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Abstract Background Hepatocellular carcinoma (HCC) is the most common type of malignant liver tumor with poor prognosis. In this study, we investigated the expression of transforming growth factor beta regulator 4 (TBRG4) in HCC and its effects on the proliferation, invasion, and metastasis of HCC cells, and analyzed the possible molecular mechanisms. Method Downloading the expression and clinical information of HCC samples in the TCGA database, analyzing the expression differences of TBRG4 by bioinformatics methods, analyzing the clinical relevance and prognostic significance. Performing GO, KEGG and GSEA enrichment analysis on the TBRG4-related gene set in patient HCC tissues. Applying cell counting, scratch test and Transwell experiment to study the biological function of TBRG4 in HCC. Mitochondrial membrane potential, apoptosis and ROS levels were evaluated to assess cell iron death. Western blot, RT-PCR, laser confocal microscopy and co-immunoprecipitation were used to detect and analyze the downstream signaling pathways and interacting molecules of TBRG4. Results Bioinformatics analysis revealed that TBRG4 was abnormally highly expressed in HCC tumor tissues and was associated with poor prognosis and metastasis in HCC patients. GO and KEGG functional enrichment analysis showed that TBRG4 was related to oxidative stress and NADH dehydrogenase (ubiquinone) activity. GSEA enrichment analysis showed that TBRG4 was associated with Beta catenin independent wnt signaling and B cell receptor. Functional experiments confirmed that knocking down TBRG4 could inhibit the proliferation, migration, and invasion of HCC cells. Mechanistically, TBRG4 inhibited the function of HCC cells through the DDX56/p-AKT/GSK3β signaling pathway. In addition, interference with TBRG4 expression could reduce the mitochondrial membrane potential and accumulate ROS in HCC cells, leading to increased ferroptosis. Co-IP analysis showed that TBRG4 specifically bound to Beclin1. Conclusion TBRG4 is highly expressed in HCC tumor tissues and is associated with poor prognosis. It may regulate the proliferation, invasion, and metastasis of HCC cells through the DDX56/p-AKT/GSK3β signaling pathway. TBRG4 may interact with Beclin1 to regulate the ferroptosis of HCC cells.

Nattokinase (NK) and red yeast rice (RYR) are both indicated for their potential in cardiovascular disease prevention and management, but their combined effects especially in coronary artery disease (CAD) are scarcely examined. This 90-day randomized, double-blind trial aims to investigate the effect of NK and RYR supplementations on cardiometabolic parameters in patients with stable CAD. 178 CAD patients were randomized to four groups: NK + RYR, NK, RYR, and placebo. No adverse effects due to the interventions were reported. In comparisons across groups, NK + RYR showed the maximum effect in reducing triglyceride (−0.39 mmol), total cholesterol (−0.66 mmol/L), diastolic blood pressure (−7.39 mmHg), and increase in high-density lipoprotein cholesterol (0.195 mmol/L) than other groups (all p for multiple groups comparison

Abstract Recent findings have shown that fatty acid metabolism is profoundly involved in ferroptosis. However, the role of cholesterol in this process remains incompletely understood. In this work, we show that modulating cholesterol levels changes vulnerability of cells to ferroptosis. Cholesterol alters metabolic flux of the mevalonate pathway by promoting Squalene Epoxidase (SQLE) degradation, a rate limiting step in cholesterol biosynthesis, thereby increasing both CoQ10 and squalene levels. Importantly, whereas inactivation of Farnesyl-Diphosphate Farnesyltransferase 1 (FDFT1), the branch point of cholesterol biosynthesis pathway, exhibits minimal effect on ferroptosis, simultaneous inhibition of both CoQ10 and squalene biosynthesis completely abrogates the effect of cholesterol. Mouse models of ischemia-reperfusion and doxorubicin induced hepatoxicity confirm the protective role of cholesterol in ferroptosis. Our study elucidates a potential role of ferroptosis in diseases related to dysregulation of cholesterol metabolism and suggests a possible therapeutic target that involves ferroptotic cell death.

