Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.

Objective:To explore the diagnostic value of serum solute carrier family 7 member 11 (SLC7A11), urinary retinol-binding protein (RBP) and transferrin (TRF) for acute kidney injury (AKI) in patients with sepsis.Methods:The clinical data of 204 patients with sepsis from January 2020 to December 2023 in the Second Affiliated Hospital of Xi′an Medical College were retrospectively analyzed. Among them, 102 patients complicated with AKI (AKI group), including Kidney Disease: Improving Global Outcomes (KDIGO) classification Ⅰ stage 43 cases, Ⅱ stage 36 cases, Ⅲ stage 23 cases; 102 patients did not complicate with AKI (non-AKI group). Additionally, 102 healthy individuals from the same period were selected as a healthy control group. Enzyme-linked immunosorbent assay was used to detect the serum expression level of SLC7A11, and fully automatic biochemical analyzers were used to detect urinary RBP and TRF levels. For patients in AKI group and non-AKI group, the sequential organ failure assessment (SOFA) was recorded; fully automatic analyzers were used to test hematological indicators, including creatinine, hemoglobin, platelet, albumin, uric acid, lactate, procalcitonin and C-reactive protein, and estimated glomerular filtration rate (eGFR) was calculated. Multivariate Logistic regression analysis was used to analyze the independent risk factors of AKI in patients with sepsis. Receiver operating characteristic (ROC) curve was plotted to analyze the values of serum SLC7A11 and urinary RBP, TRF in assessing the risk of AKI in patients with sepsis.Results:The serum SLC7A11 and urinary RBP, TRF in non-AKI group and AKI group were significantly higher than those in healthy control group: (28.66 ± 6.22) and (36.18 ± 7.29) ng/L vs. (14.32 ± 2.63) ng/L, (1.20 ± 0.25) and (1.47 ± 0.31) mg/L vs. (0.44 ± 0.08) mg/L, (1.82 ± 0.39) and (2.26 ± 0.45) mg/L vs. (1.08 ± 0.19) mg/L, furthermore the indexes in AKI group were significantly higher than those in non-AKI group, and there were statistical differences ( P<0.05). The serum SLC7A11 and urinary RBP, TRF in patients with KDIGO Ⅱ stage and Ⅲ stage were significantly higher than those in patients with KDIGO Ⅰ stage: (37.16 ± 7.41) and (45.20 ± 8.29) ng/L vs. (30.53 ± 6.46) ng/L, (1.50 ± 0.28) and (1.72 ± 0.35) mg/L vs. (1.31 ± 0.26) mg/L, (2.26 ± 0.46) and (2.77 ± 0.59) mg/L vs. (1.99 ± 0.40) mg/L, furthermore the indexes in patients with KDIGO Ⅲ stage were significantly higher than those in patients with KDIGO Ⅱ stage, and there were statistical differences ( P<0.05). The SOFA, creatinine and lactate in AKI group were significantly higher than those in non-AKI group: 12 (9, 15) scores vs. 7 (5, 9) scores, (133.71 ± 13.58) μmol/L vs. (108.18 ± 14.32) μmol/L and (13.61 ± 3.57) mmol/L vs. (10.95 ± 3.10) mmol/L, the albumin and eGFR were significantly lower than those in non-AKI group: (21.48 ± 2.48) g/L vs. (24.85 ± 2.83) g/L and (51.57 ± 9.64) ml/(min·1.73 m 2) vs. (59.21 ± 10.67) ml/(min·1.73 m 2), and there were statistical differences ( P<0.01); there were no statistical differences in hemoglobin, platelet, uric acid, procalcitonin and C-reactive protein between two groups ( P>0.05). Multivariate Logistic regression analysis result showed that the high SOFA, creatinine, lactate, SLC7A11, urinary RBP, urinary TRF, and low eGFR, albumin were independent risk factors for AKI in patients with sepsis ( OR = 4.864, 5.631, 2.315, 5.862, 6.852, 6.218, 0.328 and 0.226; 95% CI 1.701 to 13.907, 1.803 to 17.585, 1.350 to 3.969, 2.115 to 16.242, 2.177 to 21.566, 1.900 to 20.353, 0.151 to 0.713 and 0.092 to 0.555; P<0.01). The ROC curve analysis result showed that the area under the curve of the combined assessment of serum SLC7A11 and urinary RBP, TRF for AKI in patients with sepsis was significantly larger than serum SLC7A11 and urinary RBP, TRF alone (0.892 vs. 0.774, 0.765 and 0.755), and there was statistical difference ( Z = 2.97, 3.20 and 3.38; P<0.01). Conclusions:The elevated expression levels of serum SLC7A11 and urinary RBP and TRF in patients with sepsis have a high value for the combined detection and assessment of AKI.

