Function and contribution of two putative Enterococcus faecalis glycosaminoglycan degrading enzymes to bacteremia and catheter-associated urinary tract infection.

Enterococcus faecalis is a common cause of healthcare-acquired bloodstream infections and catheter-associated urinary tract infections (CAUTIs) in both adults and children. Treatment of E. faecalis infection is frequently complicated by multi-drug resistance. Based on protein homology, E. faecalis encodes two putative hyaluronidases, EF3023 (HylA) and EF0818 (HylB). In other Gram-positive pathogens, hyaluronidases have been shown to contribute to tissue damage and immune evasion, but the function in E. faecalis has yet to be explored. Here, we show that both hylA and hylB contribute to E. faecalis pathogenesis. In a CAUTI model, ΔhylA exhibited defects in bladder colonization and dissemination to the bloodstream, and ΔhylB exhibited a defect in kidney colonization. Furthermore, a ΔhylAΔhylB double mutant exhibited a severe colonization defect in a model of bacteremia while the single mutants colonized to a similar level as the wild-type strain, suggesting potential functional redundancy within the bloodstream. We next examined enzymatic activity, and demonstrate that HylB is capable of digesting both hyaluronic acid (HA) and chondroitin sulfate in vitro, while HylA exhibits only a very modest activity against heparin. Importantly, HA degradation by HylB provided a modest increase in cell density during the stationary phase and also contributed to dampening of lipopolysaccharide-mediated NF-κB activation. Overall, these data demonstrate that glycosaminoglycan degradation is important for E. faecalis pathogenesis in the urinary tract and during bloodstream infection.

Adverse pregnancy outcomes and risk of type 2 diabetes in postmenopausal women.

BACKGROUND: Although gestational diabetes mellitus and delivering high-birthweight infants are known to predict a higher risk of future type 2 diabetes mellitus, the association of hypertensive disorders of pregnancy and other adverse pregnancy outcomes with type 2 diabetes mellitus is not well established. OBJECTIVE: This study aimed to examine the associations between different types of adverse pregnancy outcomes and incident type 2 diabetes mellitus among postmenopausal women. STUDY DESIGN: The Women's Health Initiative, a nationwide cohort of postmenopausal women, collected self-reported history of adverse pregnancy outcomes, including gestational diabetes mellitus, hypertensive disorders of pregnancy, preterm birth, and delivering low- birthweight (<2500 g) or high-birthweight (>4500 g) infants. Participants were followed up annually for self-reported incident type 2 diabetes mellitus treated with medication from baseline (1993-1998) to March 2021. This study used logistic regression to examine the associations of any and individual adverse pregnancy outcomes with diabetes mellitus. Stratified analyses were performed to assess effect modification by body mass index, race and ethnicity, education, parity, breastfeeding, and age at first birth. RESULTS: This analysis included 49,717 women without a history of diabetes mellitus at enrollment who had a least 1 pregnancy and responded to the questionnaire about adverse pregnancy outcomes. After adjusting for body mass index, demographic, lifestyle, and reproductive factors, gestational diabetes mellitus (odds ratio, 2.26; 95% confidence interval, 1.94-2.63), high birthweight (odds ratio, 1.30; 95% confidence interval, 1.18-1.44), and hypertensive disorders of pregnancy (odds ratio, 1.18; 95% confidence interval, 1.08-1.30) were independently associated with higher odds of type 2 diabetes mellitus, whereas preterm birth and low birthweight were not associated with diabetes mellitus risk. A history of ≥2 adverse pregnancy outcomes was associated with higher odds of type 2 diabetes mellitus (odds ratio, 1.55; 95% confidence interval, 1.28-1.88). This study further observed higher odds of type 2 diabetes mellitus (odds ratio, 3.69; 95% confidence interval, 2.38-5.70) among women with a history of both gestational diabetes mellitus and hypertensive disorders of pregnancy than those without any adverse pregnancy outcomes. CONCLUSION: Postmenopausal women with a history of gestational diabetes mellitus, those delivering high-birthweight infants, or those with hypertensive disorders of pregnancy are at risk of future type 2 diabetes mellitus. In addition, women with ≥2 conditions had an augmented risk and might be prioritized for screening and prevention efforts for type 2 diabetes mellitus.

Association of prenatal exposure to PM2.5 and NO2 with gestational diabetes in Western New York.

