Age-related increase of kynurenic acid in human cerebrospinal fluid-IgG and beta(2)-microglobulin changes

Kynurenic acid (KYNA) is an endogenous metabolite in the kynurenine pathway of tryptophan degradation and is an antagonist at the glycine site of the N-methyl-D-aspartate as well as at the alpha 7 nicotinic cholinergic receptors. In the brain tissue KYNA is synthesised from L-kynurenine by kynurenine aminotransferases (KAT) I and II. A host of immune mediators influence tryptophan degradation. In the present study, the levels of KYNA in cerebrospinal fluid (CSF) and serum in a group of human subjects aged between 25 and 74 years were determined by using a high performance liquid chromatography method. In CSF and serum KAT I and II activities were investigated by radioenzymatic assay, and the levels of β2-microglobulin, a marker for cellular immune activation, were determined by ELISA. The correlations between neurochemical and biological parameters were evaluated. Two subject groups with significantly different ages, i.e. 50 years, p < 0.001, showed statistically significantly different CSF KYNA levels, i.e. 2.84 ± 0.16 fmol/μl vs. 4.09 ± 0.14 fmol/μl, p < 0.001, respectively; but this difference was not seen in serum samples. Interestingly, KYNA is synthesised in CSF principally by KAT I and not KAT II, however no relationship was found between enzyme activity and ageing. A positive relationship between CSF KYNA levels and age of subjects indicates a 95% probability of elevated CSF KYNA with ageing (R = 0.6639, p = 0.0001). KYNA levels significantly correlated with IgG and β2-microglobulin levels (R = 0.5244, p = 0.0049; R = 0.4253, p = 0.043, respectively). No correlation was found between other biological parameters in CSF or serum. In summary, a positive relationship between the CSF KYNA level and ageing was found, and the data would suggest age-dependent increase of kynurenine metabolism in the CNS. An enhancement of CSF IgG and β2-microglobulin levels would suggest an activation of the immune system during ageing. Increased KYNA metabolism may be involved in the hypofunction of the glutamatergic and/or nicotinic cholinergic neurotransmission in the ageing CNS

Studies on the physics and chemistry of estuarine waters In Chesapeake Bay

Estuarine waters are understood to be those water masses which by virtue of their position are directly subject to the combined action of river and tidal currents. They may be considered to reflect certain dominant forces as well as progressive trends that determine their individualistic though changing hydrographic as well as biologic properties. The factors that lend individuality to these bodies may exhibit profound differences in different latitudes and yet, in certain fundamental respects, the waters possess important characteristics in common...

A Pilot Study of Wichita Indian Archeology and Ethnohistory

In 1965 several anthropologists drew up plans for a one-year pilot study of the archeology and ethnohistory of the Wichita Indian tribes. After financial support had been generously provided by the National Science Foundation, the proposed research was carried out. This is a report on the results of that study. The pilot study was designed to: a) obtain a body of field data from the components of the Spanish Fort sites, the largest and best=documented of the historic Wichita sites in the Red River area; b) make test excavations at several other sites in order that a problem=oriented program of future research can be accurately planned; c) attempt to locate, by field reconnaissance, sites that relate to the Wichita occupation of the southern plains on both the historic and prehistoric time levels; d) make a survey of available ethnohistorical data in order (1) to compile a bibliography of documentary materials relevant to Wichita ethnohistory, (2) to make a detailed study of documents that relate specifically to the excavations being carried out at Spanish Fort and at the sites being tested, (3) to seek information that might lead to the field locations of other Wichita sites, and (4) to appraise those sources best suited for more extended examination. The co-investigators of the project were Tyler Bastian of the Museum of the Great Plains, Robert E. Bell of The University of Oklahoma, Edward B. Jelks of Southern Methodist University, and W.W. Newcomb of the Texas Memorial Museum at The University of Texas. Bastian supervised the archeological field work in Oklahoma under the direction of Bell. Jelks directed the archeological work in Texas. Newcomb directed the ethnohistorical research. Marvin E. Tong of the Museum of the Great Plains served the project as general coordinator. The main part of the ethnohistorical study consisted of a thorough search of the archives at The University of Texas for documents relating to Wichita ethnohistory. The archeological work included extensive excavations at the Longest Site in Oklahoma and at the Upper Tucker and Coyote Sites in Texas. More limited excavations were carried out at the Glass and Gas Plant Sites in Texas. Several other archeological sites were visited but not excavated beyond a test pit or two: the Devils Canyon and Wilson Springs Sites in Oklahoma, and the Gilbert, Stone, Vinson, and Womack Sites in Texas. An effort was also made to locate several sites in Oklahoma and Texas which were reported in historical documents but which had not been located in the field. After the library research and the archeological field work had been completed, a brief, general report could have been prepared to satisfy our contractual obligation to the National Science Foundation. It was felt, however, that the data which had been collected would be of interest to archeologists and ethnohistorians and, if possible, it should be made available to them in some detail without delay. Consequently, a series of descriptive papers was prepared instead of a summary report. Those papers are presented here

