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The paper aims to return to the structural linguistics of Ferdinand de Saussure to examine the application of the structural linguistic terminologies in Lacanian psychoanalysis and the critique of ideology by Slavoj Žižek. First, the author examines Saussure’s structural linguistics terminologies in his book Course in General Linguistics. Then, the differences between its original definitions and their application in Lacanian psychoanalysis and the critique of the ideology of Slavoj Žižek are compared. The author found that although the French psychoanalyst Jacques Lacan used various linguistic terminologies that are initially from Saussure’s structural linguistics, he radically rewrote those concepts and perfectly “quilt” them into his theory of psychoanalysis. Besides, Slovenian philosopher Slavoj Žižek carefully examined the Lacanian linguistic view and applied it to the critique of ideology. Indeed, many correlations between Lacanian linguistic terminologies and Saussure’s terminologies in his structural linguistics have been fully concerned by scholars around the world. Nevertheless, from the author’s point of view, it is essential for people nowadays who would like to examine contemporary philosophy deeply, psychoanalysis as well as the critique of ideology to return to Saussure’s book and carefully examine the original forms of the linguistic terms. Thus, this paper mainly focuses on the idea of Sassure’s structural linguistics to give readers some new inspiration by tracing the origin of structural linguistic terms.

Background For the study, we determine the potential biomarkers and uncover the regulatory mechanisms of lncRNA MALAT1 / miR-145 / SOX9 axis on the abilities of cell growth and cell metastasis of colorectal cancer. Methods Previously published dataset GSE18105 from GEO database was used for microarray analysis to identify differential-expressed lncRNAs and mRNAs. The miRNA which had targeted relationships with both lncRNA and mRNA was predicted using miRCode and Targetscan. The association between lncRNA and miRNA, miRNA and mRNA was verified using dual-luciferase reporter assay. Expression levels of lncRNA MALAT1, miR-145 and SOX9 were examined by quantitative RT-PCR analysis. The cell viability of two cancer cell lines was compared by CCK-8 assay. Colony formation was hired to detected cell proliferation. The cell cycle distribution and apoptotic cell rate were conducted by flow cytometry assay. Wound healing as well as transwell assay were compare the cell migration and cell invasion respectively among groups. The effect of MALAT1 on colorectal cancer in vivo was constructed by xenograft model. Results Significantly dysregulated lncRNAs and mRNAs were identified by microarray analysis. By experimental verification, MALAT1 and SOX9 were expressed in a high percentage of colorectal cancer tumors and cells, while miR-145 was in a low expression. We also identified miR-145 as a target of MALAT1 and SOX9 . MALAT1 played a role in regulating cancer process by functioning as a competing endogenous RNA. Silencing MALAT1 could effectively decrease the expression level of SOX9 , thus suppress cell viability and metastasis. Down-regulated MALAT1 could induce resistance of G1 phase in cell cycle, and facilitation of colorectal cancer cell apoptosis. Nude mice injected with cells transfected with si-MALAT1 had smaller tumor on size and weight. Conclusions The regulatory function of lncRNA MALAT1 / miR-145 / SOX9 axis was revealed in colorectal cancer based on bioinformatics analysis. LncRNA MALAT1 could facilitate colorectal cancer cell proliferation, invasion and migration by down-regulating miR-145 and up-regulating SOX9 . LncRNA MALAT1 could suppress cell cycle and apoptosis through MALAT1 / miR-145 / SOX9 axis.

A hub motor is an effective drive system for Battery Electric Vehicles (BEVs). However, due to limitations on packaging and cost, there are few applications in which hub motors are taken as the only actuators for a brake vehicle. Most applications involve a Regenerative Braking System (RBS) combined with a Hydraulic Braking System (HBS). In this paper, a top hierarchy Advanced Emergency Braking System (AEBS) controller is designed in Matlab/Simulink and State-flow, including functionalities of basic emergency braking, brake force distribution between front and rear wheels, anti-lock braking and coordination between RBS and HBS based on Model Predictive Control (MPC); a Seven Degrees of Freedom (DOF) BEV chassis model is constructed and rear-end crash test scenarios are created in Carsim with a high and low road adhesion coefficient. A series of comparison tests show that not only are the stopping distances between the ego vehicle and target vehicle shorter, but also the braking torques, longitudinal slip ratio and rotation speed of each wheel are well controlled without wheel locking. To sum up, in addition to meeting the AEBS requirements of avoiding a rear-end collision, the control strategy developed in this paper also levels up braking performance and enhances vehicle stability on both high-mu and low-mu roads for BEVs driven by a hub motor independently.

Myocarditis, a life-threatening disease that can result in cardiac arrest and sudden cardiac death, has garnered significant attention in recent years. This review provides a comprehensive overview of the management of myocarditis-related sudden cardiac death, encompassing its pathology, diagnostic methods, therapeutic strategies, preventive measures, prognostic factors, and risk stratification. Additionally, the review highlights current challenges and future directions in this field. The aim is to enhance understanding of myocarditis-related sudden cardiac death and inform clinical practice, ultimately leading to improved patient outcomes.

