Effects of multiple protection model in the operating room on physiological stress and risk events in patients undergoing coronary artery stent implantation.

OBJECTIVE: To analyze the impact of multiple protection model in the operating room on patients' physiological stress and risk events after coronary artery stent implantation (CASI). METHODS: During October 2021 to October 2022, 150 patients with coronary heart disease (CHD) were picked as the research subjects, all of whom underwent CASI. The clinical data were retrospectively analyzed, and the patients were divided into two groups according to different nursing methods, with 75 cases in each group. Patients in the intervention group received multiple protection model intervention in the operating room, and the patients in the control group adopted conventional care model. The patient satisfaction with nursing, postoperative recovery, psychological stress scores, physiological stress indicators, and adverse cardiac risk events were recorded. RESULTS: Patients in the intervention group had much higher percentage of the patient satisfaction with nursing than those in the control group (P < 0.05). The time to get out of bed and hospital stay was significantly shorter and the 6-min walking distance was markedly longer in the intervention group than the control (P < 0.05). The Hamilton Anxiety (HAMA) scale and Hamilton Depression (HAMD) scale score of patients in two groups were sharply decreased after the intervention (P < 0.05), which were strongly lower in the intervention group than the control (P < 0.001). After the intervention, the heart rate, cortisol and epinephrine of patients were all sensibly elevated in two groups (P < 0.05), which were all memorably lower in the intervention group than the control (P < 0.001). The incidence of adverse cardiac risk events in the intervention group was 5.33%, which was dramatically lower than 16.00% in the control group (P < 0.05). CONCLUSION: The application of multiple protection model in the operating room on patients undergoing coronary stent implantation promoted postoperative recovery, reduced patients' psychological and physiological stress, maintained blood pressure and other vital signs, reduced the incidence of adverse cardiac risk events, and improved the patient satisfaction with nursing.

Operation room nursing based on humanized nursing mode combined with nitric oxide on rehabilitation effect after lung surgery.

BACKGROUND: With advancements in the diagnosis and treatment of lung diseases, lung segment surgery has become increasingly common. Postoperative rehabilitation is critical for patient recovery, yet challenges such as complications and adverse outcomes persist. Incorporating humanized nursing modes and novel treatments like nitric oxide inhalation may enhance recovery and reduce postoperative complications. AIM: To evaluate the effects of a humanized nursing mode combined with nitric oxide inhalation on the rehabilitation outcomes of patients undergoing lung surgery, focusing on pulmonary function, recovery speed, and overall treatment costs. METHODS: A total of 79 patients who underwent lung surgery at a tertiary hospital from March 2021 to December 2021 were divided into a control group (n = 39) receiving a routine nursing program and an experimental group (n = 40) receiving additional humanized nursing interventions and atomized inhalation of nitric oxide. Key indicators were compared between the two groups alongside an analysis of treatment costs. RESULTS: The experimental group demonstrated significant improvements in pulmonary function, reduced average recovery time, and lower total treatment costs compared to the control group. Moreover, the quality of life in the experimental group was significantly better in the 3 months post-surgery, indicating a more effective rehabilitation process. CONCLUSION: The combination of humanized nursing mode and nitric oxide inhalation in postoperative care for lung surgery patients significantly enhances pulmonary rehabilitation outcomes, accelerates recovery, and reduces economic burden. This approach offers a promising reference for improving patient care and rehabilitation efficiency following lung surgery.

Exploring Ferroptosis-Associated Gene Signatures as Diagnostic and Therapeutic Targets for Sepsis-Induced Cardiomyopathy.

BACKGROUND: Sepsis-induced cardiomyopathy (SICM) is a severe complication of sepsis associated with high mortality rates. Despite its significance, the molecular mechanisms underlying SICM remain poorly understood, particularly the role of ferroptosis - a form of iron-dependent programmed cell death. METHODOLOGY: This study analyzed the GSE79962 dataset from the Gene Expression Omnibus, containing cardiac gene expression profiles from SICM patients and controls. A list of ferroptosis-related genes (FRGs) was retrieved from the FerrDb. We used the limma package in R for differential expression analysis, setting an adjusted P-value cutoff of <0.05 and a log2-fold change threshold of ±1 to identify differentially expressed ferroptosis-related genes (DE-FRGs). We applied machine learning algorithms for biomarker identification, including least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine with recursive feature elimination (SVM-RFE), implemented via the glmnet and e1071 packages in R, respectively. Gene set enrichment analysis (GSEA) was conducted using the GSEA package to investigate the biological pathways related to key DE-FRGs. RESULTS: After differential expression analysis, we identified 145 DE-FRGs. Functional enrichment analyses underscored the involvement of these genes in critical biological processes and pathways, such as lipid metabolism and insulin resistance. Machine learning approaches pinpointed five key DE-FRGs (NCOA4, GABARAPL1, GJA1, CISD1, CP), with strong predictive potential for SICM. Further analyses, including the construction of a ceRNA network, revealed intricate post-transcriptional regulatory mechanisms that may influence the expression of these key genes. CONCLUSIONS: Our findings highlight the central role of ferroptosis in SICM and identify potential biomarkers and therapeutic targets that could help refine diagnostic and treatment strategies. This study advances our understanding of the molecular underpinnings of SICM and sets the stage for future research aimed at mitigating this severe sepsis complication.

