Recent pace of change in human impact on the world's ocean.

Humans interact with the oceans in diverse and profound ways. The scope, magnitude, footprint and ultimate cumulative impacts of human activities can threaten ocean ecosystems and have changed over time, resulting in new challenges and threats to marine ecosystems. A fundamental gap in understanding how humanity is affecting the oceans is our limited knowledge about the pace of change in cumulative impact on ocean ecosystems from expanding human activities - and the patterns, locations and drivers of most significant change. To help address this, we combined high resolution, annual data on the intensity of 14 human stressors and their impact on 21 marine ecosystems over 11 years (2003-2013) to assess pace of change in cumulative impacts on global oceans, where and how much that pace differs across the ocean, and which stressors and their impacts contribute most to those changes. We found that most of the ocean (59%) is experiencing significantly increasing cumulative impact, in particular due to climate change but also from fishing, land-based pollution and shipping. Nearly all countries saw increases in cumulative impacts in their coastal waters, as did all ecosystems, with coral reefs, seagrasses and mangroves at most risk. Mitigation of stressors most contributing to increases in overall cumulative impacts is urgently needed to sustain healthy oceans

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

Priorities for synthesis research in ecology and environmental science

ACKNOWLEDGMENTS We thank the National Science Foundation grant #1940692 for financial support for this workshop, and the National Center for Ecological Analysis and Synthesis (NCEAS) and its staff for logistical support.Peer reviewedPublisher PD

Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder.

A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.PEV was supported by the Medical Research Council (grant no. MR/K020706/1) and is a Fellow of MQ: Transforming Mental Health (MQF17_24)

Numerical light dosimetry in murine tissue: analysis of tumor curvature and angle of incidence effects upon fluence in the tissue

In order to better understand light dosimetry issues for photodynamic therapy (PDT), we have used various tumor and normal tissue geometries to develop a diffusion model of light transport in tissues. We hypothesize that tumor tissues with curved surfaces will have significantly different internal fluence distributions, as compared to tissues with flat surfaces. Using a mouse subcutaneous tumor and rear limb muscle model we compared the internal fluence values within the tissue. In addition, numerical simulations for these corresponding tissue geometries and laser light incidence angles were made. Assuming that the relative photon fluence in the tissue can be accurately modeled by the diffusion equation, we used a finite element approach to approximate the distribution inside the tissue. Meshes with different geometries (flat and curved with different curvatures) were used in this study to mimic the tumor and leg geometries of the murine tumors treated in the lab. Results suggest that tissues surface geometries and incidence angle of light can significantly alter the photon fluence inside the tissue. The photon fluence difference for an 8 mm diameter, curved surface mouse tumor vs. flat muscle tissue can be as high as 20%. In general, the greater the tissues curvature, the greater the potential loss in light fluence is. In summary, our data demonstrates the importance of tissue surface geometry and the incidence angle of light in determining optimal PDT light dosimetry, and indicates that comparisons between tissue geometries must be carried out with attention to differences in the internal optical distribution.</p

Numerical Light Dosimetry in Murine Tissue:Analysis of tumor curvature and angle of incidence effects upon fluence in the tissue

In order to better understand light dosimetry issues for photodynamic therapy (PDT), we have used various tumor and normal tissue geometries to develop a diffusion model of light transport in tissues. We hypothesize that tumor tissues with curved surfaces will have significantly different internal fluence distributions, as compared to tissues with flat surfaces. Using a mouse subcutaneous tumor and rear limb muscle model we compared the internal fluence values within the tissue. In addition, numerical simulations for these corresponding tissue geometries and laser light incidence angles were made. Assuming that the relative photon fluence in the tissue can be accurately modeled by the diffusion equation, we used a finite element approach to approximate the distribution inside the tissue. Meshes with different geometries (flat and curved with different curvatures) were used in this study to mimic the tumor and leg geometries of the murine tumors treated in the lab. Results suggest that tissues surface geometries and incidence angle of light can significantly alter the photon fluence inside the tissue. The photon fluence difference for an 8 mm diameter, curved surface mouse tumor vs. flat muscle tissue can be as high as 20%. In general, the greater the tissues curvature, the greater the potential loss in light fluence is. In summary, our data demonstrates the importance of tissue surface geometry and the incidence angle of light in determining optimal PDT light dosimetry, and indicates that comparisons between tissue geometries must be carried out with attention to differences in the internal optical distribution.</p

The relationship between partial pressure of oxygen and perfusion in two murine tumors after X-ray irradiation: a combined gadopentetate dimeglumine dynamic magnetic resonance imaging and in vivo electron paramagnetic resonance oximetry study

Changes of partial pressure of oxygen (pO2) and blood perfusion were studied in MTG-B and RIF-1 tumors (n = 5 each) before and after a single 20-Gy dose of X-ray irradiation. Using electron paramagnetic resonance oximetry, we have observed an initial fast decrease of pO2 after irradiation, followed by a slow increase. The time course of these changes was faster in the MTG-B tumors than in the RIF-1 tumors. Gadopentetate dimeglumine (Gd-DTPA) dynamic magnetic resonance imaging studies showed a reduction in uptake of Gd-DTPA at the time of minimum pO2 and a recovery at the time of maximum pO2 in each tumor. Previous work indicates that there is microscopic heterogeneity in tumors, with well-vascularized "capillary regions" being closer to capillaries than poorly vascularized "noncapillary regions." We propose a two-component (slow and fast) model of Gd-DTPA uptake that is designed to quantify the kinetics of these two compartments by analyzing the total tumor uptake kinetics without having to identify specific regions of interest. Total perfusion in the tumors was greatly reduced at the time of minimum oxygenation, and the volume of the slow component increased after irradiation. We conclude that a decrease in blood perfusion is one of the main causes of the decline in pO2 observed after irradiation