The effect of carbon and nutrient loading during nursery culture on the growth of black spruce seedlings: a six-year field study

Abstract We tested the effects of exponential nutrient loading and springtime carbon loading during nursery culture on the field performance of black spruce (Picea mariana (Mill.) B.S.P.). Seedlings were grown from seed with a conventional, fixed dose fertilizer (10 mg N seedling À1 ) or an exponential nutrient loading regime (75 mg N seedling À1 ). The following spring, seedlings were exposed for two weeks to either ambient (370 ppm) or elevated levels of CO 2 (800 ppm) and then planted in the field; seedling growth was followed for the next six years. Exponential nutrient loading increased seedling height, stem diameter and leader growth, with the largest increases in height and leader length occurring in the first three years after outplanting. Carbon loading increased seedling height and leader length, but only in seedlings that had been exponentially nutrient loaded. A combination of carbon and nutrient loading increased shoot height 26%, stem diameter 37% and leader length 40% over trees that received neither treatment. These results demonstrate that the growth enhancement seen under exponential nutrient loading is maintained under field conditions for at least six years. Carbon loading just before outplanting was a useful supplement to nutrient loading, but was ineffective in the absence of nutrient loading

Predicting the Risk of Rheumatoid Arthritis and Its Age of Onset through Modelling Genetic Risk Variants with Smoking

The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively

Validation of the standardised assessment of personality - abbreviated scale in a general population sample

BACKGROUND: Personality disorder (PD) is associated with important health outcomes in the general population. However, the length of diagnostic interviews poses a significant barrier to obtaining large scale, population‐based data on PD. A brief screen for the identification of people at high risk of PD in the general population could be extremely valuable for both clinicians and researchers. AIM: We set out to validate the Standardised Assessment of Personality – Abbreviated Scale (SAPAS), in a general population sample, using the Structured Clinical Interviews for DSM‐IV Personality Disorders (SCID‐II) as a gold standard. METHOD: One hundred and ten randomly selected, community‐dwelling adults were administered the SAPAS screening interview. The SCID‐II was subsequently administered by a clinical interviewer blind to the initial SAPAS score. Receiver operating characteristic analysis was used to assess the discriminatory performance of the SAPAS, relative to the SCID‐II. RESULTS: Area under the curve for the SAPAS was 0.70 (95% CI = 0.60 to 0.80; p < 0.001), indicating moderate overall discriminatory accuracy. A cut point score of 4 on the SAPAS correctly classified 58% of participants. At this cut point, the sensitivity and specificity were 0.69 and 0.53 respectively. CONCLUSION: The SAPAS operates less efficiently as a screen in general population samples and is probably most usefully applied in clinical populations. © 2015 The Authors Personality and Mental Health published by John Wiley & Sons Lt

ACPA-positive and ACPA-negative rheumatoid arthritis differ in their requirements for combination DMARDs and corticosteroids:secondary analysis of a randomized controlled trial

INTRODUCTION: UK guidelines recommend that all early active rheumatoid arthritis (RA) patients are offered combination disease-modifying antirheumatic drugs (DMARDs) and short-term corticosteroids. Anti-citrullinated protein antibody (ACPA)-positive and ACPA-negative RA may differ in their treatment responses. We used data from a randomized controlled trial - the Combination Anti-Rheumatic Drugs in Early RA (CARDERA) trial - to examine whether responses to intensive combination treatments in early RA differ by ACPA status. METHODS: The CARDERA trial randomized 467 early active RA patients to receive: (1) methotrexate, (2) methotrexate/ciclosporin, (3) methotrexate/prednisolone or (4) methotrexate/ciclosporin/prednisolone in a factorial-design. Patients were assessed every six months for two years. In this analysis we evaluated 431 patients with available ACPA status. To minimize multiple testing we used a mixed-effects repeated measures ANOVA model to test for an interaction between ACPA and treatment on mean changes from baseline for each outcome (Larsen, disease activity scores on a 28-joint count (DAS28), Health Assessment Questionnaire (HAQ), EuroQol, SF-36 physical component summary (PCS) and mental component summary (MCS) scores). When a significant interaction was present, mean changes in outcomes were compared by treatment group at each time point using t-tests stratified by ACPA status. Odds ratios (ORs) for the onset of new erosions with treatment were calculated stratified by ACPA. RESULTS: ACPA status influenced the need for combination treatments to reduce radiological progression. ACPA-positive patients had significant reductions in Larsen score progression with all treatments. ACPA-positive patients receiving triple therapy had the greatest benefits: two-year mean Larsen score increases comprised 3.66 (95% confidence interval (CI) 2.27 to 5.05) with triple therapy and 9.58 (95% CI 6.76 to 12.39) with monotherapy; OR for new erosions with triple therapy versus monotherapy was 0.32 (95% CI 0.14 to 0.72; P = 0.003). ACPA-negative patients had minimal radiological progression irrespective of treatment. Corticosteroid’s impact on improving DAS28/PCS scores was confined to ACPA-positive RA. CONCLUSIONS: ACPA status influences the need for combination DMARDs and high-dose tapering corticosteroids in early RA. In CARDERA, combination therapy was only required to prevent radiological progression in ACPA-positive patients; corticosteroids only provided significant disease activity and physical health improvements in ACPA-positive disease. This suggests ACPA is an important biomarker for guiding treatment decisions in early RA. TRIAL REGISTRATION: Current Controlled Trials ISRCTN3248487

Non-HLA RA susceptibility SNP allele frequencies and their association with seropositive RA in WTCCC and UKRAGG.

<p>SNPs are ordered by significance (most significant by <i>P</i>_GWAS listed first); all alleles attained genome-wide significance in the published meta-analysis; Ca = Cases; Co = Controls; MAF = Minor Allele Frequency;</p>a<p> = MAF in controls.</p

Number of individuals evaluated in each prediction model.

<p>Number of individuals evaluated in each prediction model.</p

Prediction model generated risk profiles for ACPA-positive RA and controls.

<p>Panel A = WTCCC; Panel B = UKRAGG; the upper set of lines for each model refer to RA cases; the lower set of lines refer to controls; OR = odds ratio.</p

Kaplan-Meier curves: RA age of onset stratified by HLA model risk categorisation and smoking status.

<p>Panel A = WTCCC Curves Stratified By Risk Categorisation; Panel B = UKRAGG Curves Stratified By Risk Categorisation; Panel C = WTCCC Curves Stratified By Risk Categorisation and Ever-Smoking Status; Panel D = UKRAGG Curves Stratified By Risk Categorisation and Ever-Smoking Status; Δ = change in onset age; Δ_m = maximum change in onset age across strata.</p