Preserving Madagascar's Natural Heritage: The Importance of Keeping the Island's Vertebrate Fossils in the Public Domain

No Abstrac

Collective emotions online and their influence on community life

E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information - how participants feel about the subject discussed or other group members. Emotions are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. It is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. We show the collective character of affective phenomena on a large scale as observed in 4 million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. Our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.Comment: 23 pages including Supporting Information, accepted to PLoS ON

Reliability of dynamic contrast-enhanced magnetic resonance imaging data in primary brain tumours: a comparison of Tofts and shutter speed models

Purpose To investigate the robustness of pharmacokinetic modelling of DCE-MRI brain tumour data and to ascertain reliable perfusion parameters through a model selection process and a stability test. Methods DCE-MRI data of 14 patients with primary brain tumours were analysed using the Tofts model (TM), the extended Tofts model (ETM), the shutter speed model (SSM) and the extended shutter speed model (ESSM). A no-effect model (NEM) was implemented to assess overfitting of data by the other models. For each lesion, the Akaike Information Criteria (AIC) was used to build a 3D model selection map. The variability of each pharmacokinetic parameter extracted from this map was assessed with a noise propagation procedure, resulting in voxel-wise distributions of the coefficient of variation (CV). Results The model selection map over all patients showed NEM had the best fit in 35.5% of voxels, followed by ETM (32%), TM (28.2%), SSM (4.3%) and ESSM (<0.1%). In analysing the reliability of Ktrans, when considering regions with a CV<20%, ≈25% of voxels were found to be stable across all patients. The remaining 75% of voxels were considered unreliable. Conclusions The majority of studies quantifying DCE-MRI data in brain tumours only consider a single model and whole-tumour statistics for the output parameters. Appropriate model selection, considering tissue biology and its effects on blood brain barrier permeability and exchange conditions, together with an analysis on the reliability and stability of the calculated parameters, is critical in processing robust brain tumour DCE-MRI data

Mental Health Diagnoses and Utilization of VA Non-Mental Health Medical Services Among Returning Iraq and Afghanistan Veterans

Over 35% of returned Iraq and Afghanistan veterans in VA care have received mental health diagnoses; the most prevalent is post-traumatic stress disorder (PTSD). Little is known about these patients’ use of non-mental health medical services and the impact of mental disorders on utilization. To compare utilization across three groups of Iraq and Afghanistan veterans: those without mental disorders, those with mental disorders other than PTSD, and those with PTSD. National, descriptive study of 249,440 veterans newly utilizing VA healthcare between October 7, 2001 and March 31, 2007, followed until March 31, 2008. We used ICD9-CM diagnostic codes to classify mental health status. We compared utilization of outpatient non-mental health services, primary care, medical subspecialty, ancillary services, laboratory tests/diagnostic procedures, emergency services, and hospitalizations during veterans’ first year in VA care. Results were adjusted for demographics and military service and VA facility characteristics. Veterans with mental disorders had 42–146% greater utilization than those without mental disorders, depending on the service category (all P &lt; 0.001). Those with PTSD had the highest utilization in all categories: 71–170% greater utilization than those without mental disorders (all P &lt; 0.001). In adjusted analyses, compared with veterans without mental disorders, those with mental disorders other than PTSD had 55% higher utilization of all non-mental health outpatient services; those with PTSD had 91% higher utilization. Female sex and lower rank were also independently associated with greater utilization. Veterans with mental health diagnoses, particularly PTSD, utilize significantly more VA non-mental health medical services. As more veterans return home, we must ensure resources are allocated to meet their outpatient, inpatient, and emergency needs

A simple, reproducible method for monitoring the treatment of tumours using dynamic contrast-enhanced MR imaging

Dynamic contrast-enhanced MR imaging (DCE-MRI) may act as a biomarker for successful cancer therapy. Simple, reproducible techniques may widen this application. This paper demonstrates a single slice imaging technique. The image acquisition is performed in less than 500 ms making it relatively insensitive to respiratory motion. Data from phantom studies and a reproducibility study in solid human tumours are presented. The reproducibility study showed a coefficient of variation (CoV) of 19.1% for Ktrans and 15.8% for the initial area under the contrast enhancement curve (IAUC). This was improved to 16 and 13.9% if tumours of diameter less than 3 cm were excluded. The individual repeatability (the range within which individual measurements are expected to fall) was 30.6% for Ktrans and 26.5% for IAUC for tumours greater than 3 cm diameter. This approach to DCE–MRI image acquisition can be performed with standard clinical scanners, and data analysis is straightforward. For treatment trials with 10 patients in a cohort, the CoV implies that the method would be sensitive to a treatment effect of greater than 18%. The individual repeatability is well inside the 40% change shown to be important in clinical studies using this DCE–MRI technique

Relationship between human tumour angiogenic profile and combretastatin-induced vascular shutdown: an exploratory study

Combretastatin-A4-phosphate (CA4P) acts most effectively against immature tumour vasculature. We investigated whether histological angiogenic profile can explain the differential sensitivity of human tumours to CA4P, by correlating the kinetic changes demonstrated by dynamic MRI (DCE-MRI) in response to CA4P, with tumour immunohistochemical angiogenic markers. Tissue was received from 24 patients (mean age 59, range 32–73, 18 women, 6 men). An angiogenic profile was performed using standard immunohistochemical techniques. Dynamic MRI data were obtained for the same patients before and 4 h after CA4P. Three patients showed a statistically significant fall in Ktrans following CA4P, and one a statistically significant fall in IAUGC60. No statistically significant correlations were seen between the continuous or categorical variables and the DCE-MRI kinetic parameters other than between ang-2 and Ktrans (P=0.044). In conclusion, we found no strong relationships between changes in DCE-MRI kinetic variables following CA4P and the immunohistochemical angiogenic profile

Breast imaging technology: Application of magnetic resonance imaging to angiogenesis in breast cancer

Magnetic resonance imaging (MRI) techniques enable vascular function to be mapped with high spatial resolution. Current methods for imaging in breast cancer are described, and a review of recent studies that compared dynamic contrast-enhanced MRI with histopathological indicators of tumour vascular status is provided. These studies show correlation between in vivo dynamic contrast measurements and in vitro histopathology. Dynamic contrast enhanced MRI is also being applied to assessment of the response of breast tumours to treatment

Ten years of major equestrian injury: are we addressing functional outcomes?

YesFunding provided by the Open Access Authors Fund

Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic response

Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic respons