BACKGROUND: Although many studies have examined the association between prenatal air pollution exposure and gestational diabetes (GDM), the relevant exposure windows remain inconclusive. We aim to examine the association between preconception and trimester-specific exposure to PM2.5 and NO2 and GDM risk and explore modifying effects of maternal age, pre-pregnancy body mass index (BMI), smoking, exercise during pregnancy, race and ethnicity, and neighborhood disadvantage. METHODS: Analyses included 192,508 birth records of singletons born to women without pre-existing diabetes in Western New York, 2004-2016. Daily PM2.5 and NO2 at 1-km2 grids were estimated from ensemble-based models. We assigned each birth with exposures averaged in preconception and each trimester based on residential zip-codes. We used logistic regression to examine the associations and distributed lag models (DLMs) to explore the sensitive windows by month. Relative excess risk due to interaction (RERI) and multiplicative interaction terms were calculated. RESULTS: GDM was associated with PM2.5 averaged in the first two trimesters (per 2.5 µg/m3: OR = 1.08, 95% CI: 1.01, 1.14) or from preconception to the second trimester (per 2.5 µg/m3: OR = 1.10, 95% CI: 1.03, 1.18). NO2 exposure during each averaging period was associated with GDM risk (per 10 ppb, preconception: OR = 1.10, 95% CI: 1.06, 1.14; first trimester: OR = 1.12, 95% CI: 1.08, 1.16; second trimester: OR = 1.10, 95% CI: 1.06, 1.14). In DLMs, sensitive windows were identified in the 5th and 6th gestational months for PM2.5 and one month before and three months after conception for NO2. Evidence of interaction was identified for pre-pregnancy BMI with PM2.5 (P-for-interaction = 0.023; RERI = 0.21, 95% CI: 0.10, 0.33) and with NO2 (P-for-interaction = 0.164; RERI = 0.16, 95% CI: 0.04, 0.27). CONCLUSION: PM2.5 and NO2 exposure may increase GDM risk, and sensitive windows may be the late second trimester for PM2.5 and periconception for NO2. Women with higher pre-pregnancy BMI may be more susceptible to exposure effects.

Types of garlic and their anticancer and antioxidant activity: a review of the epidemiologic and experimental evidence.

Garlic, an Allium vegetable, contains rich flavonoids organosulfur compounds (OSCs) that have potent anticancer properties. The aim of the review is to provide an overview of the different types of garlic, their active compounds, and the potential anticancer benefits with a focus on antioxidant activity. Animal and cell line studies have provided convincing evidence that garlic and its organosulfur compounds inhibit carcinogenesis through a number of events including induction of apoptosis, inhibiting cellular proliferation, scavenging radical oxygen species (ROS), increasing the activities of enzymes such as glutathione S-transferase, and reducing tumor size. Epidemiological studies showed compelling evidence that garlic consumption is associated with decreased risk of colorectal cancer, but inconsistent evidence for stomach, breast, and prostate cancers. Studies also suggest that the presence and potency of garlic OSCs varies with respect to the preparation and form of garlic. Further epidemiological studies with information on garlic form consumed or preparation methods and molecular studies regarding its antioxidant mechanisms, such as increasing enzymatic and nonenzymatic antioxidants levels, are warranted.

A Cross-Sectional Analysis of Telomere Length and Sleep in the Women's Health Initiative.

Telomere length is a heritable marker of cellular age that is associated with morbidity and mortality. Poor sleep behaviors, which are also associated with adverse health events, may be related to leukocyte telomere length (LTL). We studied a subpopulation of 3,145 postmenopausal women (1,796 European-American (EA) and 1,349 African-American (AA)) enrolled in the Women's Health Initiative in 1993-1998 with data on Southern blot-measured LTL and self-reported usual sleep duration and sleep disturbance. LTL-sleep associations were analyzed separately for duration and disturbance using weighted and confounder-adjusted linear regression models in the entire sample (AAs + EAs; adjusted for race/ethnicity) and in racial/ethnic strata, since LTL differs by ancestry. After adjustment for covariates, each additional daily hour of sleep beyond 5 hours, approximately, was associated with a 27-base-pair (95% confidence interval (CI): 6, 48) longer LTL in the entire sample. Associations between sleep duration and LTL were strongest among AAs (adjusted ß = 37, 95% CI: 4, 70); a similar, nonsignificant association was observed for EAs (adjusted ß = 20, 95% CI: -7, 48). Sleep disturbance was not associated with LTL in our study. Our models did not show departure from linearity (quadratic sleep terms: P ≥ 0.55). Our results suggest that longer sleep duration is associated with longer LTL in postmenopausal women.

Interindividual variability in the cardiac expression of anthracycline reductases in donors with and without Down syndrome.

