Properties of Spherically Symmetric Black Holes in the Generalized Brans-Dicke Modified Gravitational Theory.

The many problems faced by the theory of general relativity (GR) have always motivated us to explore the modified theory of GR. Considering the importance of studying the black hole (BH) entropy and its correction in gravity physics, we study the correction of thermodynamic entropy for a kind of spherically symmetric black hole under the generalized Brans-Dicke (GBD) theory of modified gravity. We derive and calculate the entropy and heat capacity. It is found that when the value of event horizon radius r+ is small, the effect of the entropy-correction term on the entropy is very obvious, while for larger values r+, the contribution of the correction term on entropy can be almost ignored. In addition, we can observe that as the radius of the event horizon increases, the heat capacity of BH in GBD theory will change from a negative value to a positive value, indicating that there is a phase transition in black holes. Given that studying the structure of geodesic lines is important for exploring the physical characteristics of a strong gravitational field, we also investigate the stability of particles' circular orbits in static spherically symmetric BHs within the framework of GBD theory. Concretely, we analyze the dependence of the innermost stable circular orbit on model parameters. In addition, the geodesic deviation equation is also applied to investigate the stable circular orbit of particles in GBD theory. The conditions for the stability of the BH solution and the limited range of radial coordinates required to achieve stable circular orbit motion are given. Finally, we show the locations of stable circular orbits, and obtain the angular velocity, specific energy, and angular momentum of the particles which move in circular orbits.

Long non-coding RNA SNHG3 promotes breast cancer cell proliferation and metastasis by binding to microRNA-154-3p and activating the notch signaling pathway.

BACKGROUND: Breast cancer (BC) is a malignant tumor that occurs in the epithelial tissue of the breast gland. Long non-coding RNA (lncRNA) small nucleolar RNA host gene 3 (SNHG3) has been found to promote BC cell proliferation and invasion by regulating the microRNA (miR)-101/zinc-finger enhancer binding axis in BC. Herein, the objective of the present study is to evaluate the effect of lncRNA SNHG3 on BC cell proliferation and metastasis with the Notch signaling pathway. METHODS: Differentially expressed lncRNA in BC tissues and normal breast tissues was analyzed. SNHG3 si-RNA-1 and SNHG3 si-RNA-2 were constructed to detect the mechanism of SNHG3 interference in BC cell proliferation, viability, migration and invasion. Then, dual-luciferase reporter gene assay was utilized to verify the binding relation between SNHG3 and miR-154-3p as well as miR-154-3p and Notch2. Moreover, xenograft transplantation was applied to confirm the in vitro experiments. RESULTS: Highly expressed SNHG3 was observed in BC tissues. The growth of BC cells in vivo and in vitro was evidently repressed after silencing SNHG3. BC cell invasion and migration were inhibited by silencing SNHG3 in vitro. SNHG3 could act as a competing endogenous RNA of miR-154-3p and upregulate the Notch signaling pathway to promote BC cell development. Activation of the Notch signaling pathway can partly reverse the inhibition of cell activity induced by silencing SNHG3. CONCLUSION: Our study demonstrated that interfered lncRNA SNHG3 promoted BC cell proliferation and metastasis by activating the Notch signaling pathway. This investigation may offer new insight for BC treatment.

Locally Trapping the C-C Chemokine Receptor Type 7 by Gene Delivery Nanoparticle Inhibits Lymphatic Metastasis Prior to Tumor Resection.

