ObjectiveThe purpose of this study was to investigate the effects of transcutaneous electrical acupoint stimulation (TEAS) on cognitive function of vascular dementia (VD) rats and its mechanism. MethodsVD rat model was established by modified two-vessel occlusion (2-VO). After modeling, TEAS and electroacupuncture (EA) were used to stimulate Baihui and Zusanli points of rats respectively for 14 d. After treatment, novel object recognition test, Morris water maze test, and Y maze test were used to evaluate the spatial memory and learning ability of rats. Hematoxylin and eosin staining was used to observe the morphology of hippocampal neurons. Transmission electron microscopy was used to observe the ultrastructure of hippocampal mitochondria. Enzyme-linked immunosorbent assay kits were used to detected the levels of SOD, CAT, GSH-Px, MDA and ROS in serum of rats. Western blot was used to detect the expression of PGC-1α, TFAM, HO-1, NQO1 proteins in the hippocampus, Keap1 protein in the cytoplasm and Nrf2, NRF1 proteins in the nucleus. ResultsAfter treatment for 14 d, compared to the model group, the escape latency of VD rats decreased, while the discrimination index, the times of rats crossing the original platform area, the residence time in the original platform quadrant, and the percentage of alternation increased. TEAS can improve the structure of hippocampal neurons and mitochondria of VD rats, showing that neurons were arranged more regularly and distributed more evenly, nuclear membrane and nucleoli were clearer, and mitochondrial swelling were reduced, mitochondrial matrix density were increased, and mitochondrial cristae were more obvious. The levels of SOD, GSH-Px and CAT in serum increased significantly, while the concentration of MDA and ROS decreased. TEAS also up-regulated the expression levels of PGC-1α TFAM, NQO1 and HO-1 proteins in the hippocampus and Nrf2, NRF1 proteins in the nucleus, but down-regulated the Keap1 protein in the cytoplasm. ConclusionTEAS can improve cognition, hippocampal neurons and mitochondrial structure of VD rats, and the effect is better than EA. The mechanism may be the activation of PGC-1α mediated mitochondrial biogenesis and antioxidant stress, which also provides a potential therapeutic technology and experimental basis for the treatment of VD.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
Humans ; Nomograms ; Retrospective Studies ; Carcinoma, Renal Cell/pathology* ; Prognosis ; Risk Factors ; Nephrectomy ; Kidney Neoplasms/pathology* ; Necrosis

OBJECTIVE: To compare the posterior cruciate ligament(PCL) index with six different measurement methods, and analyze and verify its clinical diagnostic value in anterior cruciate ligament (ACL) injury. METHODS: The Magnetic resonance imaging (MRI) data of 225 knee joints in our hospital from May 2018 to March 2022 were retrospectively analyzed, aged from 18 to 60 years old, with a median of 32 years old. On the sagittal MRI images of 114 patients with ACL injury and 111 patients with intact ACL, Measure the straight-line distance (A) between the femoral attachment point and the tibial attachment point of the PCL on the MRI sagittal image and the maximum vertical distance (B) between the straight line and the arcuate mark point of the PCL on the sagittal image, calculate the PCL index and evaluate the diagnostic value of the PCL index for ACL injury. RESULTS: The PCL index of the ACL normal group and the ACL injury group were statistically described. There was no significant difference in PCL index 1, 2, 3 and 6 between the two groups(P>0.05). The difference of PCL index 4 and 5 between the two groups was statistically significant (P<0.001). This study only found that the PCL index 2, 6 in the ACL normal group had a negative correlation with the patient's age (correlation coefficient=-0.213, -0.819;P<0.05), and the PCL index 5 in the ACL injury group was significantly correlated with the patient's body mass index(BMI)had a negative correlation (correlation coefficient=-0.277, P<0.05). CONCLUSION The change of PCL index is helpful for the diagnosis of ACL injury, PCL index 4 and 5 can be used as effective reference indexes for diagnosing ACL injury in clinic.
Humans ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Posterior Cruciate Ligament/diagnostic imaging* ; Anterior Cruciate Ligament Injuries/diagnostic imaging* ; Anterior Cruciate Ligament ; Retrospective Studies ; Knee Joint ; Magnetic Resonance Imaging/methods*

UiO-66 (University of Oslo 66) is a kind of promising material that can improve the release and bioavailability of poorly water-soluble bioactive compounds of traditional Chinese medicine. However, the loading of quercetin in raw UiO-66 was not ideal. In this study, UiO-66-BH (UiO-66-blend-heating) was obtained by heating UiO-66 and KOH solution following blended them. UiO-66-BH maintained the outline of octahedral structure of UiO-66 but with obvious rough and uneven pores on the surface. UiO-66-BH had good adsorption of quercetin with saturation adsorption was 138.92 mg·g^-1, the adsorption process belonged to single molecular layer adsorption and was controlled by chemisorption. UiO-66-BH can control the release of quercetin in simulated gastrointestinal fluid, and the drug concentration was significantly higher than that of free quercetin after long-term release (36% vs 9%). Compared with quercetin, the ABTS (2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) ammonium salt) radical scavenging activity of UiO-66-BH@quercetin drug delivery system decreased, while the DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity remained almost unchanged. The drug delivery system showed a strong antioxidant effect similar to quercetin. The findings indicated that UiO-66-BH could control release of quercetin and was expected to be used as a drug carrier material for some insoluble active components of traditional Chinese medicine such as quercetin.