Integrated membrane systems for toxic cyanobacteria removal

Blue-green algae (cyanobacteria) provide a major problem for the water industry as they can produce metabolites toxic to humans in addition to taste and odour (T&O) compounds that make drinking water aesthetically displeasing. This problem is likely to be intensified by the effects of climate change through reservoir warming. Microfiltration (MF) provides a potential solution for dealing with blooms of toxic blue green algae. In the past, coagulation and sand filtration have been successfully used for removal of cyanobacteria, however as membrane technology has become more economically viable, the demand for information on the application of membranes for cyanobacterial metabolite removal has increased. MF pore size is a key matter as cyanobacterial metabolites should permeate such membranes. However, if cyanobacterial metabolites remain within the algal cells MF might be effective through the removal of these intact cells. This study investigated an integrated membrane system incorporating coagulation, powdered activated carbon and MF for the removal of intracellular and extracellular cyanobacterial metabolites. A laboratory scale MF unit was designed and studied. It utilised PVDF fibres with a nominal 0.02 micron pore size. Three species of blue-green algae were tested and three different coagulants were used on each species for removal of intact cells. Powdered activated carbon (PAC) was dosed prior to the MF at 20mg/L to remove extracellular metabolites. Cell counts as well as analysis for total and extracellular toxin and T&O were undertaken to assess each stage of the IMS. The results of this study are promising.Mike Dixon, Brian O'Neill, Yann Richard, Lionel Ho, Chris Chow and Gayle Newcombehttp://www.chemeca2010.com/abstract/460.as

Low-cost fluid flow sensor to enable electronic control of fractional distillation columns

A sensor is described that measures fluid flow up to 20 ml/minute, and down to 0.001 ml/minute. The measurement involves counting drips as they fall through a pair of optical beams. The beams are formed using a pair of ordinary optical proximity sensors arranged to face each other so that each photo- receiver sees the other sensor’s emitter. The beams operate at two different frequencies so as to prevent reflected signals interfering. Only two sensors, an 8-pin microcontroller, and four resistors are required for the sensing. Calibration for a specific fluid is straightforward. An ethanol-water mixture produces 16 drips/ml, significantly different from the default pharmaceutical value of 12 drips/ml

Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation. The devised architecture is the result of an in-depth analysis of the limitations of current networks proposed for similar applications. To overcome the computational burden of processing 3D medical scans, we have devised an efficient and effective dense training scheme which joins the processing of adjacent image patches into one pass through the network while automatically adapting to the inherent class imbalance present in the data. Further, we analyze the development of deeper, thus more discriminative 3D CNNs. In order to incorporate both local and larger contextual information, we employ a dual pathway architecture that processes the input images at multiple scales simultaneously. For post-processing of the networks soft segmentation, we use a 3D fully connected Conditional Random Field which effectively removes false positives. Our pipeline is extensively evaluated on three challenging tasks of lesion segmentation in multi-channel MRI patient data with traumatic brain injuries, brain tumors, and ischemic stroke. We improve on the state-of-the-art for all three applications, with top ranking performance on the public benchmarks BRATS 2015 and ISLES 2015. Our method is computationally efficient, which allows its adoption in a variety of research and clinical settings. The source code of our implementation is made publicly available

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation

We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation. The devised architecture is the result of an in-depth analysis of the limitations of current networks proposed for similar applications. To overcome the computational burden of processing 3D medical scans, we have devised an efficient and effective dense training scheme which joins the processing of adjacent image patches into one pass through the network while automatically adapting to the inherent class imbalance present in the data. Further, we analyze the development of deeper, thus more discriminative 3D CNNs. In order to incorporate both local and larger contextual information, we employ a dual pathway architecture that processes the input images at multiple scales simultaneously. For post-processing of the network's soft segmentation, we use a 3D fully connected Conditional Random Field which effectively removes false positives. Our pipeline is extensively evaluated on three challenging tasks of lesion segmentation in multi-channel MRI patient data with traumatic brain injuries, brain tumours, and ischemic stroke. We improve on the state-of-the-art for all three applications, with top ranking performance on the public benchmarks BRATS 2015 and ISLES 2015. Our method is computationally efficient, which allows its adoption in a variety of research and clinical settings. The source code of our implementation is made publicly available.This work is supported by the EPSRC First Grant scheme (grant ref no. EP/N023668/1) and partially funded under the 7th Framework Programme by the European Commission (TBIcare: http: //www.tbicare.eu/ ; CENTER-TBI: https://www.center-tbi.eu/). This work was further supported by a Medical Research Council (UK) Program Grant (Acute brain injury: heterogeneity of mechanisms, therapeutic targets and outcome effects [G9439390 ID 65883]), the UK National Institute of Health Research Biomedical Research Centre at Cambridge and Technology Platform funding provided by the UK Department of Health. KK is supported by the Imperial College London PhD Scholarship Programme. VFJN is supported by a Health Foundation/Academy of Medical Sciences Clinician Scientist Fellowship. DKM is supported by an NIHR Senior Investigator Award. We gratefully acknowledge the support of NVIDIA Corporation with the donation of two Titan X GPUs for our research

Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation

We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation. The devised architecture is the result of an in-depth analysis of the limitations of current networks proposed for similar applications. To overcome the computational burden of processing 3D medical scans, we have devised an efficient and effective dense training scheme which joins the processing of adjacent image patches into one pass through the network while automatically adapting to the inherent class imbalance present in the data. Further, we analyze the development of deeper, thus more discriminative 3D CNNs. In order to incorporate both local and larger contextual information, we employ a dual pathway architecture that processes the input images at multiple scales simultaneously. For post-processing of the network’s soft segmentation, we use a 3D fully connected Conditional Random Field which effectively removes false positives. Our pipeline is extensively evaluated on three challenging tasks of lesion segmentation in multi-channel MRI patient data with traumatic brain injuries, brain tumors, and ischemic stroke. We improve on the state-of-theart for all three applications, with top ranking performance on the public benchmarks BRATS 2015 and ISLES 2015. Our method is computationally efficient, which allows its adoption in a variety of research and clinical settings. The source code of our implementation is made publicly availabl