Age is not appropriate to be a mediating factor Fan, Zheqi; Zhao, Houming; Zhou, Jingcheng ...
International journal of surgery (London, England),
07/2024, Volume:
110, Issue:
7
Journal Article
The importance of long noncoding RNAs (lncRNAs) has been certified in malignant melanoma. Nonetheless, the functions of lncRNA paternally expressed gene 10 (PEG10) in malignant melanoma remain ...uninvestigated. This research discloses the influence of PEG10 in the biological actions of malignant melanoma cells. The sh‐PEG10 plasmid was transfected into A375 cells; meanwhile, the effects of declined PEG10 on cell viability, apoptosis, migration, invasion, and the correlative protein levels were probed. The miR‐33a expression in sh‐PEG10‐transfected cells was examined, and the above biological processes were studied again in miR‐33a inhibitor‐transfected A375 cells. Phosphoinositide 3‐kinase/protein kinase B (PI3K/AKT) and mechanistic target of rapamycin (mTOR) pathways were delved via Western blot. We found that the enhancement of PEG10 was discovered in melanoma tissues compared to related nonmelanoma tissues. Declination of PEG10 frustrated cell viability, repressed cyclinD1 and CDK4 expression, and triggered apoptosis, as well as suppressed migration and invasion in A375 cells. A negative correction between PEG10 and miR‐33a was confirmed, and repressed miR‐33a inverted the functions of PEG10 repression in A375 cells. In addition, PEG10 repression discouraged the activation of PI3K/AKT and mTOR pathways via elevation of miR‐33a. These results indicated that declination of PEG10 restrained A375 cell growth, migration, and invasion via adjusting miR‐33a and PI3K/AKT and mTOR pathways.
The results uncovered that PEG10 knockdown restrained cell growth, migration, and invasion in A375 cells by obstructing phosphoinositide 3‐kinase/protein kinase B and the mechanistic target of rapamycin pathways through enhancement of miR‐33a. These explorations hinted that PEG10 might be a therapeutic target in malignant melanoma. The potential application of PEG10 in the advancement of malignant melanoma remains to be further studied.
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•A new unsupervised model adaptation (UMA) method is proposed, termed as domain adaptation regularization based kernel partial least squares (DarKPLS).•Aims to align the ...distributional means and variances across different spectral domains in the reproducing kernel hilbert space simultaneously.•Projected maximum mean discrepancy (PMMD) is utilized to eliminate the distributional mean-shift further.•Comparing with 4 classical UMA methods, DarKPLS demonstrates its superiority in all the cases.
In chemometrics, calibration model adaptation is desired when training- and test-samples come from different distributions. Domain-invariant feature representation is currently a successful strategy to realize model adaptation and has received wide attention. The paper presents a nonlinear unsupervised model adaptation method termed as domain adaption regularization-based kernel partial least squares regression (DarKPLS). DarKPLS aims to minimize the source and target distributions in a low-dimensional latent space projected from the reproducing kernel Hilbert space (RKHS) generated with the labeled source data and unlabeled target data. Specially, the distributional means and variances between source and target latent variables are aligned in the RKHS. By extending existing domain invariant partial least square regression (di-PLS) with the projected maximum mean discrepancy (PMMD) to reduce the mean discrepancy in the RKHS further, DarKPLS could realize fine-grained domain alignment that further improves the adaptation performance. DarKPLS is applied to the γ-polyglutamic acid fermentation dataset, tobacco dataset and corn dataset, and it demonstrates improved prediction results in comparison with No adaptation partial least squares (PLS), null augmented regression (NAR), extended linear joint trained framework (ExtJT), scatter component analysis (SCA) and domain-invariant iterative partial least squares (DIPALS).