Epidermal growth factor receptor (EGFR) mutations are the strongest response predictors to EGFR tyrosine kinase inhibitors (TKI) therapy, but knowledge of the EGFR mutation frequency on lung adenocarcinoma is still limited to retrospective studies. The PIONEER study (NCT01185314) is a prospective molecular epidemiology study in Asian patients with newly diagnosed advanced lung adenocarcinoma, aiming to prospectively analyze EGFR mutation status in IIIB/IV treatment-naïve lung adenocarcinomas in Asia. We report the mainland China subset results. Eligible patients (≥20 yrs old, IIIB/IV adenocarcinoma and treatment-naïve) were registered in 17 hospitals in mainland China. EGFR was tested for mutations by amplification refractory mutation system using biopsy samples. Demographic and clinical characteristics were collected for subgroup analyses. A total of 747 patients were registered. Successful EGFR mutation analysis was performed in 741, with an overall mutation rate of 50.2%. The EGFR active mutation rate is 48.0% (with 1.3% of combined active and resistance mutations). Tobacco use (>30 pack-year vs. 0-10 pack-year, OR 0.27, 95%CI: 0.17-0.42) and regional lymph nodes involvement (N3 vs. N0, OR 0.47, 95%CI: 0.29-0.76) were independent predictors of EGFR mutation in multivariate analysis. However, even in regular smokers, the EGFR mutation frequency was 35.3%. The EGFR mutation frequency was similar between diverse biopsy sites and techniques. The overall EGFR mutation frequency of the mainland China subset was 50.2%, independently associated with the intensity of tobacco use and regional lymph nodes involvement. The relatively high frequency of EGFR mutations in the mainland China subset suggest that any effort to obtain tissue sample for EGFR mutation testing should be encouraged.

Objective Through the investigation of the current situation of bladder cancer secondary electrotomy performed by urologists in China, it provides reference for further improvement and improvement of diagnosis and treatment norms. Methods From September 3, 2023 to October 7, 2023, questionnaires compiled by researchers were distributed and collected from urologists across the country in the form of electronic questionnaires through the questionnaire Star platform; The questionnaire data were exported online using SPSS 26.0 software (SPSS Inc, Chicago, IL, USA) and R language (R Foundation for Statistical Computing, Vienna, Austria, Austria). Version 4.2.1) for data analysis. Count data were described by percentages, and comparisons between groups were made by chi-square test or Fisher’s exact test. Logistic regression was used to screen out the influencing factors related to the status of secondary electrotomy for bladder cancer performed by Chinese urologists and to construct a predictive model for the column-line diagram. ROC curves, calibration curves, and DCA curves were plotted to evaluate the model and validate its efficacy. Results A total of 514 valid questionnaires were returned. 77.2% (397/514) of the physicians interviewed were from tertiary care hospitals. 21.2% (109/514) were from secondary care hospitals. The acceptance rate of secondary electrosurgical resection of bladder cancer among Chinese urologists was 87.74%, with 12.26% still opposed to the procedure.The majority of respondents believed that secondary electroresection could be performed if the indications recommended by the guidelines were met (75%), while a significant number felt that the initial electroresection was complete and did not require a second (37.74%), or they decided whether to perform a secondary electroresection based on their clinical experience (40.27%). Conclusion Survey results indicate that secondary transurethral resection enhances staging accuracy, eliminates residual lesions, and decreases recurrence and progression rates. However, it serves as a means to compensate for shortcomings in the initial resection. Advances in NMIBC treatment techniques assist in reducing or avoiding the need for secondary transurethral resection in bladder cancer cases. This study is the first to develop a predictive model for Chinese urologists’ acceptance of secondary transurethral resection for bladder cancer and analyzes their perspectives on the procedure, offering a reference for future research.

This paper empirically examines the spatial correlation differences and mechanisms of housing prices in prefecture-level cities, considering the influence of administrative boundaries. Using an extended spatial Durbin model and panel data from 292 prefecture-level cities in China between 2000 and 2013, the study identifies the attributes and stage characteristics of real estate. The results indicate a significant spatial correlation in housing prices between neighboring prefecture-level cities, with inter-provincial administrative boundaries reducing the spatial correlation between these cities by 62.11%. Further research reveals significant changes in the spatial correlation of housing prices following the 2007 subprime mortgage crisis, with the transformation of real estate’s dominant attributes being the primary reason for these changes.

