OBJECTIVE:To evaluate the clinical efficacy of cinepazide maleate in combination with magnesium sulfate for traumatic subarachnoid hemorrhage.METHODS:A total of 160 patients with traumatic subarachnoid hemorrhage were randomly assigned to 4 groups:Control group(n=40)received conventional therapy alone(hemostasis,dehydration,hormone and drugs promoting recovery of nervous function;Group Ⅰ(Control group,n=40)received cinepazide maleate plus conventional therapy;Group Ⅱ(n=40)received magnesium sulfate plus conventional therapy,and Group Ⅲ(n=40)received cinepazide maleate in combination with magnesium sulfate in additional to the conventional therapy.All the drugs were given in every 12 h for 14 consecutive days.Transcranial Doppler(TCD)examination was scheduled at 0,3,7,14 days after admission to observe the incidences of cerebral angiospasm(CVS)and patients' prognosis.RESULTS:There were significant differences between Group Ⅲ and the other 3 groups(Control group,Group Ⅰ and Group Ⅱ)in the incidence of CVS,the change of the blood flow rate of the middle cerebral artery and patients' prognosis at 3 and 6 months respectively(P

Danshen (Salvia miltiorrhiza Bunge) hairy roots were obtained by infecting Danshen leaves with Agrobacterium rhizogenes 9402. Besides rosmarinic acid (RA) and salvianolic acid B (SAB), the hairy root could also produce salvianolic acid K (SAK), salvianolic acid L, ethyl salvianolic acid B (ESAB), methyl salvianolic acid B (MSAB), and a compound with a molecular weight of 538 (compound 538) identified by using LC-MS. Effects of methyl jasmonate (MeJA) and yeast elicitor (YE) on the accumulation of these compounds had been investigated. MeJA increased the accumulation of SAB, RA, SAK, and compound 538 from 4.21%, 2.48%, 0.29%, and 0.01% of dry weight to 7.11%, 3.38%, 0.68%, and 0.04%, respectively. YE stimulated the biosynthesis of RA from 2.83% to 5.71%, but depressed the synthesis of SAB, SAK and compound 538. It was indicated in all the results that these Danshen hairy roots could be used as alternative resources to produce salvianolic acids. Analysis of the content variation of these compounds after elicitation suggested that SAK and compound 538 might be the intermediates in the biosynthesis from RA to SAB in Danshen hairy roots.

0 05), but there were significant differen t between the positive rates with APPSWE gene (P

Discriminative common vector (DCV) is an effective method that was proposed for the small sample size problems of face recognition. There is the same problem in brain-computer interface (BCI). Using directly the linear discriminative analysis (LDA) could result in errors because of the singularity of the within-class matrix of data. In our studies, we used the DCV method from the common vector theory in the within-class scatter matrix of data of all classes, and then applied eigenvalue decomposition to the common vectors to obtain the final projected vectors. Then we used kernel discriminative common vector (KDCV) with different kernel. Three data sets that include BCI Competition I data set, Competition II data set IV, and a data set collected by ourselves were used in the experiments. The experiment results of 93%, 77% and 97% showed that this feature extraction method could be used well in the classification of imagine data in BCI.
Algorithms ; Artificial Intelligence ; Brain-Computer Interfaces ; Discriminant Analysis ; Electroencephalography ; Face ; anatomy & histology ; Humans ; Pattern Recognition, Automated ; methods ; Principal Component Analysis ; Sample Size ; Signal Processing, Computer-Assisted ; User-Computer Interface

