Met vlas naar een biobased economie: omgeving Enschede

Al zoekende naar hernieuwbare grondstoffen om producten te ontwikkelen wordt duidelijk dat vlas heel wat potenties biedt. Een aantal partijen in en rondom Enschede is daar alvast van overtuigd en klaar voor de volgende stap: een biobased vlascluster ontwikkelen in omgeving Enschede. Het Ministerie van Economische Zaken is enthousiast over deze ambitie en wil met dit onderzoek de partijen een steun in de rug geven om de volgende stap te maken. Concreet is het onderzoek gericht op de volgende vragen: - Is het mogelijk om een schaalsprong te maken in vlasteelt in omgeving Enschede ten behoeve van de biobased productontwikkeling in de regio? - En zo ja, welke instrumenten kunnen daartoe ingezet worden? Over deze vragen bundelt deze notitie een grote hoeveelheid van beschikbare informatie om de partijen te helpen om tot focus te komen. Ook worden aanbevelingen gemaakt over de route die bewandeld kan worden om de biobased vlascluster te realiseren, zoals welke acties en projecten gerealiseerd moeten worden, alsook welke financieringsinstrumenten beschikbaar zijn om deze acties te realiseren. Ook geven we suggesties over een organisatiestructuur die deze vlascluster kan realiseren

Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study

OBJECTIVE: To identify existing prediction models for the risk of development of type 2 diabetes and to externally validate them in a large independent cohort. DATA SOURCES: Systematic search of English, German, and Dutch literature in PubMed until February 2011 to identify prediction models for diabetes. DESIGN : Performance of the models was assessed in terms of discrimination (C statistic) and calibration (calibration plots and Hosmer-Lemeshow test).The validation study was a prospective cohort study, with a case cohort study in a random subcohort. SETTING: Models were applied to the Dutch cohort of the European Prospective Investigation into Cancer and Nutrition cohort study (EPIC-NL). PARTICIPANTS: 38,379 people aged 20-70 with no diabetes at baseline, 2506 of whom made up the random subcohort. OUTCOME MEASURE: Incident type 2 diabetes. RESULTS: The review identified 16 studies containing 25 prediction models. We considered 12 models as basic because they were based on variables that can be assessed non- invasively and 13 models as extended because they additionally included conventional biomarkers such as glucose concentration. During a median follow-up of 10.2 years there were 924 cases in the full EPIC-NL cohort and 79 in the random subcohort. The C statistic for the basic models ranged from 0.74 (95% confidence interval 0.73 to 0.75) to 0.84 (0.82 to 0.85) for risk at 7.5 years. For prediction models including biomarkers the C statistic ranged from 0.81 (0.80 to 0.83) to 0.93 (0.92 to 0.94). Most prediction models overestimated the observed risk of diabetes, particularly at higher observed risks. After adjustment for differences in incidence of diabetes, calibration improved considerably. CONCLUSIONS: Most basic prediction models can identify people at high risk of developing diabetes in a time frame of five to 10 years. Models including biomarkers classified cases slightly better than basic ones. Most models overestimated the actual risk of diabetes. Existing prediction models therefore perform well to identify those at high risk, but cannot sufficiently quantify actual risk of future diabetes

Liver function tests and risk prediction of incident type 2 diabetes: evaluation in two independent cohorts

BACKGROUND: Liver function tests might predict the risk of type 2 diabetes. An independent study evaluating utility of these markers compared with an existing prediction model is yet lacking. METHODS AND FINDINGS: We performed a case-cohort study, including random subcohort (6.5%) from 38,379 participants with 924 incident diabetes cases (the Dutch contribution to the European Prospective Investigation Into Cancer and Nutrition, EPIC-NL, the Netherlands), and another population-based cohort study including 7,952 participants with 503 incident cases (the Prevention of Renal and Vascular End-stage Disease, PREVEND, Groningen, the Netherlands). We examined predictive value of combination of the Liver function tests (gamma-glutamyltransferase, alanine aminotransferase, aspartate aminotransferase and albumin) above validated models for 7.5-year risk of diabetes (the Cooperative Health Research in the Region of Augsburg, the KORA study). Basic model includes age, sex, BMI, smoking, hypertension and parental diabetes. Clinical models additionally include glucose and uric acid (model1) and HbA1c (model2). In both studies, addition of Liver function tests to the basic model improved the prediction (C-statistic by~0.020; NRI by~9.0%; P<0.001). In the EPIC-NL case-cohort study, addition to clinical model1 resulted in statistically significant improvement in the overall population (C-statistic = +0.009; P<0.001; NRI = 8.8%; P<0.001), while addition to clinical model 2 yielded marginal improvement limited to men (C-statistic = +0.007; P = 0.06; NRI = 3.3%; P = 0.04). In the PREVEND cohort study, addition to clinical model 1 resulted in significant improvement in the overall population (C-statistic change = 0.008; P = 0.003; NRI = 3.6%; P = 0.03), with largest improvement in men (C-statistic change = 0.013; P = 0.01; NRI = 5.4%; P = 0.04). In PREVEND, improvement compared to clinical model 2 could not be tested because of lack of HbA1c data. CONCLUSIONS: Liver function tests modestly improve prediction for medium-term risk of incident diabetes above basic and extended clinical prediction models, only if no HbA1c is incorporated. If data on HbA1c are available, Liver function tests have little incremental predictive value, although a small benefit may be present in men

Carriage of Streptococcus pneumoniae 3 Years after Start of Vaccination Program, the Netherlands

To evaluate the effectiveness of the 7-valent pneumococcal conjugate vaccine (PCV7) program, we conducted a cross-sectional observational study on nasopharyngeal carriage of Streptococcus pneumoniae 3 years after implementation of the program in the Netherlands. We compared pneumococcal serotypes in 329 prebooster 11-month-old children, 330 fully vaccinated 24-month-old children, and 324 parents with age-matched pre-PCV7 (unvaccinated) controls (ages 12 and 24 months, n = 319 and n = 321, respectively) and 296 of their parents. PCV7 serotype prevalences before and after PCV7 implementation, respectively, were 38% and 8% among 11-month-old children, 36% and 4% among 24-month-old children, and 8% and 1% among parents. Non-PCV7 serotype prevalences were 29% and 39% among 11-month-old children, 30% and 45% among 24-month-old children, and 8% and 15% among parents, respectively; serotypes 11A and 19A were most frequently isolated. PCV7 serotypes were largely replaced by non-PCV7 serotypes. Disappearance of PCV7 serotypes in parents suggests strong transmission reduction through vaccination