Effect of retrieval reward on episodic recognition with different difficulty: ERP evidence.

Previous studies found that the reward effect is stronger in more difficult retrieval tasks of item memory. However, it remains unclear whether the effect of reward is influenced by the memory task difficulty level in the source memory. We investigated the effects and neural mechanisms of the processing depth during encoding and rewards at retrieval on the item and source memory using event-related potentials (ERPs). Participants were required to carry out the congruity-judgment (deep processing) and size-judgment (shallow processing) tasks during encoding, and they completed separate object and background tests (half presented with reward) immediately after encoding. The results revealed that congruity-judgment (compare to size-judgment) task had longer response time in encoding phase, and evoked significantly greater reward differences at Prs (the hit rate minus the false alarm rate) in item retrieval, and the reward (relative to no reward) significantly improved recognition accuracy in source retrieval. ERP results also showed that congruity-judgment (compare to size-judgment) task evoked the larger N170, P3a, LPP and a decreased P3b of the stimuli in encoding phase, and elicited the wider distribution of LPC and LPN reward effects (i.e., the average amplitudes under the reward condition were significantly more positive than under the non-reward condition) in item retrieval, and the reward effects at FN400, LPC, and LPN were found only in the congruity-judged items with optimal difficulty in source retrieval. The results suggest that reward at retrieval evoked a greater boost in the congruity-judged stimuli, whether in item or source retrieval, which maybe be related to their optimal retrieval difficulty (Pr is closer to medium 0.50). This meant that the reward is more effective in memory retrieval with optimal difficulty.

Exploration of N6-Methyladenosine Profiles of mRNAs and the Function of METTL3 in Atherosclerosis.

OBJECTIVES: N6-methylladenosine (m6A) modification has not been fully studied in atherosclerosis. The objectives of this study were to investigate differentially expressed m6A methylated peaks and mRNAs, along with the regulatory role of methyltransferase 3 (METTL3) in pathological processes of atherosclerosis. METHODS: The pathological models of human coronary artery smooth muscle cells (HCASMCs) were induced in vitro. The differentially expressed mRNAs and m6A peaks were identified by RNA-Seq and meRIP-Seq. The potential mechanisms were analyzed via bioinformatic assays. Methylases expression was tested by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting (WB) in HCASMCs, and by immunohistochemical assays in 40 human coronary arteries. The knockdown of METTL3 expression in cells was performed by siRNA transfection, and cell proliferation and migration were detected after transfection. RESULTS: We identified 5121 m6A peaks and 883 mRNAs that were expressed differentially in the pathological processes of HCASMCs. Bioinformatic analyses showed that the different m6A peaks were associated with cell growth and cell adhesion, and the 883 genes showed that the extracellular matrix and PI3K/AKT pathway regulate the processes of HCASMCs. Additionally, 10 hub genes and 351 mRNAs with differential methylation and expression levels were found. METTL3 was upregulated in the arteries with atherosclerotic lesions and in the proliferation and migration model of HCASMCs, and pathological processes of HCASMCs could be inhibited by the knockdown of METTL3. The mechanisms behind regulation of migration and proliferation reduced by siMETTL3 are concerned with protein synthesis and energy metabolism. CONCLUSIONS: These results revealed a new m6A epigenetic method to regulate the progress of atherosclerosis, which suggest approaches for potential therapeutic interventions that target METTL3 for the prevention and treatment of coronary artery diseases.

Airport route development strategy planning and performance measurement with a dynamic performance management framework.

