A zebrafish high throughput screening system used for Staphylococcus epidermidis infection marker discovery.

Animal science

Analysis of RNAseq datasets from a comparative infectious disease zebrafish model using GeneTiles bioinformatics.

Animal science

Validation of the FAM19A4/mir124-2 DNA methylation test for both lavage- and brush-based self-samples to detect cervical (pre)cancer in HPV-positive women

Objectives DNA methylation analysis of cancer-related genes is a promising tool for HPV-positive women to identify those with cervical (pre)cancer (CIN3+) in need of treatment. However, clinical performance of methylation markers can be influenced by the sample type utilized. We describe a multiplex quantitative methylation-specific PCR that targets FAM19A4 and mir124-2 loci, to detect CIN3+ using both HPV-positive lavage- and brush self-samples. Methods We determined methylation thresholds for clinical classification using HPV-positive training sets comprising lavage self-samples of 182 women (including 40 with CIN3+) and brush self-samples of 224 women (including 61 with CIN3+). Subsequently, independent HPV-positive validation sets of 389 lavage self-samples (including 78 with CIN3+), and 254 brush self-samples (including 72 with CIN3+) were tested using the preset thresholds. Furthermore, the clinical performance of combined methylation analysis and HPV16/18 genotyping was determined. Results Training set analysis revealed similar FAM19A4 and mir124-2 thresholds for both self-sample types to yield highest CIN3+ sensitivity at 70% specificity. Validation set analysis resulted in a CIN3+ sensitivity of 70.5% (95%CI: 60.4-80.6) at a specificity of 67.8% (95%CI: 62.7-73.0) for lavage self-samples, and a CIN3+ sensitivity of 69.4% (95%CI: 58.8-80.1) at a 76.4% (95%CI: 70.2-82.6) specificity for brush self-samples. In combination with HPV16/18 genotyping, CIN3+ sensitivity and specificity were 88.5% (95%CI: 81.4-95.6) and 46.0% (95%CI: 40.4-51.5) for lavage self-samples, and 84.7% (95%CI: 76.4-93.0) and 54.9% (95%CI: 47.7-62.2) for brush self-samples. Conclusions FAM19A4/mir124-2 methylation analysis performs equally well in HPV-positive la

Are Insider Sales Always Bad News? Evidence On Large Sales By Key Insiders

Investors often scrutinize stock trades by corporate insiders, hoping to infer the nature of any privileged information which may have motivated the trades. Conventional wisdom suggests that sales of stock by insiders reveal negative information; this interpretation is supported by empirical work such as the series of papers by Seyhun. However, this common interpretation fails to distinguish between sales by atomistic insiders and sales by controlling blockholders.  In this paper, I present evidence which suggests that sales by controlling insiders should not be considered bad news. Using both a series of logit regressions and traditional event-study tests, I examine the relationship between a firm's performance and the willingness of its controlling shareholder to sell a significant proportion of his shares. I find that firm value is just as likely to rise on the news of large insider sales as it is to fall, so that large sales need not imply negative private information.  One possible explanation for a positive response to a controlling blockholder's large sale is that such a sale makes the insider vulnerable to meaningful oversight by outside shareholders. Thus, a large sale may be a signal of the insider's willingness to expose himself to shareholder monitoring and discipline. However, regardless of the interpretation, the empirical evidence presented in the paper forces the conclusion that it is inappropriate to interpret all insider sales as bad news: insider sales occur in a variety of contexts, and creating buy/sell rules which ignore those contexts is simplistic and erroneous

Predicting Long-term Disease-free Survival after Resection of Pancreatic Ductal Adenocarcinoma:A Nationwide Cohort Study

Objective: To develop a prediction model for long-term (≥5 years) disease-free survival (DFS) after the resection of pancreatic ductal adenocarcinoma (PDAC). Background: Despite high recurrence rates, 10% of patients have long-term DFS after PDAC resection. A model to predict long-term DFS may aid individualized prognostication and shared decision-making. Methods: This nationwide cohort study included all consecutive patients who underwent PDAC resection in the Netherlands (2014-2016). The best-performing prognostic model was selected by Cox-proportional hazard analysis and Akaike's Information Criterion, presented by hazard ratios (HRs) with 95% confidence intervals (CIs). Internal validation was performed, and discrimination and calibration indices were assessed. Results: In all, 836 patients with a median follow-up of 67 months (interquartile range 51-79) were analyzed. Long-term DFS was seen in 118 patients (14%). Factors predictive of long-term DFS were low preoperative carbohydrate antigen 19-9 (logarithmic; HR 1.21; 95% CI 1.10-1.32), no vascular resection (HR 1.33; 95% CI 1.12-1.58), T1 or T2 tumor stage (HR 1.52; 95% CI 1.14-2.04, and HR 1.17; 95% CI 0.98-1.39, respectively), well/moderate tumor differentiation (HR 1.44; 95% CI 1.22-1.68), absence of perineural and lymphovascular invasion (HR 1.42; 95% CI 1.11-1.81 and HR 1.14; 95% CI 0.96-1.36, respectively), N0 or N1 nodal status (HR 1.92; 95% CI 1.54-2.40, and HR 1.33; 95% CI 1.11-1.60, respectively), R0 resection margin status (HR 1.25; 95% CI 1.07-1.46), no major complications (HR 1.14; 95% CI 0.97-1.35) and adjuvant chemotherapy (HR 1.74; 95% CI 1.47-2.06). Moderate performance (concordance index 0.68) with adequate calibration (slope 0.99) was achieved. Conclusions: The developed prediction model, readily available at www.pancreascalculator.com, can be used to estimate the probability of long-term DFS after resection of pancreatic ductal adenocarcinoma.</p

