Exploring the variability of the intestinal flora of patients with hepatic blastocysticercosis and searching for members of the intestinal microflora that may play a role in the disease process by means of macro-genome sequencing technology. A case-control study was used to include fecal samples from patients with hepatic vesicular schistosomiasis admitted to Qinghai Provincial People′s Hospital between October 2023 and January 2024 and individuals attending health checkups. The experimental group (AE group) consisted of 10 patients with liver vesicular schistosomiasis and the control group (NC group) consisted of 9 individuals attending health checkups. Macrogenomic sequencing was performed on these two groups of samples using the Illumina Novaseq 6000 sequencing platform, using fastp (v0.20.1) to remove junctions, and bbmap (v38.93-0) to remove the hosted sequences, followed by sequence splicing using MEGAHIT (v1.2.9), and then using prodigal (v2.6.3) to The spliced scaffold was subjected to ORF prediction and translated into amino acid sequences, followed by the construction of a non-redundant gene set using MMSeqs2 (v13.45111), and finally compared with the non-redundant gene set using salmon (v1.8.0). Species were annotated by the non-redundant database, species abundance was calculated in each sample, and the two sets were tested using Wilcoxon rank sum test. Finally, the differences in intestinal flora between the two groups were statistically analyzed using linear discriminant analysis, and the correlation between the differential intestinal flora and clinical indicators was analyzed using redundancy analysis (RDA). The results showed that the effective data volume of each sample was distributed from 10.41 to 12.46 G. The number of ORFs in the de-redundantly constructed gene catalogue (non-redundant gene set) was 4 951 408, and the annotation rate of the non-redundant genes was 97.97% when compared with the NR database. The ages of the study subjects in the two groups were (44.78±4.58) years in the NC group and (42.90±10.44) years in the AE group, and the difference was not statistically significant ( t=0.530, P=0.476). The two groups were matched for body mass index (BMI) ( t=2.368, P=0.142), gender ( χ2=0.200, P=0.655), and dietary habits. There was no statistically significant difference in alpha diversity in the AE group (ACE index, t=0.942; chao1 index, t=0.947; shannon index, t=0.813, the simpson′s index, t=0.613, P>0.05), while beta diversity analysis showed significant differences in the overall structure of the two communities (Stress=0.054 5). A total of 120 species were annotated at the phylum level, of which two differed. While 1 736 species were annotated at the genus level, 69 were different, and 309 were different at the species level. The AE group ranked the top 6 in terms of abundance of Anaplasma, Escherichiaceae, Clostridium, Alternaria, Ruminalia, and Treponema spp. at the genus level; whereas, Segatella, Prevotella, E. faecalis, Rossella, and beneficial rod-shaped bacteria were more abundant in the NC group. There were differences in the abundance and diversity of intestinal flora between the two groups, and the structure of community composition was significantly different. Statistical results by linear discriminant analysis (LDA) showed that LDA scores >2 in the NC group included beneficial bacillus spp. and E. faecalis spp. in young infants, etc. LDA scores >2 in the AE group at the mid-species level included Clostridium polterococcus, unknown microorganisms in the genus Clostridium intestinalis, Hathaway′s Henkett′s bacillus, and Clostridium oryzae in the genus Clostridium refractory to culture and small Clostridium spp. in the AE group. Clostridium intestinalis. The RDA results showed a negative correlation between beneficial rod genera and liver function indices, and a positive correlation between Clostridium intestinalis genera and liver function indices. In conclusion, patients with hepatic blastomycosis have altered intestinal flora abundance and diversity, with significant structural changes in community composition and differences in several genera, including Mycobacterium anisopliae and Clostridium intestinalis, and imbalances in the intestinal flora may affect hepatic function by influencing intestinal metabolites and may have an impact on the development of hepatic blastomycosis, a finding that warrants further in-depth study.

