Excess radiation absorbed doses from non-optimised radioiodine treatment of hyperthyroidism

Radioiodine therapy is often the method of choice for treatment of hyperthyroidism because it is considered safe, is relatively inexpensive, and is convenient for the patient and except for occasional hypothyroidism, almost without side effects. Even though radioiodine treatment has been performed for over 50 years, the method of treatment differs from country to country and even from hospital to hospital within the same country. To illuminate such differences 187 radioiodine treatments for Graves' disease at Malm? University Hospital in Sweden have been analysed. Comparative dose calculations were carried out assuming that the individual patients had also been treated according to a number of other protocols in current use. The results show that the protocol used for calculating the administered activity in radioiodine therapy is far from optimised in many hospitals. Following the protocols where the absorbed dose to the thyroid is calculated without any uptake measurements after administration of a test activity, most of the patients were treated with an unnecessarily high activity, as a mean factor of 2.5 times too high and in individual patients up to eight times too high, leading to an unnecessary radiation exposure both for the patient, the family and the public. This is not in accordance with generally accepted radiation protection principles. Using higher activity than necessary will also prolong the patient's stay at the hospital and thus increase the costs for the care. Unnecessarily high activity will also necessitate more long-lasting radiation protection restriction relative to family members when the patient is back home.     

Selecting informative data for developing peptide-MHC binding predictors using a query by committee approach

Strategies for selecting informative data points for training prediction algorithms are important, particularly when data points are difficult and costly to obtain. A Query by Committee (QBC) training strategy for selecting new data points uses the disagreement between a committee of different algorithms to suggest new data points, which most rationally complement existing data, that is, they are the most informative data points. In order to evaluate this QBC approach on a real-world problem, we compared strategies for selecting new data points. We trained neural network algorithms to obtain methods to predict the binding affinity of peptides binding to the MHC class I molecule, HLA-A2. We show that the QBC strategy leads to a higher performance than a baseline strategy where new data points are selected at random from a pool of available data. Most peptides bind HLA-A2 with a low affinity, and as expected using a strategy of selecting peptides that are predicted to have high binding affinities also lead to more accurate predictors than the base line strategy. The QBC value is shown to correlate with the measured binding affinity. This demonstrates that the different predictors can easily learn if a peptide will fail to bind, but often conflict in predicting if a peptide binds. Using a carefully constructed computational setup, we demonstrate that selecting peptides with a high QBC performs better than low QBC peptides independently from binding affinity. When predictors are trained on a very limited set of data they cannot be expected to disagree in a meaningful way and we find a data limit below which the QBC strategy fails. Finally, it should be noted that data selection strategies similar to those used here might be of use in other settings in which generation of more data is a costly process.     

Chemical,rheological and parotta making characteristics of flourmill streams

Chemical, rheological and parotta-making characteristics of wheat-milling flour streams were studied with the main aim of developing a speciality flour for parotta. Important quality characteristics such as ash, flour colour, dry gluten content, sedimentation value, free and bound lipid content, farinograph and alveograph characteristics of the mill streams were determined. The studies showed an increase in ash, gluten content and sedimentation value with increasing numbers of breaks in the flour streams. An increase in percentage whiteness and bound lipids was observed in the first five reduction passages (C1 to C5). The alveograph characteristics indicated that the average abscissa at rupture (L) length of the curve increased with increasing reduction streams from C1 to C5, and also that the curves were better balanced when compared to 1 BK to 5 BK. The parottas made from the first five break passages had a decreased spread ratio, dull brown colour, and fused layers and lower overall quality score (43–79). The initial reduction streams (C1 to C5) produced good quality parottas in terms of appearance, spread, layers and texture. The shear force values indicating the texture of the product ranged from 1,120 to 1,250 g. The speciality flour made by combining C1 to C5 streams had 0.45% ash, 9.63% dry gluten, 45 ml sodium dodecyl sulphate sedimentation value, 0.7% free lipid and 1.8% bound lipid and produced parottas having creamish white colour, excellent pliability, thin, transparent and distinct layers, soft texture and moderate chewiness. In the mouth the parottas broke down easily, without leaving any residue. The overall quality score of parotta was highest (93.5) for the speciality flour when compared to break and reduction streams (43–77 and 56–92 respectively).     

Upscaling and automation of electrophysiology: toward high throughput screening in ion channel drug discovery

Effective screening of large compound libraries in ion channel drug discovery requires the development of new electrophysiological techniques with substantially increased throughputs compared to the conventional patch clamp technique. Sophion Bioscience is aiming to meet this challenge by developing two lines of automated patch clamp products, a traditional pipette-based system called Apatchi-1, and a silicon chip-based system QPatch. The degree of automation spans from semi-automation (Apatchi-1) where a trained technician interacts with the system in a limited way, to a complete automation (QPatch 96) where the system works continuously and unattended until screening of a full compound library is completed. The performance of the systems range from medium to high throughputs.     

O-Buffer based IFT watershed from markers for large medical datasets

The watershed transform from markers is a very popular image segmentation operator. The image foresting transform (IFT) watershed is a common method to compute the watershed transform from markers using a priority queue, but which can consume too much memory when applied to three-dimensional medical datasets. This is a considerable limitation on the applicability of the IFT watershed, as the size of medical datasets keeps increasing at a faster pace than physical memory technologies develop. This paper presents the O-IFT watershed, a new type of IFT watershed based on the O-Buffer framework, and introduces an efficient data representation which considerably reduces the memory consumption of the algorithm. In addition, this paper introduces the O-Buckets, a new implementation of the priority queue which further reduces the memory consumption of the algorithm. The new O-IFT watershed with O-Buckets allows the application of the watershed transform from markers to large medical datasets.     

Parallel processing in a multifeature whole-report paradigm.

Observers given brief exposures of pairs of colored bars and asked to report both the color and the orientation of each bar showed evidence of stochastic independence between reports of the 4 features (2 colors and 2 orientations). The authors also found virtually perfect stochastic independence between reports of colors and directions of motion of pairwise presented circular disks at each of 3 levels of exposure duration that varied unpredictably from trial to trial. Stimulus triples, rather than pairs, yielded more complex results. However, the findings provide strong evidence that the relevant features of the 2-3 stimuli were identified and localized in parallel across the display. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Accelerated testing of on‐board diagnostics

Modern products frequently feature monitors designed to detect actual or impending malfunctions. False alarms (Type I errors) or excessive delays in detecting real malfunctions (Type II errors) can seriously reduce monitor utility. Sound engineering practice includes physical evaluation of error rates. Type II error rates are relatively easy to evaluate empirically. However, adequate evaluation of a low Type I error rate is difficult without using accelerated testing concepts, inducing false alarms using artificially low thresholds and then selecting production thresholds by appropriate extrapolation, as outlined here. This acceleration methodology allows for informed determination of detection thresholds and confidence in monitor performance with substantial reductions over current alternatives in time and cost required for monitor development. Copyright © 2006 John Wiley & Sons, Ltd.     

燃气管线动态泄漏扩散的危险性分析

通过对燃气管线动态泄漏过程的分析,建立了动态泄漏率计算模型。以湍流扩散微分方程为基础,根据动态泄漏率不定常的特点,建立了燃气管线动态泄漏扩散模型。讨论分析了火灾爆炸的可能性危险范围和伤害性危险范围的参考标准和计算方法。在实际应用的基础上,对各种危险范围给予了讨论和分析,并对给定条件下的伤害及破坏范围给予了计算。这将为设立和制订高压长输管线和城市主要输运管道附近的重要建筑物(学校等)的修建安全距离提供安全标准和参考,同时也为降低事故可能造成的危害程度提供保障。