Abstract Circular RNAs (circRNAs) can regulate autophagy and ovarian cancer (OC) progression. However, autophagy-associated circRNAs involved in OC progression are largely unknown. Bioinformatics, RNA sequencing, and qRT-PCR were conducted to detect circRNF144B expression in OC as well as its relationship with patient prognosis. Functional experiments were used to determine the effects of circRNF144B on the proliferation, mobility and autophagy of OC. Double luciferase reporter assays, immunoprecipitation, and ubiquitination detection were performed to determine the molecular mechanisms of circRNF144B in autophagy and OC progression. CircRNF144B was elevated in OC tissues with low autophagy levels, and associated with poor prognosis. CircRNF144B promoted the malignant biological properties of OC cells, and inhibited the autophagy. Mechanistically, circRNF144B acts as a sponge for miR-342-3p and inhibits miR-342-3p-induced degradation of lysine demethylase 2 A (FBXL11) mRNA, leading to elevated FBXL11 protein levels. Elevated FBXL11 promoted the ubiquitination and degradation of Beclin-1, thus inhibiting autophagy. In conclusion, CircRNF144B increased FBXL11 level by sponging miR-342-3p, whereas elevated FBXL11 promoted the ubiquitination and protein degradation of Beclin-1, thus suppressing autophagy flux and promoting OC progression. Thus, circRNF144B may be an effective target for OC therapy.

Bisphenol A (BPA) has a number of adverse effects on the reproductive development of females. In particular, the mechanism of disruption of ovarian development in adolescent mice is still unclear. Based on transcriptome sequencing results, a differentially expressed lncRNA, Fhad1os2, was detected in the ovaries of BPA-exposed pubertal mice. In our study, the lncRNA Fhad1os2, localized in the ovarian granulosa cell cytoplasm, could regulate the proliferation of mouse ovarian granulosa cells. Mechanistically, the results of RNA pull-down experiments as well as mass spectrometry analysis showed that ERα, an interfering signaling molecule of BPA, could directly bind lncRNA Fhad1os2 and decrease the transcription of lncRNA Fhad1os2 in response to the estrogen-like effect of BPA. BPA exposure also caused abnormal lncRNA Fhad1os2 pulldown protein-related signaling pathways in the ovaries of adolescent mice. Furthermore, lncRNA Fhad1os2 interacted with RUNX3, a transcription factor related to follicle development and hormone synthesis. As a negative regulator, lncRNA Fhad1os2 transactivated the expression of Runx3, which in turn induced RUNX3 to positively regulate aromatase (Cyp19a1) expression in mouse ovarian granulosa cells and promote estrogen synthesis. In conclusion, our study indicates that BPA exposure interferes with ERα-regulated lncRNA Fhad1os2 interactions with RUNX3 in pubertal mice, affecting estrogen synthesis in mouse granulosa cells and contributing to premature ovarian maturation in pubertal mice.

A general acoustic force field can be decomposed into a conservative gradient force (GF) and a non-conservative scattering force (SF), which have very different physical and mathematical properties. However, the profiles of such forces for Mie particles are unknown, let alone their underlying physics. Here, by using a fast Fourier transform approach, we calculated the GF and SF for spherical particle of various sizes and various incident waves. For the same focused incident waves, the normalized GF and SF are similar for different particle sizes, while the total force can be quite different owing to the varying relative strength between the GF and SF. GF and SF possess symmetries that are not found in the incident waves, indicating that these physically and mathematically distinct forces have symmetries that are hidden from the beam profile. For a vortex beam carrying a well-defined topological charge, acoustic forces alone cannot trap particles.

Ferroptosis and immune infiltration play an important role in the pathogenesis of intervertebral disc degeneration (IDD). However, there is still a lack of comprehensive analysis on the interaction between ferroptosis-related genes (FRGs) and immune microenvironment in IDD patients. Therefore, this study aims to explore the correlation between FRGs characteristics and immune infiltration in the progression of IDD. The expression profiles (GSE56081 and GSE70362) and FRGs were downloaded from the comprehensive gene expression omnibus (GEO) and FerrDb database, respectively, and the differences were analyzed using R. The intersection of IDD related differential genes (DEGs) and FRGs was taken as differentially expressed FRGs (DE-FRGs) and GO and KEGG enrichment analysis was conducted. Then, we used least absolute shrinkage and selection operator (LASSO) regression algorithm and support vector machine (SVM) algorithm to screen feature genes and draw ROC curve judge the diagnostic value of key DE-FRGs. Then CIBERSORT algorithm is used to evaluate the infiltration of immune cells and analyze the correlation between key DE-FRGs and immune infiltration. Based on the analysis results, we conducted single gene GSEA analysis on key DE-FRGs. RT-PCR and immunohistochemistry further verified the clinical value of the results of biochemical analysis and screening. Seven key DE-FRGs were screened, including the upregulated genes NOX4 and PIR, and the downregulated genes TIMM9, ATF3, ENPP2, FADS2 and TFAP2A. Single gene GSEA analysis further elucidates the role of DE-FRGs in IDD associated with ferroptosis. Correlation analysis showed that seven key DE-FRGs were closely related to immune infiltration in the development of IDD. Finally, RT-PCR and immunohistochemical staining showed that NOX4, ENPP2, FADS2 and TFAP2A were statistically significant differences. In this study, we explored the connection between ferroptosis related characteristics and immune infiltration in IDD, and confirmed that NOX4, ENPP2, FADS2, and TFAP2A may become biomarkers and potential therapeutic targets for IDD.

