Risk factor analysis and nomogram construction in patients with distant metastatic prostate cancer at different PSA levels: a study based on the SEER database.

OBJECTIVE: Prostate cancer (PCa) is the most common malignant tumor in the male genitourinary system. Once PCa has metastasized, it is very difficult to cure. The purpose of this study was to investigate the prognostic risk factor analysis of patients with different prostate-specific antigen (PSA) levels in distant metastatic PCa. At the same time, we construct effective models for predicting the survival rate of prostate cancer patients. PATIENTS AND METHODS: Data on prostate cancer patients with the presence of distant metastases were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. PCa patients with distant metastases were categorized into two groups based on PSA levels, one with PSA <20 ng/mL and the other with PSA ≥20 ng/mL. Univariate and multivariate COX regression analyses were used to identify independent factors affecting the prognosis of the patients. A nomogram was constructed using the independent prognostic factors, and the results were evaluated using calibration curves, timeROC curves, and Kaplan-Meier curves. RESULTS: In the PSA <20 ng/mL group, there were a total of 1,832 patients. COX regression analysis showed that age, marital status, N stage, grade, Gleason score, and medical household income inflation were independent prognostic factors for overall survival (OS) in patients. In addition, we found that age, marital status, N stage, bone metastasis, grade, and Gleason score were independent prognostic factors for cancer-specific survival (CSS) in patients. In the PSA ≥20 ng/mL group, there were a total of 5,314 patients. It was found that age, ethnicity, marital status, bone metastasis, first malignant primary indicator, grade, Gleason score, and medical household income inflation were patients' independent prognostic factors for OS. For CSS, we found that age, ethnicity, marital status, T stage, radiotherapy, bone metastasis, Gleason score, and Median household income inflation were independent prognostic factors. Constructing a nomogram can accurately predict the prognosis of this group of patients. CONCLUSIONS: We found different independent prognostic factors for different PSA levels in patients with distant metastatic PCa. A new nomogram was constructed to predict OS and CSS in patients, which helps in clinical-assisted decision-making.

A comprehensive analysis of essential meiotic endonuclease 1 to prognosis and immune infiltration in kidney renal clear cell carcinoma.

OBJECTIVE: Clear cell renal cell carcinoma (ccRCC) is the most common type of cancer, and its molecular pathogenesis is unclear. In this study, we investigated the prognostic value of essential meiotic endonuclease 1 (EME1) in kidney renal clear cell carcinoma (KIRC). MATERIALS AND METHODS: We downloaded the RNA-Seq expression of 526 KIRC tissues and 72 normal tissues from the TCGA database and the corresponding clinical data. The gene expression profiles associated with four clear cell renal cell carcinomas were downloaded from the GEO database for analysis. The expression of EME1 in clear renal cell carcinoma and its correlation with the clinical baseline data were analyzed. Kaplan-Meier survival curve analysis was performed to assess the relationship between EME1 and patient survival. Enrichment analysis was performed to elucidate the possible functions of EME1. We also analyzed the relationship between the EME1 expression and immune infiltration through TIMER2.0 and TISIDB online databases as well as the relationship between EME1 and common immune checkpoints. RESULTS: EME1 was identified as a risk factor for overall survival in clear cell renal cell carcinoma with a hazard ratio of 3.201 (95% confidence interval: 2.430-4.215; p < 0.001). EME1 was highly expressed in KIRC compared to that in normal tissues (p < 0.001) and in the worse TNM stages and late stages (stage 3/4) (p < 0.001). High EME1 expression was strongly associated with the advanced T stage (p = 0.003), advanced N stage (p = 0.002), and advanced M stage (p = 0.006). Research data on KIRC were simultaneously collected and analyzed from the GEO database, including GSE40435, GSE53000, GSE68417, and GSE53757. EME1 predicted the survival status in KIRC patients (AUC = 0.62). We further established a nomogram including the correlation between the high and low EME1 expression, and EME1 was found to contribute to the prediction of the probability of patient survival with a c-index = 0.796. Kaplan-Meier analysis revealed a lower likelihood of survival with a high EME1 expression (p < 0.001). In addition, further bioinformatics analysis suggested that EME1 may be associated with the extent of immune infiltration in KIRC. CONCLUSIONS: An increased expression of EME1 in KIRC is thus associated with advanced clinicopathological features, possibly acting as a potential biomarker of poor prognosis in KIRC.

[Research progress on influencing factors of early adiposity rebound in children and the effect on adolescent development in girls].

With the increasing rate of overweight and obesity in children worldwide, adiposity rebound(AR)closely related to obesity has become the spotlight, and early AR phase has a broad impact on pubertal development in girls, but the specific mechanism of action isn't very clear.This paper is review of the prevalence of early AR at home and abroad, and its influencing factors, the impact of AR on the adolescent development of girls and related mechanisms, to identify high-risk individuals with early AR, early AR to identify early adolescent development, and take early intervention measures to promote children's health.

[Independent and combined effects of pre-pregnancy BMI and gestational diabetes on early adiposity rebound timing in children].