Objective:To construct a prediction model for postoperative poor in-hospital prognosis in patients with traumatic brain injury (TBI) and evaluate its predictive performance.Methods:A retrospective case control study was conducted to analyze the clinical data of 1 120 TBI patients admitted to Changde Hospital Affiliated to Xiangya Medical College of Central South University from May 2019 to December 2024. The patients were divided into the training set ( n=784) and verification set ( n=336) at a ratio of 7∶3. Based on the Glasgow outcome scale-extended (GOS-E) at discharge, the training set was stratified into favorable prognosis group ( n=335, GOS-E 5-8 points) and poor prognosis group ( n=449, GOS-E 1-4 points). The two groups in the training set were compared in terms of general baseline indicators, TBI-related clinical indicators, and admission laboratory blood test results. Univariate analysis and Lasso regression analysis were employed to screen risk factors associated with postoperative poor in-hospital prognosis in TBI patients. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a regression equation. The regression equation was presented using R language to create a visual nomogram for predicting postoperative poor in-hospital prognosis in TBI patients. In both the training set and verification set, the predictive performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC), plotting calibration curves, and performing decision curve analysis (DCA). Results:The results of the univariate analysis indicated that the age, Charlson complication index (CCI), time from trauma to admission, time from trauma to operation, cause of injury, abbreviated injury scale (AIS) (head and neck), injury severity score (ISS), admission Glasgow coma scale (GCS), admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraventricular hemorrhage, subarachnoid hemorrhage, decompressive craniotomy, intraoperative blood loss, intraoperative blood transfusion, traumatic cerebral infarction, postoperative delayed bleeding, epilepsy seizures, as well as the following admission tested results including red blood cell count, white blood cell count, platelet count, neutrophil percentage, percentage of lymphocytes, albumin, total bilirubin, urea nitrogen, thrombin time (TT), prothrombin time (PT), international standardized ratio (INR), glutamic aminotransferase, alanine aminotransferase, creatinine, and blood glucose were statistically different between the two groups in the training set ( P<0.05). Lasso regression analysis suggested 14 risk factors of age, CCI, cause of injury, head and neck AIS, ISS, admission GCS, admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraoperative blood loss, admission platelet count, admission albumin, admission blood glucose for postoperative poor in-hospital prognosis. The results of the multivariate Logistic regression analysis showed that age ( OR=1.02, 95% CI 1.00, 1.03, P<0.01), CCI ( OR=1.46, 95% CI 1.02, 2.09, P<0.05), head and neck AIS ( OR=1.43, 95% CI 1.11, 1.85, P<0.01), ISS ( OR=2.16, 95% CI 1.39, 3.35, P<0.01), admission GCS ( OR=1.59, 95% CI 1.19, 2.13, P<0.01), intracerebral hematoma ( OR=4.41, 95% CI 2.15, 9.44, P<0.01), intraoperative blood loss ( OR=1.05, 95% CI 1.00, 1.09, P<0.05), admission platelet count ( OR=0.98, 95% CI 0.97, 0.99, P<0.01), admission blood glucose ( OR=1.08, 95% CI 1.02, 1.15, P<0.05) could be the main risk factors to construct a prediction model for postoperative poor in-hospital prognosis in TBI patients. Meanwhile, a regression equation was constructed: Logit[ P/(1- P)]=-2.4+ 0.02×"age"+0.38×"CCI"+0.36×"head and neck AIS"+0.77×"ISS"+0.47×"admission GCS"+1.48×"intracerebral hematoma"+0.05×intraoperative blood loss-0.02×admission platelet count+0.08×admission blood glucose. In the training set, the predictive model for poor postoperative in-hospital prognosis in TBI patients achieved an AUC of 0.87 (95% CI 0.84, 0.89), with a Youden′s index of 0.57, sensitivity of 73.70%, and specificity of 83.00%. In the verification set, the model showed an AUC of 0.80 (95% CI 0.76, 0.85), with a Youden′s index of 0.63, sensitivity of 65.20%, and specificity of 77.90%. In the training set, the Brier score for the calibration curve was 0.14 (95% CI 0.13, 0.16). In the verification set, the Brier score for the calibration curve was 0.18 (95% CI 0.15, 0.20). The DCA diagram indicated that the nomogram prediction model provided high clinical net benefit for predicting postoperative poor in-hospital prognosis in TBI patients. Conclusion:The prediction model for postoperative poor in-hospital prognosis in TBI patients, constructed based on age, CCI, head and neck AIS, ISS, admission GCS, intracerebral hematoma, intraoperative blood loss, admission platelet count, and admission blood glucose, exhibits good predictive performance.

