Lipidomics investigation of reversal effect of glycyrrhizin (GL) towards lithocholic acid (LCA)-induced alteration of phospholipid profiles

Context: Glycyrrhizin (GL), the major ingredient isolated from licorice, exerts multiple pharmacological activities.

Objective: To elucidate the protective mechanism of GL towards lithocholic acid (LCA)-induced liver toxicity using lipidomics.

Materials and methods: GL (200?mg/kg) dissolved in corn oil was treated intraperitoneally for 7?d. On the 4th day, 200?mg/kg LCA was used to treat mice (i.p., twice daily) for another 4?d. The protective role of GL towards LCA-induced liver toxicity was investigated through evaluating the liver histology and the activity of alanine transaminase (ALT). The complete lipid profile was employed using UFLC-Triple TOF MS-based lipidomics.

Results: Intraperitoneal (i.p.) administration of 200?mg/kg GL can significantly protect LCA-induced liver damage, indicated by alleviated histology alteration and prevention of the ALT elevation. Lipidomics analysis can well separate the control group from LCA-treated group, and three lipid components were major contributors, including LPC 16:0, LPC 18:0, and LPC 18:2. GL treatment can significantly prevent LCA-induced reduction of these three lipid compounds, providing a new explanation for GL's protection mechanism towards LCA-induced liver toxicity.

Discussion and conclusion: The recent study highlights the importance of lipidomics in elucidating the therapeutic mechanism of herbs.     

Application of Independent Component Analysis for the Data Mining of Simultaneous Eeg–fMRI: Preliminary Experience on Sleep Onset

The simultaneous acquisition of electroencephalogram (EEG) and functional MRI (fMRI) signals is potentially advantageous because of the superior resolution that is achieved in both the temporal and spatial domains, respectively. However, ballistocardiographic artifacts along with ocular artifacts are a major obstacle for the detection of the EEG signatures of interest. Since the sources corresponding to these artifacts are independent from those producing the EEG signatures, we applied the Infomax-based independent component analysis (ICA) technique to separate the EEG signatures from the artifacts. The isolated EEG signatures were further utilized to model the canonical hemodynamic response functions (HRFs). Subsequently, the brain areas from which these EEG signatures originated were identified as locales of activation patterns from the analysis of fMRI data. Upon the identification and subsequent evaluation of brain areas generating interictal epileptic discharge (IED) spikes from an epileptic subject, the presented method was successfully applied to detect the theta and alpha rhythms that are sleep onset-related EEG signatures along with the subsequent neural circuitries from a sleep-deprived volunteer. These results suggest that the ICA technique may be useful for the preprocessing of simultaneous EEG–fMRI acquisitions, especially when a reference paradigm is unavailable.     

Relative validity of dietary patterns during pregnancy assessed with a food frequency questionnaire

Abstract

This study aimed to assess the relative validity of maternal dietary patterns derived from a semi-quantitative food frequency questionnaire (FFQ). A total of 162 pregnant women aged 19–40-years-old were enrolled from the Universiti Sains Malaysia (USM) Birth Cohort Study in year 2010 and 2011. The FFQ was compared with three 24-h dietary recalls (DRs). Two major dietary patterns were derived from the principle component analysis which are labeled as Healthy and Less-Healthy patterns. The Pearson correlation coefficients between FFQ and DRs for Healthy and Less-Healthy patterns were 0.59 and 0.63, respectively. At least 45% of the participants were correctly classified into the same third from the FFQ and DR for both dietary patterns. The weighted kappa showed moderate agreement for Healthy pattern while good agreement for Less-Healthy pattern between these two dietary assessment methods. Our results indicate reasonable validity of the dietary patterns identified from the FFQ in pregnant women.     

孜然挥发油GC-MS指纹图谱的构建及主成分分析和聚类分析

目的 采用GC-MS指纹图谱并结合多元统计等方法评价不同产地孜然质量。方法 采用气相色谱-四极杆飞行时间质谱（GC-Q-TOF/MS）技术对孜然挥发油进行定性和定量分析，建立20批不同产地孜然的指纹图谱；运用"中药色谱指纹图谱相似度评价系统软件（2012年版）"进行相似度评价，并进行聚类分析和主成分分析。结果 建立的指纹图谱确定了33个共有峰，相似度均>0.961，主要成分包括枯茗醛、γ-松油烯-7-醛、α-松油烯-7-醛、γ-松油烯、o-伞花烃、桧烯、枯茗醇、3-p-孟烯-7-醛等，其相对含量约占总含量的99.7%。通过聚类分析可将20批孜然分为5大类。主成分分析得到4个主成分的累积方差贡献率为88.946%，其结果显示S20号样品综合得分较高。主成分分析与聚类分析结果基本一致。结论 该方法特征性强，仪器精密度、重复性和稳定性良好，可用于孜然挥发油及其相关产品的质量控制和评价。     

Effects of footwear fixation on joint angle variability during straight gait in the elderly

BackgroundVarious types of footwear fixation can dramatically alter gait characteristics, and could potentially contribute to an increased risk of falls in the elderly. However, no studies have been conducted to analyze the effects of footwear fixation on joint angle variabilities, particularly during the entire gait cycle.Research questionDoes the fixation of footwear significantly affect the lower limb joint angle variabilities during the gait cycle?MethodsPrincipal component analysis (PCA) was conducted on 20 healthy adults using 3D spatio-temporal data of the pelvis and lower limb joint angle that were collected during the entire gait cycle with the footwear in various conditions (well-fixated footwear, less-fixated footwear, slippers, and bare feet). Kinematic waveforms were reconstructed from the PCA data, which were used to determine the distinct differences in joint angle variabilities between footwear conditions.ResultsThe results showed large variability in the knee- and ankle-joint angles on the sagittal plane when walking in the loose condition (less-fixated footwear, slippers, and bare feet) compared with those in the well-fixated footwear condition.SignificanceThese results demonstrate the effect of footwear fixation on the joint angle variabilities of the elderly while walking. The increase in the knee- and ankle-joint angle variabilities when walking with less-fixated footwear could be a risk factor for falls.     

The WHO active ageing pillars and its association with survival: Findings from a population-based study in Spain

BackgroundThe World Health Organization’s active ageing model is based on the optimisation of four key “pillars”: health, lifelong learning, participation and security. It provides older people with a policy framework to develop their potential for well-being, which in turn, may facilitate longevity. We sought to assess the effect of active ageing on longer life expectancy by: i) operationalising the WHO active ageing framework, ii) testing the validity of the factors obtained by analysing the relationships between the pillars, and iii) exploring the impact of active ageing on survival through the health pillar.MethodsBased on data from a sample of 801 community-dwelling older adults, we operationalised the active ageing model by taking each pillar as an individual construct using principal component analysis. The interrelationship between components and their association with survival was analysed using multiple regression models.ResultsA three-factor structure was obtained for each pillar, except for lifelong learning with a single component. After adjustment for age, gender and marital status, survival was only significantly associated with the physical component of health (HR = 0.66; 95% CI = 0.47−0.93; p = 0.018). In turn, this component was loaded with representative variables of comorbidity and functionality, cognitive status and lifestyles, and correlated with components of lifelong learning, social activities and institutional support.ConclusionAccording to how the variables clustered into the components and how the components intertwined, results suggest that the variables loading on the biomedical component of the health pillar (e.g. cognitive function, health conditions or pain), may play a part on survival chances.