Objective To better understand the age related changes of cardiac structure and function and their relationship with gender, body weight and blood pressure. Methods M mode, 2 dimensional, and Doppler echocardiographic studies were performed on 306 healthy intellectuals, including 165 males and 141 females, ranging in age from 30 to 85 years. Results Parameters in both male and female including the ratio of peak E wave to peak A wave velocity(E/A), the ratio of the right ventricular peak E wave to peak A wave velocity(E/Ar), the amplitude of aortic wall (Aao) and the angle between septum and the root of aorta (?) were all decreased with the aging significantly( P

Objective:To investigate the application effect of high-altitude field-based teaching in acute mountain sickness.Methods:The medical students of the classes 2018 and 2019 majoring in clinical medicine were selected as subjects, and they were divided into conventional teaching group and field-based teaching group, with 20 students in each group. The students in the conventional teaching group received classroom teaching alone, and those in the field-based teaching group received high-altitude field-based teaching after theoretical lectures. The two groups were compared in terms of the theoretical knowledge of acute mountain sickness, the quality score of internship, and rescue operation score of acute mountain sickness, and questionnaire feedback and post-class discussion were performed among trainees and teachers to evaluate the high-altitude field-based teaching model. SPSS 19.0 was used for statistical analysis.Results:Compared with the conventional teaching group, the field-based teaching group had significantly higher scores of the theoretical knowledge of acute mountain sickness (91.72±4.34 vs. 86.10±5.15, P<0.001), the quality score of internship (89.64±5.21 vs. 83.51±2.38, P<0.001), and the rescue operation of acute mountain sickness [94.05 (89.54, 94.87) vs. 87.01 (84.33, 90.82), P<0.001]. Conclusions:High-altitude field-based teaching can improve the teaching effect of acute mountain sickness and cultivate the interest and learning enthusiasm of students, and therefore, it holds promise for wide application.

Objective To investigate the expression of(glutathione S-Transferase Omega-1,GSTO1)in cervical cancer tissue and its correlation with patient survival time,and to explore the impact of GSTO1 N-glycosylation on proliferation,migration,invasion,and epithelial-mesenchymal transition of cervical cancer.Methods By using immunohistochemistry,the expression levels of GSTO1 in tumor cells of 82 cervical cancer patients were detected,and the correlation between GSTO1 expression and clinical pathological features was analyzed.Kaplan-Meier meth-od was used to plot survival curves and evaluate the impact of GSTO1 expression in cervical cancer tissues on pa-tient survival time.Univariate and multivariate Cox regression analyses were performed to assess the independent prognostic factors influencing cervical cancer prognosis.The NetNGlyc 1.0 Server database predicted potential N-glycosylation modification sites of GSTO1(Asn55,Asnl35,Asn190).The cervical cancer cells(HeLa)were transfected with GSTO1 N-glycosylation site mutation vectors at positions 55,135,and 190,as well as GSTO1 wild-type vector and empty vector.Stable transfected cells were selected using puromycin.Western blot experi-ments were performed to assess the effectiveness of lentiviral interference.The effects of GSTO1 N-glycosylation site mutations on proliferation,migration,and invasion of HeLa cells were evaluated using EdU proliferation assay,wound healing assay,and Transwell assay.The effect of GSTO1 N-glycosylation site mutations on the epithelial-mesenchymal transition of HeLa cells was detected using the Western blot experiment.Results Immunohistochem-istry results revealed high expression of GSTO1 in cervical cancer tissues.The expression rate of GSTO1 was signifi-cantly higher in cervical cancer tissues with deep stromal invision≥1/2,lymphovascular space invasion,and lymph node metastasis(P＜0.05).Moreover,high expression of GSTO1 was associated with poorer overall surviv-al.After N-glycosylation site-specific mutation of GSTO1,the cell count of proliferation,migration,and invasion in HeLa cells significantly decreased(P＜0.05).The Western blot results showed that N-glycosylation site mutation of GSTO1 significantly inhibited the epithelial-mesenchymal transition of HeLa cells.Conclusion The expression of GSTO1 in cervical cancer tissues is associated with stromal infiltration depth,lymphovascular space invasion and lymph node metastasis,and it is also correlated with shorter patient survival time.Site-specific mutations in GSTO1 N-glycosylation significantly inhibit the proliferation,migration and epitheli al-mesenchymal transition of HeLa cells.

Objective: To investigate the diagnosis and treatment of synchronous double primary malignant tumours of the tongue and lung. Methods: A case of adenoid cystic carcinoma（ACC） and lung adenocarcinoma with double primary malignancy was retrospectively analyzed. Results: The tumor of patient′s tongue base gradually grew. MRI showed multiple enlarged lymph nodes on both sides of neck. CT of the chest showed obvious lesions in the anterior basal segment of the right lower lobe. The pathological biopsy of the tongue mass identified ACC, and pathological biopsy of the lung mass identified lung adenocarcinoma. The tongue and lung tumors were both surgically resected, and the tongue defect was repaired at the same time. No residue was found after surgery, and no recurrence was found during the follow-up period. The aesthetic and functional restoration of the lingual region was good. Conclusion There are few cases of adenoid cystic carcinoma and lung adenocarcinoma with double primary malignancies, and the related diagnosis and treatment are very difficult; the simultaneous removal of double primary malignant tumors may achieve good prognosis.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: To investigate the expression of transient receptor polycystic protein 2(TRPP2) in oral squamous epithelial cell and its effect on the invasion and migration of oral squamous cell carcinoma(OSCC), and to explore the potential signaling pathway of TRPP2 affecting OSCC metastasis. Methods: The OSCC model with TRPP2 knockdown was constructed by CRISPR-Cas9 lentivirus plasmid transfection technique. The effect of TRPP2 protein knockdown was verified by Western blot. The effect of TRPP2 on OSCC proliferation was detected by CCK-8 assay and clone formation assay. RT-qPCR was used to detect the target genes associated with TRPP2 metastasis to OSCC. Western blot and RT-qPCR were used to detect the expression of EpCAM and its transcription factors associated with unfolded protein response(UPR). The effects of TRPP2 on the invasion and migration of OSCC were examined by invasion test and scratch test. Results: Compared with HOK in oral epithelial cells, the expression of TRPP2 in OSCC was significantly higher. When TRPP2 was knocked down, OSCC proliferation and clonalformation were significantly enhanced. Compared with the control group, a total of 494 differential genes were significantly expressed in TRPP2 knockdown transcription profile, among which 234 genes were up-regulated and 260 genes were down-regulated. The expression of EpCAM gene, which is related to cell adhesion, was up-regulated. In addition, UPR related genes PERK, ATF6, GRP78 were up-regulated, while ATF6 and EpCAM were down-regulated in OSCC compared to HOK cells. The expression of ATF6 and EpCAM in oral squamous cell carcinoma cells was up-regulated by TRPP2 knockdown, and the cell migration and invasion ability decreased. The ATF6 inhibitor ceapin-A7(5 μmol/L) restored the OSCC migration and invasion ability of TRPP2 knockdown. Conclusion TRPP2 is highly expressed in OSCC. When TRPP2 is knocked down, OSCC proliferation ability is enhanced, migration and invasion ability are inhibited. TRPP2 mediates the expression of EpCAM through activation of UPR, thus affecting the invasion and migration of oral squamous cell carcinoma.