The purpose of this study was to explore transrectal ultrasound (TRUS) findings of prostate cancer (PCa) guided by multiparametric magnetic resonance imaging (mpMRI) and to improve the Prostate Imaging Reporting and Data System (PI-RADS) system for avoiding unnecessary mpMRI-guided targeted biopsy (TB). From January 2018 to October 2019, fusion mpMRI and TRUS-guided biopsies were performed in 162 consecutive patients. The study included 188 suspicious lesions on mpMRI in 156 patients, all of whom underwent mpMRI-TRUS fusion imaging-guided TB and 12-core transperineal systematic biopsy (SB). Univariate analyses were performed to investigate the relationship between TRUS features and PCa. Then, logistic regression analysis with generalized estimating equations was performed to determine the independent predictors of PCa and obtain the fitted probability of PCa. The detection rates of PCa based on TB alone, SB alone, and combined SB and TB were 55.9% (105 of 188), 52.6% (82 of 156), and 62.8% (98 of 156), respectively. The significant predictors of PCa on TRUS were hypoechogenicity (odds ratio [OR]: 9.595, P = 0.002), taller-than-wide shape (OR: 3.539, P = 0.022), asymmetric vascular structures (OR: 3.728, P = 0.031), close proximity to capsule (OR: 3.473, P = 0.040), and irregular margins (OR: 3.843, P = 0.041). We propose subgrouping PI-RADS score 3 into categories 3a, 3b, 3c, and 3d based on different numbers of TRUS predictors, as the creation of PI-RADS 3a (no suspicious ultrasound features) could avoid 16.7% of mpMRI-guided TBs. Risk stratification of PCa with mpMRI-TRUS fusion imaging-directed ultrasound features could avoid unnecessary mpMRI-TBs.
Male ; Humans ; Prostatic Neoplasms/pathology* ; Multiparametric Magnetic Resonance Imaging ; Magnetic Resonance Imaging/methods* ; Prostate/pathology* ; Image-Guided Biopsy/methods*

Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
Humans ; Nomograms ; Retrospective Studies ; Carcinoma, Renal Cell/pathology* ; Prognosis ; Risk Factors ; Nephrectomy ; Kidney Neoplasms/pathology* ; Necrosis

OBJECTIVES: To investigate the clinical treatment outcomes and the changes of the outcomes over time in extremely preterm twins in Guangdong Province, China. METHODS: A retrospective analysis was performed for 269 pairs of extremely preterm twins with a gestational age of <28 weeks who were admitted to the department of neonatology in 26 grade A tertiary hospitals in Guangdong Province from January 2008 to December 2017. According to the admission time, they were divided into two groups: 2008-2012 and 2013-2017. Besides, each pair of twins was divided into the heavier infant and the lighter infant subgroups according to birth weight. The perinatal data of mothers and hospitalization data of neonates were collected. The survival rate of twins and the incidence rate of complications were compared between the 2008-2012 and 2013-2017 groups. RESULTS: Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of severe asphyxia and smaller head circumference at birth (P<0.05). The mortality rates of both of the twins, the heavier infant of the twins, and the lighter infant of the twins were lower in the 2013-2017 group compared with the 2008-2012 group (P<0.05). Compared with the 2008-2012 group, the 2013-2017 group (both the heavier infant and lighter infant subgroups) had lower incidence rates of pulmonary hemorrhage, patent ductus arteriosus (PDA), periventricular-intraventricular hemorrhage (P-IVH), and neonatal respiratory distress syndrome (NRDS) and a higher incidence rate of bronchopulmonary dysplasia (P<0.05). CONCLUSIONS There is a significant increase in the survival rate over time in extremely preterm twins with a gestational age of <28 weeks in the 26 grade A tertiary hospitals in Guangdong Province. The incidences of severe asphyxia, pulmonary hemorrhage, PDA, P-IVH, and NRDS decrease in both the heavier and lighter infants of the twins, but the incidence of bronchopulmonary dysplasia increases. With the improvement of diagnosis and treatment, the multidisciplinary collaboration between different fields of fetal medicine including prenatal diagnosis, obstetrics, and neonatology is needed in the future to jointly develop management strategies for twin pregnancy.
Bronchopulmonary Dysplasia/epidemiology* ; Female ; Gestational Age ; Humans ; Infant ; Infant, Extremely Premature ; Infant, Newborn ; Pregnancy ; Respiratory Distress Syndrome, Newborn/epidemiology* ; Retrospective Studies ; Treatment Outcome

Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.
COVID-19 ; Cohort Studies ; Contact Tracing ; Humans ; Incidence ; Prospective Studies