Objective:The influencing factors of intraoperative hypoxemia in patients with benign central airway stenosis were investigated by machine learning algorithm, and the prediction model of hypoxemia was constructed and verified.Methods:A case-control study was used in this study. The clinical data of 650 patients with benign central airway stenosis who who received surgical treatment in the First Affiliated Hospital of PLA Naval Medical University from June 2022 to April 2024 were retrospectively analyzed. And they were divided into a training set ( n=455) and a test set ( n=195) according to 7:3. The training set was used for establishing Logistic regression model and conducting internal verification, and the test set was used for external verification. The least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm were used to select the factors affecting intraoperative hypoxemia in patients with benign central airway stenosis. A Logistic regression prediction model was constructed, and the model was evaluated using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) and calibration curve. Shapley additive interpretation (SHAP) were used to analyze the importance of influencing factors. Results:Among 650 patients, 279 were males and 371 were females, aged (37.86 ± 8.82) years. Nine feature variables were screened by LASSO regression, while 7 feature variables were screened by Boruta algorithm, the intersection of the two was operation time, complications, degree of airway stenosis, thermal ablation therapy, balloon dilation, and airway stent, respectively, based on this, a logistic regression prediction model was constructed.The AUC values of the training set, validation set and test set of the model were 0.928 (95% CI 0.903-0.954), 0.922 (95% CI 0.843-0.995) and 0.919 (95% CI 0.872-0.965), respectively. The calibration curve showed that the predicted results of the model were in good agreement with the actual results, and the DCA curve showed that the model had clinical application value. SHAP analysis showed that the importance of variables affecting intraoperative hypoxemia in benign central airway stenosis patients was ranked as operation time, thermal ablation therapy, degree of airway stenosis, comorbidification, balloon dilation, and airway stent. Conclusions:The Logistic regression prediction model of intraoperative hypoxemia built based on machine learning algorithm has good prediction efficiency, which is helpful to early identification of risk groups and prevention of hypoxemia.

Objective:The influencing factors of intraoperative hypoxemia in patients with benign central airway stenosis were investigated by machine learning algorithm, and the prediction model of hypoxemia was constructed and verified.Methods:A case-control study was used in this study. The clinical data of 650 patients with benign central airway stenosis who who received surgical treatment in the First Affiliated Hospital of PLA Naval Medical University from June 2022 to April 2024 were retrospectively analyzed. And they were divided into a training set ( n=455) and a test set ( n=195) according to 7:3. The training set was used for establishing Logistic regression model and conducting internal verification, and the test set was used for external verification. The least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm were used to select the factors affecting intraoperative hypoxemia in patients with benign central airway stenosis. A Logistic regression prediction model was constructed, and the model was evaluated using area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA) and calibration curve. Shapley additive interpretation (SHAP) were used to analyze the importance of influencing factors. Results:Among 650 patients, 279 were males and 371 were females, aged (37.86 ± 8.82) years. Nine feature variables were screened by LASSO regression, while 7 feature variables were screened by Boruta algorithm, the intersection of the two was operation time, complications, degree of airway stenosis, thermal ablation therapy, balloon dilation, and airway stent, respectively, based on this, a logistic regression prediction model was constructed.The AUC values of the training set, validation set and test set of the model were 0.928 (95% CI 0.903-0.954), 0.922 (95% CI 0.843-0.995) and 0.919 (95% CI 0.872-0.965), respectively. The calibration curve showed that the predicted results of the model were in good agreement with the actual results, and the DCA curve showed that the model had clinical application value. SHAP analysis showed that the importance of variables affecting intraoperative hypoxemia in benign central airway stenosis patients was ranked as operation time, thermal ablation therapy, degree of airway stenosis, comorbidification, balloon dilation, and airway stent. Conclusions:The Logistic regression prediction model of intraoperative hypoxemia built based on machine learning algorithm has good prediction efficiency, which is helpful to early identification of risk groups and prevention of hypoxemia.

Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.

Objective:To explore the diagnostic value of serum solute carrier family 7 member 11 (SLC7A11), urinary retinol-binding protein (RBP) and transferrin (TRF) for acute kidney injury (AKI) in patients with sepsis.Methods:The clinical data of 204 patients with sepsis from January 2020 to December 2023 in the Second Affiliated Hospital of Xi′an Medical College were retrospectively analyzed. Among them, 102 patients complicated with AKI (AKI group), including Kidney Disease: Improving Global Outcomes (KDIGO) classification Ⅰ stage 43 cases, Ⅱ stage 36 cases, Ⅲ stage 23 cases; 102 patients did not complicate with AKI (non-AKI group). Additionally, 102 healthy individuals from the same period were selected as a healthy control group. Enzyme-linked immunosorbent assay was used to detect the serum expression level of SLC7A11, and fully automatic biochemical analyzers were used to detect urinary RBP and TRF levels. For patients in AKI group and non-AKI group, the sequential organ failure assessment (SOFA) was recorded; fully automatic analyzers were used to test hematological indicators, including creatinine, hemoglobin, platelet, albumin, uric acid, lactate, procalcitonin and C-reactive protein, and estimated glomerular filtration rate (eGFR) was calculated. Multivariate Logistic regression analysis was used to analyze the independent risk factors of AKI in patients with sepsis. Receiver operating characteristic (ROC) curve was plotted to analyze the values of serum SLC7A11 and urinary RBP, TRF in assessing the risk of AKI in patients with sepsis.Results:The serum SLC7A11 and urinary RBP, TRF in non-AKI group and AKI group were significantly higher than those in healthy control group: (28.66 ± 6.22) and (36.18 ± 7.29) ng/L vs. (14.32 ± 2.63) ng/L, (1.20 ± 0.25) and (1.47 ± 0.31) mg/L vs. (0.44 ± 0.08) mg/L, (1.82 ± 0.39) and (2.26 ± 0.45) mg/L vs. (1.08 ± 0.19) mg/L, furthermore the indexes in AKI group were significantly higher than those in non-AKI group, and there were statistical differences ( P<0.05). The serum SLC7A11 and urinary RBP, TRF in patients with KDIGO Ⅱ stage and Ⅲ stage were significantly higher than those in patients with KDIGO Ⅰ stage: (37.16 ± 7.41) and (45.20 ± 8.29) ng/L vs. (30.53 ± 6.46) ng/L, (1.50 ± 0.28) and (1.72 ± 0.35) mg/L vs. (1.31 ± 0.26) mg/L, (2.26 ± 0.46) and (2.77 ± 0.59) mg/L vs. (1.99 ± 0.40) mg/L, furthermore the indexes in patients with KDIGO Ⅲ stage were significantly higher than those in patients with KDIGO Ⅱ stage, and there were statistical differences ( P<0.05). The SOFA, creatinine and lactate in AKI group were significantly higher than those in non-AKI group: 12 (9, 15) scores vs. 7 (5, 9) scores, (133.71 ± 13.58) μmol/L vs. (108.18 ± 14.32) μmol/L and (13.61 ± 3.57) mmol/L vs. (10.95 ± 3.10) mmol/L, the albumin and eGFR were significantly lower than those in non-AKI group: (21.48 ± 2.48) g/L vs. (24.85 ± 2.83) g/L and (51.57 ± 9.64) ml/(min·1.73 m 2) vs. (59.21 ± 10.67) ml/(min·1.73 m 2), and there were statistical differences ( P<0.01); there were no statistical differences in hemoglobin, platelet, uric acid, procalcitonin and C-reactive protein between two groups ( P>0.05). Multivariate Logistic regression analysis result showed that the high SOFA, creatinine, lactate, SLC7A11, urinary RBP, urinary TRF, and low eGFR, albumin were independent risk factors for AKI in patients with sepsis ( OR = 4.864, 5.631, 2.315, 5.862, 6.852, 6.218, 0.328 and 0.226; 95% CI 1.701 to 13.907, 1.803 to 17.585, 1.350 to 3.969, 2.115 to 16.242, 2.177 to 21.566, 1.900 to 20.353, 0.151 to 0.713 and 0.092 to 0.555; P<0.01). The ROC curve analysis result showed that the area under the curve of the combined assessment of serum SLC7A11 and urinary RBP, TRF for AKI in patients with sepsis was significantly larger than serum SLC7A11 and urinary RBP, TRF alone (0.892 vs. 0.774, 0.765 and 0.755), and there was statistical difference ( Z = 2.97, 3.20 and 3.38; P<0.01). Conclusions:The elevated expression levels of serum SLC7A11 and urinary RBP and TRF in patients with sepsis have a high value for the combined detection and assessment of AKI.

