Using the alluvial plot to visualize the network characteristics of 100 top-cited articles on attention-deficit/hyperactivity disorder (ADHD) since 2011: Bibliometric analysis.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a common neuro developmental disorder that affects children and adolescents. It is estimated that the prevalence of ADHD is 7.2% throughout the world. There have been a number of articles published in the literature related to ADHD. However, it remains unclear which countries, journals, subject categories, and articles have the greatest influence. The purpose of this study was to display influential entities in 100 top-cited ADHD-related articles (T100ADHD) on an alluvial plot and apply alluvial to better understand the network characteristics of T100ADHD across entities. METHODS: Using the PubMed and Web of Science (WoS) databases, T100ADHD data since 2011 were downloaded. The dominant entities were compared using alluvial plots based on citation analysis. Based on medical subject headings (MeSH terms) and research areas extracted from PubMed and WoS, social network analysis (SNA) was performed to classify subject categories. To examine the difference in article citations among subject categories and the predictive power of MeSH terms on article citations in T100ADHD, one-way analysis of variance and regression analysis were used. RESULTS: The top 3 countries (the United States, the United Kingdom, and the Netherlands) accounted for 75% of T100ADHD. The most citations per article were earned by Brazil (=415.33). The overall impact factor (IF = citations per 100) of the T100ADHD series is 188.24. The most cited article was written by Polanczyk et al from Brazil, with 772 citations since 2014. The majority of the articles were published and cited in Biol Psychiatry (13%; IF = 174.15). The SNA was used to categorize 6 subject areas. On the alluvial plots, T100ADHD's network characteristics were successfully displayed. There was no difference in article citations among subject categories (F = 1.19, P = .320). The most frequently occurring MeSH terms were physiopathology, diagnosis, and epidemiology. A significant correlation was observed between MeSH terms and the number of article citations (F = 25.36; P < .001). CONCLUSION: Drawing the alluvial plot to display network characteristics in T100ADHD was a breakthrough. Article subject categories can be classified using MeSH terms to predict T100ADHD citations. Bibliometric analyses of 100 top-cited articles can be conducted in the future.

Using the forest plot to compare citation achievements in bibliographic and meta-analysis studies since 2011 using data on PubMed Central: A retrospective study.

BACKGROUND: We saw a steady increase in the number of bibliographic studies published over the years. The reason for this rise is attributed to the better accessibility of bibliographic data and software packages that specialize in bibliographic analyses. Any difference in citation achievements between bibliographic and meta-analysis studies observed so far need to be verified. In this study, we aimed to identify the frequently observed MeSH terms in these 2 types of study and investigate whether the highlighted MeSH terms are strongly associated with one of the study types. METHODS: By searching the PubMed Central database, 5121 articles relevant to bibliometric and meta-analysis studies were downloaded since 2011. Social network analysis was applied to highlight the major MeSH terms of quantitative and statistical methods in these 2 types of studies. MeSH terms were then individually tested for any differences in event counts over the years between study types using odds of 95% confidence intervals for comparison. RESULTS: In these 2 studies, we found that the most productive countries were the United States (19.9%), followed by the United Kingdom (8.8%) and China (8.7%); the most number of articles were published in PLoS One (2.9%), Stat Med (2.5%), and Res Synth (2.4%); and the most frequently observed MeSH terms were statistics and numerical data in bibliographic studies and methods in meta-analysis. Differences were found when compared to the event counts and the citation achievements in these 2 study types. CONCLUSION: The breakthrough was made by developing a dashboard using forest plots to display the difference in event counts. The visualization of the observed MeSH terms could be replicated for future academic pursuits and applications in other disciplines using the odds of 95% confidence intervals.

NT5C2 methylation regulatory interplay between DNMT1 and insulin receptor in type 2 diabetes.

