generates the accurate three-dimensional portrait of the research team through the generation of the research team profile, the construction of the research cooperation relationship, and the construction of the research team topic cloud. The research team is identified on the data set of scientific research achievements, and the accurate three-dimensional portraits of the research team are generated and visualized. Experiments verify the effectiveness of the proposed algorithm

Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer

Background: Colon cancer (CC) is common, and the mortality rate greatly increases as the disease progresses to the metastatic stage. Early detection of metastatic colon cancer (mCC) is crucial for reducing the mortality rate. Most previous studies have focused on the top-ranked differentially expressed transcriptomic biomarkers between mCC and primary CC while ignoring non-differentially expressed genes. Results: This study proposed that the complicated inter-feature correlations could be quantitatively formulated as a complementary transcriptomic view. We used a regression model to formulate the correlation between the expression levels of a messenger RNA (mRNA) and its regulatory transcription factors (TFs). The change between the predicted and real expression levels of a query mRNA was defined as the mqTrans value in the given sample, reflecting transcription regulatory changes compared with the model-training samples. A dark biomarker in mCC is defined as an mRNA gene that is non-differentially expressed in mCC but demonstrates mqTrans values significantly associated with mCC. This study detected seven dark biomarkers using 805 samples from three independent datasets. Evidence from the literature supports the role of some of these dark biomarkers. Conclusions: This study presented a complementary high-dimensional analysis procedure for transcriptome-based biomarker investigations with a case study on mCC

The Risk Factors of Child Lead Poisoning in China: A Meta-Analysis

Background: To investigate the risk factors of child lead poisoning in China. Methods: A document retrieval was performed using MeSH (Medical subject heading terms) and key words. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the studies, and the pooled odd ratios with a 95% confidence interval were used to identify the risk factors. We employed Review Manager 5.2 and Stata 10.0 to analyze the data. Heterogeneity was assessed by both the Chi-square and I2 tests, and publication bias was evaluated using a funnel plot and Egger’s test. Results: Thirty-four articles reporting 13,587 lead-poisoned children met the inclusion criteria. Unhealthy lifestyle and behaviors, environmental pollution around the home and potential for parents’ occupational exposure to lead were risk factors of child lead poisoning in the pooled analyses. Our assessments yielded no severe publication biases. Conclusions: Seventeen risk factors are associated with child lead poisoning, which can be used to identify high-risk children. Health education and promotion campaigns should be designed in order to minimize or prevent child lead poisoning in China

The Neuroprotective Properties of Hericium erinaceus in Glutamate-Damaged Differentiated PC12 Cells and an Alzheimer’s Disease Mouse Model

Hericium erinaceus, an edible and medicinal mushroom, displays various pharmacological activities in the prevention of dementia in conditions such as Parkinson’s and Alzheimer’s disease. The present study explored the neuroprotective effects of H. erinaceus mycelium polysaccharide-enriched aqueous extract (HE) on an l-glutamic acid (l-Glu)-induced differentiated PC12 (DPC12) cellular apoptosis model and an AlCl3 combined with d-galactose-induced Alzheimer’s disease mouse model. The data revealed that HE successfully induced PC12 cell differentiation. A 3 h HE incubation at doses of 50 and 100 µg/mL before 25 mM of l-Glu effectively reversed the reduction of cell viability and the enhancement of the nuclear apoptosis rate in DPC12 cells. Compared with l-Glu-damaged cells, in PC12 cells, HE suppressed intracellular reactive oxygen species accumulation, blocked Ca2+ overload and prevented mitochondrial membrane potential (MMP) depolarization. In the Alzheimer’s disease mouse model, HE administration enhanced the horizontal and vertical movements in the autonomic activity test, improved the endurance time in the rotarod test, and decreased the escape latency time in the water maze test. It also improved the central cholinergic system function in the Alzheimer’s mice, demonstrated by the fact that it dose-dependently enhanced the acetylcholine (Ach) and choline acetyltransferase (ChAT) concentrations in both the serum and the hypothalamus. Our findings provide experimental evidence that HE may provide neuroprotective candidates for treating or preventing neurodegenerative diseases

Insight into the Effects of Adipose Tissue Inflammation Factors on miR-378 Expression and the Underlying Mechanism

Background/Aims: Obesity and the related metabolic syndrome have emerged as major public health issues in modern society. miRNAs have been shown to play key roles in regulating obesity-related metabolic syndrome, and some miRNAs regulated by adiponectin were identified as novel targets for controlling adipose tissue inflammation. miR-378 is a candidate target that was shown to be involved in adipose differentiation, mitochondrial metabolism and systemic energy homeostasis. However, little is known about the regulatory mechanisms of miR-378 expression. To better understand the physiological role of miR-378 in obesity and metabolic syndrome, it is crucial that we understand the regulation of miR-378 gene expression in human adipocytes. Methods: In this study, we investigated the effects of adipokines and inflammatory cytokines on miR-378 expression using Real-time PCR and the potential regulatory mechanisms using luciferase reporter assays and electrophoretic mobility shift assay (EMSA). Results: We found that adipokines and cytokines upregulated miR-378 expression primarily through SREBP and C/EBP binding sites in the miR-378 promoter region. Conclusion: Our findings showed that adipokines induced miR-378 expression and revealed the most likely mechanism of adipokine-induced miR-378 dysregulation in human adipocytes. miRNAs have been shown to function in regulating obesity-related metabolic syndrome, and miR-378 may be a novel target for controlling adipose tissue inflammation. This study offers a theoretical basis for understanding systemic adipose tissue inflammation and may provide new strategies for clinical treatment