Route development programs have become popular with airports worldwide to enhance air connectivity. Enhanced air connectivity of an airport has been found to have a positive and significant impact on the competitiveness and attractiveness of the airport and the regional economy in which the airport is located. However, the drivers behind route development programs and their performance are not always clear; this has been less explored in the literature. In this paper, a dynamic performance management approach is taken to build a modeling framework in which key drivers affecting route development performance and strategic resources affecting key drivers are identified. Route-level planning is used in an empirical study to demonstrate the dynamic mechanism of airport route development initiatives and performance measurements. The proposed framework can not only provide performance monitoring, but also suggest suitable indicators to evaluate the performance for policymakers in future airport route development.

Encoding tasks moderated the reward effect on brain activity during memory retrieval.

Previous studies have explored the effects of retrieval reward and depth of processing in encoding on recognition, but it remains unclear whether and how reward and depth of processing during encoding influence recognition. We investigated the effect and neural mechanisms of encoding reward and processing depth on recognition using event-related potentials (ERPs) in this study. In the study phase, participants were asked to perform two encoding tasks: congruity-judgment (deep processing) and size-judgment (shallow processing) in reward and no-reward conditions. The test phases included object (item) and background (source) tests. The results of item retrieval showed that the accuracy of rewarded items was higher than that of unrewarded items only in the congruity-judgment task, and the reward effect (the average amplitudes in the reward condition were significantly more positive than those in the no-reward condition) in the 300-500 and 500-700 ms were greater in the congruity-judgment task than in the size-judgment task. The results of source retrieval showed that the accuracy of rewarded items was higher than that of unrewarded items, that the difference in the size-judgment task was significantly larger, and that the reward effect in the 300-500 and 500-700 ms were greater in the size-judgment task than in the congruity-judgment task. In conclusion, the encoding task moderated the reward effect in item and source memory.

The Effects of Reward on Associative Memory Depend on Unitization Depths.

Previous studies have found that reward effect is stronger for more difficult to retrieve items, but whether this effect holds true for the associative memory remains unclear too. We investigated the effects and neural mechanisms of the different unitization depths and reward sets on encoding associative memory using event-related potentials (ERPs), which were recorded through a Neuroscan system with a 64-channel electrode cap according to the international 10-20 system, and five electrodes (Fz, FCz, Cz, CPz, and Pz) were selected for analysis. Thirty healthy college students took part in this study. During encoding, participants were carried out two encoding tasks, a congruity-judgment task with high unitization and a color-judgment task with low unitization, with half of the items rewarded. The test phase was conducted immediately after the encoding phase. The results for false alarm rates and Prs (i.e., hit rates for old pairs minus false alarm rates for new pairs) in relational retrieval revealed that the reward differences in the color-judgment task were greater than those in the congruity-judgment task. The ERP results further showed significant reward effects (i.e., the reward significantly improved the average amplitudes compared to no reward) at P300 (300-500 ms) and LPP (500-800 ms) in the color-judgment task both for intact and rearranged items, and the reward effects at LPP (electrodes Fz, FCz, Cz, CPz, and Pz) were distributed more widely than the reward effects at P300 (electrodes Fz and FCz) in the color-judgment task. These results suggest that reward provided a greater boost when retrieving associative memory of low unitized items.

DL-SMILES#: A Novel Encoding Scheme for Predicting Compound Protein Affinity Using Deep Learning.

INTRODUCTION: Drug repositioning aims to screen drugs and therapeutic goals from approved drugs and abandoned compounds that have been identified as safe. This trend is changing the landscape of drug development and creating a model of drug repositioning for new drug development. In the recent decade, machine learning methods have been applied to predict the binding affinity of compound proteins, while deep learning is recently becoming prominent and achieving significant performances. Among the models, the way of representing the compounds is usually simple, which is the molecular fingerprints, i.e., a single SMILES string. METHODS: In this study, we improve previous work by proposing a novel representing manner, named SMILES#, to recode the SMILES string. This approach takes into account the properties of compounds and achieves superior performance. After that, we propose a deep learning model that combines recurrent neural networks with a convolutional neural network with an attention mechanism, using unlabeled data and labeled data to jointly encode molecules and predict binding affinity. RESULTS: Experimental results show that SMILES# with compound properties can effectively improve the accuracy of the model and reduce the RMS error on most data sets. CONCLUSION: We used the method to verify the related and unrelated compounds with the same target, and the experimental results show the effectiveness of the method.

A High-Efficiency Fatigued Speech Feature Selection Method for Air Traffic Controllers Based on Improved Compressed Sensing.