Abstract Infection with Brucella is characterized by the inhibition of host immune responses. MicroRNA-155 (miR-155) has been implicated in the immune response to many diseases. In this study, its expression during Brucella 16M infection of macrophages and mice was analyzed. Expression of miR-155 was significantly induced in macrophages at 24 h post infection. Further, an analysis of infected mice showed that miR-155 was inhibited at 7 and 14 days but induced at 28 days. Interestingly, this trend in induction or inhibition was reversed at 7 and 14 days in 16M△virB-infected mice. This suggested that decreased expression of miR-155 at an early stage of infection was dependent on intracellular replication. In humans with brucellosis, serum levels of miR-155 were significantly decreased compared to those in individuals without brucellosis and healthy volunteers. Significant correlations were observed between serum level of miR-155 and serum anti-Brucella antibody titers and the sweating symptom. This effect suggests that Brucella interferes with miR-155-regulated immune responses via a unique mechanism. Taken together, data from this study indicate that Brucella infection affects miR-155 expression and that human brucellosis patients show decreased serum levels of miR-155.

Abstract A two‐step process, including the premetallization of the SiC ceramic by Ag‐26.7Cu‐4Ti+B4C and the followed brazing with the Al‐based filler alloy, was developed to join 2219 aluminum alloy and the metallized SiC. The influence of metallization temperature and the B4C addition on the microstructure and mechanical properties of the joint was analyzed. The reaction products of Ti and B4C were detected in the brazing seam, such as Ti2B, TiC and graphite. With increasing of metallization temperature and B4C addition content, the shear strength of joint first increased and then decreased. The joint shear strength reached 14.0 MPa when SiC metallized with Ag‐26.7Cu‐4Ti+1%B4C at 930°C for 10 min, which showed that appropriate addition of B4C in Ag‐26.7Cu‐4Ti metallization layer could regulate the coefficient of thermal expansion difference between 2219 aluminum alloy and SiC to relieve the residual stress and improve the shear strength of their brazed joint.

Background: The occurrence and development of solid tumors depend on the blood supply in the tumor microenvironment (TME). Blocking angiogenesis is a new therapeutic strategy to inhibit tumor growth. The anti-angiogenic drug bevacizumab has been approved for gynecological malignancies, especially for advanced recurring cervical cancers and recurring ovarian cancers (OC). Studies in OC have shown a limited effect of bevacizumab in the general population, with a slight improvement in progression-free survival (PFS) and no effect on overall survival (OS). This might be related to the bevacizumab’s role in aggravating the hypoxia in the TME, which helps maintain the stemness of ovarian cancer stem cells (CSCs) and promotes the invasion and metastasis of cancer cells. Drugs that target CSCs, such as metformin, may enhance the efficacy of anti-vascular therapies. Therefore, this study aimed to evaluate the effect of metformin combined with bevacizumab on the proliferation of OC cells both in vitro and in vivo, as well as on tumor hypoxia and tumor stem cell markers of human ovarian cancer SKOV3 cells.Methods: The OC cell model SKOV3 was treated with metformin, bevacizumab, and cisplatin alone or in combinations. Cell Counting Kit-8 (CCK-8) was used to measure the rate of cell proliferation. Metformin and bevacizumab were studied in vivo in nude mice. SKOV3 cells were transplanted subcutaneously in nude mice, and different drug interventions were performed after tumor formation, including blank control, bevacizumab alone, metformin alone, cisplatin alone, bevacizumab + metformin, bevacizumab + cisplatin, metformin + cisplatin, and bevacizumab + metformin + cisplatin treatments. The growth of transplanted tumors was routinely monitored and visualized by the tumor growth curve. We used flow cytometry to examine the proportion of CD44+/CD117+ CSCs in each group. The immunohistochemistry (IHC) method was applied to detect expressions of vascular endothelial growth factor (VEGF), hypoxia-inducible factor 1α (HIF-1α), and microvascular density-associated factor CD34 in tumor cells. The limit dilution method was used to re-inject tumor cells in nude mice to examine the tumor recurrence rate.Results: Combination therapy of metformin and bevacizumab significantly reduced the proliferation rate of SKOV3 cells and the growth rate of transplanted tumors in nude mice compared with the monotherapy effects. In vivo results showed that metformin significantly reduced the proportion of CD44+/CD117+ CSCs (p < 0.01). Although bevacizumab increased the proportion of CD44+/CD117+ CSCs, the addition of metformin did offset this fluctuating trend. The combination of bevacizumab, metformin, and cisplatin efficiently decreased the proportion of CSCs in the OC animal model. IHC results exhibited that expressions of VEGF, CD34, and HIF-1α in transplanted tumors were decreased by metformin alone compared with the control (p < 0.05). In the bevacizumab treatment, VEGF, and CD34 expressions were decreased, while that of HIF-1α was increased, suggesting that the degree of hypoxia was differentially aggravated after the bevacizumab treatment. The VEGF, CD34, and HIF-1α expressions in the bevacizumab + metformin + cisplatin group were the lowest among all other treatment groups (p < 0.05). Subcutaneous statistics of nude mice reseeded by the limit dilution method showed that the tumor recurrence rate in the bevacizumab + metformin + cisplatin group was relatively lower.Conclusion: Metformin, bevacizumab combined with platinum-based chemotherapy can significantly inhibit the growth of ovarian cancer cells and transplanted tumors, which is due to the reduction of the proportion of CD44+/CD117+ CSCs and the alleviation of hypoxia in the tumor microenvironment. Therefore, this may be a reasonable and promising treatment regimen.

