NanoporeBased Surveillance involving Zoonotic Bacterial Pathogens in FarmDwelling Peridomestic Mice

Inflammation of the chorion and/or amnion during pregnancy is called chorioamnionitis. Acute chorioamnionitis is implicated in approximately 40% of preterm births and has wide-ranging implications for the mother, fetus, and newborn. Large disease burden and lack of therapeutic approaches drive the discovery programs to define and test targets to tackle chorioamnionitis. Central to the advancement of these studies is the use of animal models. These models are necessary to deepen our understanding of basic mechanisms of host-pathogen interactions central to chorioamnionitis disease pathogenesis. Models of chorioamnionitis have been developed in numerous species, including mice, rabbits, sheep, and non-human primates. The various models present an array of strategies for initiating an inflammatory response and unique opportunities for studying its downstream consequences for mother, fetus, or newborn. In this review, we present a discussion of the key features of human chorioamnionitis followed by evaluation of currently available animal models in light of these features and consideration of how these models can be best applied to tackle outstanding questions in the field.[This corrects the article DOI 10.3389/fonc.2021.697156.].[This corrects the article DOI 10.3389/fonc.2021.689538.].Tumor microenvironment (TME) formation is a major cause of immunosuppression. The TME consists of a considerable number of macrophages and stromal cells that have been identified in multiple tumor types. CCL2 is the strongest chemoattractant involved in macrophage recruitment and a powerful initiator of inflammation. Evidence indicates that CCL2 can attract other host cells in the TME and direct their differentiation in cooperation with other cytokines. Overall, CCL2 has an unfavorable effect on prognosis in tumor patients because of the accumulation of immunosuppressive cell subtypes. However, there is also evidence demonstrating that CCL2 enhances the anti-tumor capability of specific cell types such as inflammatory monocytes and neutrophils. The inflammation state of the tumor seems to have a bi-lateral role in tumor progression. Here, we review works focusing on the interactions between cancer cells and host cells, and on the biological role of CCL2 in these processes.Advanced prostate cancer (PCa) represents the fifth cause of cancer death worldwide. Although survival has improved with second-generation androgen signaling and Parp inhibitors, the benefits are not long-lasting, and new therapeutic approaches are sorely needed. Lipids and their metabolism have recently reached the spotlight with accumulating evidence for their role as promoters of PCa development, progression, and metastasis. As a result, interest in targeting enzymes/transporters involved in lipid metabolism is rapidly growing. Moreover, the use of lipogenic signatures to predict prognosis and resistance to therapy has been recently explored with promising results. Despite the well-known association between obesity with PCa lethality, the underlying mechanistic role of diet/obesity-derived metabolites has only lately been unveiled. Furthermore, the role of lipids as energy source, building blocks, and signaling molecules in cancer cells has now been revisited and expanded in the context of the tumor microenvironment (TME), which is heavily influenced by the external environment and nutrient availability. Here, we describe how lipids, their enzymes, transporters, and modulators can promote PCa development and progression, and we emphasize the role of lipids in shaping TME. In a therapeutic perspective, we describe the ongoing efforts in targeting lipogenic hubs. Finally, we highlight studies supporting dietary modulation in the adjuvant setting with the purpose of achieving greater efficacy of the standard of care and of synthetic lethality. PCa progression is "a matter of fats", and the more we understand about the role of lipids as key players in this process, the better we can develop approaches to counteract their tumor promoter activity while preserving their beneficial properties.
Leukemic stem cell (LSC) is thought to be responsible for chronic myelogenous leukemia (CML) initiation and relapse. However, the inherent regulation of LSCs remains largely obscure. Herein, we integratedly analyzed miRNA and gene expression alterations in bone marrow (BM) Lin
Sca1
c-Kit
cells (LSKs) of a tet-off inducible CML mouse model, Scl/tTA-BCR/ABL (BA).
Scl/tTA and TRE-BA transgenic mice were crossed in the presence of doxycycline to get double transgenic mice. Both miRNA and mRNA expression profiles were generated from BM LSKs at 0 and 3 weeks after doxycycline withdrawal. The target genes of differentially expressed miRNAs were predicted, followed by the miRNA-mRNA network construction.
and
experiments were further performed to elucidate their regulation and function in CML progression.
As a result of the integrated analysis and experimental validation, an anti-apoptotic pathway emerged from the fog. miR-142a was identified to be downregulated by enhanced ERK-phosphorylation in BA-harboring cells, thereby relieving its repression on Ciapin1, an apoptosis inhibitor. read more Moreover, miR-142a overexpression could partially rescue the abnormal anti-apoptotic phenotype and attenuate CML progression.