Air traffic controller fatigue has recently received considerable attention from researchers because it is one of the main causes of air traffic incidents. Numerous research studies have been conducted to extract speech features related to fatigue, and their practical utilization has achieved some positive detection results. However, there are still challenges associated with the applied speech features usually being of high dimension, which leads to computational complexity and inefficient fatigue detection. This situation makes it meaningful to reduce the dimensionality and select only a few efficient features. This paper addresses these problems by proposing a high-efficiency fatigued speech selection method based on improved compressed sensing. For adapting a method to the specific field of fatigued speech, we propose an improved compressed sensing construction algorithm to decrease the reconstruction error and achieve superior sparse coding. The proposed feature selection method is then applied to optimize the high-dimension fatigued speech features based on the fractal dimension. Finally, a support vector machine classifier is applied to a series of comparative experiments using the Civil Aviation Administration of China radiotelephony corpus to demonstrate that the proposed method provides a significant improvement in the precision of fatigue detection compared with current state-of-the-art approaches.

CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction.

The binding affinity of small molecules to receptor proteins is essential to drug discovery and drug repositioning. Chemical methods are often time-consuming and costly, and models for calculating the binding affinity are imperative. In this study, we propose a novel deep learning method, namely CSConv2d, for protein-ligand interactions' prediction. The proposed method is improved by a DEEPScreen model using 2-D structural representations of compounds as input. Furthermore, a channel and spatial attention mechanism (CS) is added in feature abstractions. Data experiments conducted on ChEMBLv23 datasets show that CSConv2d performs better than the original DEEPScreen model in predicting protein-ligand binding affinity, as well as some state-of-the-art DTIs (drug-target interactions) prediction methods including DeepConv-DTI, CPI-Prediction, CPI-Prediction+CS, DeepGS and DeepGS+CS. In practice, the docking results of protein (PDB ID: 5ceo) and ligand (Chemical ID: 50D) and a series of kinase inhibitors are operated to verify the robustness.

SE-OnionNet: A Convolution Neural Network for Protein-Ligand Binding Affinity Prediction.

Deep learning methods, which can predict the binding affinity of a drug-target protein interaction, reduce the time and cost of drug discovery. In this study, we propose a novel deep convolutional neural network called SE-OnionNet, with two squeeze-and-excitation (SE) modules, to computationally predict the binding affinity of a protein-ligand complex. The OnionNet is used to extract a feature map from the three-dimensional structure of a protein-drug molecular complex. The SE module is added to the second and third convolutional layers to improve the non-linear expression of the network to improve model performance. Three different optimizers, stochastic gradient descent (SGD), Adam, and Adagrad, were also used to improve the performance of the model. A majority of protein-molecule complexes were used for training, and the comparative assessment of scoring functions (CASF-2016) was used as the benchmark. Experimental results show that our model performs better than OnionNet, Pafnucy, and AutoDock Vina. Finally, we chose the macrophage migration inhibitor factor (PDB ID: 6cbg) to test the stability and robustness of the model. We found that the prediction results were not affected by the docking position, and thus, our model is of acceptable robustness.

MiR-889 promotes cell growth in human non-small cell lung cancer by regulating KLF9.

Currently, non-small cell lung cancer (NSCLC) is still the most common malignancy worldwide. Although miR-889 has been reported to play an important role in various malignancies, the physiological function of miR-889 in NSCLC remains unknown. This paper places emphasis on the influence of miR-889 on the development and progression of non-small cell lung cancer. To detect the expression level of miR-889 in NSCLC tissues and cell lines, quantitative real-time polymerase chain reaction (qRT-PCR) assay and In Situ Hybridization (ISH) were adopted in this study. Cell proliferation and colony forming ability were examined by Cell Counting Kit-8 (CCK-8) and colony formation assays. Furthermore, transwell experiments were conducted to determine the influence of miR-889 on migration. KLF9 expression was evaluated by qRT-PCR and Western blotting. First, miR-889 expression was increased in the cancer tissues of non-small cell lung cancer patients (n = 40) compared with adjacent tissues. Subsequently, knockdown of miR-889 significantly inhibited cell proliferation and migration, while overexpression of miR-889 had the opposite effect. KLF9 may be a potential target of miR-889. In addition, upregulation of miR-889 promotes tumorigenesis in vitro, and KLF9 protein levels are also reduced. The current study suggests that miR-889 may play a potential therapeutic role for NSCLC by targeting KLF9 to control NSCLC proliferation and migration.

