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 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 related factors of central regional lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC).Methods The clinical and pathological fea tures of 550 cases of PTMC with clinical lymph node negative (cN0) were retrospectively analyzed.x2 test and multivariate logistic regression analysis were used to analyze the related factors of CLNM.ROC curve was used to analyze tumor diameter and CLNM of PTMC.Results The CLNM rate was 35.6％.Univariate analysis showed that patients aging less than 45 y(x2=13.983,P＜0.001),with tumor diameter≥7 mm (x2=14.263,P＜0.001),with capsule invasion (x2=7.316,P=0.006),multifocality (x2=14.321,P＜0.05) and bilateral tumors (x2=9.265,P=0.002) were more likely to have CLNM.Multivariate Logistic regression analysis showed that age ＜45 y,tumor diameter ≥7 mm,invasion of capsule and multifocal are all independent risk factors of CLNM for patients with PTMC.The optimal cutoff value of CLNM by diameter was 8 mm.Conclusion The CLNM of PTMC is related to many factors.When the age of the patient is less than 45 y,the diameter of the tumor is more than 7 mm,the invasion of the capsule and the multifocal lesion,the central lymph node dissection should be performed.

Objective To explore the lateral neck lymph node metastasis (LNM) in patients affected by papillary thyroid carcinoma(PTC) with clinically negative neck (cN0-PTC) and to discuss the necessity of prophylactic lateral neck lymph node dissection.Methods Clinical data of 651 cN0-PTC patients who underwnt surgical procedure in Tumor Hospital of Zhengzhou University from Jan.2012 to May.2015 were retrospectively analyzed.Chi-square test was used for univariate analysis.Results Of the 651 cN0-PTC patients,62.9％ had LNM (51.3％ in central neck,41.0％ in lateral neck,and 11.7％ with "skip" metastasis).The lateral neck metastasis rate was 50.9％ in men and 37.7％ in women (P＜0.05),61.9％ in patients with tumor diameter ＞1.0 cm and 25.9％ in patients with tumor diameter ≤ 1.0 cm (P＜0.001),47.2％ with multifocal cancer and 40.3％ with unifocal tumor(P＜0.05),63.1％ with extrathyroidal extention and 34.3％ without extention (P＜0.001),64.1％ with ≥3 positive nodes in central neck and 48.3％ with ＜3 positive nodes (P＜0.05),52.4％ with upper lobe cancer and 32.9％ with other locations(P＜0.001),41.0％ in patients ≤45 years and 40.9％ in patients ＞45 years(P＞0.05).Conclusion Central neck dissection should be performed in all cN0-PTC patients.Prophylactic lateral neck dissection should beselectively performed in cN0-PTC patients with following high-risk factors:male,tumor diameter ＞1.0 cm,multifocal cancer,extrathyroidal extention,≥ 3 positive nodes in central neck and upper lobe cancer.

Objective To study the rule of lymph node metastasis rate in cN 0 papillary thyroid microcar-cinoma( cN0-PTMC) and to evaluate an appropriate region of neck dissection .Methods Data of 233 cases of cN0-PTMC were retrospectively analyzed .Univariate analysis with chi-square test was used to analyze the statisti-cal correlation between gender , age, tumor diameter and lymph node metastasis respectively .Results 81 out of 233 patients(34.8%)had cervical lymph node metastasis (30.0%in central region and 9.9%in lateral region). For patients with tumor diameter ( D)≤5 mm and D>5 mm, lymph node metastasis rate in central region was 21.6%and 36.6%(χ2 =6.199,P<0.05) and it was 4.9% and 13.7% respectively in lateral region (χ2 =5.035,P<0.05).For male and female patients, lymph node metastasis rate in central region was 42.1% and 26.1%respectively(χ2 =5.224,P<0.05), and it was 21.1% and 6.3% respectively in lateral region (χ2 =10.604,P<0.01).Lymph node metastasis rate in patients≤45 years old and >45 years old was 37.9% and 21.1% respectively (χ2 =7.792, P <0.01 ) .The lateral region lymph node metastasis rate was 17.1% and 6.7%when the central region lymph node was infringed or not (χ2 =5.947, P<0.05).Conclusions All cN0-PTMC patients should have a normative central neck dissection .Male patients with PTMC and tumor diameter >5 mm should receive the lateral neck lymphoid tissue exploration during surgery in order to find subclinical metas -tasis.