Abstract Background Extensive clinical evidence suggests that a preventive screening of coronary heart disease (CHD) at an earlier stage can greatly reduce the mortality rate. We use 64 two-dimensional speckle tracking echocardiography (2D-STE) features and seven clinical features to predict whether one has CHD. Methods We develop a machine learning approach that integrates a number of popular classification methods together by model stacking, and generalize the traditional stacking method to a two-step stacking method to improve the diagnostic performance. Results By borrowing strengths from multiple classification models through the proposed method, we improve the CHD classification accuracy from around 70–87.7% on the testing set. The sensitivity of the proposed method is 0.903 and the specificity is 0.843, with an AUC of 0.904, which is significantly higher than those of the individual classification models. Conclusion Our work lays a foundation for the deployment of speckle tracking echocardiography-based screening tools for coronary heart disease.

The combination of histone deacetylase inhibitor and BRAF inhibitor (BRAFi) has been shown to enhance the antineoplastic effect and reduce the progress of BRAFi resistance. In this study, a series of (thiazol-5-yl)pyrimidin-2-yl)amino)-N-hydroxyalkanamide derivatives were designed and synthesized as novel dual inhibitors of BRAF and HDACs using a pharmacophore hybrid strategy. In particular, compound 14b possessed potent activities against BRAF, HDAC1, and HDAC6 enzymes. It potently suppressed the proliferation of HT-29 cells harboring BRAFV600E mutation as well as HCT116 cells with wild-type BRAF. The dual inhibition against BRAF and HDAC downstream proteins was validated in both cells. Collectively, the results support 14b as a promising lead molecule for further development and a useful tool for studying the effects of BRAF/HDAC dual inhibitors.

Specialized services and management must understand students' behavioral patterns in a timely and accurate manner. Based on these patterns, we can make targeted rules, especially for unexpected patterns. To perform this type of work, a questionnaire method is usually used to collect data and analyze students' behavioral states. However, the effectiveness of this method is greatly influenced by the timeliness and validity of the feedback data. To address this problem, we propose an unsupervised ensemble clustering framework to use student behavioral data to discover behavioral patterns. Because the behavioral data produced by students on campus are available in real time without intentional bias, clustering analysis can be relatively efficient and reliable. The proposed framework extracts behavior features from the two perspectives of statistics and entropy and then combines density-based spatial clustering of applications with noise (DBSCAN) and k-means algorithms to discover behavioral patterns. To evaluate the performance of the proposed framework, we carry out experiments on six types of behavioral data produced by undergraduates in a university in Beijing and analyze the relationships between different behavioral patterns and students' grade point averages (GPAs). The results show that the framework can not only detect anomalous behavioral patterns but also find mainstream patterns. The findings from this research can assist student-related departments in providing better services and management, such as psychological consulting and academic guidance.

