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Objective@#To investigate the impact of obstructive sleep apnea hypopnea syndrome (OSAHS) on platelet function in patients with ischemic stroke.@*Methods@#Patients with ischemic stroke treated in the Department of Neurology, Weihai Municipal Hospital from January 2017 to November 2017 were collected prospectively. The presence or absence of OSAHS was determined by polysomnography. After oral administration of aspirin enteric coated tablets for 7±1 d, the maximum aggregation ratio (MAR) induced by arachidonic acid (AA) was determined by PL-12 Platelet Function Analyzer. MAR-AA ≥50% was defined as platelet hyperresponsiveness. Multivariate logistic regression analysis was used to evaluate the risk factors for platelet hyperresponsiveness in patients with ischemic stroke, and multiple linear regression analysis was used to determine the correlation between sleep parameters reflecting the severity of sleep apnea and MAR-AA.@*Results@#Among the 124 patients with ischemic stroke, 58 (46.77%) complicated with OSAHS, 66 (53.23%) without complicated with OSAHS; 84 (67.74%) had platelet hyperresponsiveness, and 40 (32.26%) had not platelet hyperresponsiveness. MAR-AA in the complicated OSAHS group was significantly higher than that in the non-complicated OSAHS group (48.98%±20.61% vs. 26.45%±15.15%; t=-6.858, P<0.001). Multivariate logistic regression analysis showed that OSAHS was an independent risk factor for platelet hyperresponsiveness in patients with ischemic stroke (odds ratio 9.551, 95% confidence interval 3.051-29.905; P<0.001). Multiple linear regression analysis showed that there was a significant linear relationship between apnea hypopnea index and MAR-AA (β=0.499, P<0.001).@*Conclusions@#OSAHS is an independent risk factor for platelet hyperresponsiveness in patients with ischemic stroke. Apnea hypopnea index is significantly correlated with MAR-AA.
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Objective To observe the changes of spleen volume in patients with acute cerebral infarction, and to explore the relationship between the spleen volume and platelet reactivity , inflammatory factors'lymphocyte subsets.Methods This is a case control study.Thirty patients with acute cerebral infarction from January 2017 to June 2017 in Department of Neurology , Weihai Municipal Hospital were included.The spleen volume, arachidonic acid-induced maximum platelet aggregation ratio ( AA-MAR), interferon gamma (IFN-γ) and lymphocyte subsets of patients were monitored in 24 hours of stroke, at 48 hours of stroke, at four days of stroke and at seven days of stroke.Twenty patients without acute cerebral infarction with the same baseline data were selected as the control group , to determine the baseline of spleen volume, AA-MAR, IFN-γand lymphocyte subsets.A t test was used to describe the changes of spleen volume, AA-MAR, IFN-γand lymphocyte subsets at different time points , and Pearson's correlation analysis was used to estimate the relationship between the spleen volume and these variables .Results Compared with the control group ((120.12 ±10.28) cm3), the patients with acute cerebral infarction in 24 hours of stroke ((117.48 ±7.93) cm3) and at 48 hours of stroke ((111.61 ±9.21) cm3) had smaller spleen volume (t＝-2.142, P＜0.05; t＝-2.790, P＜0.01), whereas at four days ((121.31 ±8.16) cm3) and seven days of stroke ((126.11 ±10.31) cm3) had bigger spleen volume (t＝2.242, P＜0.05;t＝2.762, P＜0.01), with the spleen volume decreased first and increased later.Compared with the control group, the patients with acute cerebral infarction had more AA-MAR (control group:20.97%±8.21%;24 h:31.86%±9.54%,t＝3.165,P＜0.01;48 h:41.38%±8.55%,t＝3.254,P＜0.01;4 d:35.34%± 8.15%, t＝3.203,P＜0.01;7 d:29.38% ±10.46%,t＝2.494,P＜0.05) and IFN-γ(pg/L, control group:15.21 ±5.21;24 h:29.75 ±4.57,t＝3.262,P＜0.01;48 h:43.37 ±12.15,t＝3.304,P＜0.01;4 d:40.44 ±9.86, t＝3.291,P＜0.01;7 d:20.93 ±5.51, t＝2.417,P＜0.05) at different time points, with the most AA-MAR at 48 hours of onset, and the most IFN-γat four days of stroke.Compared with the control group, the patients with acute cerebral infarction had more T 4, B lymphocytes and natural killer lymphocytes at the four time points , while the level of T8lymphocytes did not show statistically significant difference even though also increased at the four time points.The correlation analysis results showed that in patients with acute cerebral infarction , the level of AA-MAR (r＝-0.397, P＜0.05; r＝-0.515, P＜0.01; r＝-0.382, P＜0.05) and IFN-γ(r＝-0.408, P＜0.05; r＝-0.479, P＜0.01; r＝-0.378, P＜0.05) was negatively corelated with the spleen volume in 24 hours of onset, at 48 hours of stroke and at four days of stroke; the level of T4, B and natural killer lymphocytes were negatively corelated with the spleen volume in 24 hours of stroke and at 48 hours of stroke.Conclusion After the acute cerebral infarction onset, the spleen volume tends to reduce and then increases , the levels of platelet reactivity , inflammatory factors and lymphocyte subsets are correlated with the spleen volume , and the spleen may aggravate the brain injury by releasing platelets inflammatory factors and lymphocyte subsets.
