Real-time refinement of subthalamic nucleus targeting using Bayesian decision-making on the root mean square measure.

The subthalamic nucleus (STN) is a major target for treatment of advanced Parkinson's disease patients undergoing deep brain stimulation surgery. Microelectrode recording (MER) is used in many cases to identify the target nucleus. A real-time procedure for identifying the entry and exit points of the STN would improve the outcome of this targeting procedure. We used the normalized root mean square (NRMS) of a short (5 seconds) MER sampled signal and the estimated anatomical distance to target (EDT) as the basis for this procedure. Electrode tip location was defined intraoperatively by an expert neurophysiologist to be before, within, or after the STN. Data from 46 trajectories of 27 patients were used to calculate the Bayesian posterior probability of being in each of these locations, given RMS-EDT pair values. We tested our predictions on each trajectory using a bootstrapping technique, with the rest of the trajectories serving as a training set and found the error in predicting the STN entry to be (mean +/- SD) 0.18 +/- 0.84, and 0.50 +/- 0.59 mm for STN exit point, which yields a 0.30 +/- 0.28 mm deviation from the expert's target center. The simplicity and computational ease of RMS calculation, its spike sorting-independent nature and tolerance to electrode parameters of this Bayesian predictor, can lead directly to the development of a fully automated intraoperative physiological procedure for the refinement of imaging estimates of STN borders.     

Is the apparent U-shape of well-being over the life course a result of inappropriate use of control variables? A commentary on Blanchflower and Oswald (66: 8, 2008, 1733–1749)

In their article in this journal “Is well-being U-shaped over the life cycle?” Blanchflower and Oswald (Blanchflower, D.G., & Oswald, A.J. (2008). Is well-being U-shaped over the life cycle? Social Science & Medicine, 66, 1733–1749) report the results of an ambitious cross-national study of age and well-being and conclude that in most societies studied the well-being of adults tends to be high in young adulthood and old age and lowest around age 40. I argue that the appearance of this U-shaped curve of well-being is the result of the use of inappropriate and questionable control variables. The most clearly inappropriate control variable is marital status, the control of which to a large extent accounts for the U-shaped curve. Most researchers who have studied the relationship between being married and being happy believe that happiness affects marital status (happier people are more likely to marry and stay married), and of course a variable that is affected by the dependent variable should not be included as a control variable in a simple recursive model. Such control variables as income and education are suspect because the relationship between them and well-being is likely to be partially spurious, and such variables as race and whether or not persons lived with both parents at age 16 should not be controlled, because they cannot affect or be affected by age. Finally, year of survey should not be controlled because of the age-period-cohort conundrum, which makes including age, period, and cohort all as predictor variables in a regression inappropriate (and impossible if the three variables are measured precisely and comparably). The only clearly appropriate control variable is birth cohort, and when only it is controlled, the regression data become estimates of how the well-being of persons has actually changed as they have gone through the life course. I argue that such estimates are much more useful than the counterfactual abstractions provided by Blanchflower and Oswald (Blanchflower, D.G., & Oswald, A.J. (2008). Is well-being U-shaped over the life cycle? Social Science & Medicine, 66, 1733–1749), and I conclude that those authors (or someone else) could make a very important contribution by redoing their analyses with birth cohort as the only control variable. I do that with the American happiness data and find that the results do not come close to the U-shaped pattern.     

时滞系统鲁棒稳定性的新判据

基于Ｌｙａｐｎｕｏｖ泛函方法，研究了满足匹配条件的不确定性时滞系统的鲁棒稳定性及具有稳定度β〉０鲁棒稳定性，给出了已有结果不能推出的新判据。这些新判据对已有结果难以使用的情况下也可有是有效的，或有时减少了已有结果的保守性。     

Use of current situational information and causal inference: Do dysphoric individuals make “unwarranted” causal inferences?

