肌少症动物模型的研究进展

肌少症是随着年龄增长,出现的自身肌肉质量减少与力量相应减弱的现象。近年来,肌少症动物模型在老年人肌肉萎缩的预防及其机制探讨方面已有广泛应用。本文综述近年来肌少症动物模型的研究现状,动物肌少症模型的建立及应用进行对比分析,并对各类模型的优缺点进行探讨,为开展相关的实验提供参考。     

面向血液葡萄糖测量的生物组织阻抗模型

本文推导了细胞膜电容与血糖浓度之间的关系,并将这种关系应用到Pauly和Schwan提出的弛豫模型中,再将弛豫模型应用于多重Cole-Cole介电模型,最后通过介电模型得出阻抗模型,建立起人体血糖浓度与组织介电谱,阻抗谱之间的联系。通过分析发现,细胞膜电容随着血糖浓度增加而增大,且当血糖浓度趋于无穷大时,细胞膜电容等于血糖浓度为0时细胞膜电容的1.53倍。对介电谱的仿真得出,当外加信号频率小于1 MHz时,介电常数实部随着葡萄糖浓度改变而发生明显变化。阻抗谱的研究结果表明,随着葡萄糖浓度的升高,阻抗的实部减小,阻抗虚部模增大,且分别在频率为1.48 MHz和0.55 MHz时变化得最快。本文建立的模型为血糖无创检测提供了一种新的方法和手段。     

去负荷小鼠比目鱼肌收缩特性和纤维类型转化

目的:探讨去负荷后小鼠比目鱼肌的收缩特性与骨骼肌纤维类型转化之间的关系。方法:采用离体肌肉灌流技术和电刺激方法,在小鼠后肢去负荷28 d引起骨骼肌萎缩后,观察比目鱼肌单收缩、强直收缩能力和肌疲劳指标等收缩特性的改变,同时利用组织免疫荧光染色和实时定量聚合酶链式反应(real-time PCR)等技术检测去负荷后比目鱼肌快慢肌纤维组成和纤维类型转化的变化。结果:去负荷28 d后,小鼠比目鱼肌单收缩力、强直收缩能力和疲劳指数(fatigue index)均有显著性下降,同时伴有快肌纤维亚型的增加和慢肌纤维亚型的减少。结论:去负荷28 d后小鼠比目鱼肌收缩特性的改变和快慢肌纤维类型的转化有关。     

失重状态下肌萎缩研究进展

失重条件下人和动物生理状态会发生一系列的变化,其中骨骼肌萎缩和力量下降较为显著,目前其发生的机制仍不明确且缺少特效的干预措施。本文从肌肉湿重及肌纤维横截面积的变化、肌纤维类型的变化、肌纤维超微结构的变化、肌梭的适应性变化四个方面进行简要阐述,探讨肌肉萎缩的可能发生机制。     

糖尿病后肢缺血大鼠模型的建立与评估

目的研究糖尿病肢体缺血模型的建立方法,为糖尿病下肢缺血和糖尿病足研究提供试验方法。方法取25只Wistar大鼠分为模型组、对照组及假手术组,模型组腹腔注射链脲佐菌素(60 mg/kg)诱发糖尿病,血糖达16.8 mmol/L模型成功。糖尿病造模成功后,手术结扎大鼠左侧股动脉、剪断周围动脉分支,建立左后肢缺血模型。术后激光多普勒监测动态监测双后肢血流,同时观察血糖、体重及尿量变化。术后21 d取后肢腓肠肌行肌肉HE染色,取结扎处股动脉免疫荧光染色观察血管平滑肌增殖情况,CD31免疫组织化学染色检测后肢肌肉毛细血管密度。结果在治疗后21 d时,无论是最大膀胱容量、漏尿点压力还是收缩力/肌重比,IGF-1组、电刺激组治疗效果更佳;而IGF-1组与电刺激组两组之间比较差异无显著性(P0.05)。结论成功建立有效、简便易行的糖尿病后肢缺血模型,可用于糖尿病肢体缺血及糖尿病足的药物干预研究。     