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Objective To investigate the leukemia incidence among residents in the vicinity area of a nuclear installation.Methods The data were collected by the retrospective survey.Diagnosis is based on the medical records in all the relevant hospitals.The study area was those residential areas within 10 km of radium surrounding the installation.All residents who had lived in the study area for six months and over were recruited into the study group.Results The survey ascertained 643 newly diagnosed leukemia cases in the study area during 1997 to 2007.The crude rate was 2.51/100,000,and its standardized rate to national population structure was 2.53/100,000.The incidence rate in the study area was slightly lower than that in the whole city.No increase trend was detected during the period.Conclusions No significant difference of the leukemia incidence rate was found between the vicinity area of the nuclear installation and the whole city.
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ObjectiveTo test the antifungal activity of berberine (BBR) against Candida albicans in vitro. MethodsAccording to the National Committee for Clinical Laboratory Standards (NCCLS) M27-A protocol, broth microdilution test was performed to assess the susceptibility of 30 clinical isolates of Candida albicans to BBR and fluconazole alone or in combination. ResultsThe geometric mean minimum inhibitory concentration (MIC) was 248.18 mg/L and 2.64 mg/L for BBR and fluconazole alone, respectively. When combined with BBR of 320, 160 and 80 mg/L, the geometric mean MIC decreased to 0.03, 0.35 and 1.35 mg/L respectively for fluconazole. Fluconazole and BBR showed synergistic effects in 26.7％ of these isolates including 3 fluconazoleresistant strains, additive effects in 56.7％, indifferent effects in 16.7％, antagonistic effects in none. Conclu sionIn vitro, BBR has antifungal activity against Candida albicans and can enhance the activity of fluconazole against Candida albicans.
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In this paper is proposed a new method for functional connectivity detection using regression analysis. First, the resting state functional magnetic resonance imaging (fMRI) data from each voxel is passed through a bandpass filter to obtain frequencies between 0.01 Hz and 0.1 Hz. Then, the region of interest (ROI) is defined and the mean time course of all voxels in ROI is used as a regressor. Finally, the linear relationship between the time course of other voxels and the regressor in the resting brain is estimated. By the application of this new method in simulation data and fMRI data, the relevant validity and reliability are demonstrated.
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Humans , Brain , Physiology , Image Processing, Computer-Assisted , Magnetic Resonance Imaging , Methods , Regression Analysis , Signal Processing, Computer-AssistedABSTRACT
Objective: Combining spatial independent component analysis (sICA) with temporal correlation analysis to investigate the functional connectivity of human brain using resting state fMRI. Methods: First, activated area was localized by performing sICA on the data from block design run, then one of the activated brain areas was chosen as a region of interest (ROI)and low frequency correlations between ROI and other regions were calculated in resting state to detect the functional connectivity networks. To validate the method, neural connectivity to primary motor cortex was assessed using this method during a resting state. Results: Functional connectivity network of motor cortex was detected, including primary motor cortex (M1), supplementary motor area (SMA), primary sensory cortex (S1), dorsal premotor cortex (PMd) and posterior parietal somatosensory association area (PSAAp). The connectivity implied by the resting state correlation was far more similar to the connectivity established by non-imaging methods. Conclusion: Functional connectivity of human motor primary cortex was investigated by combining sICA with temporal correlation using resting fMRI data. It provided a simple and noninvasive method for the research of brain functional connectivity.