Objective:To investigate the in vitro bacteriostatic effect of ethyl alcohol extract of Moutan Cortex (EAEMC) on Candida tropicalis and its effect on virulence factors, including aspartic protease, hemolysin, phospholipase, esterase, lipase activities and biofilm. Methods:EAEMC powder was obtained by ultrasonic extraction, decompression concentration and lyophilization; the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of EAEMC on 21 clinical strains and one standard strain of Candida tropicalis were determined by microdilution. Five extracellular enzyme activities of Candida tropicalis and the effect of EAEMC on them were detected by the plate assay, and the results were analyzed by ANOVA. The biofilm model of Candida tropicalis was constructed in vitro, and the inhibition rate of EAEMC on Candida tropicalis biofilm was evaluated using the thiazolyl blue (MTT) method. Results:The MIC of EAEMC against Candida tropicalis BNCC335988 was 12.5 g/L and the MBC value was 25 g/L, while for the clinical strains, the MIC was 12.5-25 g/L and the MBC was 25-50 g/L. Aspartic protease, esterase and hemolytic activities of Candida tropicalis were positive, but phospholipase and lipase showed negative activities. At a concentration of 1/2 MIC of EAEMC, the aspartic protease and hemolytic activities of Candida tropicalis were completely inhibited the aspartic protease and hemolytic activities of Candida tropicalis were completely inhibited and the esterase activity was completely inhibited at a concentration of MIC of EAEMC. The inhibition of Candida tropicalis BNCC335988 biofilm by EAEMC reached more than 70% at a concentration of 2MIC, more than 80% at a concentration of 4MIC, and more than 90% at a concentration of 8MIC. Conclusion:EAEMC can achieve bacteriostatic effects by reducing the aspartic protease, esterase and hemolysin activities of Candida tropicalis, as well as inhibiting biofilm formation.

Exploring the variability of the intestinal flora of patients with hepatic blastocysticercosis and searching for members of the intestinal microflora that may play a role in the disease process by means of macro-genome sequencing technology. A case-control study was used to include fecal samples from patients with hepatic vesicular schistosomiasis admitted to Qinghai Provincial People′s Hospital between October 2023 and January 2024 and individuals attending health checkups. The experimental group (AE group) consisted of 10 patients with liver vesicular schistosomiasis and the control group (NC group) consisted of 9 individuals attending health checkups. Macrogenomic sequencing was performed on these two groups of samples using the Illumina Novaseq 6000 sequencing platform, using fastp (v0.20.1) to remove junctions, and bbmap (v38.93-0) to remove the hosted sequences, followed by sequence splicing using MEGAHIT (v1.2.9), and then using prodigal (v2.6.3) to The spliced scaffold was subjected to ORF prediction and translated into amino acid sequences, followed by the construction of a non-redundant gene set using MMSeqs2 (v13.45111), and finally compared with the non-redundant gene set using salmon (v1.8.0). Species were annotated by the non-redundant database, species abundance was calculated in each sample, and the two sets were tested using Wilcoxon rank sum test. Finally, the differences in intestinal flora between the two groups were statistically analyzed using linear discriminant analysis, and the correlation between the differential intestinal flora and clinical indicators was analyzed using redundancy analysis (RDA). The results showed that the effective data volume of each sample was distributed from 10.41 to 12.46 G. The number of ORFs in the de-redundantly constructed gene