Atypical Motor Neuron Disease variants: Still a diagnostic challenge in Neurology

Motor neuron disease (MND) represents a wide and heterogeneous expanding group of disorders involving the upper or lower motor neurons, mainly represented by amyotrophic lateral sclerosis (ALS), primary lateral sclerosis, progressive muscular atrophy and progressive bulbar palsy. Primary motor neuronopathies are characterized by progressive degenerative loss of anterior horn cell motoneurons (lower motor neurons) or loss of giant pyramidal Betz cells (upper motor neurons). Despite its well-known natural history, pathophysiological and clinical characteristics for the most common MND, atypical clinical presentation and neurodegenerative mechanisms are commonly observed in rare clinical entities, so-called atypical variants of MND-ALS, including flail-leg syndrome, flail-arm syndrome, facial-onset sensory and motor neuronopathy (FOSMN), finger extension weakness and downbeat nystagmus (FEWDON-MND) and long-lasting and juvenile MND-ALS. Herein, we provide a review article presenting clinical, genetic, pathophysiological and neuroimaging findings of atypical variants of MND-ALS in clinical practice.     

上海市新生儿低出生体重流行趋势及危险因素分析

目的 分析上海市新生儿低出生体重流行趋势及相关危险因素,为控制上海市新生儿低出生体重流行水平提供决策依据。方法 收集上海市卫计委发布的2000年至2015年上海市常住人口新生儿低出生体重流行率数据,应用AAPC方法描述其趋势。收集覆盖全市所有接产机构的2015年上海市沪籍新生儿出生登记信息,应用卡方分析和基于偏最小二乘法的logistic回归模型开展低出生体重流行的危险因素分析。结果 2000年至2015年间,上海市新生儿低出生体重流行率累计上升了43.52%,年平均上升速度为1.70%(95%CI:1.26%~2.15%,P<0.05)。上海市新生儿低出生体重流行的危险因素包括早产、双多胎、女性、有畸形、高产次和父亲学历低。结论 有关部门应进一步开展调查研究,建立有效控制和减少早产等危险因素的综合干预策略。     

基于偏最小二乘法的近红外光谱模型用于丹参口服液提取过程的分析

目的探讨丹参口服液提取过程采用近红外光谱(NIR)分析的可能性及其方法。方法制备共122份提取液,采用高效液相色谱法(HPLC)测定原儿茶醛含量,并收集NIR图,用偏最小二乘法(PLS)建立校正模型。结果采用二阶求导及Savitzky-Golay平滑处理后的校正模型交叉验证均方根误差(RMSECV)为3.456,相关系数为0.988,优于其他优化方式。结论基于PLS的原儿茶醛NIR模型可用于丹参口服液提取过程的在线分析。     

Effects and Detection of Raw Material Variability on the Performance of Near-Infrared Calibration Models for Pharmaceutical Products

The impact of raw material variability on the prediction ability of a near-infrared calibration model was studied. Calibrations, developed from a quaternary mixture design comprising theophylline anhydrous, lactose monohydrate, microcrystalline cellulose, and soluble starch, were challenged by intentional variation of raw material properties. A design with two theophylline physical forms, three lactose particle sizes, and two starch manufacturers was created to test model robustness. Further challenges to the models were accomplished through environmental conditions. Along with full-spectrum partial least squares (PLS) modeling, variable selection by dynamic backward PLS and genetic algorithms was utilized in an effort to mitigate the effects of raw material variability. In addition to evaluating models based on their prediction statistics, prediction residuals were analyzed by analyses of variance and model diagnostics (Hotelling's T² and Q residuals). Full-spectrum models were significantly affected by lactose particle size. Models developed by selecting variables gave lower prediction errors and proved to be a good approach to limit the effect of changing raw material characteristics. Hotelling's T² and Q residuals provided valuable information that was not detectable when studying only prediction trends. Diagnostic statistics were demonstrated to be critical in the appropriate interpretation of the prediction of quality parameters.     

Identification of active compounds from Caesalpinia sappan L. extracts suppressing IL-6 production in RAW 264.7 cells by PLS

Ethnopharmacological relevance

Caesalpinia sappan L. is distributed in Southeast Asia and also used as herbal medicine for the treatment of various diseases such as burning sensations, leprosy, dysentery, osteoarthritis and rheumatoid arthritis (RA). The overproduction of IL-6 plays an important role in the prognosis of RA, but the active compounds from the extracts of Caesalpinia sappan L. suppressing IL-6 production remain unknown.

Aims of the study

Identifying the main active compounds of Caesalpinia sappan L. extracts inhibiting the IL-6 production in LPS-stimulated RAW 264.7 cells by partial least squares (PLS).

