Purpose To detect the distribution of cerebral microbleeds (CMB) in patients with hypertension and evaluate its related risk factors in order to reduce long-term risk of cerebral hemorrhage in large areas. Materials and Methods A consecutive 110 patients of hypertension and 50 patients of non-hypertension in the departments of cardiovascular medicine and neurology were enrolled. All the patients underwent T2 star weighted angiography (SWAN) sequence scan of head. The location and quantity of CMB and other related information of patients were recorded. The distribution of CMB in patients with hypertension and correlation between CMB and age, sex, level of hypertension, duration of time, hemoglobin, platelets, smoking, diabetes, hyperlipidemia were also analyzed. Results A total of 472 CMB were detected in the hypertension group, of which 212 CMB (44.9%) were found in deep brain, 149 (31.6%) were in cortical and subcortical region, 111 (23.5%) under the tentorium. The highest distribution of CMB was in thalamus (98, 20.8%), followed by basal ganglia (78, 16.5%), temporal lobe (64, 13.6%) and brainstem (62, 13.1%). The univariate analysis showed that CMB group had significantly higher rate of hypertension and diabetes than that without CMB and the average age in CMB group was also higher (P<0.05). The results of multivariate analysis showed that age and hypertension were independent risk factors for CMB. In hypertension group, there was statistically significant difference in the incidence of CMB between patients aged 45 and older and those aged under 45 (P<0.05);the differences were significant between the patients with hypertension duration time less than 5 years, those with hypertension duration time 5 to 10 years and those over 10 years (P<0.05);the differences also existed between the patients with hypertension at class I and those patients with hypertension at class II and III (P<0.05). The quantity of CMB in patients with hypertension was correlated with duration time (P<0.05), but not correlated with age and the severity of hypertension (P>0.05). Conclusion Hypertension and age are independent risk factors for CMB. Patients aged 45 and older, with more than 5 years duration of hypertension, or with hypertension at class II and III, should be paid more attention in clinic. If necessary, magnetic resonance examination is suggested to be used, in order to reduce long-term risk of cerebral hemorrhage.

Aim To establish the rat model of Spleen-Qi deficiency, analyse the metabolic pathways and investigate the connection between the changed urinary metabolites and Spleen-Qi deficiency, in order to explore the potential mechanisms of Spleen-Qi deficiency.Methods With the binding methods of diarrhea induced by bitter and cold, abnormal of starvation and excessive tiredness, the rat Spleen-Qi deficiency model was established.Then the activity of creatine phosphokinase(CPK) was detected.The endogenous metabolites in the urine were detected by NMR, and the data were analyzed with multivariate and statistical methods.Then the metabolites were selected that could be clearly distinct in the two groups with the fold change value(>1.2) and the P<0.05 of Student′s t-test.Both the pathway analysis and enrichment analysis were performed with Metabo Analyst 3.0.Results Compared with the normal rats, the activity of CPK decreased significantly in model rats(P<0.05).A significant separation appeared in the principal components analysis(PCA) score plot when the control group and the model group were compared, indicating that the Spleen-Qi deficiency model was successfully duplicated.The 33 differential metabolites, which mainly involved in the metabolic pathways, were distinguished from the comparision of Spleen-Qi deficiency model group and control group.The metabolic pathways was related to energy metabolism, amino acid metabolism, nucleotide metabolism and disturbance of gut microbes.Conclusions The main energy metabolic pathways (tricarboxylic acid cycle, glycolysis and liquid oxidation) may be disturbed in Spleen-Qi deficiency rats.The energy supply function is suppressed, which leads to the fatigue and weight loss in rats.