Objective: To examine the independent and combined effects of pre-pregnancy BMI and gestational diabetes (GDM) on early adiposity rebound (AR) timing in children. Methods: Based on the "Ma'anshan Birth Cohort Study", 2 896 eligible maternal and infant pairs were recruited. In the cohort, we collected pre-pregnancy height, weight, 24 to 28 weeks GDM diagnosis, follow-up at 42 days, three months, six months, nine months of age, and every six months after one year of age, and continuously followed up to 6 years old, and obtained the child's length/height, weight, and other data. The intensity of the association between pre-pregnancy BMI, GDM, and early AR timing was analyzed by the multivariate logistic regression model. Multiplication and additive models were used to analyze how pre-pregnancy BMI and GDM influenced early AR timing in children. Results: The prevalence of underweight, average weight, overweight, and obesity before pregnancy were 23.2% (672), 66.4% (1 923), 8.7% (251), and 1.7% (50). The prevalence of GDM was 12.4%. We found that 39.3% of children had AR, and the average age at AR was (4.38±1.08). The results of multifactorial logistic regression analysis showed that pre-pregnancy overweight (OR=1.67,95%CI:1.27-2.19), pre-pregnancy obesity (OR=3.05,95%CI:1.66-5.56), and maternal GDM (OR=1.40,95%CI:1.11-1.76) were risk factors for early AR timing in children. In contrast, pre-pregnancy underweight (OR=0.60,95%CI:0.49-0.73) was a protective factor for early AR timing in children. Compared with the different effects of pre-pregnancy overweight/obesity and maternal GDM alone, the combined effect caused a higher risk of early AR timing in children, with OR values (95%CI) were 2.03 (1.20-3.44), 3.43 (1.06-11.12), respectively. The multiplication and additive models showed no interaction between pre-pregnancy BMI and GDM-influenced early AR timing in children. Conclusion: Higher pre-pregnancy BMI and maternal GDM are the independent risk factors for the early AR timing in children, and the co-occurrence of the two is higher risks, but there was no statistical interaction.

[Accuracy and clinical outcome of a real-time surgical navigation system for the placement of quad zygomatic implants].

Objective: To evalute the accuracy and clinical outcome of a real-time navigation system for the placement of quad zygomatic implants. Methods: Twenty-four patients [9 males and 15 females, mean age was (50.8±14.7) years old], from January 2015 to December 2019, with 96 zygomatic implants placed under a real-time navigation system in Department of Second Dental Center and Department of Oral Implantology of Ninth People's Hospital, Shanghai Jiaotong University School of Medicine were included in the study. The preoperative and the postoperative multislice CT or cone-beam CT were fused to measure and record the entry, exit and angle deviation between the planned and placed implants. The implants were divided into groups according to implant insertion approach (real-time navigation and free-hand), implant length (<47.5 mm and ≥47.5 mm) and implant position (proximal and distal implant). And the differences of implant accuracy were analyzed. The intraoperative and postoperative complications were also recorded. The implant survival rate was evaluated after 6 months follow-up. A P value<0.05 indicates statistical significance. Results: The mean entry, exit and angle deviation of zygomatic implants were (1.49±0.64) mm, [2.03(1.58, 2.40)] mm and (2.49°±1.12°), respectively. The average entry, exit and angle deviation of the navigation guided implant insertion group were (1.45±0.60) mm, (1.96±0.44) mm and (2.66±1.13°) respectively, while those of the free-hand group were (1.50±0.64) mm, (2.04±0.79) mm and (2.50°±1.13°) respectively. There was no significant difference between the two groups (P>0.05). The average entry, exit and angle deviation of the group with length<47.5 mm were (1.42±0.60) mm, (2.13±0.60) mm and (2.61°±1.08°) respectively and those of the group with length ≥ 47.5 mm were (1.52±0.65) mm, (1.98±0.82) mm and (2.43°±1.14°) respectively. No significant difference was found between the two groups (P>0.05). In proximal implant group, the average entry, exit and angle deviation were (1.55±0.69) mm, (2.05±0.92) mm and (2.48°±1.16 °) respectively while those of distal implant group were (1.43±0.57) mm, (2.01±0.57) mm and (2.49°±1.10°), respectively. No significant difference was detected between the two groups (P>0.05). All zygomatic implants were placed uneventfully. There were no intra-operative complications, and post-operative reversible complications developed in 3 patients. Two zygomatic implants were lost and the overall zygomatic implant survival rate was 97.9% (94/96) within a follow-up of 6 months. Conclusions: Quad zygomatic implant placement can be achieved with high accuracy and predictable clinical outcome under guidance of a real-time navigation system.

miR-132 weakens proliferation and invasion of glioma cells via the inhibition of Gli1.

OBJECTIVE: Transcriptional factor Gli1 in Hedgehog signal pathway facilitates epithelial mesenchymal transition (EMT) and is associated with invasion or proliferation of multiple tumor cells. The previous study showed the correlation between miR-132 down-regulation and glioma pathogenesis. We investigated the role of miR-132 in mediating Gli1 expression and in affecting proliferation or invasion of glioma cells. PATIENTS AND METHODS: Dual luciferase reporter gene assay was used to confirm the targeted regulation between miR-132 and Gli1. Tumor tissues at different pathological grades (grade II, III and IV) were collected from glioma patients, in parallel with brain tissues from contusion surgery. The expression of miR-132 and Gli1 was measured by RT-PCR. Glioma cell line U251 was treated with miR-132 or si-Gli1 followed by measuring the expression of Gli1, E-cadherin, Vimentin and Cyclin D1. In addition, flow cytometry and transwell assay were performed to evaluate cell invasion potency. RESULTS: Bioinformatics analysis showed the complementary binding sites between miR-132 and 3'-UTR of Gli1 mRNA. Transfection of miR-132 mimic significantly reduced luciferase activity, indicating the targeted regulatory relationship between miR-132 and Gli1 mRNA. Compared with control group, miR-132 expression was decreased and Gli1 level was elevated in glioma tissues, both of which were correlated with the pathological grade. Transfection of miR-132 mimic or si-Gli1 remarkably suppressed the expression of Gli1, Vimentin or Cyclin D1 in U251 cells, up-regulated E-cadherin expression, suppressed cell proliferation and invasion. CONCLUSIONS: Our data indicated that over-expression of miR-132 could inhibit proliferation or invasion of glioma cells via targeted inhibition of Gli1 expression.