在鸡慢肌神经支配下由快肌碎片形成的新生肌肉保持快肌的某些性质

本工作使用肌肉的切碎移植的方法来作快、慢肌肉的运动神经的交叉支配。将鸡右侧前背阔肌(慢)摘除而使其神经留在原位,再将左侧后背阔肌(快)取出切碎并放在右前肌的空位(第一组),在另一组动物是将右前肌摘出切碎后仍放回原位(第二组)。数月后用电刺激慢神经并用等长杠杆记录肌肉的收缩。第一组动物的新生肌肉的单收缩显然比第二组快些,而且在高频(250/s)刺激下表现抑制现象。第二组动物的新生肌肉不但收缩较慢,而且与前背阔肌一样不产生高频抑制。上述现象证明鸡的由快肌碎片形成的新生肌肉仍保持快肌的某些性质,而且在慢肌神经支配下仍能如此。本工作也进一步提供了维金斯基抑制与神经无关而与肌肉有关的证据。本文推测肌肉很可能是通过其卫星细胞而把某些性质传给新生肌肉的。     

小鼠骨胳肌在切腱、协同肌切腱和肉毒杆菌毒素中毒后对辣根过氧化物酶(HRP)的胞纳作用

本文报道了用生物化学方法测定离体小鼠比目鱼肌对 HRP 的胞纳作用。结果表明,在切断神经或切腱后引起萎缩的肌肉侧或在协同肌切腱后引起代偿性肥大的肌肉侧,与它们各自对照的正常肌肉侧相比,都可发生对 HRP 胞纳的明显增加。而在肉毒杆菌毒素中毒后引起萎缩的肌肉侧,和它正常的对照肌肉侧相比,却意外地不发生这种胞纳摄取的明显增加。本文的实验结果进一步证实。肌肉的胞纳增加并不一定导致肌纤维的变性和萎缩(例如代偿性肥大的肌肉);而肌纤维的变性和萎缩亦不一定需要肌肉的胞纳增加为前提(例如肉毒杆菌毒素中毒的肌肉)。本工作结果还提示:肌肉的胞纳增加有其神经原性和肌原性因素。本文还对肌肉胞纳增加的可能机制进行了讨论。     

功率谱熵在痫性发作大鼠脑电检测中的应用研究

目的:研究功率谱熵在痫性发作大鼠脑电检测中的应用。方法:采用青霉素在大鼠海马微注射制备急性痫性发作模型,以深部电极记录大鼠原始脑电信号,将24只SD大鼠随机分成四组,即正常组(A),对照组(B),单电极组(C),多电极组(D)。C、D组大鼠经致痫后观察未发作期、发作前期、发作期和发作后期四期脑电信号的变化,运用谱熵对四期脑电信号进行分析,并与A、B组进行对比。结果:C组和D组脑电功率谱熵显示两组发作期与未发作期、发作前期、发作后期比较有显著差异(P0.05),发作期明显低于其它各期;未发作期和发作前期相比有明显差异(P0.05),发作前期较未发作期降低;将D组大鼠海马致痫灶(a)及其同侧附近(b)、对侧(c)三点发作各期脑电功率谱熵进行对比分析,发作前期和发作期a、b、c三点比较有明显差异(P0.05),a点最低,c点的功率谱熵值最高。结论:功率谱熵可以预报痫性发作并可对癫痫病灶的定位提供一定的帮助。     

食蟹猴肌肉萎缩模型的建立

目的 采用限制下肢活动方法,建立食蟹猴肌肉萎缩动物模型,建立模型评价的方法。方法 采用高分子纤维绷带固定食蟹猴右侧下肢(踝关节至膝关节)15周,期间每两周测量体重、双侧小腿腿围、下肢容积,造模11、13、15周行双侧小腿腓肠肌MRI检查,15周行肌肉组织活检。结果 造模15周后,动物体重无明显变化,右小腿腿围、右大腿腿围、右下肢体积比造模前均明显下降(P0.05);造模15周后血清肌酐、血糖、碱性磷酸酶均出现显著下降(P0.05),血清胆固醇水平明显升高(P0.05);MRI显示右侧腓肠肌萎缩,右侧腓肠肌容积较造模前减小;肌肉组织活检显示右侧腓肠肌萎缩,肌纤维变细;腓肠肌纤维横截面积缩小。结论 通过外固定限制食蟹猴下肢活动的方法制作肌肉萎缩模型,造模周期适当,操作性强。综合采用腿围、下肢排水体积、生化指标、MRI成像及肌肉活检相结合的评价方法,能够简单、客观评价食蟹猴肌肉萎缩模型。     

