Additional file 1: of The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature

Interaction keywords and INO type annotations for the LLL data set. This additional file includes annotations of the LLL dataset with INO multiple keyword interaction types. (XLSX 29 kb

Additional file 2: of Ontology-based literature mining of E. coli vaccine-associated gene interaction networks

A Cytoscape session file containing the E. coli gene-vaccine interaction network and its sub-networks. (CYS 76 kb

Early Gestational Weight Gain Rate and Adverse Pregnancy Outcomes in Korean Women

<div><p>During pregnancy, many women gain excessive weight, which is related to adverse maternal and neonatal outcomes. In this study, we evaluated whether rate of gestational weight gain (RGWG) in early, mid, and late pregnancy is strongly associated with adverse pregnancy outcomes. A retrospective chart review of 2,789 pregnant Korean women was performed. Weights were recorded at the first clinic visit, during the screening test for fetal anomaly, and during the 50g oral glucose challenge test and delivery, to represent early, mid, and late pregnancy, respectively. A multivariate logistic regression analysis was performed to examine the relationship between RGWG and adverse pregnancy outcomes. At early pregnancy, the RGWG was significantly associated with high risk of developing gestational diabetes mellitus (GDM), pregnancy-induced hypertension (PIH), large for gestational age (LGA) infants, macrosomia, and primary cesarean section (P-CS). The RGWG of mid pregnancy was not significantly associated with any adverse pregnancy outcomes. The RGWG at late pregnancy was significantly associated with a lower risk of developing GDM, preterm birth and P-CS, but with a higher risk of developing LGA infants and macrosomia. When the subjects were divided into three groups (Underweight, Normal, and Obese), based on pre-pregnancy body mass index (BMI), the relationship between early RGWG and adverse pregnancy outcomes was significantly different across the three BMI groups. At early pregnancy, RGWG was not significantly associated to adverse pregnancy outcomes for subjects in the Underweight group. In the Normal group, however, early RGWG was significantly associated with GDM, PIH, LGA infants, macrosomia, P-CS, and small for gestational weight (SGA) infants, whereas early RGWG was significantly associated with only a high risk of PIH in the Obese group. The results of our study suggest that early RGWG is significantly associated with various adverse pregnancy outcomes and that proper preemptive management of early weight gain, particularly in pregnant women with a normal or obese pre-pregnancy BMI, is necessary to reduce the risk of developing adverse pregnancy outcomes.</p></div

Additional file 1: of Ontology-based literature mining of E. coli vaccine-associated gene interaction networks

A PDF file containing three other gene-vaccine sub-networks. (DOCX 932 kb

Clinical characteristics of study subjects.

<p>Clinical characteristics of study subjects.</p

Systems Pharmacological Analysis of Drugs Inducing Stevens–Johnson Syndrome and Toxic Epidermal Necrolysis

Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are serious cutaneous adverse reactions. We mined the approved labels in Drugs@FDA, identified the SJS/TEN list of 259 small molecular drugs and biologics, and conducted systems pharmacological network analyses. Pharmacological network analysis revealed that drugs with treatment-related SJS and/or TEN are pharmacologically diverse and that the largest subnetwork is associated with antiepileptic drugs and their pharmacological targets. Our pharmacological network analysis identified CTNNB1 [catenin (cadherin-associated protein), beta 1, 88 kDa] as a significant intermediator. This protein is involved in maintaining the functional integrity of the epithelium through regulating cell growth and adhesion between cells in various organs, including the skin. Leveraging a publicly accessible genome-wide transcriptional expression database, we found that human leukocyte antigen-related (HLA) genes were significantly perturbed by various SJS/TEN-inducing drugs. Notably, carbamazepine (CBZ) perturbed several HLA genes, among which <i>HLA</i>-<i>DQB1*0201</i> was reportedly shown to be associated with CBZ-induced SJS/TEN in caucasians. In short, systems analysis by leveraging a publicly accessible knowledge base and databases could produce meaningful results for further mechanistic investigation. Our study sheds light on the utility of systems pharmacology analysis for gaining insight into clinical drug toxicity

Risk analysis of developing adverse pregnancy outcomes–pre-pregnancy BMI.

<p>Odd ratios and 95% confidence intervals are shown in the table.</p><p>§: significant P < 0.05; GDM: gestational diabetes mellitus; PIH: pregnancy-induced hypertension; LGA: large for gestational age; SGA: small for gestational age; P-CS: primary caesarean section.</p><p>Risk analysis of developing adverse pregnancy outcomes–pre-pregnancy BMI.</p

Average rate of gestational weight gain.

<p>Average rate of gestational weight gain.</p

Times of weight measurement and pregnancy term definition.

<p>The rate of gestational weight gain (lb/week) was calculated for terms defined as followings: early pregnancy (from pre-pregnancy to fetal anomaly screening test), mid pregnancy (from fetal anomaly screening test to oral glucose tolerance test), late pregnancy (from oral glucose tolerance test to delivery), “early and mid pregnancy” (from pre-pregnancy to oral glucose tolerance test), “mid and late pregnancy” (from fetal anomaly screening test to delivery), and whole.</p

Systems Pharmacological Analysis of Drugs Inducing Stevens–Johnson Syndrome and Toxic Epidermal Necrolysis

Stevens–Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are serious cutaneous adverse reactions. We mined the approved labels in Drugs@FDA, identified the SJS/TEN list of 259 small molecular drugs and biologics, and conducted systems pharmacological network analyses. Pharmacological network analysis revealed that drugs with treatment-related SJS and/or TEN are pharmacologically diverse and that the largest subnetwork is associated with antiepileptic drugs and their pharmacological targets. Our pharmacological network analysis identified CTNNB1 [catenin (cadherin-associated protein), beta 1, 88 kDa] as a significant intermediator. This protein is involved in maintaining the functional integrity of the epithelium through regulating cell growth and adhesion between cells in various organs, including the skin. Leveraging a publicly accessible genome-wide transcriptional expression database, we found that human leukocyte antigen-related (HLA) genes were significantly perturbed by various SJS/TEN-inducing drugs. Notably, carbamazepine (CBZ) perturbed several HLA genes, among which <i>HLA</i>-<i>DQB1*0201</i> was reportedly shown to be associated with CBZ-induced SJS/TEN in caucasians. In short, systems analysis by leveraging a publicly accessible knowledge base and databases could produce meaningful results for further mechanistic investigation. Our study sheds light on the utility of systems pharmacology analysis for gaining insight into clinical drug toxicity