1,608 research outputs found
Tau Kinetics in Alzheimer\u27s Disease
The Cytoskeletal Protein Tau is Implicated in the Pathogenesis of Alzheimer\u27s Disease Which is Characterized by Intra-Neuronal Neurofibrillary Tangles Containing Abnormally Phosphorylated Insoluble Tau. Levels of Soluble Tau Are Elevated in the Brain, the CSF, and the Plasma of Patients with Alzheimer\u27s Disease. to Better Understand the Causes of These Elevated Levels of Tau, We Propose a Three-Compartment Kinetic Model (Brain, CSF, and Plasma). the Model Assumes that the Synthesis of Tau Follows Zero-Order Kinetics (Uncorrelated with Compartmental Tau Levels) and that the Release, Absorption, and Clearance of Tau is Governed by First-Order Kinetics (Linearly Related to Compartmental Tau Levels). Tau that is Synthesized in the Brain Compartment Can Be Released into the Interstitial Fluid, Catabolized, or Retained in Neurofibrillary Tangles. Tau Released into the Interstitial Fluid Can Mix with the CSF and Eventually Drain to the Plasma Compartment. However, Losses of Tau in the Drainage Pathways May Be Significant. the Kinetic Model Estimates Half-Life of Tau in Each Compartment (552 H in the Brain, 9.9 H in the CSF, and 10 H in the Plasma). the Kinetic Model Predicts that an Increase in the Neuronal Tau Synthesis Rate or a Decrease in Tau Catabolism Rate Best Accounts for Observed Increases in Tau Levels in the Brain, CSF, and Plasma Found in Alzheimer\u27s Disease. Furthermore, the Model Predicts that Increases in Brain Half-Life of Tau in Alzheimer\u27s Disease Should Be Attributed to Decreased Tau Catabolism and Not to Increased Tau Synthesis. Most Clearance of Tau in the Neuron Occurs through Catabolism Rather Than Release to the CSF Compartment. Additional Experimental Data Would Make Ascertainment of the Model Parameters More Precise
Volunteer RR® corn management in Roundup Ready® soybean-corn succession system.
ABSTRACT - The present study evaluated the effects of cover crops (Pennisetum glaucum, Crotalaria spectabilis and Urochloa ruziziensis) associated with the application of herbicides {glyphosate; (glyphosate + haloxyfop-R); (glyphosate + fluazifop-p-butyl); (glyphosate + imazethapyr) and (glyphosate + imazaquin)} in soybean desiccation management for volunteer RR® corn control. The experiment was conducted under field conditions at Sinop-MT, during the 2013/2014 crop season, in a randomized complete blocks design with factorial scheme and four replications. The following parameter were evaluated: dry matter of cover crops and ground coverage rate, control of volunteer RR® corn present at the time of desiccation, dry matter, height and intoxication level on soybean plants caused by herbicides at 7, 14 and 28 days after emergence (DAE), control of volunteer RR® corn derived from emergence fluxes subsequent to desiccation management and soybean yield. The joint application of (glyphosate + haloxyfop-R) provided the best level of volunteer RR® corn control present at the time of desiccation. Satisfactory control (80%) of volunteer corn was obtained with the application of (glyphosate + imazethapyr). This treatment displayed an additional residual effect of imazethapyr, which efficiently controled volunteer RR® corn derived from fluxes subsequent to desiccation management, especially in treatments performed under U. ruziziensis straw. None of the herbicides used in desiccation management caused any significant effect on dry matter, height and phytotoxicity of soybean plants at 7, 14 and 28 DAE nor on grain yield. RESUMO - Avaliaram-se nesta pesquisa os efeitos de plantas de cobertura (Pennisetum glaucum, Urochloa ruziziensis e Crotalaria spectabilis) associadas à aplicação de herbicidas {glyphosate; (glyphosate+haloxyfop-R), (glyphosate+fluazifop-p-butil), (glyphosate+imazethapyr) e (glyphosate+imazaquin)} no manejo de dessecação na cultura da soja, visando o controle do milho RR® voluntário. O experimento foi conduzido em campo no município de Sinop-MT, na safra 2013/2014, no delineamento experimental de blocos casualizados, em esquema fatorial, com quatro repetições. Foram avaliados: matéria seca das plantas de cobertura e cobertura do solo, controle do milho RR® voluntário presente no momento da dessecação, matéria seca, altura e intoxicação das plantas de soja pelos herbicidas aos 7, 14 e 28 dias após a emergência (DAE), controle do milho RR® voluntário oriundo de fluxos de emergência posterior ao manejo de dessecação e produtividade da soja. A aplicação conjunta de (glyphosate+haloxyfop-R) proporcionou o melhor nível de controle do milho RR® voluntário presente no momento da dessecação. Controle satisfatório (80%) do milho voluntário foi obtido com a aplicação de (glyphosate+imazethapyr). Este tratamento teve como adicional o efeito residual do imazethapyr, que controlou de maneira eficiente o milho RR® voluntário oriundo de fluxo posterior ao manejo de dessecação, principalmente nos tratamentos cultivados sob palhada de U. ruziziensis. Não houve efeito significativo dos herbicidas utilizados no manejo de dessecação na matéria seca, altura e fitotoxicidade das plantas de soja aos 7, 14 e 28 DAE e na produtividade de grãos
