853 resultados para Small Area Estimation
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Proton radiation therapy is gaining popularity because of the unique characteristics of its dose distribution, e.g., high dose-gradient at the distal end of the percentage-depth-dose curve (known as the Bragg peak). The high dose-gradient offers the possibility of delivering high dose to the target while still sparing critical organs distal to the target. However, the high dose-gradient is a double-edged sword: a small shift of the highly conformal high-dose area can cause the target to be substantially under-dosed or the critical organs to be substantially over-dosed. Because of that, large margins are required in treatment planning to ensure adequate dose coverage of the target, which prevents us from realizing the full potential of proton beams. Therefore, it is critical to reduce uncertainties in the proton radiation therapy. One major uncertainty in a proton treatment is the range uncertainty related to the estimation of proton stopping power ratio (SPR) distribution inside a patient. The SPR distribution inside a patient is required to account for tissue heterogeneities when calculating dose distribution inside the patient. In current clinical practice, the SPR distribution inside a patient is estimated from the patient’s treatment planning computed tomography (CT) images based on the CT number-to-SPR calibration curve. The SPR derived from a single CT number carries large uncertainties in the presence of human tissue composition variations, which is the major drawback of the current SPR estimation method. We propose to solve this problem by using dual energy CT (DECT) and hypothesize that the range uncertainty can be reduced by a factor of two from currently used value of 3.5%. A MATLAB program was developed to calculate the electron density ratio (EDR) and effective atomic number (EAN) from two CT measurements of the same object. An empirical relationship was discovered between mean excitation energies and EANs existing in human body tissues. With the MATLAB program and the empirical relationship, a DECT-based method was successfully developed to derive SPRs for human body tissues (the DECT method). The DECT method is more robust against the uncertainties in human tissues compositions than the current single-CT-based method, because the DECT method incorporated both density and elemental composition information in the SPR estimation. Furthermore, we studied practical limitations of the DECT method. We found that the accuracy of the DECT method using conventional kV-kV x-ray pair is susceptible to CT number variations, which compromises the theoretical advantage of the DECT method. Our solution to this problem is to use a different x-ray pair for the DECT. The accuracy of the DECT method using different combinations of x-ray energies, i.e., the kV-kV, kV-MV and MV-MV pair, was compared using the measured imaging uncertainties for each case. The kV-MV DECT was found to be the most robust against CT number variations. In addition, we studied how uncertainties propagate through the DECT calculation, and found general principles of selecting x-ray pairs for the DECT method to minimize its sensitivity to CT number variations. The uncertainties in SPRs estimated using the kV-MV DECT were analyzed further and compared to those using the stoichiometric method. The uncertainties in SPR estimation can be divided into five categories according to their origins: the inherent uncertainty, the DECT modeling uncertainty, the CT imaging uncertainty, the uncertainty in the mean excitation energy, and SPR variation with proton energy. Additionally, human body tissues were divided into three tissue groups – low density (lung) tissues, soft tissues and bone tissues. The uncertainties were estimated separately because their uncertainties were different under each condition. An estimate of the composite range uncertainty (2s) was determined for three tumor sites – prostate, lung, and head-and-neck, by combining the uncertainty estimates of all three tissue groups, weighted by their proportions along typical beam path for each treatment site. In conclusion, the DECT method holds theoretical advantages in estimating SPRs for human tissues over the current single-CT-based method. Using existing imaging techniques, the kV-MV DECT approach was capable of reducing the range uncertainty from the currently used value of 3.5% to 1.9%-2.3%, but it is short to reach our original goal of reducing the range uncertainty by a factor of two. The dominant source of uncertainties in the kV-MV DECT was the uncertainties in CT imaging, especially in MV CT imaging. Further reduction in beam hardening effect, the impact of scatter, out-of-field object etc. would reduce the Hounsfeld Unit variations in CT imaging. The kV-MV DECT still has the potential to reduce the range uncertainty further.