Abstract Background Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential response shown by altered kinases to drug treatment in patients and cell-based assays. However, an incomplete understanding of the relationships connecting genome, proteome and drug sensitivity profiles present a major bottleneck in targeting kinases for personalized medicine. Results In this study, we propose a multi-component Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model and neural networks framework for providing explainable models of protein kinase inhibition and drug response ( $$\hbox {IC}_{50}$$ IC 50 ) profiles in cell lines. Using non-small cell lung cancer as a case study, we show that interaction terms that capture associations between drugs, pathways, and mutant kinases quantitatively contribute to the response of two EGFR inhibitors (afatinib and lapatinib). In particular, protein–protein interactions associated with the JNK apoptotic pathway, associations between lung development and axon extension, and interaction terms connecting drug substructures and the volume/charge of mutant residues at specific structural locations contribute significantly to the observed $$\hbox {IC}_{50}$$ IC 50 values in cell-based assays. Conclusions By integrating multi-omics data in the QSMART model, we not only predict drug responses in cancer cell lines with high accuracy but also identify features and explainable interaction terms contributing to the accuracy. Although we have tested our multi-component explainable framework on protein kinase inhibitors, it can be extended across the proteome to investigate the complex relationships connecting genotypes and drug sensitivity profiles.

The incidence of metabolic diseases is increasing every year, and several studies have highlighted the activity of persistent organic pollutants (POPs) in causing hyperlipidemia and diabetes, and these compounds are considered to be endocrine disrupting chemicals (EDCs). Chlordane is classified as an endocrine disruptor, but the mechanism of how it functions is still unclear. This study investigates the effects of chlordane exposure on Drosophila larvae. Drosophila was cultured in diet containing 0.01 μM, 0.1 μM, 1 μM, 5 μM, and 10 μM chlordane, and the toxicity of chlordane, the growth and development of Drosophila, the homeostasis of glucose and lipid metabolism and insulin signaling pathway, lipid peroxidation-related indicators and Nrf2 signaling pathway were evaluated. We here found that exposure to high concentrations of chlordane decreased the survival rate of Drosophila and that exposure to low concentrations of chlordane caused disruption of glucose and lipid metabolism, increased insulin secretion and impairment of insulin signaling. Notably, it also led to massive ROS production and lipid peroxidation despite of the activation of Nrf2 signaling pathway, an important pathway for maintaining redox homeostasis. Collectively, chlordane causes lipid peroxidation and disrupts redox homeostasis, which may be a potential mechanism leading to impaired insulin signaling and the metabolism of glucose and lipid, ultimately affects Drosophila development.

To better guide microbial risk management and control, growth kinetic models of Salmonella with the coexistence of two other dominant background bacteria in pork were constructed. Sterilized pork cutlets were inoculated with a cocktail of Salmonella Derby (S. Derby), Pseudomonas aeruginosa (P. aeruginosa), and Escherichia coli (E. coli), and incubated at various temperatures (4–37 °C). The predictive growth models were developed based on the observed growth data. By comparing R2 of primary models, Baranyi models were preferred to fit the growth curves of S. Derby and P. aeruginosa, while the Huang model was preferred for E. coli (all R2 ≥ 0.997). The secondary Ratkowsky square root model can well describe the relationship between temperature and μmax (all R2 ≥ 0.97) or Lag (all R2 ≥ 0.98). Growth models were validated by the actual test values, with Bf and Af close to 1, and MSE around 0.001. The time for S. Derby to reach a pathogenic dose (105 CFU/g) at each temperature in pork was predicted accordingly and found to be earlier than the time when the pork began to be judged nearly fresh according to the sensory indicators. Therefore, the predictive microbiology model can be applied to more accurately predict the shelf life of pork to secure its quality and safety.

Background: The objective of this study is to identify independent risks and protective factors and to construct a mortality prediction model for gastrectomy in the Chinese population.Study design: This is a population-based prospective cohort at an institutional level. Seventy-two participating hospitals reported their annual gastrectomy data between 2014 and 2016, while 44 variables covering the institution and surgical information were included in the analysis. We used R software to encode and complete data pre-processing. The first difference model was applied to build the risk model. Data from 2014 and 2015 were assigned to risk model development, while data from 2016 was used for validation.Results: In the included centers with 94,277 gastric cancer cases, the in-hospital mortality rate was 0.32%. The regression model revealed that provinces with low-middle GDP, hospitals with annual gastrectomy volume between 100 and 500, greater volume of urgent surgeries performed, larger proportion of males, and a higher proportion of liver metastasis were independent risk factors for mortality following gastric surgeries, while higher laparoscopic resection volume, greater volume of distal gastrectomy with B2 reconstruction, and larger proportion of palliative surgery were independent protective factors (p < 0.05, respectively). In the prediction test, the mean square error of the training set was 0.948, while that of the test set was 0.728, demonstrating the effectiveness of this model.Conclusions: We constructed the first mortality risk prediction model for gastric cancer surgery in the Chinese population. The identified risk factors will help with the therapy selection, while further informing Chinese medical policy decision-makers.