Liver and Intestine Transplantation in the United States, 1996–2005
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72937/1/j.1600-6143.2007.01782.x.pd
A Kinetic Model for Blood Biomarker Levels after Mild Traumatic Brain Injury
Traumatic brain injury (TBI) imposes a significant economic and social burden. The diagnosis and prognosis of mild TBI, also called concussion, is challenging. Concussions are common among contact sport athletes. After a blow to the head, it is often difficult to determine who has had a concussion, who should be withheld from play, if a concussed athlete is ready to return to the field, and which concussed athlete will develop a post-concussion syndrome. Biomarkers can be detected in the cerebrospinal fluid and blood after traumatic brain injury and their levels may have prognostic value. Despite significant investigation, questions remain as to the trajectories of blood biomarker levels over time after mild TBI. Modeling the kinetic behavior of these biomarkers could be informative. We propose a one-compartment kinetic model for S100B, UCH-L1, NF-L, GFAP, and tau biomarker levels after mild TBI based on accepted pharmacokinetic models for oral drug absorption. We approximated model parameters using previously published studies. Since parameter estimates were approximate, we did uncertainty and sensitivity analyses. Using estimated kinetic parameters for each biomarker, we applied the model to an available post-concussion biomarker dataset of UCH-L1, GFAP, tau, and NF-L biomarkers levels. We have demonstrated the feasibility of modeling blood biomarker levels after mild TBI with a one compartment kinetic model. More work is needed to better establish model parameters and to understand the implications of the model for diagnostic use of these blood biomarkers for mild TBI
Is Thick Brane Model Consistent with the Recent Observations?
There exist many observational evidences implying the expansion of our
universe is undergoing a late-time acceleration, the mechanism of this
acceleration is yet unknown. In the so-called thick brane model this phenomena
is attributed to the thickness of the brane along the extra dimension. In this
study we mainly rely to the consistency of this model with most recent
observational data related to the background evolution. The new Supernova Type
Ia (SNIa) Gold sample and Supernova Legacy Survey (SNLS) data, the position of
the acoustic peak at the last scattering surface from the WMAP observations and
the baryon acoustic oscillation peak found in the Sloan Digital Sky Survey
(SDSS) are used to constrain the free parameter of the thick codimension 1
brane model. To infer its consistency with age of our universe, we compare the
age of old cosmological objects with what computed using the best fit values
for the model parameters. When the universe is matter dominated, , at 68%
level of confidence, the combination of Gold sample SNIa, CMB shift parameter
and SDSS databases provides ,
, , hence a
spatially open universe with . The same
combination with SNLS supernova observation gives
, ,
consequently provides a spatially open universe
. These results obviously seem to be in
contradiction with the most recent WMAP results indicating a flat universe.Comment: 15 pages and 15 figures, V2: Added references and minor corrections,
main results and conclusions unchange
Quality of life and sexual function in patients aged 35 years or younger undergoing hysterectomy for benign gynecologic conditions: A prospective cohort study
Objective: To evaluate how hysterectomy performed for benign gynecologic pathologies affects the quality of life and sexual function of patients aged 35 years or younger,
and if outcomes differ according to the surgical technique.
Methods: Seventy-three patients who underwent total laparoscopic hysterectomy
(TLH), supracervical laparoscopic hysterectomy (SLH), or vaginal hysterectomy (VH)
for benign uterine disorders between April 2014 and June 2020 at the Department of
Gynecology and Obstetrics, Saarland University Hospital, Homburg, Germany, were
enrolled in this prospective observational cohort study. Quality of life and sexual
function were assessed preoperatively and 6 months postoperatively using standardized validated questionnaires: the European Quality of Life Five-Dimension Scale
(EQ-5D) and the Female Sexual Function Index (FSFI).
Results: Thirty-three (45%) patients underwent TLH, 25 (34%) underwent SLH, and
15 (21%) patients underwent VH. The median preoperative EQ-5D score, FSFI score,
and EQ-5D visual analog scale were 0.9 (range 0.62–1), 19.25 (range 2.4–27.4), and 50
(range 0–100); postoperative scores were 1 (range 0.61–1), 24.15 (range 3.9–29.3), and
90 (range 30–100), respectively (P ≤ 0.001). Postoperative scores were significantly
higher than preoperative scores, with no significant difference according to the surgical technique.