PURPOSE: The intracardiac synthesis of anthracycline alcohol metabolites (e.g., daunorubicinol) contributes to the pathogenesis of anthracycline-related cardiotoxicity. Cancer patients with Down syndrome (DS) are at increased risk for anthracycline-related cardiotoxicity. We profiled the expression of anthracycline metabolizing enzymes in hearts from donors with- and without- DS. METHODS: Cardiac expression of CBR1, CBR3, AKR1A1, AKR1C3 and AKR7A2 was examined by quantitative real time PCR, quantitative immunoblotting, and enzyme activity assays using daunorubicin. The CBR1 polymorphism rs9024 was investigated by allelic discrimination with fluorescent probes. The contribution of CBRs/AKRs proteins to daunorubicin reductase activity was examined by multiple linear regression. RESULTS: CBR1 was the most abundant transcript (average relative expression; DS: 81%, non-DS: 58%), and AKR7A2 was the most abundant protein (average relative expression; DS: 38%, non-DS: 35%). Positive associations between cardiac CBR1 protein levels and daunorubicin reductase activity were found for samples from donors with- and without- DS. Regression analysis suggests that sex, CBR1, AKR1A1, and AKR7A2 protein levels were significant contributors to cardiac daunorubicin reductase activity. CBR1 rs9024 genotype status impacts on cardiac CBR1 expression in non-DS hearts. CONCLUSIONS: CBR1, AKR1A1, and AKR7A2 protein levels point to be important determinants for predicting the synthesis of cardiotoxic daunorubicinol in heart.

Integrated Graph Propagation and Optimization with Biological Applications.

Mathematical models that utilize network representations have proven to be valuable tools for investigating biological systems. Often dynamic models are not feasible due to their complex functional forms that rely on unknown rate parameters. Network propagation has been shown to accurately capture the sensitivity of nodes to changes in other nodes; without the need for dynamic systems and parameter estimation. Node sensitivity measures rely solely on network structure and encode a sensitivity matrix that serves as a good approximation to the Jacobian matrix. The use of a propagation-based sensitivity matrix as a Jacobian has important implications for network optimization. This work develops Integrated Graph Propagation and OptimizatioN (IGPON), which aims to identify optimal perturbation patterns that can drive networks to desired target states. IGPON embeds propagation into an objective function that aims to minimize the distance between a current observed state and a target state. Optimization is performed using Broyden's method with the propagationbased sensitivity matrix as the Jacobian. IGPON is applied to simulated random networks, DREAM4 in silico networks, and over-represented pathways from STAT6 knockout data and YBX1 knockdown data. Results demonstrate that IGPON is an effective way to optimize directed and undirected networks that are robust to uncertainty in the network structure.

Antioxidant and Antiproliferative Activities of Several Garlic Forms.

It is hypothesized that garlic, Allium sativum, might protect against oxidative stress that causes damage to cells and tissues leading to the development of various health conditions including cancer. However, it is not known whether garlic's potential anticancer benefits differ by form of garlic consumed. This study aimed to quantify and compare the in vitro antioxidant and antiproliferative activity of several garlic forms in water and alcohol extracts including fresh garlic, fresh garlic set aside, heated garlic, heated garlic set aside, garlic powder, black garlic, two commercially available garlic supplements. Antioxidant activity of different garlic forms were measured using three assays: DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate) assay, superoxide assay, and hydroxyl assay. In vitro effects of garlic extracts were investigated against the most common lung cancer subtypes: H520, H1975, and A549 cell lines using the sulforhodamine B (SRB) assay. Among free radical scavenging assays, Garlicin®, a commercially available supplement, displayed high antioxidant activity in water and alcohol extracts (DPPH assay: 2.02 mg AAE (mg ascorbic acid equivalent)/g garlic and 3.53 mg AAE/g garlic, respectively; superoxide assay: 6.73 mg AAE/g garlic and 7.13 mg AAE/g garlic, respectively). In the hydroxyl assay, water extract of fresh garlic crushed and set aside for 10 min showed the highest antioxidant activity. Garlicin® alcohol extract and fresh garlic water extracts strongly inhibited the proliferation of H1975, A549 and H520 cells. Other forms of garlic including garlic powder and black garlic exhibited low antioxidant and antiproliferative activity. Our results demonstrate that the preparation and processing methods of garlic may lead to different antioxidant benefits.

Scalable module detection for attributed networks with applications to breast cancer.

