AIM To observe effects of IBMX on cGMP and GFAP production in gerbil hippocampus after recirculation following ischemia. METHODS Bilateral occlusion of common carotid arteries and immunofluorescent stain methods in gerbil hippocampal tissue slice were used. RESULTS Recirculation following ischemia leads to a rise in hippocampus cGMP and GFAP concentration. cGMP and GFAP positive cells mainly distributed in rediatum layer and molecular layer in the CA 1 subfield, Most of cGMP positive cells are astrocytes under double immunofluorescent stain. Most of cGMP strong positive cells are also those of GFAP strong positive cells. IBMX increased cGMP and GFAP production. CONCLUSION cGMP is possible to play an important role in the activation or regulation of GFAP in the hippocampus.

0.05). The laser group with the dose of 3 J?cm-2 showed more increase in cell survival at 24 and 48 h after being seeded as compared with control group(P

Objective To observe the distribution and location of TGF-?_1 in different stages of experimental lesions and to discuss its potential function. Methods Thirty Wistar rats were established experimental periapical lesions in maxillary first and second molar as experimental group while mandibular molar as control group, and they were divided into ten groups by the time(1,2,3,4,5,6,7,8,9, and 10 weeks)after pulp exposure, three rats in every group. Expression of TGF-?_1 was detected by histopathology and immunohistochemistry. Results Strong expression of TGF-?_1 was observed in acute inflammation of pulp (1st-2nd week) and periapical tissue (4th-6th week), and idisappeared in pulp aecrosis and in chronic inflammation of periapical tissue(7th week). The main cells expressing TGF-?_1 were macrophage,lymphocyte and fibroblast. Conclusion TGF-?_1 has the certain function in inflammation and prevention of experimental periapical lesions.

Objective To develop a recognition method of liver steatosis degree on type-B ultrasonic images based on multi-fractal spectrum texture analysis method and pattern recognition. Methods Features of singularity strength width and multi-spectrum area were extracted from the curve of multi-fractal spectrum of each liver ultrasonic images. These two features and the feature of mean intensity ratio comprised a three-dimensional feature vector, which would be classified by BP neural network. Results The classification accuracy was 96.00% for normal liver, 80.00% for mild fatty liver, 88.00% for moderate fatty liver and 92.00% for severe fatty liver. Conclusion Feature vector combined with BP neural network can identify the steatosis degree of liver on the ultrasonic images and can be used as an assistant diagnostic method.

Through the study of the pathology of sleep apnea-hypopnea syndrome, evaluation indexes, diagnosis requirements and so on, a portable sleep monitoring system was designed, which had the characteristics of convenience, wireless transmission and no disturbance. The system can be assessed by respiration monitoring and pulse oximetry, which is based on the pressure variation in miniature air-bag and spectral absorption method. It provides the value of the apnea-hypopnea index (AHI), which is used to evaluate OSAHS severity. The experiment of the system's stability and accuracy is done, which exhibits good performance, it can diagnose OSAHS effectively and provide convenience for home monitoring.
Humans ; Oximetry ; Polysomnography ; instrumentation ; Sleep Apnea, Obstructive ; diagnosis

Objective To analyze the stress distribution of abutment and alveolar ridge between two kinds of distal-extention absence dentures,and provide evidence for the application of different dentures in clinic.Methods Attachment denture and cantilever fixed bridge were used to restore the distal-extention absence respectively,the stress distribution of abutment and alveolar ridge was compared by three-dimensioal finit element method.Results The stress peak values of abutmen root,periodontal membrance,alveolar ridge were(1.42E+5)MPa,(1.33E+4)MPa and(3.49E+5)MPa,respectively,in attachment denture;while in cantilever fixed bridge,the stress peak values of them were(1.45E+7)MPa and(2.25E+6) MPa,(1.45E+3)MPa,respectively.And the stress peak values of these two kinds of dentures were all located in the mid-upper 1/3 and the cervical of abutment.Conclusion Compared with cantilever fixed bridge,the attachment denture could decrease the stress of abutment and be helpful to its protection,the hight of residual alveolar ridge should be taken into account when the two kinds of dentures are used for distal-extention absence.

