MiR-92a-2-5p suppresses esophageal squamous cell carcinoma cell proliferation and invasion by targeting PRDX2.

MicroRNAs (miRNAs) can function as negative regulators of gene expression by binding to the 3'-untranslated region (3'-UTR) of target genes. The aberrant expression of miRNAs in neoplasm is extensively associated with tumorigenesis and cancer progression, including esophageal squamous cell carcinoma (ESCC). Our previous investigation has identified the oncogenic roles of Peroxiredoxin2 (PRDX2) in ESCC progression; however, its upstream regulatory mechanism remains to be elucidated. By merging the prediction results from miRWalk2.0 and miRNA differential expression analysis results based on The Cancer Genome Atlas Esophageal Carcinoma (TCGA-ESCA) database, eight miRNA candidates were predicted to be the potential regulatory miRNAs of PRDX2, followed by further identification of miR-92a-2-5p as the putative miRNA of PRDX2. Subsequent functional studies demonstrated that miR-92a-2-5p can suppress ESCC cell proliferation and migration, as well as tumor growth in subcutaneous tumor xenograft models, which might be mediated by the suppression of AKT/mTOR and Wnt3a/ß-catenin signaling pathways upon miR-92a-2-5p mimic transfection condition. These data revealed the tumor suppressive functions of miR-92a-2-5p in ESCC by targeting PRDX2.

Leveraging a disulfidptosis-related signature to predict the prognosis and immunotherapy effectiveness of cutaneous melanoma based on machine learning.

BACKGROUND: Disulfidptosis is a recently discovered programmed cell death pathway. However, the exact molecular mechanism of disulfidptosis in cutaneous melanoma remains unclear. METHODS: In this study, clustering analysis was performed using data from public databases to construct a prognostic model, which was subsequently externally validated. The biological functions of the model genes were then investigated through various experimental techniques, including qRT-PCR, Western blotting, CCK-8 assay, wound healing assay, and Transwell assay. RESULTS: We constructed a signature using cutaneous melanoma (CM) data, which accurately predicts the overall survival (OS) of patients. The predictive value of this signature for prognosis and immune therapy response was validated using multiple external datasets. High-risk CM subgroups may exhibit decreased survival rates, alterations in the tumor microenvironment (TME), and increased tumor mutation burden. We initially verified the expression levels of five optimum disulfidptosis-related genes (ODRGs) in normal tissues and CM. The expression levels of these genes were further confirmed in HaCaT cells and three melanoma cell lines using qPCR and protein blotting analysis. HLA-DQA1 emerged as the gene with the highest regression coefficient in our risk model, highlighting its role in CM. Mechanistically, HLA-DQA1 demonstrated the ability to suppress CM cell growth, proliferation, and migration. CONCLUSION: In this study, a novel signature related to disulfidptosis was constructed, which accurately predicts the survival rate and treatment sensitivity of CM patients. Additionally, HLA-DQA1 is expected to be a feasible therapeutic target for effective clinical treatment of CM.

High-Performance Reversible Furan-Maleimide Resins Based on Furfuryl Glycidyl Ether and Bismaleimides.

Two reversible furan-maleimide resins, in which there are rigid -Ph-CH2-Ph- structures and flexible -(CH2)6- structures in bismaleimides, were synthesized from furfuryl glycidyl ethers (FGE), 4,4'-diaminodiphenyl ether (ODA), N,N'-4,4'-diphenylmethane-bismaleimide (DBMI), and N,N'-hexamethylene-bismaleimide (HBMI). The structures of the resins were confirmed using Fourier transform infrared analysis, and the thermoreversibility was evidenced using differential scanning calorimetry (DSC) analysis, as well as the sol-gel transformation process. Mechanical properties and recyclability of the resins were preliminarily evaluated using the flexural test. The results show the Diels-Alder (DA) reaction occurs at about 90 °C and the reversible DA reaction occurs at 130-140 °C for the furan-maleimide resin. Thermally reversible furan-maleimide resins have high mechanical properties. The flexural strength of cured FGE-ODA-HBMI resin arrives at 141 MPa. The resins have a repair efficiency of over 75%. After being hot-pressed three times, two resins display flexural strength higher than 80 MPa.

