Epidural spinal cord stimulation (eSCS) represents an emerging neuromodulation technology that ameliorates motor dysfunction in patients with spinal cord injury, Parkinson's disease, and stroke by activating sensory afferent fibers, enhancing spinal cord neural network integration, optimizing brain-spinal cord information transmission, and inducing neural plasticity. This article reviews the mechanism, electrode implantation, and stimulation parameter of eSCS, and application of eSCS in spinal cord injury, Parkinson's disease, and stroke, aiming to provide valuable insight for its clinical implementation.

Epidural spinal cord stimulation (eSCS) represents an emerging neuromodulation technology that ameliorates motor dysfunction in patients with spinal cord injury, Parkinson's disease, and stroke by activating sensory afferent fibers, enhancing spinal cord neural network integration, optimizing brain-spinal cord information transmission, and inducing neural plasticity. This article reviews the mechanism, electrode implantation, and stimulation parameter of eSCS, and application of eSCS in spinal cord injury, Parkinson's disease, and stroke, aiming to provide valuable insight for its clinical implementation.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective:To evaluate the efficacy and safety of apatinib in combination with chemoradiotherapy for head and neck squamous cell carcinoma (HNSCC).Methods:37 patients orally received apatinib at 250 mg/d during concurrent chemoradiotherapy until completion of radiotherapy, complete remission assessed by imaging examination, the onset of unacceptable toxicity or death. Baseline characteristics, objective response rates (ORR) and adverse events were assessed in all enrolled patients with complete baseline and safety data. Progression-free survival (PFS) and overall survival (OS) were calculated by Kaplan-Meier method. Prognostic factors were statistically identified using Cox regression models.Results:The ORR was 85%(95% CI: 72%-98%). The median PFS was 17.9 months and the 2-year OS rate was 62%(95% CI: 48%-80%). Ineffective short-term efficacy ( HR=0.035, 995% CI: 0.02-0.652, P=0.025) was an independent risk factor for poor OS. In addition, ineffective short-term efficacy ( HR=0.104, 95% CI: 0.017-0.633, P=0.014) and lymphocytopenia ( HR=17.539, 95% CI: 2.040-150.779, P=0.009) were independent risk factors for poor PFS. Common adverse events (>60%) included lymphocytopenia (76%), leukopenia (68%) and irradiation-induced mucosal injury (65%). The most common treatment-associated grade 3 adverse event was lymphopenia (49%). Conclusions:Apatinib combined with chemoradiotherapy yield significant anti-tumor activity for HNSCC with controllable toxicity. For patients with advanced HNSCC, short-term efficacy and lymphocytopenia may be potential predictors for clinical efficacy of apatinib combined with chemoradiotherapy.

Objective: To explore the molecular biological mechanism of curcumol in regulating ferroptosis and autophagy. Methods: The Pharm Mapper database was used to screen out curcumol targets, various known related databases were used to establish a database of ferroptosis and autophagy related targets, and the String database was used to construct a protein-protein interaction network. The key targets were enriched and analyzed using DAVID database. Results: 152 curcumol targets, 259 ferroptosis targets, and 796 autophagy targets were obtained; curcumol mainly regulated the ferroptosis process through PTGS2, ALB, MAPK1, MAPK8, and MAPK14 targets, and curcumol mainly through HSP90 AA1, MAPK1, MAPK8, ALB, NOS3 targets regulated the autophagy process, and curcumol mainly regulated the ferroptosis and autophagy process through ALB, MAPK1, MAPK8 targets. Conclusion Curcumol can exert pharmacological effects by regulating ferroptosis and autophagy.

Objective To investigate the correlation between the expression of glucose transporters 1 (GLUT1),monocarboxylate transporter 1 (MCT1),monocarboxylate transporter 4(MCT4) and clinical characteristics in colon cancer. Methods From January 2008 to January 2016,the carcinoma tissues of 84 cases with colon cancer after gastrointestinal surgery, and 40 samples of corresponding adjacent normal colon tissues in the First People＇s Hospital of Hangzhou were collected. The clinical data were collected. Immunohistochemistry was performed to detect the expression of GLUT1, MCT1 and MCT4, the results were analyzed. Results The positive expression rates of MCT1,GLUT1 and MCT4 in colon cancer were 54. 8% (46/84),47. 6% (40/84),58. 3% (49/84),respectively, which were significantly higher than those of the control group[12. 5% (5/40),7. 5% (3/40),15. 0% (6/40)],the differences were statistically significant (χ2=19. 987,19. 253,20. 615,all P＜0. 01). The expressions of GLUT1, MCT1,and MCT4 were not related to gender,age and tumor size,but related to lesion location,differentiation,lymph node metastasis,distant metastasis and clinical stage( GLUT1:χ2=6. 227,11. 629,10. 029,14. 817,4. 709;MCT1:χ2=6. 891,8. 615,9. 185,5. 337,16. 131;MCT4:χ2=8. 641,7. 077,12. 131,6. 917,7. 077;all P ＜0. 05). Conclusion High expression of GLUT1,MCT1 and MCT4 were observed in colon cancer. GLUT1,MCT1 and MCT4 may affect the development of colon cancer through energy metabolism pathway in colon cancer tissues.