非线性动力学方法可预警直立倾斜试验中血管迷走性晕厥的发生

目的 量化评价血管迷走性晕厥血压下降过程中的脑血流自动调节功能,用于在晕厥相关症状出现前预测其发生。方法 选取20位直立倾斜试验证实的血管迷走性晕厥患者,另选取20名正常对照者。所有被试在直立倾斜试验前都要平卧30 min,同时使用TCD 2 MHz Doppler监测探头监测双侧大脑中动脉血流速度,心电监护监测心率,使用连续每搏血压监测指端无创连续血压。在进行10 min基线数据采集后,被试继续进行70°直立倾斜试验,每位被试至少直立30 min,或在30 min内出现晕厥发作或晕厥前兆时或当被试出现突发血压下降≥20 mmHg时终止检查。利用多模态血流血压分析(multimodal pressure-flow analysis,MMPF)的非线性动力学方法对不同时相的脑血流自动调节功能进行分析。利用信号分析的方法将脑血流信号记录中的重搏切迹深度量化测量,定义新的预测参数晕厥指数(syncope index,SI)用于评估血压变化时的脑血管张力。结果 病例组在血管迷走性晕厥发生时的晕厥指数与倾斜试验开始时的基线数值相比存在明显下降(0.16±0.10 vs. 0.27±0.10,P<0.01), 而对照组在倾斜试验结束时的晕厥指数与倾斜试验开始时的基线数值相比差异无统计学意义。对于血管迷走性晕厥组的患者,在晕厥发生前3 min,搏动指数与基线数据相比未见明显变化(P>0.05),但晕厥指数已出现明显下降(0.23±0.07 vs.0.29±0.07,P<0.01)。结论 当血管迷走性晕厥发生时脑血流动态调节功能衰竭,小血管张力的丧失与脑血流自动调节功能的丧失是相关的;晕厥指数可以作为提前预测血管迷走性晕厥发生的一个有用的参数。     

Second‐order refinement of empirical likelihood ratio tests of nonlinear restrictions

In this paper, we investigate the second‐order properties of empirical likelihood ratio (ELR) tests of general nonlinear parametric restrictions for over‐identified moment restriction models. We derive the stochastic expansion of the ELR statistic for this very large class of testing problems and its formal distributional expansion. We show that we can improve the size properties of the ELR tests via either Bartlett correction or pseudo observation adjustment. Monte Carlo experiments show that tests based on these modified ELR statistics exhibit good finite‐sample properties.     

喹硫平在中国精神分裂症及情感性障碍患者中的群体药代动力学研究

目的：用非线性混合效应模型（NONMEM）方法建立喹硫平在中国精神分裂症及情感性障碍患者中的群体药代动力学（PPK）模型并研究其影响因素。方法：回顾性收集304例患者的485份血药浓度数据及临床资料,血药浓度为临床常规监测采集的稳态谷浓度。采用NONMEM 软件建立中国精神分裂症及情感性障碍患者的群体药代动力学模型,并考察生理指标以及实验室指标等对喹硫平药代动力学参数的影响。采用拟合优度诊断图、自举法（bootstrap）和正态化预测分布误差法（NPDE）进行模型评估。结果：最终模型中喹硫平的表观清除率（CL/F）和表观分布容积（V/F）的群体典型值分别为 83 L·h-1和 1350 L。协变量分析结果显示年龄对喹硫平的CL/F具有显著性影响,建立的最终模型CL/F参数公式如下：CL/F（L·h-1）= 83 × (AGE /43.1)-0.301。CL/F的个体间变异和残差变异分别为20.8%和11.1%。结论：本研究为首次在中国精神分裂症及情感性障碍患者中开展的喹硫平的群体药代动力学研究,模型验证显示最终模型具有较好的稳定性和可靠性,可为其临床个体化给药提供参考依据。     

Innate Immune Recovery Predicts CD4+ T Cell Reconstitution after Hematopoietic Cell Transplantation