catalogue (non-redundant gene set) was 4 951 408, and the annotation rate of the non-redundant genes was 97.97% when compared with the NR database. The ages of the study subjects in the two groups were (44.78±4.58) years in the NC group and (42.90±10.44) years in the AE group, and the difference was not statistically significant ( t=0.530, P=0.476). The two groups were matched for body mass index (BMI) ( t=2.368, P=0.142), gender ( χ2=0.200, P=0.655), and dietary habits. There was no statistically significant difference in alpha diversity in the AE group (ACE index, t=0.942; chao1 index, t=0.947; shannon index, t=0.813, the simpson′s index, t=0.613, P>0.05), while beta diversity analysis showed significant differences in the overall structure of the two communities (Stress=0.054 5). A total of 120 species were annotated at the phylum level, of which two differed. While 1 736 species were annotated at the genus level, 69 were different, and 309 were different at the species level. The AE group ranked the top 6 in terms of abundance of Anaplasma, Escherichiaceae, Clostridium, Alternaria, Ruminalia, and Treponema spp. at the genus level; whereas, Segatella, Prevotella, E. faecalis, Rossella, and beneficial rod-shaped bacteria were more abundant in the NC group. There were differences in the abundance and diversity of intestinal flora between the two groups, and the structure of community composition was significantly different. Statistical results by linear discriminant analysis (LDA) showed that LDA scores >2 in the NC group included beneficial bacillus spp. and E. faecalis spp. in young infants, etc. LDA scores >2 in the AE group at the mid-species level included Clostridium polterococcus, unknown microorganisms in the genus Clostridium intestinalis, Hathaway′s Henkett′s bacillus, and Clostridium oryzae in the genus Clostridium refractory to culture and small Clostridium spp. in the AE group. Clostridium intestinalis. The RDA results showed a negative correlation between beneficial rod genera and liver function indices, and a positive correlation between Clostridium intestinalis genera and liver function indices. In conclusion, patients with hepatic blastomycosis have altered intestinal flora abundance and diversity, with significant structural changes in community composition and differences in several genera, including Mycobacterium anisopliae and Clostridium intestinalis, and imbalances in the intestinal flora may affect hepatic function by influencing intestinal metabolites and may have an impact on the development of hepatic blastomycosis, a finding that warrants further in-depth study.

Objective:To construct a prediction model for postoperative poor in-hospital prognosis in patients with traumatic brain injury (TBI) and evaluate its predictive performance.Methods:A retrospective case control study was conducted to analyze the clinical data of 1 120 TBI patients admitted to Changde Hospital Affiliated to Xiangya Medical College of Central South University from May 2019 to December 2024. The patients were divided into the training set ( n=784) and verification set ( n=336) at a ratio of 7∶3. Based on the Glasgow outcome scale-extended (GOS-E) at discharge, the training set was stratified into favorable prognosis group ( n=335, GOS-E 5-8 points) and poor prognosis group ( n=449, GOS-E 1-4 points). The two groups in the training set were compared in terms of general baseline indicators, TBI-related clinical indicators, and admission laboratory blood test results. Univariate analysis and Lasso regression analysis were employed to screen risk factors associated with postoperative poor in-hospital prognosis in TBI patients. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a regression equation. The regression equation was presented using R language to create a visual nomogram for predicting postoperative poor in-hospital prognosis in TBI patients. In both the training set and verification set, the predictive performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC), plotting calibration curves, and performing decision curve analysis (DCA). Results:The results of the univariate analysis indicated that the age, Charlson complication index (CCI), time from trauma to admission, time from trauma to operation, cause of injury, abbreviated injury scale (AIS) (head and neck), injury severity score (ISS), admission Glasgow coma scale (GCS), admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraventricular hemorrhage, subarachnoid hemorrhage, decompressive craniotomy, intraoperative blood loss, intraoperative blood transfusion, traumatic cerebral infarction, postoperative delayed bleeding, epilepsy seizures, as well as the following admission tested results including red blood cell count, white blood cell count, platelet count, neutrophil percentage, percentage of lymphocytes, albumin, total bilirubin, urea nitrogen, thrombin time (TT), prothrombin time (PT), international standardized ratio (INR), glutamic aminotransferase, alanine aminotransferase, creatinine, and blood glucose were statistically different between the two groups in the training set ( P<0.05). Lasso regression analysis suggested 14 risk factors of age, CCI, cause of injury, head and neck AIS, ISS, admission GCS, admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraoperative blood loss, admission platelet count, admission albumin, admission blood glucose for postoperative poor in-hospital prognosis. The results of the multivariate Logistic regression analysis showed that age ( OR=1.02, 95% CI 1.00, 1.03, P<0.01), CCI ( OR=1.46, 95% CI 1.02, 2.09, P<0.05), head and neck AIS ( OR=1.43, 95% CI 1.11, 1.85, P<0.01), ISS ( OR=2.16, 95% CI 1.39, 3.35, P<0.01), admission GCS ( OR=1.59, 95% CI 1.19, 2.13, P<0.01), intracerebral hematoma ( OR=4.41, 95% CI 2.15, 9.44, P<0.01), intraoperative blood loss ( OR=1.05, 95% CI 1.00, 1.09, P<0.05), admission platelet count ( OR=0.98, 95% CI 0.97, 0.99, P<0.01), admission blood glucose ( OR=1.08, 95% CI 1.02, 1.15, P<0.05) could be the main risk factors to construct a prediction model for postoperative poor in-hospital prognosis in TBI patients. Meanwhile, a regression equation was constructed: Logit[ P/(1- P)]=-2.4+ 0.02×"age"+0.38×"CCI"+0.36×"head and neck AIS"+0.77×"ISS"+0.47×"admission GCS"+1.48×"intracerebral hematoma"+0.05×intraoperative blood loss-0.02×admission platelet count+0.08×admission blood glucose. In the training set, the predictive model for poor postoperative in-hospital prognosis in TBI patients achieved an AUC of 0.87 (95% CI 0.84, 0.89), with a Youden′s index of 0.57, sensitivity of 73.70%, and specificity of 83.00%. In the verification set, the model showed an AUC of 0.80 (95% CI 0.76, 0.85), with a Youden′s index of 0.63, sensitivity of 65.20%, and specificity of 77.90%. In the training set, the Brier score for the calibration curve was 0.14 (95% CI 0.13, 0.16). In the verification set, the Brier score for the calibration curve was 0.18 (95% CI 0.15, 0.20). The DCA diagram indicated that the nomogram prediction model provided high clinical net benefit for predicting postoperative poor in-hospital prognosis in TBI patients. Conclusion:The prediction model for postoperative poor in-hospital prognosis in TBI patients, constructed based on age, CCI, head and neck AIS, ISS, admission GCS, intracerebral hematoma, intraoperative blood loss, admission platelet count, and admission blood glucose, exhibits good predictive performance.