A risk prognostic model for patients with esophageal squamous cell carcinoma basing on cuproptosis and ferroptosis.

BACKGROUND: Cuproptosis, a form of copper-dependent programmed cell death recently presented by Tsvetkov et al., have been identified as a potential therapeutic target for refractory cancers and ferroptosis, a well-known form describing iron-dependent cell death. However, whether the crossing of cuproptosis-related genes and ferroptosis-related genes can introduce some new idea, thus being used as a novel clinical and therapeutic predictor in esophageal squamous cell carcinoma (ESCC) remains unknown. METHODS: We collected ESCC patient data from the Gene Expression Omnibus and the Cancer Genome Atlas databases and used Gene Set Variation Analysis to score each sample based on cuproptosis and ferroptosis. We then performed weighted gene co-expression network analysis to identify cuproptosis and ferroptosis-related genes (CFRGs) and construct a ferroptosis and cuproptosis-related risk prognostic model, which we validated using a test group. We also investigated the relationship between the risk score and other molecular features, such as signaling pathways, immune infiltration, and mutation status. RESULTS: Four CFRGs (MIDN, C15orf65, COMTD1 and RAP2B) were identified to construct our risk prognostic model. Patients were classified into low- and high-risk groups based on our risk prognostic model and the low-risk group showed significantly higher survival possibilities (P < 0.001). We used the "GO", "cibersort" and "ESTIMATE" methods to the above-mentioned genes to estimate the relationship among the risk score, correlated pathways, immune infiltration, and tumor purity. CONCLUSION: We constructed a prognostic model using four CFRGs and demonstrated its potential clinical and therapeutic guidance value for ESCC patients.

Cuproptosis/ferroptosis-related gene signature is correlated with immune infiltration and predict the prognosis for patients with breast cancer.

Background: Breast invasive carcinoma (BRCA) is a malignant tumor with high morbidity and mortality, and the prognosis is still unsatisfactory. Both ferroptosis and cuproptosis are apoptosis-independent cell deaths caused by the imbalance of corresponding metal components in cells and can affect the proliferation rate of cancer cells. The aim in this study was to develop a prognostic model of cuproptosis/ferroptosis-related genes (CFRGs) to predict survival in BRCA patients. Methods: Transcriptomic and clinical data for breast cancer patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cuproptosis and ferroptosis scores were determined for the BRCA samples from the TCGA cohort using Gene Set Variation Analysis (GSVA), followed by weighted gene coexpression network analysis (WGCNA) to screen out the CFRGs. The intersection of the differentially expressed genes grouped by high and low was determined using X-tile. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) were used in the TGCA cohort to identify the CFRG-related signature. In addition, the relationship between risk scores and immune infiltration levels was investigated using various algorithms, and model genes were analyzed in terms of single-cell sequencing. Finally, the expression of the signature genes was validated with quantitative real-time PCR (qRT‒PCR) and immunohistochemistry (IHC). Results: A total of 5 CFRGs (ANKRD52, HOXC10, KNOP1, SGPP1, TRIM45) were identified and were used to construct proportional hazards regression models. The high-risk groups in the training and validation sets had significantly worse survival rates. Tumor mutational burden (TMB) was positively correlated with the risk score. Conversely, Tumor Immune Dysfunction and Exclusion (TIDE) and tumor purity were inversely associated with risk scores. In addition, the infiltration degree of antitumor immune cells and the expression of immune checkpoints were lower in the high-risk group. In addition, risk scores and mTOR, Hif-1, ErbB, MAPK, PI3K/AKT, TGF-ß and other pathway signals were correlated with progression. Conclusion: We can accurately predict the survival of patients through the constructed CFRG-related prognostic model. In addition, we can also predict patient immunotherapy and immune cell infiltration.

