基于中药注射液穴位注射治疗慢性肺系疾病的数据挖掘分析

目的：基于数据挖掘技术探讨中药注射液穴位注射治疗慢性肺系疾病的取穴规律。方法：以中国期刊全文数据库（CNKI）、万方、维普、中国生物医学文献数据库（CBM）为检索库,检索各个数据库自建库以来关于慢性肺系疾病的穴位注射相关文献,建立穴位注射治疗慢性肺系疾病的文献数据库,采用数据挖掘软件对取穴规律进行频数分析、聚类分析、关联分析等。结果：共纳入文献64篇,其中针刺穴位24个,以肺俞使用频率最高（22.66%）;涉及经脉10条,主要归足太阳膀胱经和足阳明胃经;主要中药注射液25种,使用频率最多的是黄芪注射液（21.43%）。聚类分析结果并不理想,但由关联分析可见,腧穴配伍多以肺俞为主穴,配以定喘、肾俞、足三里、天突、丰隆等穴。结论：穴位注射治疗慢性肺系疾病在经脉循行上主要选取足太阳膀胱经和足阳明胃经,一般多选用肺俞、定喘、足三里、肾俞等穴位,采用多穴配伍治疗。     

基于互信息的失眠用药关联性分析

基于中医传承辅助系统软件,分析郭蓉娟教授治疗失眠的用药经验。收集郭蓉娟教授治疗失眠的中药方剂,采用关联规则apriori算法、改进的互信息算法、复杂系统熵聚类等无监督数据挖掘方法,确定处方中各种药物的使用频次及药物之间的关联规则,分析郭蓉娟教授治疗失眠的用药经验。对筛选出的3 084首处方进行分析,确定处方中药物的使用频次,药物之问的关联规则,挖掘出41个核心组合和7首新处方。结论符合郭教授对失眠病因病机的认识:以肝郁化火为核心病机,肝郁脾虚、久病及肾的特点,中医传承辅助系统对于挖掘名中医临床经验具有重要实用价值。     

The estimation of moments: A technical note

The calculation of several common pharmacokinetic parameters requires estimates of both the area under the curve of the concentration of the drug in a sampled fluid vs. time, and also the first moment about t=0 of this area. It is proposed that the methods used to estimate these quantities should make consistent assumptions about the concentration of the drug. There appears to be an inconsistency in the standard published formulas in the case where concentration is interpolated linearly. A more consistent formula is derived.     

The dynamic efficiency of the Ramsey model with endogenous labour participation rate

This paper incorporates the hypothesis of labour participation rate into the Ramsey model. It is shown that the economy can be dynamically inefficient if the average productivity of capital is greater than the sum of the rate of time preference, the population growth rate, the depreciation rate and the marginal rate of substitution between labour and consumption. The modified golden rule holds when the wage rate is equal to the marginal rate of substitution between labour and consumption. However, there is no guarantee that it will happen, since labour supply is driven by capital allocation decisions. Copyright © 2001 John Wiley & Sons, Ltd.     

Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships

The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships.     

Optical Bandgap Definition via a Modified Form of Urbach’s Rule

We are reporting an esoteric method to determine the optical bandgap of direct gap materials by employing Urbach’s rule. The latter, which describes the slope of the band tail absorption in semiconductors, in its original version, cannot be employed to pinpoint the optical bandgap. Herein, however, we show that a modified form of Urbach’s rule defines the optical bandgap, and therefore, enables the accurate determination of the optical bandgap energy, which turns out to be identical with the threshold energy for the band tail absorption. The model further produces an explicit expression for the absorption coefficient at the optical bandgap energy.     

Quantitative visualization of passive transport across bilayer lipid membranes

The ability to predict and interpret membrane permeation coefficients is of critical importance, particularly because passive transport is crucial for the effective delivery of many pharmaceutical agents to intracellular targets. We present a method for the quantitative measurement of the permeation coefficients of protonophores by using laser confocal scanning microscopy coupled to microelectrochemistry, which is amenable to precise modeling with the finite element method. The technique delivers well defined and high mass transport rates and allows rapid visualization of the entire pH distribution on both the cis and trans side of model bilayer lipid membranes (BLMs). A homologous series of carboxylic acids was investigated as probe molecules for BLMs composed of soybean phosphatidylcholine. Significantly, the permeation coefficient decreased with acyl tail length contrary to previous work and to Overton's rule. The reasons for this difference are considered, and we suggest that the applicability of Overton's rule requires re-evaluation.     

Learning to Synchronize: Midfrontal Theta Dynamics during Rule Switching

In recent years, several hierarchical extensions of well-known learning algorithms have been proposed. For example, when stimulus-action mappings vary across time or context, the brain may learn two or more stimulus-action mappings in separate modules, and additionally (at a hierarchically higher level) learn to appropriately switch between those modules. However, how the brain mechanistically coordinates neural communication to implement such hierarchical learning remains unknown. Therefore, the current study tests a recent computational model that proposed how midfrontal theta oscillations implement such hierarchical learning via the principle of binding by synchrony (Sync model). More specifically, the Sync model uses bursts at theta frequency to flexibly bind appropriate task modules by synchrony. The 64-channel EEG signal was recorded while 27 human subjects (female: 21, male: 6) performed a probabilistic reversal learning task. In line with the Sync model, postfeedback theta power showed a linear relationship with negative prediction errors, but not with positive prediction errors. This relationship was especially pronounced for subjects with better behavioral fit (measured via Akaike information criterion) of the Sync model. Also consistent with Sync model simulations, theta phase-coupling between midfrontal electrodes and temporoparietal electrodes was stronger after negative feedback. Our data suggest that the brain uses theta power and synchronization for flexibly switching between task rule modules, as is useful, for example, when multiple stimulus-action mappings must be retained and used.SIGNIFICANCE STATEMENT Everyday life requires flexibility in switching between several rules. A key question in understanding this ability is how the brain mechanistically coordinates such switches. The current study tests a recent computational framework (Sync model) that proposed how midfrontal theta oscillations coordinate activity in hierarchically lower task-related areas. In line with predictions of this Sync model, midfrontal theta power was stronger when rule switches were most likely (strong negative prediction error), especially in subjects who obtained a better model fit. Additionally, also theta phase connectivity between midfrontal and task-related areas was increased after negative feedback. Thus, the data provided support for the hypothesis that the brain uses theta power and synchronization for flexibly switching between rules.