Knowledge expand one’s life: Evidence from Chinese Science Scholars

One of the solutions of healthcare may lie in the analysis of the longevity of scholars by probing the underlying reasons and determining factors. This study sets out to investigate the reasons why scholars in mathematics, physics, and chemistry generally live a longer and healthier life, and in particular, why longer than the common value, by compiling and analyzing data from information on those scholars. The society at large can learn from the research results of this paper which indicate that reading can, to a certain extent, lead to a long and a relatively healthy life

Knowledge expand one’s life: Evidence from Chinese Science Scholars

One of the solutions of healthcare may lie in the analysis of the longevity of scholars by probing the underlying reasons and determining factors. This study sets out to investigate the reasons why scholars in mathematics, physics, and chemistry generally live a longer and healthier life, and in particular, why longer than the common value, by compiling and analyzing data from information on those scholars. The society at large can learn from the research results of this paper which indicate that reading can, to a certain extent, lead to a long and a relatively healthy life

Factors that influence the health of mathematicians, physicists, and chemists: Data obtained from China

Given the practical implications of looking into the health of scholars, it is of great priority to figure out the factors that are generally agreed to be the contributors to sustained health, to which end, this paper sets out to collect the mainstream insight into all possible influencing factors. Three research scheme are proposed in this paper under which basic personal information are collected first from 520 scholars in mathematics, physics, and chemistry for an analysis of their longevity performance via a comparison with common values under the demographic perspective to derive the raw longevity information of the scholars. Also, the ways they manage to maintain health are ascertained, on the basis of which the reasons for their sustained health are provided

Vertical Graphene-Supported NiMo Nanoparticles as Efficient Electrocatalysts for Hydrogen Evolution Reaction under Alkaline Conditions

Water electrolysis as an important and facile strategy to generate hydrogen has attracted great attention, and efficient electrocatalysts play a key role in hydrogen evolution reaction (HER). Herein, vertical graphene (VG)-supported ultrafine NiMo alloy nanoparticles (NiMo@VG@CC) were fabricated successfully via electro-depositing as efficient self-supported electrocatalysts for HER. The introduction of metal Mo optimized the catalytic activity of transition metal Ni. In addition, VG arrays as the three-dimensional (3D) conductive scaffold not only ensured high electron conductivity and robust structural stability, but also endowed the self-supported electrode large specific surface area and exposed more active sites. With the synergistic effect between NiMo alloys and VG, the optimized NiMo@VG@CC electrode exhibited a low overpotential of 70.95 mV at 10 mA cm−2 and a remarkable stable performance over 24 h. This research is anticipated to offer a powerful strategy for the fabrication of high-performance hydrogen evolution catalysts

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort

Abstract Background The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ1–42 are potential early diagnostic markers for probable Alzheimer’s disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. Results The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ1–42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). Conclusions This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta production but also multiple genes enriching several KEGG pathways such as Alzheimer’s disease, colorectal cancer, gliomas, renal cell carcinoma, Huntington’s disease, and others. This study demonstrated that integration of gene-level associations with CMs could yield statistically significant findings to offer valuable biological insights (e.g., functional interaction among the protein products of these genes) and suggest high confidence candidates for subsequent analyses