The diagnostic value of ADC histogram and direct ADC measurements for coexisting isocitrate dehydrogenase mutation and O6-methylguanine-DNA methyltransferase promoter methylation in glioma.

Objectives: To non-invasively predict the coexistence of isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in adult-type diffuse gliomas using apparent diffusion coefficient (ADC) histogram and direct ADC measurements and compare the diagnostic performances of the two methods. Materials and methods: A total of 118 patients with adult-type diffuse glioma who underwent preoperative brain magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) were included in this retrospective study. The patient group included 40 patients with coexisting IDH mutation and MGMT promoter methylation (IDHmut/MGMTmet) and 78 patients with other molecular status, including 32 patients with IDH wildtype and MGMT promoter methylation (IDHwt/MGMTmet), one patient with IDH mutation and unmethylated MGMT promoter (IDHmut/MGMTunmet), and 45 patients with IDH wildtype and unmethylated MGMT promoter (IDHwt/MGMTunmet). ADC histogram parameters of gliomas were extracted by delineating the region of interest (ROI) in solid components of tumors. The minimum and mean ADC of direct ADC measurements were calculated by placing three rounded or elliptic ROIs in solid components of gliomas. Receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to evaluate the diagnostic performances of the two methods. Results: The 10th percentile, median, mean, root mean squared, 90th percentile, skewness, kurtosis, and minimum of ADC histogram analysis and minimum and mean ADC of direct measurements were significantly different between IDHmut/MGMTmet and the other glioma group (P < 0.001 to P = 0.003). In terms of single factors, 10th percentile of ADC histogram analysis had the best diagnostic efficiency (AUC = 0.860), followed by mean ADC obtained by direct measurements (AUC = 0.844). The logistic regression model combining ADC histogram parameters and direct measurements had the best diagnostic efficiency (AUC = 0.938), followed by the logistic regression model combining the ADC histogram parameters with statistically significant difference (AUC = 0.916) and the logistic regression model combining minimum ADC and mean ADC (AUC = 0.851). Conclusion: Both ADC histogram analysis and direct measurements have potential value in predicting the coexistence of IDHmut and MGMTmet in adult-type diffuse glioma. The diagnostic performance of ADC histogram analysis was better than that of direct ADC measurements. The combination of the two methods showed the best diagnostic performance.

Discriminating three motor imagery states of the same joint for brain-computer interface.

The classification of electroencephalography (EEG) induced by the same joint is one of the major challenges for brain-computer interface (BCI) systems. In this paper, we propose a new framework, which includes two parts, feature extraction and classification. Based on local mean decomposition (LMD), cloud model, and common spatial pattern (CSP), a feature extraction method called LMD-CSP is proposed to extract distinguishable features. In order to improve the classification results multi-objective grey wolf optimization twin support vector machine (MOGWO-TWSVM) is applied to discriminate the extracted features. We evaluated the performance of the proposed framework on our laboratory data sets with three motor imagery (MI) tasks of the same joint (shoulder abduction, extension, and flexion), and the average classification accuracy was 91.27%. Further comparison with several widely used methods showed that the proposed method had better performance in feature extraction and pattern classification. Overall, this study can be used for developing high-performance BCI systems, enabling individuals to control external devices intuitively and naturally.

Synthesis and Characterization of Block Copolymers of Poly(silylene diethynylbenzen) and Poly(silylene dipropargyl aryl ether).

Poly(silylene diethynylbenzene)-b-poly(silylene dipropargyloxy diphenyl propane) copolymer (ABA-A), poly(silylene diethynylbenzene)-b-poly(silylene dipropargyloxy diphenyl ether) copolymer (ABA-O), and a contrast poly(silylene diethynylbenzene) with equivalent polymerization degree were synthesized through Grignard reactions. The structures and properties of the copolymers were investigated via hydrogen nuclear magnetic resonance, Fourier transform infrared spectroscopy, Haake torque rheometer, differential scanning calorimetry, dynamic mechanical analysis, thermogravimetric analysis and mechanical tests. The results show that the block copolymers possess comprehensive properties, especially good processability and good mechanical properties. The processing windows of these copolymers are wider than 58 °C. The flexural strength of the cured ABA-A copolymer reaches as high as 40.2 MPa. The degradation temperatures at 5% weight loss (Td5) of the cured copolymers in nitrogen are all above 560 °C.