Epigenetics alternation of non-genetic variation and genome-wide association study proven allelic variants may associate with insulin secretion in type 2 diabetes (T2D) development. We analyzed promoter DNA methylation array to evaluate the associated with increased susceptibility to T2D (30 cases, 10 controls) and found 1,091 gene hypermethylated in promoter regions. We performed the association study of T2D and found 698 single nucleotide polymorphisms in exon and promoter sites by using 2,270 subjects (560 cases, 1,710 controls). A comparison of DNA hypermethylation and gene silencing of mouse T2D results in our T2D patients' results showed that the 5'-nucleotidase, cytosolic II (NT5C2) and fucosyltransferase 8 (FUT8) genes were strongly associated with increased susceptibility to T2D. DNA hypermethylation in promoter regions reduced NT5C2 gene expression, but not FUT8 in T2D patients. NT5C2 protein expression was decreased in pancreatic ß-cells from T2D mice. Transient transfection NT5C2 into RIN-m5F cells down-regulated DNA methyltransferase I (DNMT1) expression and up-regulation of the insulin receptor. Moreover, NT5C2 knockdown induced in DNMT1 overexpression and insulin receptor inhibition. Taken together, these results showed that NT5C2 epigenetically regulated insulin receptor in patients and mice with T2D, and maybe provide for T2D therapy strategy.

Rapid and reversible photoinduced switching of a rotaxane crystal.

Crystalline phase transitions caused by external stimuli have been used to detect physical changes in the solid-state properties. This study presents the mechanical switching of crystals of ferrocene-containing rotaxane controlled by focused laser light. The expansion and contraction of the crystals can be driven by turning on and off laser light at 445 nm. The irradiation-induced expansion of the crystal involves elongation along the a, b and c axes at 30 °C, whereas heating of the crystal at 105 °C causes the shortening of c axis. The expansions reversibly occur and have the advantage of a rapid relaxation (reverse) process. Single-crystal X-ray crystallography reveals the detailed structural changes of the molecules, corresponding to a change in the size of the crystals on laser irradiation. This molecular crystal behaviour induced by laser irradiation, is demonstrated for the remote control of objects, namely, microparticle transport and microswitching in an electric circuit.

Inhibition of DNA methyltransferase 1 increases nuclear receptor subfamily 4 group A member 1 expression and decreases blood glucose in type 2 diabetes.

Our previous genome-wide association studies showed that DNA methyltransferase 1 (DNMT1) is associated with increased susceptibility to type 2 diabetes (T2D) in Han Chinese individuals. Here, we aimed to further evaluate the role of DNMT1 in T2D. We performed a genome-wide DNA methylation array and found that the nuclear receptor subfamily 4 group A member 1 (NR4A1) promoter was hypermethylated in patients with T2D and in a mouse model of T2D. Moreover, DNA hypermethylation of the NR4A1 promoter reduced NR4A1 mRNA expression. Transient transfection of human NR4A1 into RIN-m5F and 293T cells caused DNMT1 inhibition and induced insulin receptor activation. NR4A1knockdown by shRNA resulted in overexpression of DNMT1 and inhibition of insulin receptor, suggesting that the NR4A1 gene is involved in the epigenetics pathway. Furthermore, T2D model mice treated with the DNMT1 inhibitor aurintricarboxylic acid (ATA) showed reduced activation of DNMT1 in pancreatic ß cells; this effect reversed the changes in NR4A1 expression and decreased blood glucose in T2D model mice. Thus, our results showed for the first time that DNMT1 caused NR4A1 DNA hypermethylation and blocked insulin signaling in patients with T2D. Importantly, ATA therapy may be useful for decreasing blood glucose levels by reversing NR4A1-dependent insulin signaling. These findings improve our understanding of the crucial roles of these regulatory elements in human T2D.

Interleukin-4 receptor-targeted liposomal doxorubicin as a model for enhancing cellular uptake and antitumor efficacy in murine colorectal cancer.

Our previous studies showed that colorectal tumor has high interleukin-4 receptor α (IL-4Rα) expression, whereas adjacent normal tissue has low or no IL-4Rα expression. We also observed that human atherosclerotic plaque-specific peptide-1 (AP1) can specifically target to IL-4Rα. In this study, we investigated the therapeutic efficacy and systemic toxicity of AP1-conjuagted liposomal doxorubicin. AP1 bound more strongly to and was more efficiently internalized into IL-4Rα-overexpressing CT26 cells than CT26 control cells. Selective cytotoxicity experiment revealed that AP1-conjugated liposomal doxorubicin preferentially killed IL-4Rα-overexpressing CT26 cells. AP1-conjugated liposomal doxorubicin administered intravenously into mice produced significant inhibition of tumor growth and showed decreased cardiotoxicity of doxorubicin. These results indicated that AP1-conjugated liposomal doxorubicin has a potent and selective anticancer potential against IL-4Rα-overexpressing colorectal cancer cells, thus providing a model for targeted anticancer therapy.