优秀赛艇运动员不同部位肌肉微循环血流灌注量的变化特点

目的：探讨优秀赛艇运动员不同部位肌肉微循环血流灌注量（MB）的变化特点,为无创微循环相关指标更好的应用于运动员机能监控提供参考和借鉴。方法：运用PeriFlux System5000系列激光多普勒血流仪对12名优秀男子赛艇运动员不同部位肌肉微循环血流灌注量进行无创测试,测试环境为室内,温度（25±3）℃,湿度45．O％～65．O％。结果：①基础值：肱二头肌〉肱桡肌〉股四头肌〉腓肠肌,且肱二头肌显著高于肱桡肌（P〈0．05）,极显著高于股四头肌和腓肠肌（P〈0．01）;②加热后值及加热前后差值：肱桡肌〉肱二头肌〉股四头肌〉腓肠肌,且肱二头肌、肱桡肌显著高于腓肠肌（P〈0．05）。结论：优秀男子赛艇运动员上肢肌肉值MBF值要明显高于下肢肌肉,尤其加热后值上肢肌肉明显高于下肢肌,而上肢肌肉或下肢肌肉之间则不存在明显差异,因此为了使监测结果更具有代表性,赛艇运动员进行微循环血流灌注量及其相关指标监测时应选取上肢相同肌肉上同一空间的解剖位点。     

Electromyogram median frequency, spectral compression and muscle fibre conduction velocity during sustained sub-maximal contraction of the brachioradialis muscle.

Changes in the median frequency of the power spectrum of the surface electromyogram (EMG) are commonly used to detect muscle fatigue. Previous research has indicated that changes in the median frequency are related to decreases in muscle fibre conduction velocity (MFCV) during sustained fatiguing contractions. However, in experimental studies the median frequency has been consistently observed to decrease by a relatively greater amount than MFCV. In this paper, a new estimate of EMG frequency compression, the Spectral Compression Estimate (SCE), is compared with the median frequency of the EMG power spectrum, the median frequency of the EMG amplitude spectrum and MFCV measured during sustained, isometric, fatiguing contractions of the brachioradialis muscle at 30, 50 and 80% maximum voluntary contraction (MVC). The SCE is found to provide a better estimate of the observed changes in MFCV than the median frequency of either the EMG power spectrum or EMG amplitude spectrum.     

Surface EMG power spectrum and intramuscular pH in human vastus lateralis muscle during dynamic exercise

The relationship between intramuscular pH and the frequency components of the surface electromyographic (EMG) power spectrum from the vastus lateralis muscle was studied in eight healthy male subjects during brief dynamic exercise. The studies were carried out in placebo control and metabolic alkalosis induced by oral administration of NaHCO3. At the onset of exercise, blood pH was 0.08 units higher in alkalosis compared with placebo. Muscle lactate accumulation during exercise was higher in alkalosis (32 +/- 5 mmol/kg wet wt) than in placebo (17 +/- 4 mmol/kg wet wt), but no difference in intramuscular pH was found between the two conditions. The EMG power spectrum was shifted toward lower frequencies during fatigue in the control condition (10.1 +/- 0.9%), and these spectral shifts, evaluated from changes in the mean power frequency (MPF) of the EMG power spectrum, were further accentuated in alkalosis (19 +/- 2%). Although the changes in frequency components of EMG correlated with muscle lactate accumulation (r = 0.68, P less than 0.01), no direct relationship with muscle pH was observed. We conclude that alkalosis results in a greater reduction in MPF associated with a higher muscle lactate accumulation. However, the good correlation observed between the two variables is not likely causative, and a dissociation between intramuscular pH and the increase in the low-frequency content of EMG power spectrum appears during muscle fatigue.     

The mechanomyography of persons after stroke during isometric voluntary contractions.