The primal–dual hybrid gradient (PDHG) method has been widely used for solving saddle point problems emerged in imaging processing. In particular, PDHG can be used to solve convex problems with ...linear constraints. Recently, it was shown that without further assumptions, the original PDHG may fail to converge. In this paper, we modify the original PDHG to obtain a convergent method. The method is in a prediction–correction fashion: the predictor is generated by PDHG and the correction is completed by two minor computations. The requirement of the step size parameters in our method is
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Glioblastoma multiforme (GBM) is one of the most aggressive human tumors, and it has a poor prognosis. Temozolomide (TMZ) is the primary alkylating agent used to treat GBM. Nevertheless, a number of ...GBM patients are resistant to TMZ. Therefore, there is an urgent need for more effective therapeutic options. Cordycepin (COR) is a natural chemical with anti-tumor effects, although its mechanism of action is poorly understood. Several lines of evidence suggest that O6-methylguanine DNA methyltransferase (MGMT) repairs damaged DNA and contributes to drug resistance to TMZ in gliomas. The Wnt/β-catenin pathway regulates MGMT gene expression. However, whether cordycepin inhibits MGMT expression by downregulating the β catenin pathway and augmenting chemosensitivity to TMZ in glioma cells remains unclear. In the present study, we found that cordycepin inhibited the viability of glioma cells and induced apoptosis, cell cycle arrest, overproduction of reactive oxygen species (ROS) and reduction of glutathione (GSH) in vitro. Moreover, cordycepin significantly reduced tumor volume and prolonged median survival of tumor-bearing rats in vivo. We also found that cordycepin inhibited MGMT expression and augmented chemosensitivity to TMZ in glioma cells in vitro and in vivo, accompanied by downregulation of p-GSK-3β and β-catenin. Moreover, overexpression of MGMT reversed the synergistic effect of cordycepin and TMZ. Pharmacological inhibition of GSK-3β with CHIR-99021 or overexpression of β-catenin reversed cordycepin-induced reduction of cell viability, downregulation of β-catenin and MGMT, increase of apoptosis and reduction of TMZ resistance. Furthermore, we found that β-catenin regulated cordycepin-induced overproduction of ROS by decreasing GSH. Inhibition of ROS production with N-acetyl-l-cysteine (NAC) not only rescued the reduction of cell viability but also eliminated β-catenin and MGMT inhibition, prevented glioma cells apoptosis and reversed the synergistic effect of cordycepin and TMZ. Taken together, we demonstrated that β-catenin contributed to cordycepin-induced MGMT inhibition and reduction of TMZ resistance in glioma cells via increasing intracellular ROS. These results indicate that cordycepin may be a novel agent to improve GBM treatment, especially in TMZ-resistant GBM with high MGMT expression.
•Cordycepin inhibited the viability of glioma cells in vitro and in vivo.•Cordycepin reduced the expression of MGMT and augmented TMZ-mediated chemotherapy in vitro and in vivo.•Cordycepin-induced reduction of TMZ resistance in glioma cells was MGMT-dependent.•β-catenin regulated cordycepin-induced MGMT inhibition and reduction of TMZ resistance in glioma cells.•ROS is required for cordycepin-induced MGMT inhibition and reduction of TMZ resistance in glioma cells.
The issue of hearing protection in the presence of noise pollution is of great importance in the fields of environmental science and clinical medicine. Currently, the clinical significance of Klotho ...in relation to hearing has not been revealed. The aim of this study was to examine the correlation between serum Klotho levels and Pure Tone Average (PTA) hearing thresholds among individuals in the U.S.. The analysis involved a sample of 1,781 individuals aged 20 to 69, obtained from the 2007–2012 National Health and Nutrition Examination Survey. Various methods were utilized for the analysis, including univariate and multivariate linear regression, stratified analysis, smooth curve fitting, a two-segment linear regression model, and log-likelihood ratio analysis. The results of the univariate analysis indicated that serum Klotho concentration, age, education level, hypertension, diabetes, and smoking all exhibited a significant influence on PTAs. After adjusting for potential confounding factors, it was observed that a decrease in serum Klotho was significantly associated with PTA thresholds at low frequency (β = -0.002; 95% CI: -0.003, -0.001; P = 0.004), speech frequency (β = -0.002; 95% CI: -0.003, -0.001; P = 0.007), and high frequency (β = -0.002; 95% CI: -0.003, -0.001; P = 0.045). Specifically, for every 1 pg/ml decrease in serum Klotho concentration, the PTAs increased by 0.002 dB. Moreover, age and gender-specific analyses revealed significant associations. For individuals aged 59–69, a significant association was found between serum Klotho concentration and high-frequency PTA (β = -4.153; 95% CI: -7.948, -0.358; P = 0.032). Additionally, among females, significant associations were observed between serum Klotho concentration and speech-frequency PTA (β = -1.648, 95% CI: -3.197, -0.099; P = 0.037) as well as high-frequency PTA (β = -3.046; 95% CI: -5.319, -0.772; P = 0.009). Finally, the results of smooth curve fitting and threshold effect analyses indicated a potential negative linear correlation between serum Klotho concentration and PTA thresholds. In conclusion, a lower level of serum Klotho was found to be associated with increased hearing thresholds, particularly among the elderly population. This finding has significant implications for the prevention and treatment of hearing damage.