A Generative Model for Volume Rendering.

We present a technique to synthesize and analyze volume-rendered images using generative models. We use the Generative Adversarial Network (GAN) framework to compute a model from a large collection of volume renderings, conditioned on (1) viewpoint and (2) transfer functions for opacity and color. Our approach facilitates tasks for volume analysis that are challenging to achieve using existing rendering techniques such as ray casting or texture-based methods. We show how to guide the user in transfer function editing by quantifying expected change in the output image. Additionally, the generative model transforms transfer functions into a view-invariant latent space specifically designed to synthesize volume-rendered images. We use this space directly for rendering, enabling the user to explore the space of volume-rendered images. As our model is independent of the choice of volume rendering process, we show how to analyze volume-rendered images produced by direct and global illumination lighting, for a variety of volume datasets.

Molecular characteristics of CTA056, a novel interleukin-2-inducible T-cell kinase inhibitor that selectively targets malignant T cells and modulates oncomirs.

Interleukin-2-inducible T-cell kinase (Itk) is a member of the Btk (Bruton's tyrosine kinase) family of tyrosine kinases. Itk plays an important role in normal T-cell functions and in the pathophysiology of both autoimmune diseases and T-cell malignancies. Here, we describe the initial characterization of a selective inhibitor, 7-benzyl-1-(3-(piperidin-1-yl)propyl)-2-(4-(pyridin-4-yl)phenyl)-1H-imidazo[4,5-g]quinoxalin-6(5H)-one (CTA056), that was developed through screening a 9600-compound combinatorial solution phase library, followed by molecular modeling, and extensive structure-activity relationship studies. CTA056 exhibits the highest inhibitory effects toward Itk, followed by Btk and endothelial and epithelial tyrosine kinase. Among the 41 cancer cell lines analyzed, CTA056 selectively targets acute lymphoblastic T-cell leukemia and cutaneous T-cell lymphoma. Normal T cells are minimally affected. Incubation of Jurkat and MOLT-4 cells with CTA056 resulted in the inhibition of the phosphorylation of Itk and its effectors including PLC-γ, Akt, and extracellular signal-regulated kinase, as well as the decreased secretion of targeted genes such as interleukin-2 and interferon-γ. Jurkat cells also underwent apoptosis in a dose-dependent manner when incubated with CTA056. The potent apoptosis-inducing potential of CTA056 is reflected by the significant modulation of microRNAs involved in survival pathways and oncogenesis. The in vitro cytotoxic effect on malignant T cells is further validated in a xenograft model. The selective expression and activation of Itk in malignant T cells, as well as the specificity of CTA056 for Itk, make this molecule a potential therapeutic agent for the treatment of T-cell leukemia and lymphoma.

[Establishment of a cell based high throughput screening model for transient receptor potential V3 modulators].

We established a cell based high throughput screening model by calcium assay on fluorometric imaging plate reader for finding modulators of TRPV3. The TRPV3 expression vector was transfected into HEK-293 and stable cell line expressing TRPV3 was selected with antibiotics. Upon TRPV3 specific modulators stimulated, pharmacological characteristics of TRPV3 over expression cell line were detected by calcium assay on fluorometric imaging plate reader. Assay conditions were optimized and stability of the model was observed. The reliability and accuracy of application to 96 and 384 well format high throughput screening were also evaluated. A stable HEK-293 cell line highly expressing TRPV3 was established. TRPV3 specific modulators could modulate calcium signal through TRPV3 in dose dependent manner. Optimized screening condition was established by assay development. This model is stable and sensitive, and meets the requirement of high throughput screening by Z'factor validation and Spiking test. This cell model can be applied to screening TRPV3 modulators by calcium assay.