Objective To investigate the effects and mechanisms of modified Taohong Siwu Decoction on myocardial ischemia-reperfusion injury in rats based on transcriptome sequencing.Methods Totally 15 SPF rats were randomly divided into sham-operation group,model group and modified Taohong Siwu Decoction group,with 5 rats in each group.The modified Taohong Siwu Decoction group was pre-administered with modified Taohong Siwu Decoction by gavage for 5 days,while the sham-operation group and model group were given equal volume of distilled water by gavage,myocardial ischemia-reperfusion injury rat model was established.The cardiac function of the rats was assessed using echocardiography,serum oxidative stress and inflammatory factor contents were detected using reagent kits,TUNEL staining was used to detect myocardial cell apoptosis,transcriptome sequencing was performed on myocardial tissue,and differential expression genes were analyzed using Venn diagram and heatmap.GO and KEGG pathway enrichment analysis were performed on common differentially expressed genes.RT-qPCR was used to validate differentially expressed genes PTX3 and EGR2.Results Compared with the sham-operation group,the EF and FS of the model group rats significantly decreased(P<0.01),the cells apoptosis rate of myocardial tissue and serum LDH,TNF-α,IL-1β and IL-6 contents significantly increased(P<0.01),and SOD activity and IL-10 content significantly decreased(P<0.01).Compared with the model group,the modified Taohong Siwu Decoction group showed a significant increase in EF and FS(P<0.05),while the cell apoptosis rate of myocardial tissue and serum CK-MB,LDH,TNF-α,IL-1β and IL-6 contents significantly decreased(P<0.01),and SOD activity and IL-10 content significantly increased(P<0.01).Transcriptome sequencing revealed 4 227 differentially expressed genes(2 259 upregulated and 1 968 downregulated)between the sham-operation group and the model group,1 933 differentially expressed genes(1 301 upregulated and 632 downregulated)between the sham-operation group and the modified Taohong Siwu Decoction group,and 94 differentially expressed genes(46 upregulated and 48 downregulated)between the model group and the modified Taohong Siwu Decoction group.There were 35 common differential genes in the three groups,and the differential genes were mainly enriched in signaling pathways such as fluid shear stress and atherosclerosis,ubiquitin mediated proteolysis,C-type lectin receptor signaling pathway,sphingolipid signaling pathway,cell cycle,chemokine signaling pathway,lipid and atherosclerosis.RT-qPCR showed that gene expressions of PTX3 and EGR2 in myocardial tissue of the model group were significantly increased than that of the sham-operation group,and the gene expressions of PTX2 and EGR2 of modified Taohong Siwu Decoction group were significantly decreased than that of the model group(P<0.01).Conclusion Modified Taohong Siwu Decoction exhibits a certain protective effect against myocardial ischemia-reperfusion injury in rats,characterized by improvements in rat cardiac function,reduction in cell apoptosis and inflammatory cytokine release,as well as alleviation of oxidative stress levels.The mechanism may be related to the regulation of PTX3 and EGR2 gene expression.