Atherosclerosis (AS) plays an important role in the pathogenesis of cardiovascular and cerebrovascular diseases. Danggui-Shaoyao-San (DSS) is not only a representative Chinese formula to treat ...gynecological disorder, but also found its use in AS-related diseases. However, the active ingredients and the anti-AS effects are vague yet.
An integrated strategy combined ultrahigh-performance liquid chromatography quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS), network pharmacology and experiments was carried out to investigate the potential materials and pharmacological mechanisms of DSS for AS.
First, UHPLC-Q-Orbitrap-HRMS was applied to identify the active compositions of DSS. Then, the putative targets of DSS relevant to AS were predicted from TCMSP and BATMAN, which were further determined through bioinformatic analyses, including protein-protein interactions (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, Western blot, qPCR and ELISA were carried out for target validation in human umbilical vein endothelial cells (HUVECs).
A total of 37 active ingredients of DSS, connecting 47 key targets were identified. The functional enrichment showed that DSS may treat AS through regulating a series of signaling pathways which involving inflammatory responses, immune systems and metabolism. The in vitro experiment revealed that DSS ameliorated AS mainly through anti-inflammatory effects, by reducing the levels of vascular cell adhesion molecule-1 (VCAM1), intercellular adhesion molecule-1 (ICAM1), IL-6, TNF-α, cyclooxygenase-2 (Cox-2) and IL-1β. DSS also inhibited the phosphorylation of IκB-α, NF-κB (p65), p38 and JNK in lipopolysaccharide (LPS)-induced HUVEC injury model. Moreover, as the main bioactive compounds of DSS, paeoniflorin (PF), ferulic acid (FA) and pachymic acid (PA) inhibited IL-6 and TNF-α secretion as well as IκB-α, NF-κB (p65), p38 and JNK activation. All these findings were consistent with the predicted targets and pathways.
Collectively, the basic pharmacological effects and relevant mechanisms of DSS in the treatment of AS were revealed. The results suggest that DSS is a potential drug for AS treatment, and PF, FA, PA may be the core compositions contributing to the pharmacological function of this formula.
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•The active compositions of Danggui-Shaoyao-San (DSS) were identified by UHPLC-Q-Orbitrap-HRMS in this study.•Paeoniflorin, ferulic acid and pachymic acid may be the core compounds contributing to the pharmacological function of DSS.•The mechanisms of DSS against atherosclerosis were mostly relevant to the inactivation of IκB-α, NF-κB (p65), p38 and JNK.•The combination use of UHPLC-Q-Orbitrap-HRMS and network pharmacology may provide a reliable approach to TCM research.