Triple negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Currently, no targeted treatment is available for TNBC, and the most common clinical therapy is tumor resection, which often promotes metastasis risks. Strong evidence suggests that the lymphatic metastasis is mediated by the C-C chemokine receptor type 7 (CCR7)/C-C motif chemokine ligand 21 crosstalk between tumor cells and the lymphatic system. It is hypothesized that CCR7 is a key immune modulator in the tumor microenvironment and the local blockade of CCR7 could effectively inhibit TNBC lymphatic metastasis. Accordingly, a plasmid encoding an antagonistic CCR7 affinity protein-CCR7 trap is delivered by tumor targeting nanoparticles in a highly metastatic 4T1 TNBC mouse model. Results show that CCR7 traps are transiently expressed, locally disrupt the signaling pathways in the tumor site, and efficiently inhibit TNBC lymphatic metastasis, without inducing immunosuppression as observed in systemic therapies using CCR7 monoclonal antibody. Significantly, upon applying CCR7 trap therapy prior to tumor resection, a 4T1 TNBC mouse model shows good prognosis without any further metastasis and relapse. In addition, CCR7 trap therapy efficiently inhibits the lymphatic metastasis in a B16F10 melanoma mouse model, indicating its great potential for various metastatic diseases treatment.

[Study on the soil salinization monitoring based on measured hyperspectral and HSI data].

The present paper selects the Kuqa Oasis as the study area, studies spectrum characteristics of soil salinity, and establishes soil spectrum library. Through transforming and analyzing varying degrees of soil salinization reflectance spectra data in the typical study area, and selecting the most sensitive spectral bands in response to salinization, we established the measured hyperspectral soil salinity monitoring model, and by correcting the soil salinity monitoring model established by HIS image through scale effect conversion improved the model accuracy under the conditions of a regional-scale monitoring of soil salinization. The results show that both measured hyperspectral soil salinity monitoring model and HSI image soil salinity inversion model have good accuracy, model determination coefficient (R2) is higher than 0.57 and the model stability is better. Compared with the corrected HSI image soil salinity inversion model and uncorrected HSI image soil salinity inversion model, the coefficient of determination has been greatly improved, which increased from 0.571 to 0.681, and through the 0.01 significance level, the root mean square error (RMSE) value is 0.277. The correction HIS image soil salinization monitoring model can better improve the model accuracy under the condition of regional scale soil salinization monitoring, and using this method to carry out the soil salinization quantitative remote sensing monitoring is feasible, and also can provide scientific reference for future research.

Correlation of ADC value with pathologic indexes in colorectal tumor homografts in Balb/c mouse.

OBJECTIVE: Noninvasive diffusion-weighted magnetic resonance imaging (DWI) is a well-studied MR imaging technique for quantifying water diffusion especially in tumor area. The correlation between apparent diffusion coefficient (ADC) value and apoptosis or proliferation is not clear by now. This study aimed to investigate whether DWI-ADC value could be used as an imaging marker related with pathologic indexes of tumors. METHODS: A total of 30 Balb/c mice with HT29 colorectal carcinoma were subjected to DWI and histologic analysis. The percentage of ADC changes and the apoptotic and proliferating indexes were calculated at predefined time points. Kolmogorov-Smirnov distances were considered to determine whether the percentage of ADC changes, and the apoptotic and proliferating indexes were normally distributed. An independent-samples t-test was used to analyze the difference between apoptotic and proliferating indexes in the two groups. RESULTS: THERE WAS A STATISTICALLY SIGNIFICANT DIFFERENCE IN PROLIFERATING INDEX BETWEEN THE RADIOTHERAPY AND CONTROL GROUPS (MEAN PROLIFERATING INDEX: 49.27% vs. 83.09%), and there was a statistically significant difference in apoptotic index between the two groups (mean apoptotic index: 37.7% vs. 2.71%). A significant positive correlation was found between the percentage of ADC changes of the viable tissue and apoptotic index. Pearson's correlation coefficient was 0.655 (P=0.015). A significant negative correlation was found between the percentage of ADC changes of the viable tissue and ki-67 proliferation index. Pearson's correlation coefficient was 0.734 (P<0.001). CONCLUSIONS: Our results suggest that ADC value may be used in measurement of cell apoptotic and proliferating indexes in colorectal carcinoma.

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status.

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.

Construction of a prognostic 6-gene signature for breast cancer based on multi-omics and single-cell data.

