MiR expression profiles of paired primary colorectal cancer and metastases by next-generation sequencing.

MicroRNAs (miRs) have been recognized as promising biomarkers. It is unknown to what extent tumor-derived miRs are differentially expressed between primary colorectal cancers (pCRCs) and metastatic lesions, and to what extent the expression profiles of tumor tissue differ from the surrounding normal tissue. Next-generation sequencing (NGS) of 220 fresh-frozen samples, including paired primary and metastatic tumor tissue and non-tumorous tissue from 38 patients, revealed expression of 2245 known unique mature miRs and 515 novel candidate miRs. Unsupervised clustering of miR expression profiles of pCRC tissue with paired metastases did not separate the two entities, whereas unsupervised clustering of miR expression profiles of pCRC with normal colorectal mucosa demonstrated complete separation of the tumor samples from their paired normal mucosa. Two hundred and twenty-two miRs differentiated both pCRC and metastases from normal tissue samples (false discovery rate (FDR) <0.05). The highest expressed tumor-specific miRs were miR-21 and miR-92a, both previously described to be involved in CRC with potential as circulating biomarker for early detection. Only eight miRs, 0.5% of the analysed miR transcriptome, were differentially expressed between pCRC and the corresponding metastases (FDR <0.1), consisting of five known miRs (miR-320b, miR-320d, miR-3117, miR-1246 and miR-663b) and three novel candidate miRs (chr 1-2552-5p, chr 8-20656-5p and chr 10-25333-3p). These results indicate that previously unrecognized candidate miRs expressed in advanced CRC were identified using NGS. In addition, miR expression profiles of pCRC and metastatic lesions are highly comparable and may be of similar predictive value for prognosis or response to treatment in patients with advanced CRC.

Characteristics of successful technological interventions in mental resilience training.

In the last two decades, several effective virtual reality-based interventions for anxiety disorders have been developed. Virtual reality interventions can also be used to build resilience to psychopathology for populations at risk of exposure to traumatic experiences and developing mental disorders as a result, such as for people working in vulnerable professions. Despite the interest among mental health professionals and researchers in applying new technology-supported interventions for pre-trauma mental resilience training, there is a lack of recommendations about what constitutes potentially effective technology-supported resilience training. This article analyses the role of technology in the field of stress-resilience training. It presents lessons learned from technology developers currently working in the area, and it identifies some key clinical requirements for the supported resilience interventions. Two processes made up this research: 1) developers of technology-assisted resilience programs were interviewed regarding human-computer interaction and system development; 2) discussions with clinicians were prompted using technology-centered concept storyboards to elicit feedback, and to refine, validate and extend the initial concepts. A qualitative analysis of the interviews produced a set of development guidelines that engineers should follow and a list of intervention requirements that the technology should fulfill. These recommendations can help bridge the gap between engineers and clinicians when generating novel resilience interventions for people in vulnerable professions.

Colonic work-up after incomplete colonoscopy: significant new findings during follow-up.

BACKGROUND AND STUDY AIMS: Cecal intubation is not achieved in 2 - 23 % of colonoscopies. The efforts made by physicians to visualize the remaining colon and the number of missed significant lesions are unknown. This study evaluates 1) the reasons for incomplete colonoscopy, 2) the rates of complete colonic evaluation after incomplete colonoscopy, and 3) the number of (pre-) malignant lesions missed by incomplete colonoscopy. PATIENTS AND METHODS: In this population-based cohort study index colonoscopies were performed between September and December 2005. Prospectively collected data from consecutive patients with an incomplete colonoscopy were analyzed. For up to 18 months after the index colonoscopy, any further examinations performed in these patients were identified retrospectively. These secondary examinations included: repeat colonoscopy, computed tomography (CT) colonography, barium enema, abdominal CT scan, and surgery involving the colorectum. RESULTS: Of 5278 colonoscopies, 511 were incomplete (9.7 %). The most frequent causes of incomplete colonoscopy were looping of the scope (20.4 %), patient discomfort (15.3 %), and obstructing tumor (13.9 %). Secondary examination was performed in 278 patients (54.4 %) after incomplete colonoscopy. Patients undergoing surveillance after colorectal cancer (CRC) (78.9 %) and those with anemia (73.1 %) most frequently received a secondary examination. Incomplete colonoscopies due to stenosis (78.9 %), severe inflammation (77.8 %) or an obstructing tumor (74.6 %) were most frequently followed by a secondary examination. In all of the follow-up examinations, CRC was diagnosed in 18 patients (3.5 %) and advanced adenoma in four patients (0.8 %). CONCLUSIONS: In 4.3 % of the patients, advanced neoplasia was missed by incomplete colonoscopy. Our data therefore suggest that additional imaging is obligatory to visualize the remaining colon adequately.

Usability of an adaptive computer assistant that improves self-care and health literacy of older adults.

OBJECTIVES: We developed an adaptive computer assistant for the supervision of diabetics' self-care, to support limiting illness and need for acute treatment, and improve health literacy. This assistant monitors self-care activities logged in the patient's electronic diary. Accordingly, it provides context-aware feedback. The objective was to evaluate whether older adults in general can make use of the computer assistant and to compare an adaptive computer assistant with a fixed one, concerning its usability and contribution to health literacy. METHODS: We conducted a laboratory experiment in the Georgia Tech Aware Home wherein 28 older adults participated in a usability evaluation of the computer assistant, while engaged in scenarios reflecting normal and health-critical situations. We evaluated the assistant on effectiveness, efficiency, satisfaction, and educational value. Finally, we studied the moderating effects of the subjects' personal characteristics. RESULTS: Logging self-care tasks and receiving feedback from the computer assistant enhanced the subjects' knowledge of diabetes. The adaptive assistant was more effective in dealing with normal and health-critical situations, and, generally, it led to more time efficiency. Subjects' personal characteristics had substantial effects on the effectiveness and efficiency of the two computer assistants. CONCLUSIONS: Older adults were able to use the adaptive computer assistant. In addition, it had a positive effect on the development of health literacy. The assistant has the potential to support older diabetics' self care while maintaining quality of life.

Cognitive task load in a naval ship control centre: from identification to prediction.

Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed. It is based on a model distinguishing three load factors: time occupied, task-set switching, and level of information processing. Application of the method resulted in eight scenarios for eight extremes of task load (i.e. low and high values for each load factor). These scenarios were performed by 13 teams in a high-fidelity control centre simulator of the Royal Netherlands Navy. The results show that the method provides good prediction of the task load that will actually appear in the simulator. The model allowed identification of under- and overload situations showing negative effects on operator performance corresponding to controlled experiments in a less realistic task environment. Tools proposed to keep the operator at an optimum task load are (adaptive) task allocation and interface support.

Cognitive task analysis: harmonizing tasks to human capacities.

This paper presents the development of a cognitive task analysis that assesses the task load of jobs and provides indicators for the redesign of jobs. General principles of human task performance were selected and, subsequently, integrated into current task modelling techniques. The resulting cognitive task analysis centres around four aspects of task load: the number of actions in a period, the ratio between knowledge- and rule-based actions, lengthy uninterrupted actions, and momentary overloading. The method consists of three stages: (1) construction of a hierarchical task model, (2) a time-line analysis and task load assessment, and (3), if necessary, adjustment of the task model. An application of the cognitive task analysis in railway traffic control showed its benefits over the 'old' task load analysis of the Netherlands Railways. It provided a provisional standard for traffic control jobs, conveyed two load risks -- momentary overloading and underloading -- and resulted in proposals to satisfy the standard and to diminish the two load risk.