TRAUMATIC AXONAL INJURY IN THE MOUSE BRAIN

Despite decades of research into neurotrauma prevention and treatment, the underlying mechanisms responsible for Traumatic Brain Injury (TBI) are not well understood. This is a result of inadequate mechanical characterization of the brain during the traumatic event (e.g. blunt head impact), the resulting biochemical cascade occurring that the cellular level, and the following neurocognitive deficits that evolve over time. Traumatic Axonal Injury (TAI) can lead to widespread white matter disruption and is believed to play a large role in the neurocognitive outcomes of TBI patients, but the ability to assess TAI in humans is limited since most pathologies are only observable post-mortem. This creates a fundamental problem in the TBI research community: how can the deformations of the brain be linked with the pathological outcomes if both are difficult to measure in living humans? One solution to this problem is to evaluate TAI using animal models. Mouse models are commonly used together with blunt impact experiments to understand the pathologies and neurophysiological deficits related to TAI at different times post-injury, but the relationships between the initial impact, the subsequent motion of the mouse head, and the brain tissue distortion are not well established. To address this gap, this work examines the mechanics of the mouse brain during dynamic head rotations, which occur during head impacts in both the mouse and human. The first portion of the current work presents optical measurements of post-mortem mouse brain tissue during forced dynamic rotations. Using the experimental strain field measurements as a validation source, a Finite Element Model (FEM) of the mouse brain is developed in the second portion of the current work. The purpose of the mouse brain FEM is to calculate tissue strains that occur for a given rigid-body motion of the skull. In the third portion of current work, the FEM brain strain calculations are presented for a recent CHIMERA (Closed Head Impact Model of Engineered Rotational Acceleration) mouse experiments, and the axonal strains calculated by the model are compared TAI patterns observed in the experiments. The results here give insight to TAI mechanisms and thresholds, which is critical to better understanding TBI in humans

Raised temperatures over the Kericho Tea Estates: revisiting the climate in the East African highlands malaria debate: Supplemental Information

Supplemental information to a study examining a time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, for the 30-year period 1 January 1979 to 31 December 2009

Raised temperatures over the Kericho tea estates: revisiting the climate in the East African highlands malaria debate

<p>Abstract</p> <p>Background</p> <p>Whether or not observed increases in malaria incidence in the Kenyan Highlands during the last thirty years are associated with co-varying changes in local temperature, possibly connected to global changes in climate, has been debated for over a decade. Studies, using differing data sets and methodologies, produced conflicting results regarding the occurrence of temperature trends and their likelihood of being responsible, at least in part, for the increases in malaria incidence in the highlands of western Kenya. A time series of quality controlled daily temperature and rainfall data from Kericho, in the Kenyan Highlands, may help resolve the controversy. If significant temperature trends over the last three decades have occurred then climate should be included (along with other factors such as land use change and drug resistance) as a potential driver of the observed increases in malaria in the region.</p> <p>Methods</p> <p>Over 30 years (1 January 1979 to 31 December 2009) of quality controlled daily observations ( > 97% complete) of maximum, minimum and mean temperature were used in the analysis of trends at Kericho meteorological station, sited in a tea growing area of Kenya's western highlands. Inhomogeneities in all the time series were identified and corrected. Linear trends were identified via a least-squares regression analysis with statistical significance assessed using a two-tailed t-test. These 'gold standard' meteorological observations were compared with spatially interpolated temperature datasets that have been developed for regional or global applications. The relationship of local climate processes with larger climate variations, including tropical sea surface temperatures (SST), and El Niño-Southern Oscillation (ENSO) was also assessed.</p> <p>Results</p> <p>An upward trend of ≈0.2°C/decade was observed in all three temperature variables (P < 0.01). Mean temperature variations in Kericho were associated with large-scale climate variations including tropical SST (r = 0.50; p < 0.01). Local rainfall was found to have inverse effects on minimum and maximum temperature. Three versions of a spatially interpolated temperature data set showed markedly different trends when compared with each other and with the Kericho station observations.</p> <p>Conclusion</p> <p>This study presents evidence of a warming trend in observed maximum, minimum and mean temperatures at Kericho during the period 1979 to 2009 using gold standard meteorological observations. Although local factors may be contributing to these trends, the findings are consistent with variability and trends that have occurred in correlated global climate processes. Climate should therefore not be dismissed as a potential driver of observed increases in malaria seen in the region during recent decades, however its relative importance compared to other factors needs further elaboration. Climate services, pertinent to the achievement of development targets such as the Millennium Development Goals and the analysis of infectious disease in the context of climate variability and change are being developed and should increase the availability of relevant quality controlled climate data for improving development decisions. The malaria community should seize this opportunity to make their needs heard.</p

