Offline two-dimensional liquid chromatography coupled with ion mobility-quadrupole time-of-flight mass spectrometry enabling four-dimensional separation and characterization of the multicomponents from white ginseng and red ginseng / 药物分析学报

Inherent complexity of plant metabolites necessitates the use of multi-dimensional information to accomplish comprehensive profiling and confirmative identification. A dimension-enhanced strategy, by offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spec-trometry (2D-LC/IM-QTOF-MS) enabling four-dimensional separations (2D-LC, IM, and MS), is proposed. In combination with in-house database-driven automated peak annotation, this strategy was utilized to characterize ginsenosides simultaneously from white ginseng (WG) and red ginseng (RG). An offline 2D-LC system configuring an Xbridge Amide column and an HSS T3 column showed orthogonality 0.76 in the resolution of ginsenosides. Ginsenoside analysis was performed by data-independent high-definition MSE (HDMSE) in the negative ESI mode on a Vion TM IMS-QTOF hybrid high-resolution mass spectrometer, which could better resolve ginsenosides than MSE and directly give the CCS information. An in-house ginsenoside database recording 504 known ginsenosides and 58 reference compounds, was estab-lished to assist the identification of ginsenosides. Streamlined workflows, by applying UNIFI TM to auto-matedly annotate the HDMSE data, were proposed. We could separate and characterize 323 ginsenosides (including 286 from WG and 306 from RG), and 125 thereof may have not been isolated from the Panax genus. The established 2D-LC/IM-QTOF-HDMSE approach could also act as a magnifier to probe differ-entiated components between WG and RG. Compared with conventional approaches, this dimension-enhanced strategy could better resolve coeluting herbal components and more efficiently, more reli-ably identify the multicomponents, which, we believe, offers more possibilities for the systematic exposure and confirmative identification of plant metabolites.

Integrating channel selection and feature selection in a real time epileptic seizure detection system.

Automated real time seizure detection is difficult since detection sensitivity, false detection rate and seizure onset detection latency need to be considered simultaneously. Traditional pattern recognition and classification system usually suffers huge performance variation due to patient specificity and algorithm inadaptability. To address this problem, we propose a two stage seizure detection system which integrates off-line channel selection and feature selection before the construction of the final model. This system allows patient specific channel selection and flexible feature set extraction for individual patient, so that a more compact and reliable model could be developed. Employing the two stage scheme not only decreases hardware cost in signal readout and feature extraction, but also remarkably improves detection sensitivity and reduces false detections. Mutual information based method is used for channel selection, while Random Forests and nonlinear SVM-RFE are evaluated for feature selection. The whole system achieves a mean detection latency of 6 seconds and a false detection rate of 0.356 per hour. Based on the test dataset, the sensitivity is found to 74.2% by sample or 98.4% by record with only two detection misses. Our design is also hardware-friendly, which could be implemented as a single chip closed loop neural modulation system.

Automatic seizure detection using correlation integral with nonlinear adaptive denoising and Kalman filter.

The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection rate, which are comparable to many machine learning based methods, but at much lower computational cost. Since this algorithm is tested with long-term scalp EEG, it has the potential to achieve higher performance with intracranial EEG. The clinical value of this algorithm includes providing a pre-judgement to assist the doctor's diagnosis procedure and acting as a reliable warning system in a wearable device for epilepsy patients.

Protective effects of recombinant human erythropoietin on oligodendrocyte after cerebral infarction / 中华病理学杂志

<p><b>OBJECTIVE</b>To study biological effect of recombinant human erythropoietin (RhEPO) on the expression of oligodendrocyte in the neuron glia antigen 2(NG2), Nogo receptor-interacting protein 1(LINGO-1), myelin basic protein (MBP) and myelin associated glycoprotein (MAG), and to explore the protective mechanism of RhEPO for oligodendrocyte after cerebral infarction.</p><p><b>METHODS</b>Experimental rats were randomly divided into the treatment group (RhEPO at a dose of 3 000 U/kg) or saline control group. Both groups received intraperitoneal injection of RhEPO after cerebral ischemia in 30 min, 3 h, 6 h, 12 h and 24 h, which was administered daily for 7 days. The modified neurological severity score (mNSS) and histology were analyzed, and immunohistochemistry was used to detect the protein expression of NG2, MAG, MBP and LINGO-1.</p><p><b>RESULTS</b>The overall mNSS of RhEPO treatment group significantly decreased compared with the saline control group on the seventh day after cerebral infarction (P<0.05). Such treatment effect was more obvious in the treatment group at 30 min and 3 h (P<0.01). Compared with the saline control group, the numbers of NG2 positive cells increased in RhEPO treatment group. In contrast, the expression of LINGO-1 protein significantly decreased (P<0.05), with a dramatic decrease observed at 30 min and 3 h (P<0.01). However, the expression of MBP protein decreased more significantly in saline control group, while the level of the MAG protein expression increased. The differences were statistically significant (P<0.05), especially at 30 min (P<0.01).</p><p><b>CONCLUSIONS</b>After cerebral ischemia, RhEPO promotes the proliferation of NG2 positive cells, and inhibits the expression of LINGO-1 and MAG proteins. RhEPO improves the proliferation and differentiation of oligodendrocyte precursor cells, which in turn protects neuronal function, particularly at the early phase of ischemia.</p>

Expression and diagnostic value of CK19,HBME-1 and MIB-1 between hyalinizing trabecular tumor and thyroid papillary carcinoma / 实用肿瘤学杂志

Objective Hyalinizing trabecular tumor ( HTT) is often mistaken as thyroid papillary carcino-ma( TPC) ,which shares some morphological features with TPC .The aim of this study is to investigate HTT and TPC with immunohistochemical methods .Methods we detected the expression of the three Immunohistochemical index((CK19,HBME-1,MIB-1)in thirteen cases HTT and twenty cases TPC.Results In HTT samples, CK19:three of the thirteen were positive and focal positivity (1+);HBME-1:None of the thirteen samples was stained.MIB-1:ten in thirteen cases were stained in nucleus .In TPC samples,CK19:all of the twenty samples were intensely stained;HBME-1:nineteen of twenty samples were intensely stained;MIB-1:all of the twenty samples were stained in nucleus .The sensitivity and specific degrees of CK 19 and HBME-1 combination to diag-nosis HTT and TPC were 90.0%and 69.2%.Conclusion Our research could provide potent aid to differential diagnosis of HTT and TPC .The combination of CK19 and HBME-1 are adequate to identify HTT and TPC .