Deep learning models have emerged as rapid, accurate, and effective approaches for clinical decisions. Through a combination of drug screening and deep learning models, drugs that may benefit ...patients before and after surgery can be discovered to reduce the risk of complications or speed recovery. However, most existing drug prediction methods have high data requirements and lack interpretability, which has a limited role in adjuvant surgical treatment. To address these limitations, we propose the attention-based convolution transpositional interfusion network (ACTIN) for flexible and efficient drug discovery. ACTIN leverages the graph convolution and the transformer mechanism, utilizing drug and transcriptome data to assess the impact of chemical pharmacophores containing certain elements on gene expression. Remarkably, just with only 393 training instances, only one-tenth of the other models, ACTIN achieves state-of-the-art performance, demonstrating its effectiveness even with limited data. By incorporating chemical element embedding disparity and attention mechanism-based parameter analysis, it identifies the possible pharmacophore containing certain elements that could interfere with specific cell lines, which is particularly valuable for screening useful pharmacophores for new drugs tailored to adjuvant surgical treatment. To validate its reliability, we conducted comprehensive examinations by utilizing transcriptome data from the lung tissue of fatal COVID-19 patients as additional input for ACTIN, we generated novel lead chemicals that align with clinical evidence. In summary, ACTIN offers insights into the perturbation biases of elements within pharmacophore on gene expression, which holds the potential for guiding the development of new drugs that benefit surgical treatment.Deep learning models have emerged as rapid, accurate, and effective approaches for clinical decisions. Through a combination of drug screening and deep learning models, drugs that may benefit patients before and after surgery can be discovered to reduce the risk of complications or speed recovery. However, most existing drug prediction methods have high data requirements and lack interpretability, which has a limited role in adjuvant surgical treatment. To address these limitations, we propose the attention-based convolution transpositional interfusion network (ACTIN) for flexible and efficient drug discovery. ACTIN leverages the graph convolution and the transformer mechanism, utilizing drug and transcriptome data to assess the impact of chemical pharmacophores containing certain elements on gene expression. Remarkably, just with only 393 training instances, only one-tenth of the other models, ACTIN achieves state-of-the-art performance, demonstrating its effectiveness even with limited data. By incorporating chemical element embedding disparity and attention mechanism-based parameter analysis, it identifies the possible pharmacophore containing certain elements that could interfere with specific cell lines, which is particularly valuable for screening useful pharmacophores for new drugs tailored to adjuvant surgical treatment. To validate its reliability, we conducted comprehensive examinations by utilizing transcriptome data from the lung tissue of fatal COVID-19 patients as additional input for ACTIN, we generated novel lead chemicals that align with clinical evidence. In summary, ACTIN offers insights into the perturbation biases of elements within pharmacophore on gene expression, which holds the potential for guiding the development of new drugs that benefit surgical treatment.
Early spontaneous detection of thrombin activation benefits precise theranostics for thrombotic vascular disease. Herein, a thrombin-responsive nanoprobe conjugated by a FITC dye, PEGylated Fe3O4 ...nanoparticles, and a thrombin-sensitive peptide (LASG) was constructed to visualize thrombin activation and subsequent thrombosis in vivo. The FITC dye was linked to the LASG coated on the Fe3O4 nanoparticles for sensing the thrombin activity via the Förster resonance energy transfer effect. In vitro fluorescence imaging showed that the fluorescence signal intensity increased significantly after incubation with thrombin in contrast to that of the control group (p < 0.05), and the signal intensity was enhanced with the increase in thrombin concentration. Further in vivo fluorescence imaging also revealed that the signal elevated markedly in the left common carotid artery (LCCA) lesion of the mice thrombosis model after nanoprobe injection, in contrast to that of the control + nanoprobe group (p < 0.05). Moreover, the thrombin inhibitor bivalirudin could decrease the filling defect of the LCCA. Three-dimensional fusion images of micro-CT and fluorescence confirmed that filling defects in the LCCA were nicely colocalized with fluorescence signal caused by nanoprobes. The nanoplatform based on a thrombin-activatable visualization system could provide smart responsive and dynamic imaging of thrombosis in vivo.
The accuracy of classification models using spectral data decreases significantly with the increase numbers of categories. In order to overcome this problem, a middle layer is built based on the main ...factors of the sample. Herein, ten indicators, including chemical components, position and aroma styles, were selected to determine the identification of geographical origin and grade of flue-cured tobacco. Chemometrical algorithms were used to build quantitative prediction models based on labeled data. A voting algorithm was performed to determine the most likely geographical origin and grade of unknown samples. Experimental results show that the proposed method provides outstanding results for the independent test samples compared with traditional classify methods such as SIMCA and PLS-DA. The proposed method can be useful for origin traceability or adulteration detection of various agricultural products.