Resumo:
Introduction The aim of this study was to determine which single measurement on post-mortem cardiac MR reflects actual heart weight as measured at autopsy, assess the intra- and inter-observer reliability of MR measurements, derive a formula to predict heart weight from MR measurements and test the accuracy of the formula to prospectively predict heart weight. Materials and methods 53 human cadavers underwent post-mortem cardiac MR and forensic autopsy. In Phase 1, left ventricular area and wall thickness were measured on short axis and four chamber view images of 29 cases. All measurements were correlated to heart weight at autopsy using linear regression analysis. In Phase 2, single left ventricular area measurements on four chamber view images (LVA_4C) from 24 cases were used to predict heart weight at autopsy based on equations derived during Phase 1. Intra-class correlation coefficient (ICC) was used to determine inter- and intra-reader agreement. Results Heart weight strongly correlates with LVA_4C (r=0.78 M; p<0.001). Intra-reader and inter-reader reliability was excellent for LVA_4C (ICC=0.81–0.91; p<0.001 and ICC=0.90; p<0.001 respectively). A simplified formula for heart weight ([g]≈LVA_4C [mm2]×0.11) was derived based on linear regression analysis. Conclusions This study shows that single circumferential area measurements of the left ventricle in the four chamber view on post-mortem cardiac MR reflect actual heart weight as measured at autopsy. These measurements yield an excellent intra- and inter-reader reliability and can be used to predict heart weight prior to autopsy or to give a reasonable estimate of heart weight in cases where autopsy is not performed.
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The vestibular system contributes to the control of posture and eye movements and is also involved in various cognitive functions including spatial navigation and memory. These functions are subtended by projections to a vestibular cortex, whose exact location in the human brain is still a matter of debate (Lopez and Blanke, 2011). The vestibular cortex can be defined as the network of all cortical areas receiving inputs from the vestibular system, including areas where vestibular signals influence the processing of other sensory (e.g. somatosensory and visual) and motor signals. Previous neuroimaging studies used caloric vestibular stimulation (CVS), galvanic vestibular stimulation (GVS), and auditory stimulation (clicks and short-tone bursts) to activate the vestibular receptors and localize the vestibular cortex. However, these three methods differ regarding the receptors stimulated (otoliths, semicircular canals) and the concurrent activation of the tactile, thermal, nociceptive and auditory systems. To evaluate the convergence between these methods and provide a statistical analysis of the localization of the human vestibular cortex, we performed an activation likelihood estimation (ALE) meta-analysis of neuroimaging studies using CVS, GVS, and auditory stimuli. We analyzed a total of 352 activation foci reported in 16 studies carried out in a total of 192 healthy participants. The results reveal that the main regions activated by CVS, GVS, or auditory stimuli were located in the Sylvian fissure, insula, retroinsular cortex, fronto-parietal operculum, superior temporal gyrus, and cingulate cortex. Conjunction analysis indicated that regions showing convergence between two stimulation methods were located in the median (short gyrus III) and posterior (long gyrus IV) insula, parietal operculum and retroinsular cortex (Ri). The only area of convergence between all three methods of stimulation was located in Ri. The data indicate that Ri, parietal operculum and posterior insula are vestibular regions where afferents converge from otoliths and semicircular canals, and may thus be involved in the processing of signals informing about body rotations, translations and tilts. Results from the meta-analysis are in agreement with electrophysiological recordings in monkeys showing main vestibular projections in the transitional zone between Ri, the insular granular field (Ig), and SII.
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Pulmonary airways are subdivided into conducting and gas-exchanging airways. An acinus is defined as the small tree of gas-exchanging airways, which is fed by the most distal purely conducting airway. Until now a dissector of five consecutive sections or airway casts were used to count acini. We developed a faster method to estimate the number of acini in young adult rats. Right middle lung lobes were critical point dried or paraffin embedded after heavy metal staining and imaged by X-ray micro-CT or synchrotron radiation-based X-rays tomographic microscopy. The entrances of the acini were counted in three-dimensional (3D) stacks of images by scrolling through them and using morphological criteria (airway wall thickness and appearance of alveoli). Segmentation stopper were placed at the acinar entrances for 3D visualizations of the conducting airways. We observed that acinar airways start at various generations and that one transitional bronchiole may serve more than one acinus. A mean of 5612 (±547) acini per lung and a mean airspace volume of 0.907 (±0.108) μL per acinus were estimated. In 60-day-old rats neither the number of acini nor the mean acinar volume did correlate with the body weight or the lung volume.