The objective of network module detection is to identify groups of nodes within a network structure that are tightly connected. Nodes in a network often have attributes (aka metadata) associated with them. It is often desirable to identify groups of nodes that are tightly connected in the network structure, but also have strong similarity in their attributes. Utilizing attribute information in module detection is a major challenge because it requires bridging the structural network with attribute data. A Weighted Fast Greedy (WFG) algorithm for attribute-based module detection is proposed. WFG utilizes logistic regression to bridge the structural and attribute spaces. The logistic function naturally emphasizes associations between attributes and network structure accordingly, and can be easily interpreted. A breast cancer application is presented that connects a protein-protein interaction network gene expression data and a survival outcome. This application demonstrates the importance of embedding attribute information into the community detection framework on a breast cancer dataset. Five modules were significant for survival and they contained known pathways and markers for cancer, including cell cycle, p53 pathway, BRCA1, BRCA2, and AURKB, among others. Whereas, neither the gene expression data nor the network structure alone gave rise to these cancer biomarkers and signatures.

Comparative genome-wide DNA methylation analysis in myocardial tissue from donors with and without Down syndrome.

Down syndrome (DS, trisomy 21) is the most common major chromosomal aneuploidy compatible with life. The additional whole or partial copy of chromosome 21 results in genome-wide imbalances that drive the complex pathobiology of DS. Differential DNA methylation in the context of trisomy 21 may contribute to the variable architecture of the DS phenotype. The goal of this study was to examine the genomic DNA methylation landscape in myocardial tissue from non-fetal individuals with DS. >480,000 unique CpG sites were interrogated in myocardial DNA samples from individuals with (n = 12) and without DS (n = 12) using DNA methylation arrays. A total of 93 highly differentially methylated CpG sites and 16 differentially methylated regions were identified in myocardial DNA from subjects with DS. There were 18 differentially methylated CpG sites in chromosome 21, including 5 highly differentially methylated sites. A CpG site in the RUNX1 locus was differentially methylated in DS myocardium, and linear regression suggests that donors' age, gender, DS status, and RUNX1 methylation may contribute up to ~51% of the variability in RUNX1 mRNA expression. In DS myocardium, only 58% of the genes overlapping with differentially methylated regions codify for proteins with known functions and 24% are non-coding RNAs. This study provides an initial snapshot on the extent of genome-wide differential methylation in myocardial tissue from persons with DS.

A FRAMEWORK FOR ATTRIBUTE-BASED COMMUNITY DETECTION WITH APPLICATIONS TO INTEGRATED FUNCTIONAL GENOMICS.

Understanding community structure in networks has received considerable attention in recent years. Detecting and leveraging community structure holds promise for understanding and potentially intervening with the spread of influence. Network features of this type have important implications in a number of research areas, including, marketing, social networks, and biology. However, an overwhelming majority of traditional approaches to community detection cannot readily incorporate information of node attributes. Integrating structural and attribute information is a major challenge. We propose a exible iterative method; inverse regularized Markov Clustering (irMCL), to network clustering via the manipulation of the transition probability matrix (aka stochastic flow) corresponding to a graph. Similar to traditional Markov Clustering, irMCL iterates between "expand" and "inflate" operations, which aim to strengthen the intra-cluster flow, while weakening the inter-cluster flow. Attribute information is directly incorporated into the iterative method through a sigmoid (logistic function) that naturally dampens attribute influence that is contradictory to the stochastic flow through the network. We demonstrate advantages and the exibility of our approach using simulations and real data. We highlight an application that integrates breast cancer gene expression data set and a functional network defined via KEGG pathways reveal significant modules for survival.

Pla2g12b and Hpn are genes identified by mouse ENU mutagenesis that affect HDL cholesterol.

Despite considerable progress understanding genes that affect the HDL particle, its function, and cholesterol content, genes identified to date explain only a small percentage of the genetic variation. We used N-ethyl-N-nitrosourea mutagenesis in mice to discover novel genes that affect HDL cholesterol levels. Two mutant lines (Hlb218 and Hlb320) with low HDL cholesterol levels were established. Causal mutations in these lines were mapped using linkage analysis: for line Hlb218 within a 12 Mbp region on Chr 10; and for line Hlb320 within a 21 Mbp region on Chr 7. High-throughput sequencing of Hlb218 liver RNA identified a mutation in Pla2g12b. The transition of G to A leads to a cysteine to tyrosine change and most likely causes a loss of a disulfide bridge. Microarray analysis of Hlb320 liver RNA showed a 7-fold downregulation of Hpn; sequencing identified a mutation in the 3' splice site of exon 8. Northern blot confirmed lower mRNA expression level in Hlb320 and did not show a difference in splicing, suggesting that the mutation only affects the splicing rate. In addition to affecting HDL cholesterol, the mutated genes also lead to reduction in serum non-HDL cholesterol and triglyceride levels. Despite low HDL cholesterol levels, the mice from both mutant lines show similar atherosclerotic lesion sizes compared to control mice. These new mutant mouse models are valuable tools to further study the role of these genes, their affect on HDL cholesterol levels, and metabolism.