Objective:To investigate the influence of glucose regulatory protein 78 (GRP78) on prognosis and tumor cell proliferation of hepatocellular carcinoma.Methods:The experimental study and retrospective cohort study were conducted. Based on hepatocellular carcinoma tissue chip, in vitro culture of Huh7 and Hep3B hepatoma cells and LO2 normal hepatic cell, and combined with immunohistochemical staining, cell transfection, quantitative real-time polymerase chain reaction (qRT-PCR), Western blot detection, cell proliferation experiments, cell clone formation experiments and high-throughput transcription histological analysis, the GRP78 expression in hepatoma cells was analyzed. Huh7 and Hep3B hepatoma cells being transfected with the GRP78 gene-specific shRNA lentiviruses or the negative control shRNA lentivirus were set as the GRP78 gene-specific shRNA lentivirus group and the negative control shRNA lentivirus group respectively. Observation indicators: (1) GRP78 expression in hepatocellular carcinoma tissue and adjacent tissue and its correlation with the clinicopathological characteristics of hepatocellular carcinoma patients; (2) analysis of factors affecting the prognosis of hepatocellular carcinoma patients; (3) effects of inhibiting of GRP78 expression on the proliferation of hepatoma cells; (4) effects of inhibiting of GRP78 expression on the gene and protein expression of p53, p21, CDK2, CDK4, and CDK6 in hepatoma cells; (5) effects of HA15 on the proliferation and the gene and protein expression of p53, p21, CDK2, CDK4, and CDK6 in hepatoma cells. Measurement data of the normal distribution were expressed as Mean± SD, and comparison of groups was conducted using the t test or ANOVA. Repeated measurement data were analyzed using repeated ANOVA. Count data were expressed as absolute numbers, and comparisons between groups was conducted using the chi-square test. COX proportional hazards regression model was used for univariate and multivariate analysis. The Kaplan-Meier method was used to calculate the survival time and draw survival curve, and the Log-rank test was used for generative analysis. Results:(1) GRP78 expression in hepatocellular carcinoma tissue and adjacent tissue and its correlation with the clinicopathological characteristics of hepatocellular carcinoma patients: results of immunohistochemical staining of hepatocellular carcinoma tissue chip showed that GRP78 was low-expressed in 53 cases and high-expressed in 37 cases of the 90 hepatocellular carcinoma tissues. GRP78 was low-expressed in 84 cases and high-expressed in 6 cases of the 90 paracancerous tissues. There was a significant difference in GRP78 expression between hepatocellular carcinoma tissues and paracancerous tissues ( P<0.05). (2) Analysis of factors affecting the prognosis of hepatocellular carcinoma patients: all 90 patients were followed up for 5 to 56 months, with a median follow-up time of 49 months. The median overall survival time and median disease progression-free survival time were 56 months and 53 months in the 53 hepatocellular carcinoma patients with GRP78 as low-expressed, versus 32 months and 19 months in the 37 hepatocellular carcinoma patients with GRP78 as high-expressed, respec-tively, showing significant