This study was to investigate the properties of mechanomyography (MMG), or muscle sound, of the paretic muscle in the affected side of hemiplegic subjects after stroke during isometric voluntary contractions, in comparison with those from the muscle in the unaffected side of the hemiplegic subjects and from the healthy muscle of unimpaired subjects. MMG and electromyography (EMG) signals were recorded simultaneously from the biceps brachii muscles of the dominant arm of unimpaired subjects (n=5) and the unaffected and affected arms of subjects after stroke (n=8), when performing a fatiguing maximal voluntary contraction (MVC) associated with the decrease in elbow flexion torque, and then submaximal elbow flexions at 20%, 40%, 60% and 80% MVCs. The root mean squared (RMS) values, the mean power frequencies (MPF, in the power density spectrum, PDS) of the EMG and MMG, and the high frequency rate (HF-rate, the ratio of the power above 15Hz in the MMG PDS) were used for the analysis. The MMG RMS decreased more slowly during the MVC in the affected muscle compared to the healthy and unaffected muscles. A transient increase could be observed in the MMG MPFs from the unaffected and healthy muscles during the MVC, associated with the decrease in their simultaneous EMG MPFs due to the muscular fatigue. No significant variation could be seen in the EMG and MMG MPFs in the affected muscles during the MVC. The values in the MPF and HF-rate of MMG from the affected muscles were significantly lower than those from the healthy and unaffected muscles (P<0.05) at the high contraction level (80% MVC). Both the MMG and EMG RMS values in the healthy and unaffected groups were found to be significantly higher than the affected group (P<0.05) at 60% and 80% MVCs. These observations were related to an atrophy of the fast-twitch fibers and a reduction of the neural input in the affected muscles of the hemiplegic subjects. The results in this study suggested MMG could be used as a complementary to EMG for the analysis on muscular characteristics in subjects after stroke.     

Surface EMG recorded by branched electrodes during sustained muscle activity.

The purpose of the present investigation is to use surface interference EMG recorded by branched electrodes for assessment of muscle fatigue during sustained voluntary isometric contractions at different levels. Level-trigger averaging and turn/amplitude analysis have been applied. The conduction velocity (CV) of excitation was calculated from the time shift of the negative peaks of the averaged potentials (AvPs) derived from the EMG recorded by two electrodes placed along the muscle fibers. The recruitment of new motor units affects the negative amplitude (NA) of AvPs, the number of turns per second and the mean amplitude of turns in a different way depending on the level of sustained contractions. In contrast, the CV declined at all levels of sustained contractions and was the most appropriate parameter for the muscle fatigue assessment. There was a good correlation between CV decrease and torque reduction during sustained maximal efforts. The level-trigger averaging technique of the interference EMG recorded by surface branched electrodes is easy and non-invasive, thus being very convenient for routine application.     

Robust Muscle Activity Onset Detection Using an Unsupervised Electromyogram Learning Framework

Accurate muscle activity onset detection is an essential prerequisite for many applications of surface electromyogram (EMG). This study presents an unsupervised EMG learning framework based on a sequential Gaussian mixture model (GMM) to detect muscle activity onsets. The distribution of the logarithmic power of EMG signal was characterized by a two-component GMM in each frequency band, in which the two components respectively correspond to the posterior distribution of EMG burst and non-burst logarithmic powers. The parameter set of the GMM was sequentially estimated based on maximum likelihood, subject to constraints derived from the relationship between EMG burst and non-burst distributions. An optimal threshold for EMG burst/non-burst classification was determined using the GMM at each frequency band, and the final decision was obtained by a voting procedure. The proposed novel framework was applied to simulated and experimental surface EMG signals for muscle activity onset detection. Compared with conventional approaches, it demonstrated robust performance for low and changing signal to noise ratios in a dynamic environment. The framework is applicable for real-time implementation, and does not require the assumption of non EMG burst in the initial stage. Such features facilitate its practical application.     

