Tumour budding is a strong and independent prognostic factor in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer that escapes detection and resists treatment. Tumour budding, defined as the presence of de-differentiated single tumour cells or small cell clusters at the invasive front of gastrointestinal carcinomas like colorectal, oesophageal, gastric and ampullary, is linked to adverse prognosis. Tumour budding has not yet been reported in PDAC.

High HSP27 and HSP70 expression levels are independent adverse prognostic factors in primary resected colon cancer

The expression of Heat Shock Proteins (HSPs) is increased in various cancers and has been shown to correlate with biological tumor behaviour. This study aimed to investigate the impact of HSP70, HSP60 and HSP27 expression in colon cancer.

[Drug-independent blood pressure control through the autonomous nervous system]

Arterial hypertension is a chronic disease with a therapeutical challenge for the patient and the physician involved. Patient-independent techniques with good efficacy and tolerability are wanted. The autonomous nervous system insufficiently therapeutically exploited to date, is now approachable by two types of intervention: renal nerve ablation, an endovascular approach without remaining foreign body, and BAT, baroreflex activating therapy using an implantable device stimulating the carotid sinus. The blood pressure lowering potency of BAT appears more than with renal nerve ablation and also clinical study data are more prevalent. With both treatment options the patients having the most profit are insufficiently defined. Given this knowledge, any form of secondary hypertension needs to be excluded beforehand.

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.