Introduction Hepatocellular carcinoma (HCC) is characterized by the complex pathogenesis, limited therapeutic methods, and poor prognosis. Endoplasmic reticulum stress (ERS) plays an important role in the development of HCC, therefore, we still need further study of molecular mechanism of HCC and ERS for early diagnosis and promising treatment targets. Method The GEO datasets (GSE25097, GSE62232, and GSE65372) were integrated to identify differentially expressed genes related to HCC (ERSRGs). Random Forest (RF) and Support Vector Machine (SVM) machine learning techniques were applied to screen ERSRGs associated with endoplasmic reticulum stress, and an artificial neural network (ANN) diagnostic prediction model was constructed. The ESTIMATE algorithm was utilized to analyze the correlation between ERSRGs and the immune microenvironment. The potential therapeutic agents for ERSRGs were explored using the Drug Signature Database (DSigDB). The immunological landscape of the ERSRGs central gene PPP1R16A was assessed through single-cell sequencing and cell communication, and its biological function was validated using cytological experiments. Results An ANN related to the ERS model was constructed based on SRPX, THBS4, CTH, PPP1R16A, CLGN, and THBS1. The area under the curve (AUC) of the model in the training set was 0.979, and the AUC values in three validation sets were 0.958, 0.936, and 0.970, respectively, indicating high reliability and effectiveness. Spearman correlation analysis suggests that the expression levels of ERSRGs are significantly correlated with immune cell infiltration and immune-related pathways, indicating their potential as important targets for immunotherapy. Mometasone was predicted to be the most promising treatment drug based on its highest binding score. Among the six ERSRGs, PPP1R16A had the highest mutation rate, predominantly copy number mutations, which may be the core gene of the ERSRGs model. Single-cell analysis and cell communication indicated that PPP1R16A is predominantly distributed in liver malignant parenchymal cells and may reshape the tumor microenvironment by enhancing macrophage migration inhibitory factor (MIF)/CD74 + CXCR4 signaling pathways. Functional experiments revealed that after siRNA knockdown, the expression of PPP1R16A was downregulated, which inhibited the proliferation, migration, and invasion capabilities of HCCLM3 and Hep3B cells in vitro. Conclusion The consensus of various machine learning algorithms and artificial intelligence neural networks has established a novel predictive model for the diagnosis of liver cancer associated with ERS. This study offers a new direction for the diagnosis and treatment of HCC.

The coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2, has affected millions of people worldwide. The omicron variant is currently the predominant strain circulating worldwide. Serum apolipoprotein A1 (ApoA1) is linked to endothelial cell injury and serves as a valuable biomarker for monitoring the progression of inflammation in infected individuals. However, the potential roles of ApoA1 in the context of the omicron variant remain elusive. To investigate the prognostic value of serum ApoA1 levels at diagnosis, using mortality rate as the primary evaluation indicator, we performed a 65-day monitoring and retrospectively analyzed a cohort of 237 individuals diagnosed with omicron. Patients were categorized into two groups based on their ApoA1 levels, high and low. The Kaplan-Meier method was employed to assess overall survival (OS), while the log-rank test was utilized for comparative analysis between the groups. Additionally, both univariate and multivariate Cox proportional hazards models were applied to evaluate the prognostic significance of ApoA1 levels. Our results indicated that ApoA1 levels were significantly reduced in patients infected with the omicron variant. Notably, ApoA1 levels in severe cases were lower than those in mild-to-moderate cases, with this difference reaching statistical significance. Additionally, we observed a significant increase in C-reactive protein (CRP) and beta-2 microglobulin (β2-MG) levels in individuals with decreased ApoA1 levels. Furthermore, patients with reduced ApoA1 levels exhibited a statistically significant decline in OS ( = 0.001). A decreased ApoA1 level (< 0.87 g/L) was identified as an independent adverse prognostic factor for OS in omicron patients, as determined by multivariate cox proportional hazards regression analysis ( = 0.035). The serum ApoA1 level at the initial diagnosis was significantly correlated with the severity and prognosis of omicron infections. Therefore, we propose that decreased levels of ApoA1 may serve as an independent negative prognostic factor in patients infected with omicron.

Acquired and intrinsic resistance to sunitinib is a major obstacle to improving the therapeutic efficacy of treatment for clear cell renal cell carcinoma (ccRCC). This study aimed to identify novel therapeutic targets and the potential molecular mechanisms to overcome sunitinib resistance in ccRCC. Utilizing genome-wide CRISPR/Cas9 screening and resistant transcriptomics, we identified that prostaglandin reductase 2 (PTGR2) is a novel therapeutic target to overcome sunitinib resistance in ccRCC. The silencing of PTGR2 enhanced the cytotoxic effects of sunitinib in ccRCC cells, as measured by cell viability assays, and suppressed tumor growth in xenograft models. Mechanistically, PTGR2 physically interacts with lysine specific demethylase 6A (KDM6A) via endogenous/exogenous co-immunoprecipitation. PTGR2 knockdown reduced KDM6A protein expression, while KDM6A overexpression partially reversed the sensitization effect of PTGR2 silencing, suggesting KDM6A is a major downstream effector. Our findings establish the PTGR2-KDM6A axis as a potential target for overcoming sunitinib resistance in ccRCC. Pharmacological inhibition of PTGR2 or targeted modulation of KDM6A activity represents a promising combination strategy to overcome sunitinib resistance and improve patient outcomes.