Materials and methods

Sixty-four samples with different proportions of compounds were prepared from Caesalpinia sappan L. by supercritical CO₂ fluid extraction (SCFE) and refluxing. Each of 64 samples was applied to RAW 264.7 cells with LPS to evaluate whether IL-6 production by LPS is affected by addition of each sample. The IL-6 production in medium was determined by ELISA and the inhibitory activity of each sample was analyzed. In addition, the fingerprints of these 64 samples were also established by ultra-performance liquid chromatography electrospray ionization tandem mass spectrometry (UPLC–MS). We used the PLS, a simplified method, to evaluate the results from IL-6 production and fingerprints.

Results

Each of 64 samples markedly suppressed LPS-induced IL-6 production in RAW cells. The fingerprints by UPLC–MS clearly revealed variations among 64 samples produced in different extract conditions. The PLS analysis with IL-6 production and fingerprints by UPLC–MS suggested that the peaks 71, 93, 150, 157, 168 have more influence on the inhibitory activity of Caesalpinia sappan L. extracts. The peaks 71, 93, 150 are likely representing sappanone A, protosappanin E and neoprotosappanin, respectively. The peaks 157 and 168 are still at large.

Conclusion

This is the first report that sappanone A, protosappanin E, neoprotosappanin and two unidentified compounds can be considered as possible active compounds that might inhibit IL-6 production. Further studies are needed to confirm the effectiveness of these five compounds on IL-6 production and possible mechanism.     

基于偏最小二乘模型的奥氮平血药达峰浓度与个体内在因素的相关性研究

目的:探讨奥氮平血药达峰浓度(Cmax)与个体内在因素的相关性.方法:采用LC-MS/MS测定20名健康志愿者奥氮平的Cmax,采用偏最小二乘回归方法(PLS)分析Cmax与个体内在因素包括年龄、体重指数(BMI)、白细胞(WBC)、红细胞(RBC)、血小板(PLT)、血红蛋白(HB)、肌酐(Cr)、尿素氮(BUN)、总蛋白(TP)、白蛋白(ALB)、碱性磷酸酶(AKP)、谷丙转氨酶(ALT)等的相关性.结果:通过PLS分析结果表明:Cmax与BMI、WBC、BUN、TP、ALT呈正相关;与RBC、PLT、HB、Cr、ALB、AKP呈负相关,其中与BMI、WBC、RBC、BUN、TP相关性最强.预测建模分析显示,模型拟合效果较好,可以作为预测奥氮平体内Cmax的参考指标.结论:个体内在因素影响奥氮平的Cmax,可以为临床个体化用药提供参考.     

Predictive insight into the relationship between AhR binding property and toxicity of polybrominated diphenyl ethers by PLS-derived QSAR

Polybrominated diphenyl ethers (PBDEs) are experimentally indicated to be capable of binding to the cytosolic aryl hydrocarbon receptor (AhR) and show a weak or moderate toxicity. However, little is yet known about the AhR-mediated toxicology. To fully evaluate the structural effects of PBDE ligand on AhR binding affinity and toxicity, quantitative structure-activity relationships (QSARs) were developed by PLS analysis. In this study, a simple but potent QSAR that was qualified with much better or comparable performance of prediction was optimally established for PBDE toxicity. With QSAR analysis, the AhR binding property was carefully described to reflect the origin of AhR binding affinity. Besides the effects from topological characters, the dispersion and electrostatic interactions were of indispensability for AhR binding affinity whereas the dispersion was further suggested to be dominant. The structural requirement for AhR binding affinity and toxicity was also investigated. As was similarly observed for polychlorinated biphenyls (PCBs), the preferential bromination at para- and meta (particularly 3,3′-)-sites was confirmed as a key determinant to improve the AhR binding affinity and the toxicity of PBDEs.     

Simultaneous diffuse reflectance infrared determination of clavulanic acid and amoxicillin using multivariate calibration techniques

A method for simultaneous determination of clavulanic acid (CA) and amoxicillin (AMO) in commercial tablets was developed using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and multivariate calibration. Twenty-five samples (10 commercial and 15 synthetic) were used as a calibration set and 15 samples (10 commercial and 5 synthetic) were used for a prediction set. Calibration models were developed using partial least squares (PLS), interval PLS (iPLS), and synergy interval PLS (siPLS) algorithms. The best algorithm for CA determination was siPLS model with spectra divided in 30 intervals and combinations of 2 intervals. This model showed a root mean square error of prediction (RMSEP) of 5.1 mg g(-1). For AMO determination, the best siPLS model was obtained with spectra divided in 10 intervals and combinations of 4 intervals. This model showed a RMSEP of 22.3 mg g(-1). The proposed method was considered as a suitable for the simultaneous determination of CA and AMO in commercial pharmaceuticals products.