Conclusion: Hysterectomy for benign indication in women aged 35 years or less significantly improved the patients' quality of life and sexual function with no differences regarding the surgical technique
A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries
With the global rise of cardiovascular disease including atherosclerosis, there is a high demand or accurate diagnostic tools that can be used during a short consultation. In view of pathology, abnormal blood flow patterns have been demonstrated to be strong predictors of atherosclerotic lesion incidence, location, progression, and rupture. Prediction of patient-specific blood flow patterns can hence enable fast clinical diagnosis. However, the current state of art for the technique is by employing 3D-imaging-based Computational Fluid Dynamics (CFD). The high computational cost renders these methods impractical. In this work, we present a novel method to expedite the reconstruction of 3D pressure and shear stress fields using a combination of a reduced-order CFD modelling technique together with non-linear regression tools from the Machine Learning (ML) paradigm. Specifically, we develop a proof-of-concept automated pipeline that uses randomised perturbations of an atherosclerotic pig coronary artery to produce a large dataset of unique mesh geometries with variable blood flow. A total of 1407 geometries were generated from seven reference arteries and were used to simulate blood flow using the CFD solver Abaqus. This CFD dataset was then post-processed using the mesh-domain common-base Proper Orthogonal Decomposition (cPOD) method to obtain Eigen functions and principal coefficients, the latter of which is a product of the individual mesh flow solutions with the POD Eigenvectors. Being a data-reduction method, the POD enables the data to be represented using only the ten most significant modes, which captures cumulatively greater than 95% of variance of flow features due to mesh variations. Next, the node coordinate data of the meshes were embedded in a two-dimensional coordinate system using the t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm. The reduced dataset for t-SNE coordinates and corresponding vector of POD coefficients were then used to train a Random Forest Regressor (RFR) model. The same methodology was applied to both the volumetric pressure solution and the wall shear stress. The predicted pattern of blood pressure, and shear stress in unseen arterial geometries were compared with the ground truth CFD solutions on 'unseen' meshes. The new method was able to reliably reproduce the 3D coronary artery haemodynamics in less than 10 seconds
When do colliding bubbles produce an expanding universe?
It is intriguing to consider the possibility that the Big Bang of the
standard (3+1) dimensional cosmology originated from the collision of two
branes within a higher dimensional spacetime, leading to the production of a
large amount of entropy. In this paper we study, subject to certain
well-defined assumptions, under what conditions such a collision leads to an
expanding universe. We assume the absence of novel physics, so that ordinary
(4+1) -dimensional Einstein gravity remains a valid approximation. It is
necessary that the fifth dimension not become degenerate at the moment of
collision. First the case of a symmetric collision of infinitely thin branes
having a hyperbolic or flat spatial geometry is considered. We find that a
symmetric collision results in a collapsing universe on the final brane unless
the pre-existing expansion rate in the bulk just prior to the collision is
sufficiently large in comparison to the momentum transfer in the fifth
dimension. Such prior expansion may either result from negative spatial
curvature or from a positive five-dimensional cosmological constant. The
relevance of these findings to the Colliding Bubble Braneworld Universe
scenario is discussed. Finally, results from a numerical study of colliding
thick-wall branes is presented, which confirm the results of the thin-wall
approximation.Comment: 24 pages, 13 figures. Minor changes and references include
A physics-based machine learning technique rapidly reconstructs the wall-shear stress and pressure fields in coronary arteries
With the global rise of cardiovascular disease including atherosclerosis, there is a high demand for accurate diagnostic tools that can be used during a short consultation. In view of pathology, abnormal blood flow patterns have been demonstrated to be strong predictors of atherosclerotic lesion incidence, location, progression, and rupture. Prediction of patient-specific blood flow patterns can hence enable fast clinical diagnosis. However, the current state of art for the technique is by employing 3D-imaging-based Computational Fluid Dynamics (CFD). The high computational cost renders these methods impractical. In this work, we present a novel method to expedite the reconstruction of 3D pressure and shear stress fields using a combination of a reduced-order CFD modelling technique together with non-linear regression tools from the Machine Learning (ML) paradigm. Specifically, we develop a proof-of-concept automated pipeline that uses randomised perturbations of an atherosclerotic pig coronary artery to produce a large dataset of unique mesh geometries with variable blood flow. A total of 1,407 geometries were generated from seven reference arteries and were used to simulate blood flow using the CFD solver Abaqus. This CFD dataset was then post-processed using the mesh-domain common-base Proper Orthogonal Decomposition (cPOD) method to obtain Eigen functions and principal coefficients, the latter of which is a product of the individual mesh flow solutions with the POD Eigenvectors. Being a data-reduction method, the POD enables the data to be represented using only the ten most significant modes, which captures cumulatively greater than 95% of variance of flow features due to mesh variations. Next, the node coordinate data of the meshes were embedded in a two-dimensional coordinate system using the t-distributed Stochastic Neighbor Embedding ((Formula presented.) -SNE) algorithm. The reduced dataset for (Formula presented.) -SNE coordinates and corresponding vector of POD coefficients were then used to train a Random Forest Regressor (RFR) model. The same methodology was applied to both the volumetric pressure solution and the wall shear stress. The predicted pattern of blood pressure, and shear stress in unseen arterial geometries were compared with the ground truth CFD solutions on “unseen” meshes. The new method was able to reliably reproduce the 3D coronary artery haemodynamics in less than 10 s
Early Life Socioeconomic Circumstance and Late Life Brain Hyperintensities : A Population Based Cohort Study
Funding: Image acquisition and image analysis for this study was funded by the Alzheimer's Research Trust (now Alzheimer's Research UK). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments The authors would like to thank the participants of the Aberdeen 1936 Birth Cohort (ABC36), without whom this research would not have been possible.Peer reviewedPublisher PD
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