The Role of Intestinal Microbiota in the Development and Severity of Chemotherapy-Induced Mucositis

Mucositis, also referred to as mucosal barrier injury, is one of the most debilitating side effects of radiotherapy and chemotherapy treatment. Clinically, mucositis is associated with pain, bacteremia, and malnutrition. Furthermore, mucositis is a frequent reason to postpone chemotherapy treatment, ultimately leading towards a higher mortality in cancer patients. According to the model introduced by Sonis, both inflammation and apoptosis of the mucosal barrier result in its discontinuity, thereby promoting bacterial translocation. According to this five-phase model, the intestinal microbiota plays no role in the pathophysiology of mucositis. However, research has implicated a prominent role for the commensal intestinal microbiota in the development of several inflammatory diseases like inflammatory bowel disease, pouchitis, and radiotherapy-induced diarrhea. Furthermore, chemotherapeutics have a detrimental effect on the intestinal microbial composition (strongly decreasing the numbers of anaerobic bacteria), coinciding in time with the development of chemotherapy-induced mucositis. We hypothesize that the commensal intestinal microbiota might play a pivotal role in chemotherapy-induced mucositis. In this review, we propose and discuss five pathways in the development of mucositis that are potentially influenced by the commensal intestinal microbiota: 1) the inflammatory process and oxidative stress, 2) intestinal permeability, 3) the composition of the mucus layer, 4) the resistance to harmful stimuli and epithelial repair mechanisms, and 5) the activation and release of immune effector molecules. Via these pathways, the commensal intestinal microbiota might influence all phases in the Sonis model of the pathogenesis of mucositis. Further research is needed to show the clinical relevance of restoring dysbiosis, thereby possibly decreasing the degree of intestinal mucositis

Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure

Item does not contain fulltextFunctional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n=14) from healthy controls (n=12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD

Higher fat stores contribute to persistence of little brown bat populations with white‐nose syndrome

The persistence of populations declining from novel stressors depends, in part, on their ability to respond by trait change via evolution or plasticity. White‐nose syndrome (WNS ) has caused rapid declines in several North America bat species by disrupting hibernation behaviour, leading to body fat depletion and starvation. However, some populations of Myotis lucifugus now persist with WNS by unknown mechanisms. We examined whether persistence of M. lucifigus with WNS could be explained by increased body fat in early winter, which would allow bats to tolerate the increased energetic costs associated with WNS . We also investigated whether bats were escaping infection or resistant to infection as an alternative mechanism explaining persistence. We measured body fat in early and late winter during initial WNS invasion and 8 years later at six sites where bats are now persisting. We also measured infection prevalence and intensity in persisting populations. Infection prevalence was not significantly lower than observed in declining populations. However, at two sites, infection loads were lower than observed in declining populations. Body fat in early winter was significantly higher in four of the six persisting populations than during WNS invasion. Physiological models of energy use indicated that these higher fat stores could reduce WNS mortality by 58%–70%. These results suggest that differences in fat storage and infection dynamics have reduced the impacts of WNS in many populations. Increases in body fat provide a potential mechanism for management intervention to help conserve bat populations