Construction of a prediction model for prognosis of bladder cancer based on the expression of ion channel-related genes. / åŸºäºŽç¦»å­é€šé“ç›¸å ³åŸºå› çš„è†€èƒ±ç™Œæ‚£è€ é¢„åŽé£Žé™©è¯„ä¼°æ¨¡åž‹æž„å»º.

OBJECTIVES: To construct a prediction model for the prognosis of bladder cancer patients based on the expression of ion channel-related genes (ICRGs). METHODS: ICRGs were obtained from the existing researches. The clinical information and the expression of ICRGs mRNA in breast cancer patients were obtained from the Cancer Genome Atlas database. Cox regression analysis, minimum absolute shrinkage and selection operator regression analysis were used to screen breast cancer prognosis related genes, which were verified by immunohistochemistry and qRT-PCR. The risk scoring equation for predicting the prognosis of patients with bladder cancer was constructed, and the patients were divided into high-risk group and low-risk group according to the median risk score. Immune cell infiltration was compared between the two groups. Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to evaluate the accuracy and clinical application value of the risk scoring equation. The factors related to the prognosis of bladder cancer patients were analyzed by univariate and multivariate Cox regression, and a nomogram for predicting the prognosis of bladder cancer patients was constructed. RESULTS: By comparing the expression levels of ICRGs in bladder cancer tissues and normal bladder tissues, 73 differentially expressed ICRGs were dentified, of which 11 were related to the prognosis of bladder cancer patients. Kaplan-Meier survival curve suggested that the risk score based on these 11 genes was negatively correlated with the prognosis of patients. The area under the ROC curve of the risk score for predicting the prognosis of patients at 1, 3 and 5 year was 0.634, 0.665 and 0.712, respectively. Stratified analysis showed that the ICRGs-based risk score performed well in predicting the prognosis of patients with American Joint Committee on Cancer (AJCC) stage Ⅲ-Ⅳ bladder cancer (P<0.05), while it had a poor value in predicting the prognosis of patients with AJCC stage Ⅰ-Ⅱ (P>0.05). There were significant differences in the infiltration of plasma cells, activated natural killer cells, resting mast cells and M2 macrophages between the high-risk group and the low-risk group. Cox regression analysis showed that risk score, smoking, age and AJCC stage were independently associated with the prognosis of patients with bladder cancer (P<0.05). The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1, 3 and 5 year overall survival rate of bladder cancer patients. CONCLUSIONS: The study shows the potential value of ICRGs in the prognostic risk assessment of bladder cancer patients. The constructed prognostic nomogram based on ICRGs risk score has high accuracy in predicting the prognosis of bladder cancer patients.

High-Toughness Poly(Lactic Acid)/Starch Blends Prepared through Reactive Blending Plasticization and Compatibilization.

In this study, poly(lactic acid) (PLA)/starch blends were prepared through reactive melt blending by using PLA and starch as raw materials and vegetable oil polyols, polyethylene glycol (PEG), and citric acid (CA) as additives. The effects of CA and PEG on the toughness of PLA/starch blends were analyzed using a mechanical performance test, scanning electron microscope analysis, differential scanning calorimetry, Fourier-transform infrared spectroscopy, X-ray diffraction, rheological analysis, and hydrophilicity test. Results showed that the elongation at break and impact strength of the PLA/premixed starch (PSt)/PEG/CA blend were 140.51% and 3.56 kJ·m-2, which were 13.4 and 1.8 times higher than those of pure PLA, respectively. The essence of the improvement in the toughness of the PLA/PSt/PEG/CA blend was the esterification reaction among CA, PEG, and starch. During the melt-blending process, the CA with abundant carboxyl groups reacted in the amorphous region of the starch. The shape and crystal form of the starch did not change, but the surface activity of the starch improved and consequently increased the adhesion between starch and PLA. As a plasticizer for PLA and starch, PEG effectively enhanced the mobility of the molecular chains. After PEG was dispersed, it participated in the esterification reaction of CA and starch at the interface and formed a branched/crosslinked copolymer that was embedded in the interface of PLA and starch. This copolymer further improved the compatibility of the PLA/starch blends. PEGs with small molecules and CA were used as compatibilizers to reduce the effect on PLA biodegradability. The esterification reaction on the starch surface improved the compatibilization and toughness of the PLA/starch blend materials and broadens their application prospects in the fields of medicine and high-fill packaging.

Reinforcement Learning-Based Tracking Control for a Three Mecanum Wheeled Mobile Robot.

This brief investigates the robust optimal tracking control for a three Mecanum wheeled mobile robot (MWMR) with the external disturbance by the aid of online actor-critic synchronous learning algorithm. The Euler-Lagrange motion equation of MWMR subject to slipping is established by analyzing the structural characteristics of Mecanum wheels. Concatenating the tracking error with the desired trajectory, the tracking control problem is converted into a time-invariant optimal control problem of an augmented system. Then, an approximate optimal tracking controller is obtained by applying online actor-critic synchronous learning algorithm. With the help of Lyapunov-based analysis, the ultimately bounded tracking can be guaranteed. Finally, simulation results show the effectiveness of synchronous learning algorithm and approximate optimal tracking controller.

Optimal cut-off points of fasting plasma glucose for two-step strategy in estimating prevalence and screening undiagnosed diabetes and pre-diabetes in Harbin, China.

To identify optimal cut-off points of fasting plasma glucose (FPG) for two-step strategy in screening abnormal glucose metabolism and estimating prevalence in general Chinese population. A population-based cross-sectional study was conducted on 7913 people aged 20 to 74 years in Harbin. Diabetes and pre-diabetes were determined by fasting and 2 hour post-load glucose from the oral glucose tolerance test in all participants. Screening potential of FPG, cost per case identified by two-step strategy, and optimal FPG cut-off points were described. The prevalence of diabetes was 12.7%, of which 65.2% was undiagnosed. Twelve percent or 9.0% of participants were diagnosed with pre-diabetes using 2003 ADA criteria or 1999 WHO criteria, respectively. The optimal FPG cut-off points for two-step strategy were 5.6 mmol/l for previously undiagnosed diabetes (area under the receiver-operating characteristic curve of FPG 0.93; sensitivity 82.0%; cost per case identified by two-step strategy ¥261), 5.3 mmol/l for both diabetes and pre-diabetes or pre-diabetes alone using 2003 ADA criteria (0.89 or 0.85; 72.4% or 62.9%; ¥110 or ¥258), 5.0 mmol/l for pre-diabetes using 1999 WHO criteria (0.78; 66.8%; ¥399), and 4.9 mmol/l for IGT alone (0.74; 62.2%; ¥502). Using the two-step strategy, the underestimates of prevalence reduced to nearly 38% for pre-diabetes or 18.7% for undiagnosed diabetes, respectively. Approximately a quarter of the general population in Harbin was in hyperglycemic condition. Using optimal FPG cut-off points for two-step strategy in Chinese population may be more effective and less costly for reducing the missed diagnosis of hyperglycemic condition.