Background: Breast cancer (BC) is one of the females' most common malignant tumors there are large individual differences in its prognosis. We intended to uncover novel useful genetic biomarkers and a risk signature for BC to aid determining clinical strategies. Methods: A combined significance (p combined) was calculated for each gene by Fisher's method based on the RNA-seq, CNV, and DNA methylation data from TCGA-BRCA. Genes with a p combined< 0.01 were subjected to univariate cox and Lasso regression, whereby an RS signature was established. The predicted performance of the RS signature would be assessed in GSE7390 and GSE20685, and emphatically analyzed in triple-negative breast cancer (TNBC) patients, while the expression of immune checkpoints and drug sensitivity were also examined. GSE176078, a single-cell dataset, was used to validate the differences in cellular composition in tumors between TNBC patients with different RS. Results: The RS signature consisted of C15orf52, C1orf228, CEL, FUZ, PAK6, and SIRPG showed good performance. It could distinguish the prognosis of patients well, even stratified by disease stages or subtypes and also showed a stronger predictive ability than traditional clinical indicators. The down-regulated expressions of many immune checkpoints, while the decreased sensitivity of many antitumor drugs was observed in TNBC patients with higher RS. The overall cells and lymphocytes composition differed between patients with different RS, which could facilitate a more personalized treatment. Conclusion: The six genes RS signature established based on multi-omics data exhibited well performance in predicting the prognosis of BC patients, regardless of disease stages or subtypes. Contributing to a more personalized treatment, our signature might benefit the outcome of BC patients.

A Novel Necroptosis-Related miRNA Signature for Predicting the Prognosis of Breast Cancer Metastasis.

Objective: Necroptosis was recently identified as a form of programmed cell death that plays an essential role in breast cancer metastasis. MicroRNAs (miRNAs) have long been recognized to affect cell death and tumor growth. In this study, we aimed to screen for necroptosis-associated miRNAs that predict breast cancer metastasis. Method: This study used The Cancer Genome Atlas (TCGA) public database to obtain miRNA expression data and associated clinical data from breast cancer patients and then retrieved miRNA data related to necrosis and apoptosis. Next, using Cox regression model analysis (univariate or multivariate) as well as a comparison analysis (differential analysis), a prognostic multi-miRNA molecular marker was established. Finally, prognosis-related miRNAs were utilized to identify target genes, and the functions of the target genes were analyzed for enrichment to investigate the probable mechanisms of the miRNAs. Results: Ten miRNAs were screened through differential analysis to build models: hsa-miR-148a-3p, hsa-miR-223-3p, hsa-miR-331-3p, has-miR-181a-5p, hsa-miR-181b-5p, hsa-miR-181c-5p, hsa-miR-181d-5p, hsa-miR-200a-5p, hsa-miR-141-3p, and hsa-miR-425-5p. The multivariate Cox regression model was an independent prognostic factor (univariate Cox regression results: HR = 3.2642, 95%CI = 1.5773 - 6.7554, P = 0.0014; multivariate Cox regression results: HR = 3.1578, 95%CI = 1.5083 - 6, P = 0.0023). The survival curve of the risk score also revealed that patients with a high risk score had a poor prognosis (P = 2e - 04). The receiver operating characteristic (ROC) curve showed that the model has a certain prediction ability. Batch survival analysis of the miRNAs in the model was conducted and showed that hsa-miR-331-3p (P = 0.0182) was strongly associated with prognosis. Twenty-three predicted target genes were obtained, and Gene Ontology (GO) enrichment analysis showed that these target genes were strongly enriched in transcriptional initiation and cell membrane trafficking. Conclusion: Our research identified a novel miRNA marker for predicting breast cancer patient prognosis and lays the groundwork for future research on necroptosis-related genes.

MYCL promotes the progression of triple­negative breast cancer by activating the JAK/STAT3 pathway.

