Vitamin C elevates red blood cell glutathione in healthy adults

Pre-transplant nephrectomy was done in a 25-year-old man for calculous pyelonephritis using a retroperitoneal laparoscopic approach with a newly devised ligature applicator-dissector- kidney retractor.     

动态不确定环境下的决策：一种分层决策模型

本文提出一种智能体分层决策结构模型，试图通过分层决策技术有效地解决动态、不确定环境中的智能体的实时决策问题。本模型的高层采用BDI结构，以便为较长期任务的规划和推理提供充分的支持；模型的底层采用反应式结构，以保证对短期实时任务的及时响应。实验结果表明了这种分层模型在某些复杂任务领域中的有效性。     

The amount of information and the volume of ‘information tare’

A distinction is suggested between the notions ‘information tare’, the role of which is played by the signals or letters forming the message, and ‘information’, which may be contained in such messages. It is shown that Shannon's definition of the amount of information is, in fact, the definition of the volume of information tare, whereas the amount of information itself may be measured as the volume of information tare of the maximally compact message used for its recording. This allows one to express both the volume of information tare, H, and the amount of information, B, in the same units of measurement–bits–and for any message B≤H. Some consequences of these views are analysed.     

Unsupervided pattern recognition for the classification of EMG signals

The shapes and firing rates of motor unit action potentials (MUAP's) in an electromyographic (EMG) signal provide an important source of information for the diagnosis of neuromuscular disorders. In order to extract this information from EMG signals recorded at low to moderate force levels, it is required: i) to identify the MUAP's composing the EMG signal, ii) to classify MUAP's with similar shape, and iii) to decompose the superimposed MUAP waveforms into their constituent MUAP's. For the classification of MUAP's two different pattern recognition techniques are presented: i) an artificial neural network (ANN) technique based on unsupervised learning, using a modified version of the self-organizing feature maps (SOFM) algorithm and learning vector quantization (LVQ) and ii) a statistical pattern recognition technique based on the Euclidean distance. A total of 1213 MUAP's obtained from 12 normal subjects, 13 subjects suffering from myopathy, and 15 subjects suffering from motor neuron disease were analyzed. The success rate for the ANN technique was 97.6% and for the statistical technique 95.3%. For the decomposition of the superimposed waveforms, a technique using crosscorrelation for MUAP's alignment, and a combination of Euclidean distance and area measures in order to classify the decomposed waveforms is presented. The success rate for the decomposition procedure was 90%.     

Intravascular lymphomatosis: a case presenting with encephalomyelitis and reactive haemophagocytic syndrome diagnosed by renal biopsy

OBJECTIVE: To determine the frequency of characteristics associated with unprotected heterosexual intercourse in HIV infected adults in an urban area. DESIGN: Retrospective comparison of sexual risk transmission behaviour between HIV infected men and women from a drug treatment site and between women from the drug site and HIV infected women from an urban medical centre. METHODS: HIV infected women and men were asked questions on sexual behaviour for a 1 year period before enrollment. The outcome variable was heterosexual risk behaviour (HRB) defined as having vaginal sex at least once in the previous year and not always using condoms. RESULTS: 73% of the drug clinic females, 72% of the drug clinic males, and 42% of the medical centre female engaged in HRB. Using logistic regression analysis, women and men in drug treatment engaged in similar rates of HRB; however, women in drug treatment were four times (95% CI = 2.0-8.3) more likely to engage in HRB risk behaviour than women from the medical centre. CONCLUSION: The data suggest that a surprisingly large portion of HIV infected patients under treatment engaged in HRB, especially former drug users. Without specifically targeted interventions, the heterosexual spread of HIV in urban areas will continue to be a serious problem.     

A study of injected dose for brain mapping on the ECAT HR+: activation maps for a parametric verbal working memory task

The success of the 15O-water PET technique to localize statistically significant changes in regional cerebral blood flow is dependent on factors such as the activity level injected and the magnitude of the flow change. Undetectable changes may occur if insufficient activity is injected leading to high levels of statistical noise or the task performed results in only small changes in blood flow. To explore the relationship between injected activity and statistical significance, we performed a series of studies with the ECAT EXACT HR+, a high resolution PET tomograph. A parametric verbal working memory task (the N-back task) was selected to examine the relationship between regional cerebral blood flow and working memory load across a range of injected doses of 15O-water. At each activity level the volunteers were required to perform four different levels of the N-back task, a task in which a letter displayed on a monitor is matched with the letter displayed N letters previously. With increasing N, this task places increased load on working memory. For this study, 5, 10, and 15 mCi of 15O-water were injected into nine normal volunteers. The complete sequence of four tasks (N = 0, 1, 2, and 3) at three activity levels was repeated twice, for a total of 24 injections of 15O-water. We show that the peak count rate performance for the HR+ is approached at injected activity levels of 15O-water around 15 mCi. For this particular choice of N-back task, robust activation maps can nevertheless be obtained with as little as 5 mCi injected dose.