A measure of identifying influential waypoints in air route networks.

As the basic carrier of air flight operation, air route network (ARN) is of great significance to the smooth operation of flights. However, the waypoint is a core part of the route, so it is an important topic to identify influential waypoints in ARN. In this paper, a method to identify the influence of the node in ARN based on an improved entropy weight (IEW) method is proposed. Then, centrality measures including degree, closeness, betweenness and eigenvector as the multi-attribute of ARN in IEW application. IEW method is used to aggregate the multi-attribute to obtain the evaluation of the influence of each waypoint. To demonstrate the effectiveness of the IEW method, three real ARNs are selected to conduct several experiments with susceptible infected recovered (SIR) model. The results show the efficiency and practicability of the proposed method.

Total endoscopic repair of atrial septal defect under on-pump beating heart.

BACKGROUND: We previously reported the techniques for total endoscopic atrial septal defect (ASD) repair on hearts arrested with cardioplegia through three small incisions in the chest wall without aid of a surgical robotic system. The optimal results motivated us to use total thoracoscopic technology for ASD on perfused beating hearts. METHODS: From 2010 to 2017, 161 patients with a mean age of 28.31±12.34 years who underwent non-robotically assisted total thoracoscopic closure for ASD were included in this study, and those patients were also divided into two groups, including group A and group B. In group A, 115 patients underwent the procedure on beating hearts without aorta cross-clamped; in group B, 46 patients underwent the procedure on hearts arrested with cardioplegia with aorta cross-clamped. Cardiopulmonary bypass (CPB) was peripherally achieved as well. RESULTS: Total thoracoscopic ASD closures were successfully performed without in-hospital mortality or other serious complications in all patients of both groups. Dacron or bovine patches were used in 81 and 32 patients in the two groups, respectively. Duration of operation, duration of CPB, aorta cross-clamped time, duration of mechanical ventilation, the length of intensive care unit (ICU) and post-operative hospital stay in group A, were all shorter than those in group B (P<0.05). There was no statistically significant difference in blood transfusion during operation or post-operation thoracic drainage. During follow-up, echocardiograms at 3, 30, 90 and 365, showed no residual shunt or tricuspid regurgitation. CONCLUSIONS: Total thoracoscopic closure of ASD without assistance of a surgical robotic system on beating heart is safe and feasible and can be used as a therapeutic option for ASD, and by using the mentioned technique, less injuries are applied to patients.

MiR-155 inhibits proliferation and invasion by directly targeting PDCD4 in non-small cell lung cancer.

BACKGROUND: MicroRNAs are often abnormally expressed in human non-small cell lung cancer (NSCLC) and are thought to play a critical role in the emergence or maintenance of NSCLC by binding to its target messenger RNA. We assessed the effects of miR-155 on cell proliferation and invasion to elucidate the role played by miR-155/PDCD4 in NSCLC. METHODS: Quantitative reverse transcription-PCR, Western blotting, and cell counting kit-8, luciferase, and transwell invasion assays were conducted on a normal human bronchial epithelial cell line (BEAS-2B) and three NSCLC cell lines (SPC-A-1, A549, and H2170). RESULTS: We confirmed that miR-155 was upregulated, while PDCD4 messenger RNA and protein levels were downregulated in NSCLC cell lines. miR-155 negatively regulated PDCD4 at both transcriptional and post-transcriptional levels. Moreover, PDCD4 was forecast as an assumed target of miR-155 using bioinformatic methods and we demonstrated that PDCD4 was a direct target of miR-155 using luciferase reporter assays. Furthermore, PDCD4 overexpression could restrain NSCLC proliferation and invasion induced by miR-155. CONCLUSION: Our results collectively demonstrate that miR-155 exerts an oncogenic role in NSCLC by directly targeting PDCD4.

Association of ARHGAP18 polymorphisms with schizophrenia in the Chinese-Han population.