differences ( χ2=17.482, 12.097, P<0.05). Results of univariate analysis showed that alanine aminotransferase (ALT), tumor pathological grading and GRP78 expression were related factors affecting the 3-year overall survival rate and disease progression-free survival rate of hepatocellular carcinoma patients ( hazard ratio=2.317, 2.039, 3.740 and 2.194, 2.177, 2.927, 95% confidence interval as 1.150?4.671, 1.201?3.462, 2.116?6.612 and 1.048?4.593, 1.093?4.336, 1.492?5.742, P<0.05). Results of multivariate analysis showed that ALT >40 U/L, tumor pathological grading as Ⅲ-Ⅳ grade and GRP78 as high-expressed were independent risk factors affecting the 3-year overall survival rate and disease progression-free survival rate of hepatocellular carcinoma patients ( hazard ratio=2.438, 2.245, 3.223 and 3.046, 2.473, 3.307, 95% confidence interval as 1.114?5.334, 1.047?4.814, 1.396?7.440 and 1.337?6.940, 1.141?5.360, 1.399?7.819, P<0.05). (3) Effects of inhibiting of GRP78 expression on the proliferation of hepatoma cells: ①results of qRT-PCR showed that the relative expression of GRP78 messenger RNA (mRNA) in Huh7, Hep3B, and LO2 cells were 3.06±0.33, 4.42±0.60 and 1.00±0.02. There were significant differences in GRP78 mRNA expression between Huh7 and LO2 cells or Hep3B and LO2 cells ( t=6.19, 5.42, P<0.05). ②Results of Western Blot detection showed that the relative expression of GRP78 protein in Huh7, Hep3B, and LO2 cells were 1.65±0.01, 1.77±0.01 and 0.99±0.02. There were significant differences in GRP78 protein expression between Huh7 and LO2 cells or Hep3B and LO2 cells ( t=75.09, 108.10, P<0.05). ③Results of cell proliferation experiments showed that the growth rates in Hu7 GRP78 gene-specific shRNA lentiviruses group cells and Hu7 negative control shRNA lentivirus group cells at 24, 48, 72 and 96 hours were 111.51%±0.35%, 144.85%±0.68%, 188.71%±3.62%, 282.51%±5.25% and 190.08%±0.58%, 285.76%±2.69%, 459.51%±4.29%, 597.88%±12.25%, showing signifi-cant differences ( Fgroups=1 360.000, Ftime=668.500, Finteraction=197.600, P<0.05). The growth rates in Hep3B GRP78 gene-specific shRNA lentiviruses group cells and Hep3B negative control shRNA lentivirus group cells at 24, 48, 72 and 96 hours were 124.47%±0.25%, 153.25%±1.25%, 195.45%±3.19%, 282.51%±10.76% and 179.69%±0.33%, 322.67%±2.46%, 486.27%±5.82%, 622.35%±12.58%, showing significant differences ( Fgroups=1 222.000, Ftime=706.200, Finteraction=179.600, P<0.05). ④Results of the cell clone formation experiments showed that the number of cells in Hu7 GRP78 gene-specific shRNA lentiviruses group cells and Hu7 negative control shRNA lentivirus group cells were 125±3 and 435±17, showing a significant difference ( t=17.86, P<0.05). The number of cells in Hep3B GRP78 gene-specific shRNA lentiviruses group cells and Hep3B negative control shRNA lentivirus group cells were 138±3 and 388±7, showing a significant difference ( t=32.29, P<0.05). (4) Effects of inhibiting of GRP78 expression on the gene and protein expression of p53, p21, CDK2, CDK4, and CDK6 in hepatoma cells: results of high-throughput transcription histological analysis showed that the relative expression rates of p53, p21, CDK2, CDK4, and CDK6 were 19%, 334%, 398%, 41% and 49% in the Hu7 GRP78 gene-specific