油橄榄叶提取物对海洛因依赖小鼠肺组织结构及IL-1β和TNF-α表达的影响

将100只健康小鼠皮下注射海洛因(10mg/kg)40d,然后分别用不同剂量的(50、100、200mg/kg)油橄榄叶提取物(OLE)进行皮下注射治疗,观察肺脏组织结构的变化,检测肺脏中白介素-1β(interleukin-β,IL-β)和肿瘤坏死因子-α(tumor necrosis factor-A,TNF-α)的表达情况.结果表明:与模型对照组相比,OLE使海洛因依赖小鼠肺泡直径、肺泡隔厚度减小,肺脏中IL-1β和TNF-α的表达明显减弱,且呈较好的量效关系,表明OLE能够对海洛因造成的肺损害起到保护作用,其作用机制可能是OLE抑制了IL-1β和TNF-α的在肺中的表达.     

Pulse-Abnormality Analysis for Heroin Addicts

Extracting features from biomedical signals to provide some decision support for medical diagnoses is an important aspect in the development of biomedical engineering.Analyzing power spectra of pulse signals for 15 heroin addicts and 15 healthy persons and calculating the power distributions on specified frequency bands for every power spectrum based on spectral estimation in this paper,we find that the significant difference of power distributions exists between the heroin addicts and the healthy persons.A primary criterion is also obtained,upon which the 13 cases of 15 heroin addicts are identified.The research result of this paper shows that the frequency domain analysis for pulse signals of heroin addicts is really an effective method.     

不同信息词汇对海洛因戒断者注意保持影响的E R P研究

采用事件相关电位技术(ERP),以毒品、中性和性信息词汇作为预备信号,间隔1 500ms后出现灰色小方框作为命令信号,看到命令信号则迅速按键反应,通过诱发的伴随性负波(CNV)分析毒品、中性和性信息词汇对注意保持的影响.结果发现:在预备信号呈现后的400～500ms内,毒品词汇比中性和性信息词汇诱发了更正的ERP成分(P500);在1 000～1 400ms内,毒品和性信息词汇比中性词汇都诱发一个更为正向的ERP成分;在2300～2 400ms内,毒品词汇相比中性词汇诱发了一个更正的ERP成分;在2 700～2 800ms内,毒品词汇同样比中性词汇诱发了一个更正的ERP成分.说明与毒品有关的词汇对吸毒者的注意保持功能产生了一定的干扰,吸毒者对与毒品有关的线索更为关注,这些成分很有可能是吸毒者的认知功能障碍和情感障碍的体现.     

流式细胞术检测海洛因成瘾者外周血T细胞亚群的变化

目的 :观察海洛因成瘾者外周血 T细胞亚群的变化。方法 :用流式细胞术检测 5 0例海洛因成瘾者 (成瘾者 )和 5 0例正常人(对照组 )外周血 T细胞亚群的数目。结果 :海洛因成瘾者外周血 CD3+、CD4+、CD8+细胞数明显低于正常人 ( P<0 .0 5～ 0 .0 1 ) ,CD 4+/CD8+比值显著低于正常人 ( P<0 .0 1 )。结论 :海洛因成瘾者机体细胞免疫功能处于抑制状态。     

海洛因对大鼠尾核头部单位自发放电的影响

用玻璃微电极技术、分别记录海洛因成瘾大鼠（实验组）和正常组（对照组）大鼠尾核头部神经元单位自发放电，结果发现，尾核头部单位自发放电的频率明显不同，实验组以低频放电为主，而对照组则以中频放电为主，组间的差异显著（Ｐ〈０．０１），提示，海洛因对尾核头部神经元的活动有影响。     

Pulse Signal Analysis of Druggers with the Wavelet and Neural Network

The most significant difference between the human pulse signals collected from heroin druggers and healthy persons is at their amplitude waveforms as time functions. That is, the amplitude values and change rates of two types of signals, within a particular time range, appear different features. However, the partial components of the scaling and wavelet coefficients of the pulse signals obtained by using wavelet transform can reveal such key features. The pulse signals of 15 heroin druggers and 15 healthy persons are analyzed through using the muhiresolution analysis of wavelet transform. By using db2 orthogonal wavelet, every pulse signal is decomposed into three levels and the absolute values of the sixth component of scaling coefficients and the second component of the wavelet coefficients in the third level are combined to form a feature vector. A probabilistic neural network with good detection performance is successfully designed for automatically detecting 30 feature vectors. During the network design, 20 feature vectors are used as training samples. The remained 10 feature vectors are used as testing samples. Based on these steps, 15 heroin druggers and 15 healthy persons are all correctly identified. In other words, the detection rate arrives at 100%. druggers.     

Application of the Wavelet Transform to the Pulse Signal Analysis of Druggers

According to the randomness of human pulse signals,the multiresolution analysis of the wavelet transform is used to analyze such signals.Its purpose is to extract the abnormal information from the pulse signals of heroin druggers and to obtain the primary judgment criterion which can be used to identify druggers from healthy persons.The scale spectrum based on the wavelet transform of pulse signals carries the important characteristic information of the health situation of human body.The pulse signals of 15 heroin druggers and 15 healthy persons are analyzed and the scale spectrum and the total signal energy of every signal are extracted.It is found that the ratio between the sum(i.e.,scale-wavelet energy) of the scale spectrum in a specific scale-time region and the total signal energy for heroin druggers is generally higher than that of healthy persons.Using the percentage of the ratio between the scale-wavelet energy in the specific scale-time region and the total signal energy as characteristic parameter,a critical parameter is determined that is used to classify heroin druggers and healthy persons.Thus,all of the 15 healthy persons are identified correctly from 30 subjects.Only two heroin persons are misjudged.The experiment results of classification show that the method presented is feasible and effective for detecting the pulse abnormalities of heroin druggers.