RESUMO Objetivo Analisar os fatores de risco e prognóstico relacionados à epilepsia pós-traumática precoce (EPTE). Métodos Cento e oitenta e seis pacientes com lesão cerebral traumática foram incluídos. Seus dados clínicos completos foram coletados. A análise fatorial única e a análise de regressão logística dos fatores de risco relacionados à EPTE foram realizadas. O prognóstico dos pacientes foi observado. Resultados A análise fatorial única mostrou que houve diferenças significativas de idade (p = 0,011), história de epilepsia (p < 0,001), local da lesão (p = 0,004), tipo de lesão (p < 0,001) e grau de lesão (p < 0,001) entre o grupo EPTE (40 casos) e o grupo não-EPTE (146 casos), respectivamente. A análise de regressão logística mostrou que o local da lesão, tipo de lesão e grau de lesão foram os principais fatores de risco para EPTE. Os valores de razões de chance do local da lesão, tipo de lesão e grau de lesão foram 1.977 (1.473-2.679), 2.096 (1.543-2.842) e 2.376 (1.864-3.609), respectivamente. A equação de regressão logística foi P = Exp (-1,473 + 0,698 × local de lesão + 0,717 × tipo de lesão + 0,935 × grau de lesão). A sensibilidade e especificidade do local da lesão, tipo de lesão e grau de lesão para a predição da EPTE foram de 79,2% e 80,5%, 78,9% e 85,7% e 84,2% e 81,0%, respectivamente. A análise do prognóstico mostrou que o escore da Escala de Desfechos de Glasgow / Atividade de Vida Diária no grupo EPTE foi significativamente menor do que no grupo não-EPTE (P <0,05). Conclusões O local da lesão, tipo de lesão e grau de lesão são os principais fatores de risco para EPTE. A EPTE pode afetar o prognóstico de pacientes com lesão cerebral traumática.

ABSTRACT Objective To analyze the risk factors and prognosis related to early post-traumatic epilepsy (EPTE). Methods One hundred and eighty-six patients with traumatic brain injury were enrolled. Their full clinical data were collected. Single factor analysis and logistic regression analysis of risk factors related to EPTE were performed. The prognosis of patients was determined. Results Single factor analysis showed that there were significant differences of age (p = 0.011), epilepsy history (p < 0.001), injury site (p = 0.004), injury type (p < 0.001) and injury degree (p < 0.001) between the EPTE group (40 patients) and non-EPTE group (146 patients). Logistic regression analysis showed that the injury site, injury type and injury degree were the main risk factors for EPTE. The odds ratio values of injury site, injury type and injury degree were 1.977 (1.473–2.679), 2.096 (1.543–2.842) and 2.376 (1.864–3.609), respectively. The logistic regression equation was P = Exp (-1.473 + 0.698 × injury site + 0.717 × injury type + 0.935 × injury degree). The sensitivity and specificity of injury site, injury type and injury degree for predicting EPTE were 79.2% and 80.5%, 78.9% and 85.7% and 84.2% and 81.0%, respectively. The analysis of prognosis showed that the Glasgow Outcome Scale/Activity of Daily Living Scale scores in the EPTE group were significantly lower than those in non-EPTE group (p < 0.05). Conclusions Injury site, injury type and injury degree are the main risk factors for EPTE. The prognosis of patients with traumatic brain injury can be affected by EPTE.

Abstract Purpose: To investigate the effect of intermittent vibration at different intervals on bone fracture healing and optimize the vibration interval. Methods: Ninety sheep were randomized to receive no treatment (the control group), incision only (the sham control group), internal fixation with or without metatarsal fracture (the internal fixation group), and continuous vibration in addition to internal fixation of metatarsal fracture, or intermittent vibration at 1, 2, 3, 5, 7 and 17-day interval in addition to internal fixation of metatarsal fracture (the vibration group). Vibration was done at frequency F=35 Hz, acceleration a=0.25g, 15 min each time 2 weeks after bone fracture. Bone healing was evaluated by micro-CT scan, bone microstructure and mechanical compression of finite element simulation. Results: Intermittent vibration at 7-day interval significantly improved bone fracture healing grade. However, no significant changes on microstructure parameters and mechanical properties were observed among sheep receiving vibration at different intervals. Conclusions: Clinical healing effects should be the top concern. Quantitative analyses of bone microstructure and of finite element mechanics on the process of fracture healing need to be further investigated.

PURPOSE: To investigate the anticancer activity of ellagic acid (EA) in U251 human glioblastoma cells and its possible molecular mechanism. METHODS: The cells were treated with EA at various concentrations for different time periods. Cell viability and cell proliferation were detected by cell counting kit-8(CCK-8) assay and live/dead assay respectively. Cell apoptosis were measured with Annexin V-FITC/PI double staining method by flow cytometry and Mitochondrial membrane potential assay separately. Cell cycle was measured with PI staining method by flow cytometry. The expressions of Bcl-2, Survivin, XIAP, Caspase-3, Bax, JNK, p-JNK, ERK1/2, p-ERK1/2, p38, p-p38, DR4, DR5, CHOP and GRP78-related proteins were detected by western blot after EA treatment. RESULTS: Cell viability and proliferation of glioblastoma cells treated with EA were significantly lower than the control group. EA caused robust apoptosis of the glioblastoma cells compared to the control group. EA significantly decreased the proportion at G0/G1 phases of cell cycling accompanied by increased populations at S phase in U251 cell lines. And the expressions of anti-apoptotic proteins were dramatically down-regulated. CONCLUSION: Ellagic acid potentially up-regulated DR4, DR5 and MAP kinases (JNK, ERK1/2 and p38). EA also caused significant increase in the expressions of CHOP and GRP78. Our findings suggest that EA would be beneficial for the treatment of glioblastoma.