According to Beck's original theory, depressives make unwarranted negatively biased personal inferences. Specifically, Beck suggested that depressives ignore current positive situational information and are unduly influenced by current negative situational information in making inferences. To test Beck's theory, we used Kelley's normative model of causal inference to examine the utilization of causally relevant situational information by dysphoric, nondepressed, and very nondepressed subjects in making causal attributions for personal success and failure. We used Stevens and Jones' classic method from social psychology and embedded the relevant causal information in the natural flow of events. Results showed that dysphoric, nondepressed, and very nondepressed subjects did, to an equal degree, use such information to make causal attributions. Although dysphoric and both groups of nondepressed subjects used current situational information consistently with Kelley's model, clear-cut baseline differences in the content of their causal attributions existed. Thus, the results supported the reformulations of Beck's theory that emphasize content, rather than process, differences between depressive and nondepressive cognition for dysphoria.Preparation of this article was supported by a Vilas Award, a University of Wisconsin Graduate School Grant, a Romnes Fellowship, a Biomedical Grant, and NIMH Grant R01MH43866 to Lyn Y. Abramson.     

多参数信息融合实现非脑电的睡眠结构分期

目前临床睡眠分析的主要手段是多导睡眠图（Polysomnograph,PSG）,用仪器记录被测者整晚的脑电、眼动电和颏肌电等生理参数,计算机进行自动睡眠分期,再由技术人员依据国际标准进行校正.几十年来PSG保持着睡眠分期金标准的地位.提出在不使用脑电的条件下,利用较易获得的心动周期、呼吸、体动等基本生理参数,提取其中与睡眠过程及其变化有关的规律和信息,建立知识规则库,采用不确定推理的证据理论进行多参数睡眠信息融合计算,实现睡眠结构分期.50余例与PSG对照试验结果表明：醒睡的平均符合率达90%以上,基本睡眠结构的平均符合率达75%以上,证明该技术达到了应用的要求.     

黑尾蜡嘴雀原纹状体发声控制核团的传入性纤维联系

将HRP微电泳人黑尾蜡嘴雀(Eophona mihratoria)端脑原纹状体粗核内,观察其传入性纤维联系.在下列部位发现有密集的逆行标记细胞:(1):原纹状体带核;(2)上纹状体腹侧尾核;(3)新纹状体前部大细胞核外侧部;(4)脑桥蓝斑.以上标记细胞均出现在同侧.结果表明,原纹状体粗核接受原纹状体带核、上纹状体腹侧尾核、新纹状体前部大细胞核外侧部及脑桥蓝斑的传入性投射.     

Analysis of acute-phase toxicities of intensity-modulated proton therapy using a model-based approach in pharyngeal cancer patients

Pharyngeal cancer patients treated with intensity-modulated proton therapy (IMPT) using a model-based approach were retrospectively reviewed, and acute toxicities were analyzed. From June 2016 to March 2019, 15 pharyngeal (7 naso-, 5 oro- and 3 hypo-pharyngeal) cancer patients received IMPT with robust optimization. Simulation plans for IMPT and intensity-modulated X-ray therapy (IMXT) were generated before treatment. We also reviewed 127 pharyngeal cancer patients with IMXT in the same treatment period. In the simulation planning comparison, all of the normal-tissue complication probability values for dysphagia, dysgeusia, tube-feeding dependence and xerostomia were lower for IMPT than for IMXT in the 15 patients. After completing IMPT, 13 patients completed the evaluation, and 12 of these patients had a complete response. The proportions of patients who experienced grade 2 or worse acute toxicities in the IMPT and IMXT cohorts were 21.4 and 56.5% for dysphagia (P < 0.05), 46.7 and 76.3% for dysgeusia (P < 0.05), 73.3 and 62.8% for xerostomia (P = 0.43), 73.3 and 90.6% for mucositis (P = 0.08) and 66.7 and 76.4% for dermatitis (P = 0.42), respectively. Multivariate analysis revealed that IMPT was independently associated with a lower rate of grade 2 or worse dysphagia and dysgeusia. After propensity score matching, 12 pairs of IMPT and IMXT patients were selected. Dysphagia was also statistically lower in IMPT than in IMXT (P < 0.05). IMPT using a model-based approach may have clinical benefits for acute dysphagia.     