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The importance of small ruminants to the dairy industry has increased in recent years, especially in developing countries, where it has a high economic and social impact. Interestingly and despite the fact that the mammary gland is the specialised milk production organ, very few authors studied the modifications occurring in the mammary gland through the lactation period in production animals, particularly in the small ruminants, sheep (Ovis aries) and goat (Capra hircus). Nevertheless, understanding the different mammary gland patterns throughout lactation is essential to improve dairy production. In addition, associating these patterns with different milking frequencies, lactation number or different diets is also of high importance, directly affecting the dairy industry. The mammary gland is commonly composed of parenchyma and stroma, which includes the ductal system, with individual proportions of each changing during the different periods and yields in a lactation cycle. Indeed, during late gestation, as well as during early to mid-lactation, mammary gland expansion occurs, with an increase in the number of epithelial cells and lumen area, which leads to increment of the parenchyma tissue, as well as a reduction of stroma, corresponding macroscopically to the increase in mammary gland volume. Throughout late lactation, the mammary gland volume decreases owing to the regression of the secretory structure. In general, common mammary gland patterns have been shown for both goats and sheep throughout the several lactation stages, although the number of studies is limited. The main objective of this manuscript is to review the colostrogenesis and lactogenesis processes as well as to highlight the mammary gland morphological patterns underlying milk production during the lactation cycle for small ruminants, and to describe potential differences between goats and sheep, hence contributing to a better description of mammary gland development during lactation for these two poorly studied species.
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High Resolution Magic Angle Spinning (HR-MAS) NMR allows metabolic characterization of biopsies. HR-MAS spectra from tissues of most organs show strong lipid contributions that are overlapping metabolite regions, which hamper metabolite estimation. Metabolite quantification and analysis would benefit from a separation of lipids and small metabolites. Generally, a relaxation filter is used to reduce lipid contributions. However, the strong relaxation filter required to eliminate most of the lipids also reduces the signals for small metabolites. The aim of our study was therefore to investigate different diffusion editing techniques in order to employ diffusion differences for separating lipid and small metabolite contributions in the spectra from different organs for unbiased metabonomic analysis. Thus, 1D and 2D diffusion measurements were performed, and pure lipid spectra that were obtained at strong diffusion weighting (DW) were subtracted from those obtained at low DW, which include both small metabolites and lipids. This subtraction yielded almost lipid free small metabolite spectra from muscle tissue. Further improved separation was obtained by combining a 1D diffusion sequence with a T2-filter, with the subtraction method eliminating residual lipids from the spectra. Similar results obtained for biopsies of different organs suggest that this method is applicable in various tissue types. The elimination of lipids from HR-MAS spectra and the resulting less biased assessment of small metabolites have potential to remove ambiguities in the interpretation of metabonomic results. This is demonstrated in a reproducibility study on biopsies from human muscle.
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Mechanical injury of the CNS frequently results from accidents but also occurs in the course of neurosurgical interventions. A great variety of anatomical and physiological changes have been described to evolve after a brain trauma yet only little is known about processes that occur during a trauma. In the present study, I obtained whole-cell patch clamp recordings from pyramidal cells in hippocampal slice cultures while mechanically lesioning the CA3 area. Electrophysiological analysis revealed that traumatic injury massively increased excitatory and inhibitory synaptic activity in the entire CA3 region. Cutting the CA3 region induced highly rhythmic excitatory postsynaptic currents (EPSCs) that reached frequencies of around 70 Hz. Blocking voltage-dependent sodium channels with tetrodotoxin prevented the increase in synaptic activity and injury-induced neurotransmitter release in CA3 remote from the lesion site. With fast synaptic transmission blocked only neurons in the immediate vicinity of a lesion depolarized and fired action potentials upon mechanical damage. I hence suggest that mechanical injury damages the membrane and induces action potential firing in only a small population of neurons. This activity is then propagated throughout the undamaged CA3 network inducing highly rhythmic discharges. Thus mechanical brain injury initiates immediate functional changes that exceed the lesion site.
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The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.
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We reconstruct the timing of ice flow reconfiguration and deglaciation of the Central Alpine Gotthard Pass, Switzerland, using cosmogenic 10Be and in situ14C surface exposure dating. Combined with mapping of glacial erosional markers, exposure ages of bedrock surfaces reveal progressive glacier downwasting from the maximum LGM ice volume and a gradual reorganization of the paleoflow pattern with a southward migration of the ice divide. Exposure ages of ∼16–14 ka (snow corrected) give evidence for continuous early Lateglacial ice cover and indicate that the first deglaciation was contemporaneous with the decay of the large Gschnitz glacier system. In agreement with published ages from other Alpine passes, these data support the concept of large transection glaciers that persisted in the high Alps after the breakdown of the LGM ice masses in the foreland and possibly decayed as late as the onset of the Bølling warming. A younger group of ages around ∼12–13 ka records the timing of deglaciation following local glacier readvance during the Egesen stadial. Glacial erosional features and the distribution of exposure ages consistently imply that Egesen glaciers were of comparatively small volume and were following a topographically controlled paleoflow pattern. Dating of a boulder close to the pass elevation gives a minimum age of 11.1 ± 0.4 ka for final deglaciation by the end of the Younger Dryas. In situ14C data are overall in good agreement with the 10Be ages and confirm continuous exposure throughout the Holocene. However, in situ14C demonstrates that partial surface shielding, e.g. by snow, has to be incorporated in the exposure age calculations and the model of deglaciation.