BACKGROUND: It has been demonstrated that amyloid-beta 42 protein (Aβ42) immunization in transgenic mouse models of Alzheimer disease(AD)can induce specific Aβ42 antibody, clear Aβ from the brain, and thereby improve spatial learning and memory. It has been a promising treatment strategy for AD.OBJECTIVE: To explore the effect of Aβ42 and its subunit vaccines immunization on spatial learning and memory of APPSWE transgenic mice.DESIGN: A randomized controlled experiment with mice as subjects.SETTING: The brain research laboratory of the anatomy department in a the medical college of a univeristy.MATERIALS: The experiment was conducted in the Experimental Animal Center and the Anatomy Department of Sun Yat-sen University from April 2003 to February 2004. Thirty-two APPSWE transgenic mice of 5 months old were bought from Taconic Company, USA. The second generation of mice were successfully reproduced in the Anatomy Department. These mice were randomly assigned into four groups: control group, Aβ42 group, Aβ1-15group, and Aβ36-42 group. Each group contained 8 in each group.INTERVENTIONS: Aβ42 and its subunits combined with MF59 adjuvant were subcutaneously injected for fundamental immunity and then applied in nasal mucosa for intensified immunization. The immunization period was 8 months. Y-maze was used for behavior test before immunization and Morris water maze was used after immunization.MAIN OUTCOME MEASURES: Spatial learning and memory, mean escape latency, times of passing through the platform point, swimming distance percentage of the first quadrant, and swimming distance percentage of the 20% marginal area.RESULTS: The correct reaction times in Y-maze behavior test were 7.50 ±0. 81, 7.06 ±0.71, 7.19 ±0.91, and 7.50 ±0.86 respectively in the control, Aβ42, Aβ1-15, Aβ36-42 groups and there was no significant difference ( P ＞ 0. 05) . After immunization, the mean escape latencies in 8 units of localized navigation test were(67.3 ±2. 8) s, (23.6 ± 1.6) s, (26.4 ±2.0) s,and (36.5 ± 2.2) s. The results in three experiment groups were different from that in control group and there was no difference between the three experiment groups ( P ＞ 0. 05 ) . The mean times of passing through the platform point in the 4 groups were 0.71 ±0.29, 8.14 ± 1.37, 7.28 ± 1.34,and 3.29 ± 0. 67. Swimming distance percentage of the first quadrant in the4 groups were(24.3 ±2.9)%, (50.6±11.6)%, (49.9±9.3) %,and(35.4±7.0)% and the swimming distance percentages of 20%marginal area were (46.4 ± 7.3 ) %, ( 11.6 ± 3.9) %, ( 14.4 ± 2. 6) %, and (25.8 ± 3.3)%. The mice in three experiment groups showed increase in the times of passing through platform point, swimming distance percentage of the first quadrant, and decrease in distance percentage of 20% marginal area compared with control group. The results in three experiment groups were no significantly different( P ＜ 0. 05).CONCLUSION: Immunization with A342 and its subunits can effectively ameliorate impairment of spatial learning and memory in APPSWE transgenic mice.

Using human electroencephalogram (EEG) to control external devices in order to achieve a variety of functions has been focus of the field of brain-computer interface (BCI) research. P300 is experiments which stimulate the eye to produce EEG by using letters flashing, and then identify the corresponding letters. In this paper, some improvements based on the P300 experiments were made??. Firstly, the matrix of flashing letters were modified into words which represent a certain sense. Secondly, the BCI2000 procedures were added with the corresponding source code. Thirdly, the smart car systems were designed using the radiofrequency signal. Finally it was realized that the evoked potentials were used to control the state of the smart car.
Adult ; Automobiles ; Brain ; physiology ; Brain-Computer Interfaces ; Electroencephalography ; instrumentation ; methods ; Event-Related Potentials, P300 ; Evoked Potentials, Visual ; Female ; Humans ; Male ; Man-Machine Systems ; Task Performance and Analysis

To relax the presumption of strictly linear patterns in the common spatial patterns (CSP), we studied the kernel CSP (KCSP). A new multi-class KCSP (MKCSP) approach was proposed in this paper, which combines the kernel approach with multi-class CSP technique. In this approach, we used kernel spatial patterns for each class against all others, and extracted signal components specific to one condition from EEG data sets of multiple conditions. Then we performed classification using the Logistic linear classifier. Brain computer interface (BCI) competition III_3a was used in the experiment. Through the experiment, it can be proved that this approach could decompose the raw EEG singles into spatial patterns extracted from multi-class of single trial EEG, and could obtain good classification results.
Algorithms ; Brain ; physiology ; Brain-Computer Interfaces ; Data Interpretation, Statistical ; Electroencephalography ; methods ; Pattern Recognition, Automated ; methods ; Signal Processing, Computer-Assisted ; instrumentation ; User-Computer Interface