CT angiography and CT perfusion improve prediction of infarct volume in patients with anterior circulation stroke

Introduction: We investigated whether baseline CT angiography (CTA) and CT perfusion (CTP) in acute ischemic stroke could improve prediction of infarct presence and infarct volume on follow-up imaging. Methods: We analyzed 906 patients with suspected anterior circulation stroke from the prospective multicenter Dutch acute stroke study (DUST). All patients underwent baseline non-contrast CT, CTA, and CTP and follow-up non-contrast CT/MRI after 3 days. Multivariable regression models were developed including patient characteristics and non-contrast CT, and subsequently, CTA and CTP measures were added. The increase in area under the curve (AUC) and R2 was assessed to determine the additional value of CTA and CTP. Results: At follow-up, 612 patients (67.5 %) had a detectable infarct on CT/MRI; median infarct volume was 14.8 mL (interquartile range (IQR) 2.8–69.6). Regarding infarct presence, the AUC of 0.82 (95 % confidence interval (CI) 0.79–0.85) for patient characteristics and non-contrast CT was improved with addition of CTA measures (AUC 0.85 (95 % CI 0.82–0.87); p < 0.001) and was even higher after addition of CTP measures (AUC 0.89 (95 % CI 0.87–0.91); p < 0.001) and combined CTA/CTP measures (AUC 0.89 (95 % CI 0.87–0.91); p < 0.001). For infarct volume, adding combined CTA/CTP measures (R2 = 0.58) was superior to patient characteristics and non-contrast CT alone (R2 = 0.44) and to addition of CTA alone (R2 = 0.55) or CTP alone (R2 = 0.54; all p < 0.001). Conclusion: In the acute stage, CTA and CTP have additional value over patient characteristics and non-contrast CT for predicting infarct presence and infarct volume on follow-up imaging. These findings could be applied for patient selection in future trials on ischemic stroke treatment

Prediction of outcome in patients with suspected acute ischaemic stroke with CT perfusion and CT angiography: The Dutch acute stroke trial (DUST) study protocol

Background: Prediction of clinical outcome in the acute stage of ischaemic stroke can be difficult when based on patient characteristics, clinical findings and on non-contrast CT. CT perfusion and CT angiography may provide additional prognostic information and guide treatment in the early stage. We present the study protocol of the Dutch acute Stroke Trial (DUST). The DUST aims to assess the prognostic value of CT perfusion and CT angiography in predicting stroke outcome, in addition to patient characteristics and non-contrast CT. For this purpose, individualised prediction models for clinical outcome after stroke based on the best predictors from patient characteristics and CT imaging will be developed and validated.Methods/design: The DUST is a prospective multi-centre cohort study in 1500 patients with suspected acute ischaemic stroke. All patients undergo non-contrast CT, CT perfusion and CT angiography within 9 hours after onset of the neurological deficits, and, if possible, follow-up imaging after 3 days. The primary outcome is a dichotomised score on the modified Rankin Scale, assessed at 90 days. A score of 0-2 represents good outcome, and a score of 3-6 represents poor outcome. Three logistic regression models will be developed, including patient characteristics and non-contrast CT (model A), with addition of CT angiography (model B), and CT perfusion parameters (model C). Model derivation will be performed in 60% of the study population, and model validation in the remaining 40% of the patients. Additional prognostic value of the models will be determined with the area under the curve (AUC) from the receiver operating characteristic (ROC) curve, calibration plots, assessment of goodness-of-fit, and likelihood ratio tests.Discussion: This study will provide insight in the added prognosti

The Difficulty of Detecting Occult Metastases in Patients with Potentially Resectable Pancreatic Cancer:Development and External Validation of a Preoperative Prediction Model

Occult metastases are detected in 10–15% of patients during exploratory laparotomy for pancreatic cancer. This study developed and externally validated a model to predict occult metastases in patients with potentially resectable pancreatic cancer. Model development was performed within the Dutch Pancreatic Cancer Audit, including all patients operated for pancreatic cancer (January 2013–December 2017). Multivariable logistic regression analysis based on the Akaike Information Criteria was performed with intraoperative pathologically proven metastases as the outcome. The model was externally validated with a cohort from the University Hospital of Verona (January 2013–December 2017). For model development, 2262 patients were included of whom 235 (10%) had occult metastases, located in the liver (n = 143, 61%), peritoneum (n = 73, 31%), or both (n = 19, 8%). The model included age (OR 1.02, 95% CI 1.00–1.03), BMI (OR 0.96, 95% CI 0.93–0.99), preoperative nutritional support (OR 1.73, 95% CI 1.01–2.74), tumor diameter (OR 1.60, 95% CI 1.04–2.45), tumor composition (solid vs. cystic) (OR 2.33, 95% CI 1.20–4.35), and indeterminate lesions on preoperative imaging (OR 4.01, 95% CI 2.16–7.43). External validation showed poor discrimination with a C-statistic of 0.56. Although some predictor variables were significantly associated with occult metastases, the model performed insufficiently at external validation.</p