Testing a multi-malaria-model ensemble against 30 years of data in the Kenyan highlands

Background: Multi-model ensembles could overcome challenges resulting from uncertainties in models’ initial conditions, parameterization and structural imperfections. They could also quantify in a probabilistic way uncertainties in future climatic conditions and their impacts. Methods: A four-malaria-model ensemble was implemented to assess the impact of long-term changes in climatic conditions on Plasmodium falciparum malaria morbidity observed in Kericho, in the highlands of Western Kenya, over the period 1979–2009. Input data included quality controlled temperature and rainfall records gathered at a nearby weather station over the historical periods 1979–2009 and 1980–2009, respectively. Simulations included models’ sensitivities to changes in sets of parameters and analysis of non-linear changes in the mean duration of host’s infectivity to vectors due to increased resistance to anti-malarial drugs. Results: The ensemble explained from 32 to 38% of the variance of the observed P. falciparum malaria incidence. Obtained R2-values were above the results achieved with individual model simulation outputs. Up to 18.6% of the variance of malaria incidence could be attributed to the +0.19 to +0.25°C per decade significant long-term linear trend in near-surface air temperatures. On top of this 18.6%, at least 6% of the variance of malaria incidence could be related to the increased resistance to anti-malarial drugs. Ensemble simulations also suggest that climatic conditions have likely been less favourable to malaria transmission in Kericho in recent years. Conclusions: Long-term changes in climatic conditions and non-linear changes in the mean duration of host’s infectivity are synergistically driving the increasing incidence of P. falciparum malaria in the Kenyan highlands. User-friendly, online-downloadable, open source mathematical tools, such as the one presented here, could improve decision-making processes of local and regional health authorities

TRAUMATIC AXONAL INJURY IN THE MOUSE BRAIN

Despite decades of research into neurotrauma prevention and treatment, the underlying mechanisms responsible for Traumatic Brain Injury (TBI) are not well understood. This is a result of inadequate mechanical characterization of the brain during the traumatic event (e.g. blunt head impact), the resulting biochemical cascade occurring that the cellular level, and the following neurocognitive deficits that evolve over time. Traumatic Axonal Injury (TAI) can lead to widespread white matter disruption and is believed to play a large role in the neurocognitive outcomes of TBI patients, but the ability to assess TAI in humans is limited since most pathologies are only observable post-mortem. This creates a fundamental problem in the TBI research community: how can the deformations of the brain be linked with the pathological outcomes if both are difficult to measure in living humans? One solution to this problem is to evaluate TAI using animal models. Mouse models are commonly used together with blunt impact experiments to understand the pathologies and neurophysiological deficits related to TAI at different times post-injury, but the relationships between the initial impact, the subsequent motion of the mouse head, and the brain tissue distortion are not well established. To address this gap, this work examines the mechanics of the mouse brain during dynamic head rotations, which occur during head impacts in both the mouse and human. The first portion of the current work presents optical measurements of post-mortem mouse brain tissue during forced dynamic rotations. Using the experimental strain field measurements as a validation source, a Finite Element Model (FEM) of the mouse brain is developed in the second portion of the current work. The purpose of the mouse brain FEM is to calculate tissue strains that occur for a given rigid-body motion of the skull. In the third portion of current work, the FEM brain strain calculations are presented for a recent CHIMERA (Closed Head Impact Model of Engineered Rotational Acceleration) mouse experiments, and the axonal strains calculated by the model are compared TAI patterns observed in the experiments. The results here give insight to TAI mechanisms and thresholds, which is critical to better understanding TBI in humans

Designing Index-Based Weather Insurance for Farmers in Adi Ha, Ethiopia: Report to OXFAM America, July 2009

This report documents the process and results of the index insurance design effort leading to the index insurance contracts for Adi Ha in 2009. This report represents deliverables 1 and 2 in the terms of reference with Oxfam America, it outlines and compares analysis and design methodologies including the performance of rainfall simulators for index-based contract design. It also details contracts, methodologies, associated issues, and important lessons learned. A separate project report details the Experimental Games, deliverable 3 in the terms of reference