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Mobile pastoralists provide major contributions to the gross domestic product in Chad, but little information is available regarding their demography. The Lake Chad area population is increasing, resulting in competition for scarce land and water resources. For the first time, the density of people and animals from mobile and sedentary populations was assessed using randomly defined sampling areas. Four sampling rounds were conducted over two years in the same areas to show population density dynamics. We identified 42 villages of sedentary communities in the sampling zones; 11 (in 2010) and 16 (in 2011) mobile pastoralist camps at the beginning of the dry season and 34 (in 2011) and 30 (in 2012) camps at the end of the dry season. A mean of 64.0 people per km2 (95% confidence interval, 20.3-107.8) were estimated to live in sedentary villages. In the mobile communities, we found 5.9 people per km2 at the beginning and 17.5 people per km2 at the end of the dry season. We recorded per km2 on average 21.0 cattle and 31.6 small ruminants in the sedentary villages and 66.1 cattle and 102.5 small ruminants in the mobile communities, which amounts to a mean of 86.6 tropical livestock units during the dry season. These numbers exceed, by up to five times, the published carrying capacities for similar Sahelian zones. Our results underline the need for a new institutional framework. Improved land use management must equally consider the needs of mobile communities and sedentary populations.
Continental-Scale Footprint of Balancing and Positive Selection in a Small Rodent (Microtus arvalis)
Resumo:
Genetic adaptation to different environmental conditions is expected to lead to large differences between populations at selected loci, thus providing a signature of positive selection. Whereas balancing selection can maintain polymorphisms over long evolutionary periods and even geographic scale, thus leads to low levels of divergence between populations at selected loci. However, little is known about the relative importance of these two selective forces in shaping genomic diversity, partly due to difficulties in recognizing balancing selection in species showing low levels of differentiation. Here we address this problem by studying genomic diversity in the European common vole (Microtus arvalis) presenting high levels of differentiation between populations (average FST = 0.31). We studied 3,839 Amplified Fragment Length Polymorphism (AFLP) markers genotyped in 444 individuals from 21 populations distributed across the European continent and hence over different environmental conditions. Our statistical approach to detect markers under selection is based on a Bayesian method specifically developed for AFLP markers, which treats AFLPs as a nearly codominant marker system, and therefore has increased power to detect selection. The high number of screened populations allowed us to detect the signature of balancing selection across a large geographic area. We detected 33 markers potentially under balancing selection, hence strong evidence of stabilizing selection in 21 populations across Europe. However, our analyses identified four-times more markers (138) being under positive selection, and geographical patterns suggest that some of these markers are probably associated with alpine regions, which seem to have environmental conditions that favour adaptation. We conclude that despite favourable conditions in this study for the detection of balancing selection, this evolutionary force seems to play a relatively minor role in shaping the genomic diversity of the common vole, which is more influenced by positive selection and neutral processes like drift and demographic history.