Objective To investigate the effects of huaier granules on invasion and metastasis of colorectal cancer SW480 cells in vitro, and explore the basic mechanism. Methods The appropriate concentration and duration of huaier granules promoting SW480 cell apoptosis were determined by SubG1 method. Wound healing assay and transwell assay were used to observe the effect of huaier granules on SW480 cell invasion and metastasis. The changes of E-cadherin, twist, snail and vimentin at protein and mRNA levels were examined by Western blotting and Real-Time PCR. Results After treatment with huaier granules at 3. 0 g·L-1 for 36 h, apoptosis of SW480 cells was most significant, and wound healing assay revealed that relative mobility was (31. 36±2. 39)%, compared with (61. 11±1. 09)% in control group (P<0. 01). Number of invaded cells per field of view was (129±12) in treatment group and (354±20) in control group (P<0. 01). After treatment with huaier granules at 3. 0 g·L-1 for 36 h, protein and mRNA levels of E-cadherin were increased, while those of twist, snail and vimentin were decreased. Conclusion Huaier granules can inhibit invasion and metastasis of colorectal cancer SW480 cells in vitro through effectively depressing epithelial-mesenchymal transition.

OBJECTIVETo construct a luciferase reporter vector containing the response element of transcription protein AP2α for screening the effect of bone morphogenetic proteins (BMPs) on the transcriptional activity of AP2α.

METHODSFour tandem-linked response elements of AP2α were cloned to the pBGLuc luciferase reporter gene plasmid, which was digested with Bam HI and Mlu I to construct pBGLuc-AP2α-RE vector. The recombinant adenovirus Ad-AP2α and its dominant negative mutant Ad-dnAP2α were used to infect mouse mesenchymal stem cells C3H10; the changes in cellular AP2α mRNA and protein expressions were detected by real-time PCR and Western blotting, and electrophoretic mobility shift assay (EMSA) was carried out to assess the DNA-binding ability of AP2α. C3H10 cells were transfected with pBGLuc-AP2α-RE vector, and AP2α transcriptional activity was measured using luciferase reporter gene assay. In pBGLuc-AP2α-RE vector-transfected C3H10 cells infected with Ad-BMPs, luciferase reporter gene assay was performed to screen the effect of BMPs on AP2α transcriptional activity.

RESULTSThe results of PCR, enzyme digestion and sequencing all confirmed correct cloning of AP2α-RE into pBGLuc-AP2α-RE luciferase reporter vector, and Ad-AP2α infection significantly increased AP2α expression and its DNA binding ability. The dominant negative mutants expressed the corresponding mutants, and EMSA results showed that Ad-dnAP2α-δbHLH significantly lowered while Ad-dnAP2α-δTAD enhanced the DNA-binding ability of AP2α. AP2α over-expression promoted AP2α transcriptional activity, which was suppressed by the two dominant negative mutants. AP2α transcriptional activity increased in the cells infected with the recombinant adenovirus BMPs, especially in cells with BMP9 infection.

CONCLUSIONSThe luciferase reporter vector containing the response element of AP2α we constructed allows detection of AP2α transcriptional activity. BMP9 can significantly enhance AP2α transcriptional activity.

Adenoviridae ; Animals ; Bone Morphogenetic Proteins ; genetics ; metabolism ; Genes, Reporter ; Genetic Vectors ; Growth Differentiation Factor 2 ; genetics ; metabolism ; Luciferases ; genetics ; Mesenchymal Stromal Cells ; cytology ; metabolism ; Mice ; Osteogenesis ; Protein Binding ; RNA, Messenger ; metabolism ; Recombinant Proteins ; genetics ; metabolism ; Response Elements ; Transcription Factor AP-2 ; genetics ; metabolism ; Transcriptional Activation ; Transfection