Innate immune cells are the first to recover after allogeneic hematopoietic cell transplantation (HCT). Nevertheless, reports of innate immune cell recovery and their relation to adaptive recovery after HCT are largely lacking. Especially predicting CD4⁺ T cell reconstitution is of clinical interest, because this parameter directly associates with survival chances after HCT. We evaluated whether innate recovery relates to CD4⁺ T cell reconstitution probability and investigated differences between innate recovery after cord blood transplantation (CBT) and bone marrow transplantation (BMT). We developed a multivariate, combined nonlinear mixed-effects model for monocytes, neutrophils, and natural killer (NK) cell recovery after transplantation. A total of 205 patients undergoing a first HCT (76 BMT, 129 CBT) between 2007 and 2016 were included. The median age was 7.3years (range, .16 to 23). Innate recovery was highly associated with CD4⁺ T cell reconstitution probability (P < .001) in multivariate analysis correcting for covariates. Monocyte (P < .001), neutrophil (P < .001), and NK cell (P < .001) recovery reached higher levels during the first 200days after CBT compared with BMT. The higher innate recovery after CBT may be explained by increased proliferation capacity (measured by Ki-67 expression) of innate cells in CB grafts compared with BM grafts (P?=?.041) and of innate cells in vivo after CBT compared with BMT (P?=?.048). At an individual level, patients with increased innate recovery after either CBT or BMT had received grafts with higher proliferating innate cells (CB; P?=?.004, BM; P?=?.01, respectively). Our findings implicate the use of early innate immune monitoring to predict the chance of CD4⁺ T cell reconstitution after HCT, with respect to higher innate recovery after CBT compared with BMT.     

HRV非线性动力学分析的动物实验初步研究

采用非线性动力学分析方法,观察了交感,迷走神经单独作用和冠状动脉狭窄时,非线性动力学参数的改变,以探讨非线性动力学参数所反映的心脏生理功能和心脏电生理学意义。     

非线性模型统计分析体系及NoSA实现(一)

目的 介绍医用非线性统计分析模型及其ＮｏＳＡ实现。方法 建立各种非线性模型及模型参数的最大似然估计方法。并附有实例演算。结果 由于ＮｏＳＡ嵌入了网络算法技术,解释变量可以是定量、定性和有序的,产能分析变量间的交互作用可对变量作逐步选择。结论ＮｏＳＡ的非线性模型模块计算稳定,并能自动排除广义共线关系对模型参数量大似然估计值的影响。此模块较ＳＰＳＳ有其明显的优点。     

Optimization of nonlinear dose- and concentration-response models utilizing evolutionary computation

An essential part of toxicity and chemical screening is assessing the concentrated related effects of a test article. Most often this concentration-response is a nonlinear, necessitating sophisticated regression methodologies. The parameters derived from curve fitting are essential in determining a test article's potency (EC(50)) and efficacy (E(max)) and variations in model fit may lead to different conclusions about an article's performance and safety. Previous approaches have leveraged advanced statistical and mathematical techniques to implement nonlinear least squares (NLS) for obtaining the parameters defining such a curve. These approaches, while mathematically rigorous, suffer from initial value sensitivity, computational intensity, and rely on complex and intricate computational and numerical techniques. However if there is a known mathematical model that can reliably predict the data, then nonlinear regression may be equally viewed as parameter optimization. In this context, one may utilize proven techniques from machine learning, such as evolutionary algorithms, which are robust, powerful, and require far less computational framework to optimize the defining parameters. In the current study we present a new method that uses such techniques, Evolutionary Algorithm Dose Response Modeling (EADRM), and demonstrate its effectiveness compared to more conventional methods on both real and simulated data.     

Exponential decay nonlinear regression analysis of patient survival curves: Preliminary assessment in non-small cell lung cancer

Background

For processes that follow first order kinetics, exponential decay nonlinear regression analysis (EDNRA) may delineate curve characteristics and suggest processes affecting curve shape. We conducted a preliminary feasibility assessment of EDNRA of patient survival curves.

Methods

EDNRA was performed on Kaplan-Meier overall survival (OS) and time to relapse (TTR) curves for 323 patients with resected NSCLC and on OS and progression-free survival (PFS) curves from selected publications.