shRNA lentiviruses group cells comparing to the Hu7 negative control shRNA lentivirus group cells. ①Results of qRT-PCR showed that the relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 mRNA were 0.17±0.03, 4.05±0.71, 3.73±0.47, 0.49±0.09, 0.48±0.06, 0.36±0.07 in the Hu7 GRP78 gene-specific shRNA lentiviruses group cells, versus 1.00±0.05, 1.03±0.17, 1.00±0.07, 1.01±0.09, 1.02±0.14, 1.00±0.03 in the Hu7 negative control shRNA lentivirus group cells, showing significant differences ( t=14.62, 4.17, 5.72, 4.26, 3.49, 8.82, P<0.05). The relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 mRNA were 0.11±0.01, 4.28±0.43, 4.19±0.22, 0.44±0.01, 0.25±0.03, 0.68±0.04 in Hep3B GRP78 gene-specific shRNA lentiviruses group cells, versus 1.01±0.09, 1.02±0.15, 1.00±0.06, 1.01±0.09, 1.01±0.08, 1.15±0.02 in Hep3B negative control shRNA lentivirus group cells, showing significant differences ( t=10.19, 7.14, 13.79, 6.37, 9.42, 9.61, P<0.05). ②Results of Western Blot detection showed that the relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 protein were 0.45±0.01, 1.98±0.05, 2.31±0.12, 0.75±0.03, 0.69±0.04, 0.82±0.03 in the Hu7 GRP78 gene-specific shRNA lentiviruses group cells, versus 1.01±0.05, 1.03±0.01, 1.00±0.02, 1.00±0.01, 1.01±0.02, 1.00±0.03 in the Hu7 negative control shRNA lentivirus group cells, showing significant differences ( t=11.07, 14.56, 11.30, 11.29, 10.55, 11.37, P<0.05). The relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 protein were 0.61±0.03, 1.98±0.16, 2.55±0.12, 0.85±0.03, 0.78±0.01, 0.54±0.02 in Hep3B GRP78 gene-specific shRNA lentiviruses group cells, versus 1.00±0.03, 1.05±0.02, 1.05±0.01, 1.05±0.02, 1.00±0.02, 1.00±0.02 in Hep3B negative control shRNA lentivirus group cells, showing significant differences ( t=10.97, 13.40, 12.35, 11.06, 12.45, 13.78, P<0.05). (5) Effects of HA15 on the proliferation and the gene and protein expression of p53, p21, CDK2, CDK4, and CDK6 in hepatoma cells: results of 50% inhibiting concentration (IC50) test of HA15 showed that the IC50 of HA15 for Huh7 and Hep3B cells at 48 hours were 9.98 μmol/L and 13.70 μmol/L. ①Huh7 and Hep3B cells were treated with 9.98 μmol/L and 13.70 μmol/L of HA15. Results of cell proliferation experiments showed that the growth rates at 24, 48, 72, and 96 hours were 112.81%±0.27%, 154.71%±1.45%, 237.66%±16.77%, 294.40%±14.92% in the HA15-Huh7 cells, versus 133.67%±0.49%, 352.93%±2.31%, 557.17%±4.89%, 662.60%±13.31% in the normal Huh7 cells, showing a significant difference ( Fgroups=766.800, Ftime=518.200, Finteraction=133.300, P<0.05). The growth rates at 24, 48, 72, and 96 hours were 121.27%±2.32%, 203.85%±3.18%, 240.80%±3.02%, 286.50%±7.10% in the HA15-Hep3B cells, versus 239.14%±1.02%, 362.00%±5.44%, 539.37%±10.80%, 694.79%±17.13% in the normal Hep3B cells, showing a signifi-cant difference ( Fgroups=594.300, Ftime=317.900, Finteraction=78.600, P<0.05). ②Results of qRT-PCR showed that the relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 mRNA were 0.27±0.05, 3.64±0.28, 4.13±0.41, 0.51±0.07, 0.39±0.03, 0.17±0.02 in the HA15-Huh7 cells, versus 1.02±0.14, 1.00±0.03, 1.00±0.05, 1.01±0.08, 1.01±0.09, 1.03±0.17 in the normal Huh7 cells, showing significant differences ( t=5.00, 9.25, 7.63, 4.73, 6.82, 