A New Statistical Method for Dose-Finding Based on Efficacy and Toxicity in Early Phase Clinical Trials

Most statistical methods for dose-finding in phase I clinical trials determine a maximum tolerable dose based on toxicity while ignoring efficacy. Most phase II designs assume that an acceptable dose has been determined and aim to estimate treatment efficacy, possibly with early stopping rules for safety monitoring. The purpose of this paper is to describe a new statistical strategy for dose-finding in single-arm clinical trials where patient outcome is characterized in terms of both response and toxicity. The strategy, which may be considered a phase I/II hybrid, was first proposed by Thall and Russell [1] and subsequently modified by Thall [2]. The underlying mathematical model expresses the probabilities of response and toxicity as interdependent functions of dose. The method is based on fixed standards for the minimum probability of response and the maximum probability of toxicity appropriate for the particular trial. The best acceptable dose is chosen for each successive patient cohort adaptively, based on the fixed standards and the dose-outcome data from patients treated previously in the trial. The scientific goals are to select one best acceptable dose for future patients and to estimate the response and toxicity probabilities at that dose, or to stop the trial early if it becomes sufficiently unlikely that any dose is both safe and efficacious. An application of the method to a trial of donor lymphocyte infusion as salvage therapy for chemo-refractory AML/MDS patients is described. To illustrate the method's flexibility and potential breadth of application, two additional examples are provided, including a hypothetical trial in which a 5% response rate is of interest.     

Microcomputer-based automatic regulation of extracorporeal circulation: a trial for the application of fuzzy inference

Since its establishment many researchers have been trying to automate the process of extracorporeal circulation (ECC). We developed a preliminary experimental model of an automatic regulatory system for ECC. The purpose of the system was to regulate basic hemodynamic parameters such as pump flow and withdrawal blood volume. It was divided into three main components: data sampling unit, central processing unit, and controlling unit. Based on this model we were able to achieve autoregulation of ECC using minimum configuration; however, the system lacked smoothness. This was partly because it was based on a "static" regulation system which used conditional statements having multiple parameters. In this study, we applied fuzzy logic to the former model to achieve more accurate and reliable regulation. We report experimental results for the new system and compare the data between clinical circulation in 13 infants (mean body weight, 13.32 +/- 5.99 kg) and experimental regulation in 7 mongrel dogs (mean body weight, 11.9 +/- 2.53 kg). The comparative study revealed no statistical difference between the two groups. This result suggests that the automatic regulation of ECC may be an alternative to manual operation by a professional perfusionist in the near future.     

Risk stratification for mortality in cardiovascular disease survivors: A survival conditional inference tree analysis

Background and aimsEfficient analysis strategies for complex network with cardiovascular disease (CVD) risk stratification remain lacking. We sought to identify an optimized model to study CVD prognosis using survival conditional inference tree (SCTREE), a machine-learning method.Methods and resultsWe identified 5379 new onset CVD from 2006 (baseline) to May, 2017 in the Kailuan I study including 101,510 participants (the training dataset). The second cohort composing 1,287 CVD survivors was used to validate the algorithm (the Kailuan II study, n = 57,511). All variables (e.g., age, sex, family history of CVD, metabolic risk factors, renal function indexes, heart rate, atrial fibrillation, and high sensitivity C-reactive protein) were measured at baseline and biennially during the follow-up period. Up to December 2017, we documented 1,104 deaths after CVD in the Kailuan I study and 170 deaths in the Kailuan II study. Older age, hyperglycemia and proteinuria were identified by the SCTREE as main predictors of post-CVD mortality. CVD survivors in the high risk group (presence of 2–3 of these top risk factors), had higher mortality risk in the training dataset (hazard ratio (HR): 5.41; 95% confidence Interval (CI): 4.49–6.52) and in the validation dataset (HR: 6.04; 95%CI: 3.59–10.2), than those in the lowest risk group (presence of 0–1 of these factors).ConclusionOlder age, hyperglycemia and proteinuria were the main predictors of post-CVD mortality.Trial registrationChiCTR-TNRC-11001489.