Optimal examined lymph node number for accurate staging and long-term survival in rectal cancer: a population-based study.

BACKGROUND: Although the recommended minimal examined lymph node (ELN) number in rectal cancer (RC) is 12, this standard remains controversial because of insufficient evidence. We aimed to refine this definition by quantifying the relationship between ELN number, stage migration and long-term survival in RC. METHODS: Data from a Chinese multi-institutional registry (2009-2018) and the Surveillance, Epidemiology, and End Results (SEER) database (2008-2017) on stages I-III resected RC were analysed to determine the relationship between ELN count, stage migration, and overall survival (OS) using multivariable models. The series of odds ratios (ORs) for negative-to-positive node stage migration and hazard ratios (HRs) for survival with more ELNs were fitted using a Locally Weighted Scatterplot Smoothing (LOWESS) smoother, and structural breakpoints were determined using the Chow test. The relationship between ELN and survival was evaluated on a continuous scale using restricted cubic splines (RCS). RESULTS: The distribution of ELN count between the Chinese registry ( n =7694) and SEER database ( n =21 332) was similar. With increasing ELN count, both cohorts exhibited significant proportional increases from node-negative to node-positive disease (SEER, OR, 1.012, P <0.001; Chinese registry, OR, 1.016, P =0.014) and serial improvements in OS (SEER: HR, 0.982; Chinese registry: HR, 0.975; both P <0.001) after controlling for confounders. Cut-point analysis showed an optimal threshold ELN count of 15, which was validated in the two cohorts, with the ability to properly discriminate probabilities of survival. CONCLUSIONS: A higher ELN count is associated with more precise nodal staging and better survival. Our results robustly conclude that 15 ELNs are the optimal cut-off point for evaluating the quality of lymph node examination and stratification of prognosis.

Neuroadaptive dynamic surface control for induction motors stochastic system based on reduced-order observer.

This paper studies an observer-based neural network position tracking control scheme for induction motors system operating under a field-oriented control scheme with the problem of stochastic disturbance. Firstly, the angular velocity is estimated by the constructed reduced-order observer. Then, the nonlinear functions are approximated by the neural networks and the stochastic Lyapunov functions are chosen to analyze the stability of the system. Besides, the "complexity of computation" existed in traditional backstepping control is solved by using the dynamic surface control technique. At last, the results of the comparison simulation experiments show that the proposed control scheme can reduce the influence of stochastic disturbance, and have faster tracking speed smaller tracking error. The designed observer can estimate the signals effectively.

The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma.

BACKGROUND: Competitive Endogenous RNA (ceRNA) may be closely associated with tumor progression. However, studies on ceRNAs and immune cells in LUAD are scarce. METHOD: The profiles of gene expression and clinical data of LUAD patients were extracted from the TCGA database. Bioinformatics methods were used to evaluate differentially-expressed genes (DEGs) and to form a ceRNA network. Preliminary verification of clinical specimens was utilized to detect the expressions of key biomarkers at the tissues. Cox and Lasso regressions were used to identify key genes, and prognosis prediction nomograms were formed. The mRNA levels of 9 genes in the risk score model in independent clinical LUAD samples were detected by qRT-PCR. The interconnection between the risk of cancer and immune cells was evaluated using the CIBERSORT algorithm, while the conformation of notable tumor-infiltrating immune cells (TIICs) in the LUAD tissues of the high and low risk groups was assessed using the RNA transcript subgroup in order to identify tissue types. Finally, co-expression study was used to examine the interconnection between the key genes in the ceRNA networks and the immune cells. RESULT: A ceRNA network of 115 RNAs was established, and nine key genes were identified to construct a Cox proportional-hazard model and create a prognostic nomogram. This risk-assessment model might serve as an independent factor to forecast the prognosis of LUAD, and it was consistent with the preliminary verification of clinical specimens. Survival analysis of clinical samples further validated the potential value of high risk groups in predicting LUAD prognosis. Five immune cells were identified with significant differences in the LUAD tissues of the high and low risk groups. Besides, two pairs of biomarkers associated with the growth of LUAD were found, i.e., E2F7 and macrophage M1 (R = 0.419, p = 1.4e- 08) and DBF4 and macrophage M1 (R = 0.282, p < 2.2 e- 16). CONCLUSION: This study identified several important ceRNAs, i.e. (E2F7 and BNF4) and TIICs (macrophage M1), which might be related to the development and prognosis of LUAD. The established risk-assessment model might be a potential tool in predicting LUAD of prognosis.

Experimental Study on the Resistance of Synthetic Penicillin Solid Lipid Nanoparticles to Clinically Resistant Staphylococcus aureus.

BACKGROUND: With the increasing resistance of antibiotics to bacteria, new and effective methods are needed to transform existing antibiotics to solve the problem of long development cycles for new drugs. The antibiotic nanodelivery system has proven to be a promising strategy. AIM: The purpose of this study is to synthesize penicillin solid lipid nanoparticles (penicillin SLNs) to enhance the antibacterial activity of penicillin against drug-resistant Staphylococcus aureus. MATERIALS AND METHODS: Penicillin SLNs were synthesized. And particle size, the polydispersity index (PI), and zeta potential (ZP) of penicillin SLNs were measured. The surface morphology of penicillin SLNs was observed using a transmission electron microscope. RESULTS: The particle size of penicillin SLNs is 112.3 ± 11.9 nm, the polydispersity index (PI) and zeta potential (ZP) of penicillin SLNs are 0.212 ± 0.03 and -27.6 ± 5.5 mV. The encapsulation efficiency and drug loading were 98.31 ± 1.2% and 4.98 ± 0.05 (%w/w), respectively. Penicillin SLNs had a more significant inhibitory effect on the growth of methicillin-sensitive Staphylococcus aureus (MSSA) after the drug and the bacteria were incubated for 12 hours. The number of MRSA colonies in the penicillin group increased after 12 hours, while the number of MRSA colonies in the penicillin SLNs group did not change significantly. CONCLUSION: Penicillin SLNs enhance the ability of penicillin to enter cells and increase the concentration of penicillin in the cell and also extend the residence time of penicillin in the cell. Our findings indicated that penicillin SLNs enhance the inhibitory effect of penicillin on drug-resistant Staphylococcus aureus.