Minimum spanning tree analysis based on 50 multilocus sequence types (STs) in 248 chlamydia specimens.

<p>The 50 circles correspond to different STs discriminated by multilocus sequence typing (MLST). Each circle represents an ST, and ST number is given inside or next to the circle. Circle size reflects the number of isolates. Bold black lines connect single-locus variants (SLV). Broken lines connecting double-locus variants are only indicative as several alternative links with equal weight may exist. The coloured pie charts indicate ST geographic distribution. Grey shaded areas define clonal complexes i.e. clusters of genetically related STs with only one allele difference.</p

Additional file 1: Table S1. of Localization of Staphylococcus aureus in tissue from the nasal vestibule in healthy carriers

Results from spa-typing in the previous Tromsø 6 study and the present study. Additional documentation. (PDF 91 kb

Geographic distribution of <i>C. trachomatis</i> specimens according to three different strain typing methods, and genetic diversity within each area.

<p>CI: Confidence interval.</p>1<p><i>C. trachomatis</i> specimens from either the high school study (n = 60) or routine clinical samples in the laboratory (n = 20).</p>2<p>The numbers reflect the results for all 248 specimens and do not necessarily equal the sum of each row.</p>3<p>Sequence types of <i>C. trachomatis</i> detected by multilocus sequence typing.</p>4<p>Number of STs identified in an area divided by number of chlamydia specimens in the area.</p>5<p>Percentage novel STs in an area of total number of STs in the area.</p>6<p>Genovar D–K of <i>C. trachomatis</i> inferred from <i>ompA</i> sequencing.</p>7<p>Genotypes of <i>C. trachomatis</i> detected by <i>ompA</i> sequencing.</p

Number of genetic variants of <i>ompA</i> sequencing and multilocus sequence typing (MLST) within each genovar (D–K) in 248 <i>C. trachomatis</i> specimens.

1<p>Sequence types (STs) of <i>C. trachomatis</i> detected by MLST.</p>2<p>The numbers reflect the total number of unique genetic variants in the 248 chlamydia specimens and do not equal the sum of each column.</p

Risk of Breast Cancer in Relation to Infants’ and Mothers’ Birth Weights.

*<p>Presented are three associations between the risk of breast cancer and the birth weights (top quintile vs. lower quintiles) of: the infant¹, the mother² and both³ birth weights.</p>**<p>Hazard ratios were adjusted for propensity score accounting for: age, age at menarche, age at the birth of the first child, age at menopause, maternal history of breast cancer, parity, body-mass index, race/ethnicity, diabetes and use of hormone replacement therapy. All covariates were measured or reported at the entry into the study. The adjusted analyses were carried out on data with missing covariates values for mother’s own birth weight and propensity score imputed using multiple imputation.</p><p>The analyses of proportional hazard assumption were performed for all comparisons presented in subsets of subjects without missing data. All proportional hazard assumption tests showed no evidence of a significant non-proportional hazard (p>0.05, for all).</p

Association between size at birth and maternal serum estriol to alpha-fetoprotein ratio (E3/AFP) and pregnancy-associated plasma protein-A (PAPP-A) concentrations.

<p>Maternal serum concentrations of PAPP-A and ratio of E3/AFP (mean +/- SD of log ₁₀ multiples of the median, MOM or of log ₁₀ of ratio of MOMs, respectively) plotted against deciles of birth weight (A) or growth potential (B) at birth predicted from fractional polynomial regression analysis. Regression equations: log E3/AFP  =  −.0046098 + .0889807(gp⁰.⁵ −.6792581776); log PAPP-A  =  .0245553 + .1220838(gp⁰.⁵–.6792581776); P<0.0001 for both. (gp  =  growth potential) log E3/AFP  =  −.0090871+ .0000268(bw-3365.677323); log PAPP-A  =  .0160142 + .0084278((bw/1000)²-11.32778384); P<0.0001 for both. (bw  =  birth weight) Adjustment for maternal age, height, weight, race/ethnicity, parity, education, marital status, alcohol drinking and smoking status and conception assisted by reproductive technologies did not have a material effect on coefficients for birth weight or growth potential. Dashed line denotes median PAPP-A concentration or E3/AFP ratio of 1.</p

Baseline Characteristics of the Framingham Offspring Birth History Study Participants.

<p>N (%), is a total number and proportion of non-missing data for each characteristic. All characteristics are described as mean +/- SD or as numbers and proportions of participants within categories of the characteristic, n (%). Age, age at menopause, weight, height, use of hormone replacement therapy (HRT) are those at the entrance into the study.</p

Kaplan–Meier Curves of the Cumulative Probability of Breast Cancer According to Infant Birth Weight Quintile.

<p>Kaplan–Meier Curves of the Cumulative Probability of Breast Cancer According to Infant Birth Weight Quintile.</p

Baseline Characteristics of the FASTER trial Participants.

<p>All characteristics are described as mean +/− SD or as numbers and proportions of participants within categories of the characteristic, n (%). The mother’s age is the age at the time of delivery, and the weight, height, smoking status and alcohol use are those documented at her enrollment into the study in the first trimester of pregnancy.</p><p>ART, assisted reproduction technologies is conception assisted with ovulation induction.</p><p>Gestational age, is gestational age at delivery in days based on first trimester ultrasound dating.</p

Estimated odds ratios (ORs) for <i>S. aureus</i> nasal colonization by waist circumference (WC) among women and men, The Tromsø Staph and Skin Study (<i>n</i> = 3,775).

<p><i>n</i>, numbers; OR, odds ratios; CI, confidence interval.</p>a<p>WC quintiles (cm); Women: 1st <80, 2nd 80–86, 3rd 87–92, 4th 93–100, 5th ≥101; Men: 1st <91, 2nd 91– 95, 3rd 96–101, 4th 102–107, 5th ≥108.</p>b<p>Unadjusted logistic regression model restricted to those without missing data on any of the covariates (Women, <i>n</i> = 1,840, Men, <i>n</i> = 1,557).</p>b<p>Multivariate logistic regression model including: age, current smoking (yes/no), diabetes mellitus (yes/no), education level (< or ≥ college/university degree), and household income (< or ≥ level of the lowest income quintile).</p