基质金属蛋白酶与出血性转化

溶栓能有效治疗缺血性卒中,但有导致出血性转化的风险.许多研究显示,出血性转化与基质金属蛋白酶参与血脑屏障破坏、增加血管通透性密切相关.血浆MMP-9水平增高可作为出血性转化的独立预测因素.脑缺血早期应用基质金属蛋白酶抑制剂,有可能降低出血性转化的发生率和严重程度,但尚需进一步验证.     

A deficiency in prothoracicotropic hormone transduction pathway during the early last larval instar of Bombyx mori

The prothoracicotropic hormone (PTTH) is an insect cerebral peptide that stimulates the prothoracic glands to produce ecdysteroids that initiate moulting and metamorphosis. During the last larval instar of holometabolous insects, a reduction in the hemolymph juvenile hormone (JH) levels is a necessary step in initiating larval-pupal transformation. Recently we have demonstrated that very low ecdysteroid levels in the early last larval instar of Bombyx mori initiate the complete inactivation of corpora allata (CA). Results presented here further indicate that PTTH signal transduction pathways undergo specific developmental changes, with a deficiency in transduction in prothoracic gland cells occurring during the early last instar. Glands from the early last instar showed no increase in either cAMP levels or steroidogenesis to the stimulation of PTTH, indicating the absence of the PTTH receptors in gland cells. We propose that this absence of PTTH receptors plays a critical role in directing larval-pupal transformation.     

The splicing-factor oncoprotein SF2/ASF activates mTORC1

The splicing factor SF2/ASF is an oncoprotein that is up-regulated in many cancers and can transform immortal rodent fibroblasts when slightly overexpressed. The mTOR signaling pathway is activated in many cancers, and pharmacological blockers of this pathway are in clinical trials as anticancer drugs. We examined the activity of the mTOR pathway in cells transformed by SF2/ASF and found that this splicing factor activates the mTORC1 branch of the pathway, as measured by S6K and eIF4EBP1 phosphorylation. This activation is specific to mTORC1 because no activation of Akt, an mTORC2 substrate, was detected. mTORC1 activation by SF2/ASF bypasses upstream PI3K/Akt signaling and is essential for SF2/ASF-mediated transformation, as inhibition of mTOR by rapamycin blocked transformation by SF2/ASF in vitro and in vivo. Moreover, shRNA-mediated knockdown of mTOR, or of the specific mTORC1 and mTORC2 components Raptor and Rictor, abolished the tumorigenic potential of cells overexpressing SF2/ASF. These results suggest that clinical tumors with SF2/ASF up-regulation could be especially sensitive to mTOR inhibitors.     

Research of fetal ECG extraction using wavelet analysis and adaptive filtering

Extracting clean fetal electrocardiogram (ECG) signals is very important in fetal monitoring. In this paper, we proposed a new method for fetal ECG extraction based on wavelet analysis, the least mean square (LMS) adaptive filtering algorithm, and the spatially selective noise filtration (SSNF) algorithm. First, abdominal signals and thoracic signals were processed by stationary wavelet transform (SWT), and the wavelet coefficients at each scale were obtained. For each scale, the detail coefficients were processed by the LMS algorithm. The coefficient of the abdominal signal was taken as the original input of the LMS adaptive filtering system, and the coefficient of the thoracic signal as the reference input. Then, correlations of the processed wavelet coefficients were computed. The threshold was set and noise components were removed with the SSNF algorithm. Finally, the processed wavelet coefficients were reconstructed by inverse SWT to obtain fetal ECG. Twenty cases of simulated data and 12 cases of clinical data were used. Experimental results showed that the proposed method outperforms the LMS algorithm: (1) it shows improvement in case of superposition R-peaks of fetal ECG and maternal ECG; (2) noise disturbance is eliminated by incorporating the SSNF algorithm and the extracted waveform is more stable; and (3) the performance is proven quantitatively by SNR calculation. The results indicated that the proposed algorithm can be used for extracting fetal ECG from abdominal signals.     