Objective:To investigate the in vitro bacteriostatic effect of ethyl alcohol extract of Moutan Cortex (EAEMC) on Candida tropicalis and its effect on virulence factors, including aspartic protease, hemolysin, phospholipase, esterase, lipase activities and biofilm. Methods:EAEMC powder was obtained by ultrasonic extraction, decompression concentration and lyophilization; the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of EAEMC on 21 clinical strains and one standard strain of Candida tropicalis were determined by microdilution. Five extracellular enzyme activities of Candida tropicalis and the effect of EAEMC on them were detected by the plate assay, and the results were analyzed by ANOVA. The biofilm model of Candida tropicalis was constructed in vitro, and the inhibition rate of EAEMC on Candida tropicalis biofilm was evaluated using the thiazolyl blue (MTT) method. Results:The MIC of EAEMC against Candida tropicalis BNCC335988 was 12.5 g/L and the MBC value was 25 g/L, while for the clinical strains, the MIC was 12.5-25 g/L and the MBC was 25-50 g/L. Aspartic protease, esterase and hemolytic activities of Candida tropicalis were positive, but phospholipase and lipase showed negative activities. At a concentration of 1/2 MIC of EAEMC, the aspartic protease and hemolytic activities of Candida tropicalis were completely inhibited the aspartic protease and hemolytic activities of Candida tropicalis were completely inhibited and the esterase activity was completely inhibited at a concentration of MIC of EAEMC. The inhibition of Candida tropicalis BNCC335988 biofilm by EAEMC reached more than 70% at a concentration of 2MIC, more than 80% at a concentration of 4MIC, and more than 90% at a concentration of 8MIC. Conclusion:EAEMC can achieve bacteriostatic effects by reducing the aspartic protease, esterase and hemolysin activities of Candida tropicalis, as well as inhibiting biofilm formation.

ObjectiveTo obtain HSC-T6 cells with stable expression of Cas9 protein and HSC-T6-COX-2-/- cells with COX-2 gene defect by transfecting HSC-T6 cells with CRISPR/Cas9 lentiviral vector, and to provide a good method for further functional research and new strategies for the clinical treatment of liver fibrosis. MethodsThe COX-2 gene-specific sgRNAs (COX-2-sgRNA-1, COX-2-sgRNA-2, COX-2-sgRNA-3) were designed, synthesized, and connected to the GV371 vector, and the recombinant plasmid and the packaging plasmid were transfected into 293T cells to form lentivirus particles; the fluorescence method was used to measure virus titer. The most appropriate amount of the virus was calculated based on MOI. Lenti-Cas9-puro was transfected into HSC-T6 cells, and HSC-T6-Cas9 cells were screened out by puromycin; Lenti-COX-2-sgRNA-EGFP was transfected into HSC-T6-Cas9 cells to obtain HSC-T6-COX-2-/- cells. Cruiser enzyme digestion and Western blot were used to verify gene knockout at the gene and protein levels. An analysis of variance was used for comparison of continuous data between multiple groups, and the least significant difference t-test was used for further comparison between two groups. ResultsSequencing verified that the COX-2-sgRNA expression vector was constructed successfully. Recombinant expression plasmids and packaging plasmids were transfected into 293T cells to form lentivirus particles, and the fluorescence method showed a virus titer of ＞1×108. HSC-T6 cells with stable expression of Cas9 protein and HSC-T6-COX-2-/- cells with COX-2 gene defect were successfully constructed. The HSC-T6-Cas9 group had significantly higher relative mRNA expression of LV-Cas9-Puro than the CON group (541.93±105.76 vs 1.00±0.02, t=12.995, P＜0.01). Cruiser enzyme digestion and Western blot showed that the CRISPR/Cas9 lentivirus expression vectors played a role in the target, among which COX-2-sgRNA-2 knockout had the most significant effect, and this group had a significant reduction in the protein expression level of COX-2 compared with the CON group and the NC group (both P＜0.05), suggesting that COX-2-sgRNA was active. ConclusionA CRISPR/Cas9 lentivirus vector is successfully constructed for COX-2 target gene, and HSC-T6-COX-2-/- cells with stable COX-2 gene knockout are obtained.

OBJECTIVE: To investigate the effect of the combination of atrial fibrillation (AF) ablation and left atrial appendage closure (LAAC) on cardiac function and the success rate of AF ablation. METHODS: We retrospectively analyzed the data of 56 patients with AF undergoing a one-stop procedure for AF ablation and LAAC in our hospital between May, 2015 and May, 2019. Propensity score matching (PSM) at the ratio of 1:1 was used to select 56 control patients undergoing AF ablation at high risk of stroke, for matching with the hybrid procedure group. The perioperative complications, thromboembolic events, recurrence of atrial arrhythmia and cardiac function were compared between the groups. RESULTS: The two groups of patients were comparable for age, gender, BMI, duration and type of AF, concomitant diseases, CHA2DS2-VASc and HAS-BLED scores ( CONCLUSIONS The combination of AF ablation and LAAC is safe but does not improve the success rate of AF ablation. The one-stop procedure can improve cardiac function of the patients, but AF ablation alone can achieve better improvement of cardiac function.