Results and conclusions

In our resected patients, TTR curves were triphasic with a “cured” fraction of 60.7% (half-life [t1/2] >100,000 months), a rapidly relapsing group (7.4%, t1/2 = 5.9 months) and a slowly relapsing group (31.9%, t1/2 = 23.6 months). OS was uniphasic (t1/2 = 74.3 months), suggesting an impact of co-morbidities; hence, tumor molecular characteristics would more likely predict TTR than OS. Of 172 published curves analyzed, 72 (42%) were uniphasic, 92 (53%) were biphasic, 8 (5%) were triphasic. With first-line chemotherapy in advanced NSCLC, 87.5% of curves from 2 to 3 drug regimens were uniphasic vs. only 20% of those with best supportive care or 1 drug (p < 0.001). 54% of curves from 2 to 3 drug regimens had convex rapid-decay phases vs. 0% with fewer agents (p < 0.001). Curve convexities suggest that discontinuing chemotherapy after 3-6 cycles “synchronizes” patient progression and death. With postoperative adjuvant chemotherapy, the PFS rapid-decay phase accounted for a smaller proportion of the population than in controls (p = 0.02) with no significant difference in rapid-decay t1/2, suggesting adjuvant chemotherapy may move a subpopulation of patients with sensitive tumors from the relapsing group to the cured group, with minimal impact on time to relapse for a larger group of patients with resistant tumors. In untreated patients, the proportion of patients in the rapid-decay phase increased (p = 0.04) while rapid-decay t1/2 decreased (p = 0.0004) with increasing stage, suggesting that higher stage may be associated with tumor cells that both grow more rapidly and have a higher probability of surviving metastatic processes than in early stage tumors.This preliminary assessment of EDNRA suggests that it may be worth exploring this approach further using more sophisticated, statistically rigorous nonlinear modelling approaches. Using such approaches to supplement standard survival analyses could suggest or support specific testable hypotheses.     

Voice acoustic changes during bilateral subthalamic stimulation in patients with Parkinson's disease

Objectives

The purpose of this study was to investigate the effects of bilateral subthalamic nucleus deep brain stimulation on the phonation of patients with Parkinson's disease in three drug-free conditions: (1) stimulation off, (2) with clinically optimised stimulation parameters, and (3) subthreshold overstimulation, in order to detect differences following voice analysis.

Patients and methods

Conversational speech and sustained vowel sounds /a/, /i/, /o/, /u/ and high /i/ were recorded from 22 PD patients. Perceptual analysis, perturbation jitter, shimmer, noise-to-harmonics ratio, and nonlinear dynamic analysis (NDA) with detrended fluctuation analysis and recurrence period density entropy were measured and compared to the above conditions. Quadratic discriminant analysis (QDA) was used to investigate stimulation conditions for given acoustic data.

Results

The changes of perturbation measurements for the above conditions were not significant. With differences between vowels, NDA showed more significant changes and more powerful correlation with perceptual scores than perturbation measurements. NDA was significantly more sensitive during the QDA of the conditions.

Conclusions

Acoustic voice analysis of sustained vowels can help with recognizing the overstimulated condition, and, with an appropriate test battery and software package including nonlinear dynamic analysis, it can be a valuable tool for fine adjustments of stimulation parameters.     

Mobile-phone pulse triggers evoked potentials

If mobile-phone electromagnetic fields (EMFs) are hazardous, as suggested in the literature, processes or mechanisms must exist that allow the body to detect the fields. We hypothesized that the low-frequency pulses produced by mobile phones (217 Hz) were detected by sensory transduction, as evidenced by the ability of the pulses to trigger evoked potentials (EPs). Electroencephalograms (EEGs) were recorded from six standard locations in 20 volunteers and analyzed to detect brain potentials triggered by a pulse of the type produced by mobile phones. Evoked potentials having the expected latency were found in 90% of the volunteers, as assessed using a nonlinear method of EEG analysis. Evoked potentials were not detected when the EEG was analyzed using time averaging. The possibility of systematic error was excluded by sham-exposure analyses. The results implied that mobile-phones trigger EP at the rate of 217 Hz during ordinary phone use. Chronic production of the changes in brain activity might be pertinent to the reports of health hazards among mobile-phone users.