Influence of motor unit firing statistics on the median frequency of the EMG power spectrum

Changes in the EMG power spectrum during static fatiguing contractions are often attributed to changes in muscle fibre action potential conduction velocity. Mathematical models of the EMG power spectrum, which have been empirically confirmed, predict that under certain conditions a distinct maximum occurs in the low-frequency part of the spectrum, indicating the dominant firing rate of the motor units. The present study investigated the influence of this firing rate peak on the spectral changes during a static fatiguing contraction at 50% of maximum EMG amplitude in the frontalis and corrugator supercilii muscles. An exponential decrease of the median frequency (MF) of the EMG power spectrum was observed when the firing rate peak was absent. When the firing rate peak was present, an exaggerated decrease of MF in the beginning of the contraction was found, which was associated with an increase in firing rate peak magnitude. In later stages of the contraction, a partial recovery of MF occurred, concomitant with a decrease in firing rate peak magnitude. The influence of the firing rate peak on MF was also investigated during nonfatiguing contractions of the frontalis muscle at 20, 40, 60, and 80% of maximum EMG amplitude. A curvilinear relationship between MF and contraction strength was found, whether firing rate peaks were present or absent. The presence of firing rate peaks, however, was associated with a decrease in MF which was inversely related to contraction strength, due to the inverse relationship between firing rate peak magnitude and contraction strength.     

Motor unit recruitment strategies investigated by surface EMG variables.

During isometric contractions of increasing strength, motor units (MUs) are recruited by the central nervous system in an orderly manner starting with the smallest, with muscle fibers that usually show the lowest conduction velocity (CV). Theory predicts that the higher the velocity of propagation of the action potential, the higher the power at high frequencies of the detected surface signal. These considerations suggest that the power spectral density of the surface detected electromyogram (EMG) signal may give indications about the MU recruitment process. The purpose of this paper is to investigate the potential and limitations of spectral analysis of the surface EMG signal as a technique for the investigation of muscle force control. The study is based on a simulation approach and on an experimental investigation of the properties of surface EMG signals detected from the biceps brachii during isometric linearly increasing torque contractions. Both simulation and experimental data indicate that volume conductor properties play an important role as confounding factors that may mask any relation between EMG spectral variables and estimated CV as a size principle parameter during ramp contractions. The correlation between spectral variables and CV is thus significantly lower when the MU pool is not stable than during constant-torque isometric contractions. Our results do not support the establishment of a general relationship between spectral EMG variables and torque or recruitment strategy.     

Cross-spectral analysis of physiological tremor and muscle activity

We investigate the relationship between the extensor electromyogram (EMG) and tremor time series in physiological hand tremor by cross-spectral analysis. Special attention is directed to the phase spectrum and the effects of observational noise. We calculate the theoretical phase spectrum for a second-order linear stochastic process and compare the results to measured tremor data recorded from subjects who did not show a synchronized EMG activity in the corresponding extensor muscle. The results show that physiological tremor is well described by the proposed model and that the measured EMG represents a Newtonian force by which the muscle acts on the hand. Received: 7 October 1996 / Accepted in revised form: 29 January 1998     

Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization.

Amplitude and frequency content of the surface electromyographic (EMG) signal reflect central and peripheral modifications of the neuromuscular system. Classic surface EMG spectral variables applied to assess muscle functions are the centroid and median power spectral frequencies. More recently, nonlinear tools have been introduced to analyze the surface EMG; among them, the recurrence quantification analysis (RQA) was shown to be particularly promising for the detection of muscle status changes. The purpose of this work was to analyze the effect of motor unit short-term synchronization and conduction velocity (CV) on EMG spectral variables and two variables extracted by RQA, the percentage of recurrence (%Rec) and determinism (%Det). The study was performed on the basis of a simulation model, which allowed changing the degree of synchronization and mean CV of a number of motor units, and of an experimental investigation of the surface EMG signal properties detected during high-force-level isometric fatiguing contractions of the biceps brachii muscle. Simulations and experimental results were largely in agreement and show that 1) spectral variables, %Rec, and %Det are influenced by CV and degree of synchronization; 2) spectral variables are highly correlated with %Det (R = -0.95 in the simulations and -0.78 and -0.75 for the initial values and normalized slopes, respectively, in the experimental signals), and thus the information they provide on muscle properties is basically the same; and 3) variations of %Det and %Rec in response to changes in muscle properties are significantly larger than the variations of spectral variables. This study validates RQA as a means for fatigue assessment with potential advantages (such as the higher sensitivity to changes of muscle status) with respect to the classic spectral analysis.