Atrial Appendage/surgery* ; Atrial Fibrillation/surgery* ; Catheter Ablation ; Humans ; Retrospective Studies ; Treatment Outcome

Objective To study the radiation-induced mitochondrial damage and energy metabolic alteration in pancreatic exocrine cells,and to explore underlying mechanism.Methods Rat pancreatic exocrine cells (AR42 J) were divided into control group and experimental group irradiated with 6 Gy of X-rays.Mitochondrial membrane potential was detected at 24,48,72 and 96 h,the lactic acid and ATP production were detected at 24 h and 48 h,and reactive oxygen species (ROS) were detected at 24 h after irradiation.The expressions of energy metabolism related factors of HIF-1α,LDHA and PDH were detected by Western blot.The animal experiments were conducted to confirm the changes.According to random number table,eight rats were randomly divided into two groups with 4 rats in each.The irradiated group was exposed to 12 Gy of X-rays,while the control group sham-irradiated.Results Compared with the nonirradiated control group,the mitochondrial membrane potential (△Ψm) of the experimental group was progressively decreased at 24-96 h after irradiation (t =5.438-17.687,P＜0.05).The ATP content in the experimental group decreased at 24 h and 48 h (q=17.300,8.328,P＜0.05),the lactic acid increased (q =21.790,16.250,P＜0.05),and the ROS level increased (t =7.935,P＜0.05).The expressions of HIF-1α and LDHA were significantly increased,but PDH was reduced after radiation.Silencing HIF-1α by siRNA eliminated radiation-induced energy metabolic alteration.These changes were confirmed with animal experiments by locally irradiating rats.Conclusions The expression of HIF-1α is upregulated by irradiation,which leads to the change of energy metabolism as the enhancement of glycolysis pathway and the inhibition of aerobic oxidation of mitochondria in pancreatic exocrine cells.

Objective To investigate the epidemiological characteristics of nosocomial fungal infections in severe sepsis patients and analyze the influencing factors by logistic regression.Methods The clinical data of 578 patients with severe sepsis admitted to our hospital from January 2008 to January 2016 were retrospectively analyzed.The epidemiological characteristics were investigated.The possible influencing factors of nosocomial fungal infection were analyzed by univariate analysis and multivariate logistic regression analysis.Results Among 578 cases of severe sepsis,215 cases were accompanied by nosocomial fungal infection (infection rate 37.20％).The infection sites were mostly lungs and the fungal types were Candida albicans.The prognosis of the patients was poor.The survival time was less than 90 days,accounting for 42.33％ (91/215).There were significant differences in age,length of stay in intensive care unit (ICU),duration of more than two antibiotics,use of ventilators,hormones,invasive procedures,acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score between the infected group and the uninfected group (P ＜ 0.05).The danger degree from high to low of the risk factors were ICU stay ≥ 100 h (OR =5.697),use respirator (OR =5.388),invasive operation (OR =4.987),age ≥65 years (OR =4.584),and continuous use of two antibiotics ＞ 7 d (OR =3.287),use steroid (OR =2.141).Conclusions Severe sepsis with hospital acquired fungal infection is more common in the lung,and most of them are Candida albicans infection,with poor prognosis and high mortality.ICU stay ≥ 100 h,use respirator and steroid,invasive operation,age ≥65 years,and continuous use of two antibiotics ＞ 7d are risk factors.Specific preventive measures should be taken to reduce fungal infections.