Ultrasonic estimation of fetal weight is important in the management o f labor and delivery. Lots of charts and formulas have been put forward in virtu e of regression methods. Artificial neural network, a kind of computer artificia l intelligence technology, can simulate human thinking based on neural structure and physiology. With the excellence in complex and non-linear information proce ssing, artificial neural network is fitter for the forecasting of fetal weight t han traditional regression methods.

Child and adolescent mental disorders are common disorders with various symptoms,and attracting more attention due to the increasing prevalence.Mental disorders,especially the attention-deficit hyperactivity disorder (ADHD) and the autism spectrum disorder (ASD),have great influence on the development of children and adolescents.Nowadays,the biomarkers from neuroimaging such as magnetic resonance imaging (MRI) have a great importance on the diagnosis of mental disorders,and machine learning has been proved to be very powerful in the processing for neuroimages.Nowadays,many researchers are focusing on the studies of computer-aided diagnosis (CAD) based on machine learning and neuroimaging.In this review,the technical details of machine learning based CAD of child and adolescent mental disorders are briefly introduced,and the research progress in CAD of ADHD and ASD based on machine learning and structural MRI are summarized.These studies showed that many machine learning methods have been used in the diagnosis of child and adolescent mental disorders,but the relevant methods cannot be applied to clinical diagnosis.Further studies should be conducted to improve the diagnostic ability of machine learning methods from multiple perspectives,and provide an objective and reliable tool for the clinical diagnosis of child and adolescent mental disorders.

Speckle is the main reason which declines the quality of medical ultrasonic images. In this paper, the initial condition for the Downhill filter, a morphological reconstruction algorithm, is modified and applied in the speckle reduction. Firstly, the initial area and start position as the mark image was determined in the marker image. Then the modified Downhill filter was used in the ultrasonic marker image. The results showed that, in comparison with the other three filters, this modified Downhill filter, while maintaining the integrity of the contour,could reduce the speckle in the regions of cavity efficiently and rapidly.
Algorithms ; Humans ; Image Enhancement ; methods ; Image Processing, Computer-Assisted ; Ultrasonography ; methods

Objective To identify risk factors associated with the severity of acute kidney injury (AKI) in-duced by crush syndrome and whether the patient required hemodialysis (HD). Method A retrospective study was designed. Within 19 days after the Chinese Wenchuan earthquake (May 12, 2008), 63 victims (33 men, 30women) of 2139 cases were hospitalized at Mianyang Central Hospital (Siehuau, China) because of crush syn-drome caused by crush injuries. The patients with renal dysfimcfion before the earthquake were excluded. Totally 63 patients with AKI associated with crush syndrome were included in this study and were divided into two groups: group 1, 25 patients, requiring HD (when urine volume <250 mL/d;serum potassium> 6 mmol/L) ; and group 2, 38 patients, without HD. The following data were collected retrospectively for all patients: (1) epidemiological parameters: age, gender, race, time under the rubble, liquid treatmem before being rescued; (2) clinical param-eters: blood pressure, body area crushed, amputation, fasciotomy, blood transfusion, quantity of fluid infusion, urine output in the first 24 hours; (3) initial laboratory data: complete blood count, urine analysis, serum chem-istry, arterial blood gas analysis. Comparisons between the two groups were made using SPSS 10.0. The quantita-tive data and categorical data were analyzed using t tests and χ2 tests, respectively. P -values < 0.05 were consid-ered to indicate significant differences. The significant variables were entered into logistic regression models to de-termine the risk factors for the severity of AK1 in patients with crush syndrome and whether the patient required HD. Results Four significant risk factors with P -values < 0.05 were identified: fasciotomy, cystatin C (Cys C)level, myoglobin (MB) level and lactic acidosis. The odds ratios (95% confidence intervals) were 8.641 (3.027～76.479), 6.956 (3.027～76.479), 5.379 (3.027～76.479) and 4.833 (2.569～32.764), respectively. Conclusions In addition to urine output and potassium levels, we found that four risk factors, namely faseiotomy, Cys C and MB levels, and lactic acidosis, were significanfly associated with the severity of AKI and whether the patient required hemodialysis.