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After attending this presentation, attendees will: (1) understand how body height from computed tomography data can be estimated; and, (2) gain knowledge about the accuracy of estimated body height and limitations. The presentation will impact the forensic science community by providing knowledge and competence which will enable attendees to develop formulas for single bones to reconstruct body height using postmortem Computer Tomography (p-CT) data. The estimation of Body Height (BH) is an important component of the identification of corpses and skeletal remains. Stature can be estimated with relative accuracy via the measurement of long bones, such as the femora. Compared to time-consuming maceration procedures, p-CT allows fast and simple measurements of bones. This study undertook four objectives concerning the accuracy of BH estimation via p-CT: (1) accuracy between measurements on native bone and p-CT imaged bone (F1 according to Martin 1914); (2) intra-observer p-CT measurement precision; (3) accuracy between formula-based estimation of the BH and conventional body length measurement during autopsy; and, (4) accuracy of different estimation formulas available.1 In the first step, the accuracy of measurements in the CT compared to those obtained using an osteometric board was evaluated on the basis of eight defleshed femora. Then the femora of 83 female and 144 male corpses of a Swiss population for which p-CTs had been performed, were measured at the Institute of Forensic Medicine in Bern. After two months, 20 individuals were measured again in order to assess the intraobserver error. The mean age of the men was 53±17 years and that of the women was 61±20 years. Additionally, the body length of the corpses was measured conventionally. The mean body length was 176.6±7.2cm for men and 163.6±7.8cm for women. The images that were obtained using a six-slice CT were reconstructed with a slice thickness of 1.25mm. Analysis and measurements of CT images were performed on a multipurpose workstation. As a forensic standard procedure, stature was estimated by means of the regression equations by Penning & Riepert developed on a Southern German population and for comparison, also those referenced by Trotter & Gleser “American White.”2,3 All statistical tests were performed with a statistical software. No significant differences were found between the CT and osteometric board measurements. The double p-CT measurement of 20 individuals resulted in an absolute intra-observer difference of 0.4±0.3mm. For both sexes, the correlation between the body length and the estimated BH using the F1 measurements was highly significant. The correlation coefficient was slightly higher for women. The differences in accuracy of the different formulas were small. While the errors of BH estimation were generally ±4.5–5.0cm, the consideration of age led to an increase in accuracy of a few millimetres to about 1cm. BH estimations according to Penning & Riepert and Trotter & Gleser were slightly more accurate when age-at-death was taken into account.2,3 That way, stature estimations in the group of individuals older than 60 years were improved by about 2.4cm and 3.1cm.2,3 The error of estimation is therefore about a third of the common ±4.7cm error range. Femur measurements in p-CT allow very accurate BH estimations. Estimations according to Penning led to good results that (barely) come closer to the true value than the frequently used formulas by Trotter & Gleser “American White.”2,3 Therefore, the formulas by Penning & Riepert are also validated for this substantial recent Swiss population.
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Pollen and plant macrofossils were analysed at Sägistalsee (1935 m asl), a small lake near timber-line in the Swiss Northern Alps. Open forests with Pinus cembra and Abies alba covered the catchment during the early Holocene (9000–6300 cal. BP), suggesting subcontinental climate conditions. After the expansion of Picea abies between 6300 and 6000 cal. BP the subalpine forest became denser and the tree-line reached its maximum elevation at around 2260 m asl. Charcoal fragments in the macrofossil record indicate the beginning of Late-Neolithic human impact at ca. 4400 cal. BP, followed by a extensive deforestation and lowering of the forest-limit in the catchment of Sägistalsee at 3700 cal. BP (Bronze Age). Continuous human activity, combined with a more oceanic climate during the later Holocene, led to the local extinction of Pinus cembra and Abies alba and favoured the mass expansion of Picea and Alnus viridis in the subalpine area of the Northern Alps. The periods before 6300 and after 3700 cal. BP are characterised by high erosion activity in the lake's catchment, whereas during the phase of dense Picea-Pinus cembra-Abies forests (6300–3700 cal. BP) soils were stable and sediment-accumulation rates in the lake were low. Due to decreasing land-use at higher altitudes during the Roman occupation and the Migration period, forests spread beween ca. 2000 and 1500 cal. BP, before human impact increased again in the early Middle Ages. Recent reforestation due to land-use changes in the 20th century is recorded in the top sediments. Pollen-inferred July temperature and annual precipitation suggest a trend to cooler and more oceanic climate starting at about 5500 cal. BP.
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Comets often display narrow dust jets but more diffuse gas comae when their eccentric orbits bring them into the inner solar system and sunlight sublimates the ice on the nucleus. Comets are also understood to have one or more active areas covering only a fraction of the total surface active with sublimating volatile ices. Calculations of the gas and dust distribution from a small active area on a comet’s nucleus show that as the gas moves out radially into the vacuum of space it expands tangentially, filling much of the hemisphere centered on the active region. The dust dragged by the gas remains more concentrated over the active area. This explains some puzzling appearances of comets having collimated dust jets but more diffuse gaseous atmospheres. Our test case is 67P/Churyumov–Gerasimenko, the Rosetta mission target comet, whose activity is dominated by a single area covering only 4% of its surface.