Objective To construct a luciferase reporter vector containing the response element of transcription protein AP2αfor screening the effect of bone morphogenetic proteins (BMPs) on the transcriptional activity of AP2α. Methods Four tandem-linked response elements of AP2αwere cloned to the pBGLuc luciferase reporter gene plasmid, which was digested with Bam HI and Mlu I to construct pBGLuc-AP2α-RE vector. The recombinant adenovirus Ad-AP2αand its dominant negative mutant Ad-dnAP2α were used to infect mouse mesenchymal stem cells C3H10; the changes in cellular AP2α mRNA and protein expressions were detected by real-time PCR and Western blotting, and electrophoretic mobility shift assay (EMSA) was carried out to assess the DNA-binding ability of AP2α. C3H10 cells were transfected with pBGLuc-AP2α-RE vector, and AP2αtranscriptional activity was measured using luciferase reporter gene assay. In pBGLuc-AP2α-RE vector-transfected C3H10 cells infected with Ad-BMPs, luciferase reporter gene assay was performed to screen the effect of BMPs on AP2α transcriptional activity. Results The results of PCR, enzyme digestion and sequencing all confirmed correct cloning of AP2α-RE into pBGLuc-AP2α-RE luciferase reporter vector, and Ad-AP2α infection significantly increased AP2α expression and its DNA binding ability. The dominant negative mutants expressed the corresponding mutants, and EMSA results showed that Ad-dnAP2α-△bHLH significantly lowered while Ad-dnAP2α-△TAD enhanced the DNA-binding ability of AP2α. AP2α over-expression promoted AP2α transcriptional activity, which was suppressed by the two dominant negative mutants. AP2α transcriptional activity increased in the cells infected with the recombinant adenovirus BMPs, especially in cells with BMP9 infection. Conclusions The luciferase reporter vector containing the response element of AP2αwe constructed allows detection of AP2αtranscriptional activity. BMP9 can significantly enhance AP2αtranscriptional activity.

Objective To construct a luciferase reporter vector containing the response element of transcription protein AP2αfor screening the effect of bone morphogenetic proteins (BMPs) on the transcriptional activity of AP2α. Methods Four tandem-linked response elements of AP2αwere cloned to the pBGLuc luciferase reporter gene plasmid, which was digested with Bam HI and Mlu I to construct pBGLuc-AP2α-RE vector. The recombinant adenovirus Ad-AP2αand its dominant negative mutant Ad-dnAP2α were used to infect mouse mesenchymal stem cells C3H10; the changes in cellular AP2α mRNA and protein expressions were detected by real-time PCR and Western blotting, and electrophoretic mobility shift assay (EMSA) was carried out to assess the DNA-binding ability of AP2α. C3H10 cells were transfected with pBGLuc-AP2α-RE vector, and AP2αtranscriptional activity was measured using luciferase reporter gene assay. In pBGLuc-AP2α-RE vector-transfected C3H10 cells infected with Ad-BMPs, luciferase reporter gene assay was performed to screen the effect of BMPs on AP2α transcriptional activity. Results The results of PCR, enzyme digestion and sequencing all confirmed correct cloning of AP2α-RE into pBGLuc-AP2α-RE luciferase reporter vector, and Ad-AP2α infection significantly increased AP2α expression and its DNA binding ability. The dominant negative mutants expressed the corresponding mutants, and EMSA results showed that Ad-dnAP2α-△bHLH significantly lowered while Ad-dnAP2α-△TAD enhanced the DNA-binding ability of AP2α. AP2α over-expression promoted AP2α transcriptional activity, which was suppressed by the two dominant negative mutants. AP2α transcriptional activity increased in the cells infected with the recombinant adenovirus BMPs, especially in cells with BMP9 infection. Conclusions The luciferase reporter vector containing the response element of AP2αwe constructed allows detection of AP2αtranscriptional activity. BMP9 can significantly enhance AP2αtranscriptional activity.

To screen the candidate genes associated with Musca domestica antibacterial peptides using DNA microarray technique, the hybrid probes were designed from the conservative domains of the encoded area of the insect antibacterial peptide genes in GenBank with biology software Designer 2.0, and were synthesized by a chemical process, with the assistance of the automated Gen III Microarray Spotter, those oligo probes were printed on a special ready-made glass, and a cDNA microarray was constructed. The total RNA was extracted from the fat body of Musca domestic third-instar larve induced after 24 hours by Escherichia coli and Staphylococcus aureus, the strands of cDNA were labled with fluoresceine Cy3 using the method of reverse transcription PCR, after prehybridization, hybridization and washing procedure, the results of hybridization were scanned using computer system, and the data were analyzed using the software of MIDAS, fifteen valid hybridization signals were detected through two times of hybridization and scanning (the positive samples as a control were excluded). DNA microarray technique can be successfully applied screen the candidate genes associated with Musca domestica antibacterial peptides, and further provide significant evidence to discover its antibacterial peptide new genes.
Animals ; Antimicrobial Cationic Peptides ; genetics ; Base Sequence ; Gene Expression Profiling ; Genes, Insect ; Houseflies ; genetics ; growth & development ; Larva ; genetics ; growth & development ; Molecular Sequence Data ; Oligonucleotide Array Sequence Analysis ; methods ; Oligonucleotide Probes ; chemistry