Variance stabilization for computing and comparing grand mean waveforms in MEG and EEG

Grand means of time‐varying signals (waveforms) across subjects in magnetoencephalography (MEG) and electroencephalography (EEG) are commonly computed as arithmetic averages and compared between conditions, for example, by subtraction. However, the prerequisite for these operations, homogeneity of the variance of the waveforms in time, and for most common parametric statistical tests also between conditions, is rarely met. We suggest that the heteroscedasticity observed instead results because waveforms may differ by factors and additive terms and follow a mixed model. We propose to apply the asinh‐transformation to stabilize the variance in such cases. We demonstrate the homogeneous variance and the normal distributions of data achieved by this transformation using simulated waveforms, and we apply it to real MEG data and show its benefits. The asinh‐transformation is thus an essential and useful processing step prior to computing and comparing grand mean waveforms in MEG and EEG.     

Selection of pulse oximetry equipment for ambulatory monitoring

Primary objective : This communication describes the initial stage of a research project concerning the monitoring of SpO₂ in infants prone to periods of spontaneous oxygen desaturation whilst freely moving around their home environment. The primary aim was to determine an appropriate probe type and site together with an assessment of the suitability of two commercially available oximeter units. Research design : The study comprised 19 comparative tests, totalling 162 hours of recordings at resolution one sample every four seconds. Comparisons are drawn between probes, probe sites and pulse oximeters. Main outcomes/ results : The bias and precision is presented with respect to the probe and measurement site. Also, correlation between the trial and reference recordings is considered. Conclusions : It is concluded that ambulatory recording of SpO₂ in infants utilizing equipment suitable for home monitoring can produce diagnostic data equivalent to that of the Ohmeda 3700 biox, but that an indication of movement artefact may be required for confirmation of accuracy. It became apparent that 'wrap around' probes, used on the index finger or big toe are the most suitable.     

基于多模CT的区域软脑膜侧支评估与急性缺血性卒中梗死体积及出血转化的相关性研究

目的 探讨基于多模CT的区域软脑膜侧支评估(rLMC)与急性缺血性卒中梗死体积及出血转化的相关性及其应用价值.方法 回顾性分析2019年10月至2020年10月该院首次发病≤6h的急性大血管闭塞性缺血性脑卒中患者,颅脑CT排除出血性病变,采用rLMC分级,分为2个区域:大脑前动脉(ACA)-大脑中动脉(MCA)区和大脑后动脉(PCA)-MCA区.软脑膜动脉分级应用6分量表,CTA侧支评分为两个区域的总分(0～10分).入院3d内在头颅MR常规序列基础上加做DWI序列,明确梗死体积、是否合并出血转化.入院后10～14 d或患者病情加重时复查常规CT,了解是否有出血性转化.结果 不同rLMC分级评分组卒中家族史、冠心病史、入院时NIHSS评分、空腹血糖比较,差异有统计学意义(P＜0.05).rLMC分级评分与脑梗死体积呈显著负相关(γ=-0.735,P＜0.001).不同rLMC分级评分组在梗死体积、症状性颅内出血(sICH)发生率和颅内高密度灶(PCHDs)发生率比较,差异有统计学意义(P＜0.05).多因素Logistic回归分析提示卒中家族史、血糖、入院时NIHSS评分是软脑膜侧支循环的影响因素.结论 rLMC与急性缺血性卒中梗死体积、出血转化呈显著负相关,可有效反映急性缺血性卒中的病情进展及严重程度.     

基于经验模态分解-小波包变换的表面肌电信号手势识别

为了提高表面肌电信号（sEMG）手部运动识别的正确率,比较常规的sEMG预处理和特征提取方法,提出一种基于经验模态分解（EMD）和小波包变换（WPT）的sEMG手势识别模型。首先,使用EMD方法将sEMG进行平稳化,得到一系列的固有模态函数。其次,求取各个固有模态函数与原始信号的相关性,选取相关性较高的前4个分量作为有效分量。然后,采用Db3小波函数进行WPT,提取小波包系数中的平均能量、平均绝对值、最大值、均方根和方差等特征。分别采用线性判别分析和支持向量机对12种手部运动进行模式识别。结果表明基于EMD和WPT的sEMG手势识别正确率比直接提取小波包系数中的特征识别正确率高。