The present study aimed to investigate the underlying regulatory mechanism of MYCL proto­oncogene (MYCL) in triple­negative breast cancer (TNBC) progression. In vitro experiments were performed to confirm the functional roles of MYCL in TNBC, and its effects on the JAK/STAT3 pathway through flow cytometric analysis, colony formation, wound healing and Transwell assays. In addition, the GSE45498 dataset demonstrated that MYCL was upregulated in TNBC and that it was significantly related to poor survival of patients with TNBC. Knockdown of MYCL induced the apoptosis, and suppressed the proliferation, migration and invasion of TNBC cells by inhibiting the JAK/STAT3 pathway. Notably, MYCL could activate the JAK/STAT3 pathway, whereas inhibition of the JAK/STAT3 pathway could eliminate the effect of MYCL on TNBC cells. Knockdown of MYCL also suppressed the growth of TNBC xenograft tumors. In conclusion, MYCL could promote TNBC progression by activating the JAK/STAT3 pathway.

The Pharmacological Mechanisms of Xiaochaihutang in Treating Breast Cancer Based on Network Pharmacology.

Background: As a classic prescription in Chinese medicine treatment, Xiaochaihutang (XCHT) can improve the clinical effect and reduce serum tumor markers in patients with breast cancer (BC). However, there has not been any study to confirm the mechanism. We used bioinformatics analysis and network pharmacology to find the potential targets. Methods: The differentially expressed genes (DEGs) of BC were identified from the Cancer Genome Atlas (TCGA) dataset. Then, we utilized weighted coexpression network analysis (WGCNA) with the same dataset. The target genes of BC were obtained by comparing genes of DEGs and in significant modules of WGCNA. Drug targets of XCHT from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database were intersected with the targets of BC. The protein-protein interaction (PPI) of the drug targets was analysed by using the STRING database. We utilized the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analysis (KEGG) enrichment analysis to identify the specific pathways and key target proteins. Receiver operator characteristic (ROC) curve was used as the verification of drug targets. Molecular docking was performed to visualize the patterns of interactions between the effective molecule and targeted protein. Results: We obtained a set of 21 target genes, which mainly encode neurotransmitter receptors or related transporters, such as OPRD1, 5-HT2A, and so on. In addition, enrichment analyses of 21 target genes showed that they were mainly concentrated in pathways related to the nervous system. Molecular docking was performed on the target gene of BC. Six active compounds can enter the active pocket of target gene, namely, naringenin, beta-sitosterol, coumestrol, nuciferine, beta-sitosterol, and protopine, thereby exerting potential therapeutic effects in BC. Conclusions: Our analysis shows that the mechanism of XCHT in the treatment of BC is mainly acting on the neurogenesis in the microenvironment of breast tumor tissue.

[Monitoring of soil salinization in Northern Tarim Basin, Xinjiang of China in dry and wet seasons based on remote sensing].

Soil salinization is one of the most important eco-environment problems in arid area, which can not only induce land degradation, inhibit vegetation growth, but also impede regional agricultural production. To accurately and quickly obtain the information of regional saline soils by using remote sensing data is critical to monitor soil salinization and prevent its further development. Taking the Weigan-Kuqa River Delta Oasis in the northern Tarim River Basin of Xinjiang as test object, and based on the remote sensing data from Landsat-TM images of April 15, 2011 and September 22, 2011, in combining with the measured data from field survey, this paper extracted the characteristic variables modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), and the third principal component from K-L transformation (K-L-3). The decision tree method was adopted to establish the extraction models of soil salinization in the two key seasons (dry and wet seasons) of the study area, and the classification maps of soil salinization in the two seasons were drawn. The results showed that the decision tree method had a higher discrimination precision, being 87.2% in dry season and 85.3% in wet season, which was able to be used for effectively monitoring the dynamics of soil salinization and its spatial distribution, and to provide scientific basis for the comprehensive management of saline soils in arid area and the rational utilization of oasis land resources.