5.01, P<0.05). The relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 mRNA were 0.28±0.03, 3.49±0.78, 4.31±0.53, 0.38±0.05, 0.36±0.04, 0.24±0.03 in the HA15-Hep3B cells, versus 1.01±0.11, 1.03±0.18, 1.01±0.08, 1.00±0.06, 1.02±0.15, 1.00±0.06 in the normal Hep3B cells, showing significant differences ( t=6.26, 3.08, 6.21, 7.97, 4.26, 11.08, P<0.05). ③Results of Western Blot detection showed that the relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 protein were 0.52±0.05, 1.94±0.08, 1.58±0.02, 0.89±0.00, 0.86±0.02, 0.74±0.01 in the HA15-Huh7 cells, versus 1.02±0.03, 1.00±0.03, 1.02±0.02, 1.04±0.03, 1.00±0.01, 1.01±0.02 in the normal Huh7 cells, showing significant differences ( t=11.54, 10.28, 11.03, 12.81, 13.67, 10.09, P<0.05). The relative expression of GRP78, p53, p21, CDK2, CDK4, and CDK6 protein were 0.57±0.02, 1.67±0.04, 1.41±0.04, 0.82±0.03, 0.70±0.02, 0.74±0.01 in the HA15-Hep3B cells, versus 1.03±0.01, 0.98±0.03, 1.00±0.03, 1.03±0.03, 1.01±0.01, 1.04±0.01 in the normal Huh7 cells, showing significant differences ( t=10.81, 11.54, 12.26, 13.62, 14.23, 10.17, P<0.05). Conclusions:High expression of GRP78 is an independent risk factor affecting the overall survival and disease progression-free survival of hepatocellular carcinoma patients. Inhibiting of GRP78 expression can reduce cell proliferation and the expression of p53, p21, CDK2, CDK4, and CDK6 mRNA and proteins in hepatoma cells.

Objective The article is to study on the detection of α-helix proteins in post-traumatic epileptogenic focus by FTIR-mapping. Methods Fourier transform infrared spectroscopy-mapping were applied to identifying α-helix by point-by-point scanning in post-traumatic epileptogenic focus sections and to develop FTIR-mapping profiles. Result The high absorbance of α-helix is accord with post-traumatic epilepsy, there are some significant differences between high absorbance and low absorbance. Conclusion α-helix proteins are distributed in post-traumatic epileptogenic focus widely, thus α-helix protein are involved in post-traumatic epilepsy.

Objective To investigate the relationship between Ct value of mice liver and postmortem interval (PMI) under various ambient temperatures. Methods mice were stored at 10℃, 15℃, 20℃, 25℃ and 30℃ after execution, and total RNA was extracted from mice liver every 6 hours (PMI 6h to 72h). The levels of 18s rRNA were examined using real-time PCR. The results were expressed by cycle threshold (Ct) value to explore relationship between PMI and Ct value, and the interpolation functions were established to estimate PMI. Results In each group, Ct value increased with PMI increased. Surface equation was obtained after interpolation analysis on temperature range 10℃~30℃. The three-variable quintic surface equation was f(x, y)=-426.9+30.82x+44.48y-1.297x2-1.837xy-1.388y2+0.034 38x3+0.038 17x2y+0.038 67xy2+0.028 77y3-0.000 612 9x4-3.897e-7x3y-0.001 223x2y2+0.000 256 6xy3-0.000 537 4y4+3.606e-6x5-2.846e-6x4y+1.009e-5x3y2-3.439e-6x2y3-2.556e-7xy4+2.664e-6y5(r2=0.999 4). Conclusion The rule of Ct value changes at ambient temperature complied with three-variable quintic surface equation distribution. Measurement of interpolation function may be used for PMI estimation at ambient temperature.