Numerous developmental genes have been linked to schizophrenia (SZ) by case-control and genome-wide association studies, suggesting that neurodevelopmental disturbances are major pathogenic mechanisms. However, no neurodevelopmental deficit has been definitively linked to SZ occurrence, likely due to disease heterogeneity and the differential effects of various gene variants across ethnicities. Hence, it is critical to examine linkages in specific ethnic populations, such as Han Chinese. The newly identified RhoGAP ARHGAP18 is likely involved in neurodevelopment through regulation of RhoA/C. Here we describe four single nucleotide polymorphisms (SNPs) in ARHGAP18 associated with SZ across a cohort of >2000 cases and controls from the Han population. Two SNPs, rs7758025 and rs9483050, displayed significant differences between case and control groups both in genotype (P = 0.0002 and P = 7.54×10-6) and allelic frequencies (P = 4.36×10-5 and P = 5.98×10-7), respectively. The AG haplotype in rs7758025-rs9385502 was strongly associated with the occurrence of SZ (P = 0.0012, OR = 0.67, 95% CI = 0.48-0.93), an association that still held following a 1000-times random permutation test (P = 0.022). In an independently collected validation cohort, rs9483050 was the SNP most strongly associated with SZ. In addition, the allelic frequencies of rs12197901 remained associated with SZ in the combined cohort (P = 0.021), although not in the validation cohort alone (P = 0.251). Collectively, our data suggest the ARHGAP18 may confer vulnerability to SZ in the Chinese Han population, providing additional evidence for the involvement of neurodevelopmental dysfunction in the pathogenesis of schizophrenia.

An atomically thin layer of Ru/MoS2 heterostructure: structural, electronic, and magnetic properties.

The fabrication of a transition metal (TM) atomically thin layer with robust ferromagnetic ordering (FM) for the continuous miniaturization of spintronic and quantum computing devices is desired. Through first-principles calculations, we establish that Ru atoms can be epitaxially aligned on MoS2 monolayers, thus forming an atomically thin layer of 2D Ru/MoS2 heterostructure with high structural stability. The Ru layer possesses a robust FM (more than 300 K) and an out-of-plane easy axis with the magnetic anisotropy energy (MAE) of ∼3.4 meV per atom. In particular, we find that the FM can be switched by an external electric field (Efield) of 1.5 V nm-1. We propose that this atomically thin layer of Ru/MoS2 heterostructure can be used as an alternative candidate for free-standing magnetic TM layers and provides new possibilities to design 2D spintronic devices.

Interleukin 18 promotes myofibroblast activation of valvular interstitial cells.

BACKGROUND: Calcific aortic valve disease is the main heart valve disease in the elderly. Valvular interstitial cells (VICs) play an important role in the process of valve calcification. Interleukin 18 (IL-18) is expressed in stenosis aortic valves and is positively related with the clinical severity of aortic stenosis. However, the role of IL-18 in aortic valve calcification remains unclear. This study examined whether IL-18 promotes myofibroblast and/or osteoblast transdifferention of VICs. Porcine VICs were isolated and treated with recombinant porcine IL-18. METHODS: Porcine VICs were cultured and treated with IL-18. Gene and protein expression of myofibroblastic and osteoblastic markers were tested and nuclear factor κB (NF-κB) phosphorylation was also analyzed. Alkaline phosphatase (ALP) staining and activity assay were also performed. RESULTS: Our experiments demonstrated that IL-18 significantly enhanced alpha-smooth muscle actin (α-SMA) gene and protein expression. IL-18 treatment also promoted the expression of osteopontin (OPN) and runt-related transcription factor 2 (Runx2) mRNA, although OPN and Runx2 protein expressions were not changed. IL-18 could induce ALP activity in the presence of conditioning medium. We also demonstrated that IL-18 markedly enhanced NF-κB p65 phosphorylation in VICs. CONCLUSIONS: Together these results suggest that IL-18 promotes the myofibroblast differentiation of VICs and accelerates calcification in the presence of conditioning medium via the NF-κB pathway.

Essential role of STX6 in esophageal squamous cell carcinoma growth and migration.

Abnormalities in endosomes, or dysregulation in their trafficking, play an important role directly in many diseases including oncogenesis. Syntaxin-6 (STX6) is involved in diverse cellular functions in a variety of cell types and has been shown to regulate many intracellular membrane trafficking events such as endocytosis, recycling and anterograde and retrograde trafficking. However, its expression pattern and biological functions in esophageal squamous cell carcinoma (ESCC) remained unknown. Here, we have found that the expression of STX6 was up-regulated in ESCC samples, its expression was significantly correlated with tumor size, histological differentiation, lymph node metastasis and depth. On one hand, STX6 silencing inhibited ESCC cells viability and proliferation in a p53-dependent manner. On the other hand, STX6 effect integrin trafficking and regulate ESCC cells migration. Taken together, our study revealed the oncogenic roles of STX6 in the progression of ESCC, and it might be a valuable target for ESCC therapy.