Taken together, this study explored the miRNA-mRNA regulatory networks in murine CML LSKs and demonstrated that ERK-miR-142a-Ciapin1 axis played an essential role in CML pathogenesis.
Taken together, this study explored the miRNA-mRNA regulatory networks in murine CML LSKs and demonstrated that ERK-miR-142a-Ciapin1 axis played an essential role in CML pathogenesis.To identify novel hypoxia-associated long non-coding RNAs (lncRNAs) as potential biomarkers, we developed a risk stratification signature and constructed a prognosis prediction nomogram of clear cell renal cell carcinoma (ccRCC). Hypoxia-related lncRNAs were identified through Pearson correlation analysis between the expression profiles of hypoxia-related differentially expressed genes and lncRNAs from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Then, a signature of four key lncRNAs (COMETT, EMX2OS, AC026462.3, and HAGLR) was developed. The four lncRNAs were downregulated in high-grade, advanced stage, and high-risk ccRCC. The signature had an independent and long-standing prognosis prediction ability up to a 10-year follow-up. Notably, the risk score was significantly positively correlated with the infiltration abundances of six immune cells from the Tumor IMmune Estimation Resource (TIMER). The gene set enrichment analysis (GSEA) also suggested that the signature was involved in metabolism and tumorigenesis, which were closely related to the hypoxic tumor microenvironment. Ultimately, a nomogram of signature, age, stage, and grade, was built to predict the individual long-term survival possibility. Finally, the expressions of four lncRNAs were validated by quantitative real-time PCR (qRT-PCR). Our study identified a four-lncRNA signature and established a prognostic nomogram that reliably predicts survival in ccRCC. The findings may be beneficial to therapeutic customization and medical decision-making.It has been shown that circular RNA XPO1 (circXPO1) is involved in cancer (e.g., lung adenocarcinoma and osteosarcoma) progression by sponging microRNAs. Nevertheless, the role of circXPO1 and its interaction with microRNAs in prostate cancer remains unknown. In this study, the results of quantitative real-time PCR showed that circXPO1 levels were dramatically increased in human prostate cancer tissue and cell lines compared with those in normal tissue and cell line. Furthermore, cell proliferation, colony formation, and cell invasion assays showed that circXPO1 promoted the malignant behavior of pancreatic cells in vitro. Mechanistically, bioinformatics prediction, a dual-luciferase reporter assay, and pull-down assay suggested that circXPO1 physically targets miR-23a and negatively regulates its expression in pancreatic cancer cells. miR-23a mimics and inhibitors effectively reversed the effects of circXPO1 on the malignant behavior of prostate cancer cells in vitro. Consistent results were observed in the xenograft tumor model. In conclusion, circXPO1 promotes prostate cancer progression via targeting miR-23a, thus suggesting the circXPO1/miR-23a axis can be used as a potential therapeutic target for prostate cancer treatment.
(
) is a type I biological carcinogen, which may cause about 75% of the total incidence of gastric cancer worldwide.
infection can induce and activate the cancer-promoting signaling pathway and affect the occurrence and outcome of gastric cancer through controlling the regulatory functions of long non-coding RNAs (lncRNAs). However, we have no understanding of the prognostic worth of lncRNAs for gastric cancer patients infected with
.
We screened differentially expressed lncRNAs using DESeq2 method among TCGA database. And we built the
infection-related lncRNAs regulatory patterns. link2 Then, we constructed
infection-based lncRNAs prognostic signatures for gastric cancer patients together with
infection,
uni-variable and multi-variable COX regression analyses. Based on receiver operator characteristic curve (ROC) analysis, we evaluated the prediction effectiveness for this model.
We identified 115
infection-related genes were differentially expressed among
-infected gastric cancer tisignature and nomogram can predict the prognosis of these patients.
To evaluate the value of nomogram models combining apparent diffusion coefficient (ADC) value and radiomic features on magnetic resonance imaging (MRI) in predicting the type, grade, deep myometrial invasion (DMI), lymphovascular space invasion (LVSI), and lymph node metastasis (LNM) of endometrial carcinoma (EC) preoperatively.
This study included 210 EC patients. ADC value was calculated, and radiomic features were measured on T2-weighted images. The univariate and multivariate logistic regressions and cross-validations were performed to reduce valueless features, then radiomics signatures were developed. Nomogram models using ADC combined with radiomic features were developed in the training cohort. link3 The receiver operating characteristic (ROC) curve was performed to estimate the diagnostic efficiency of nomogram models by the area under the curve (AUC) in the training and validation cohorts.
The ADC value was significantly different between each subgroup. Radiomic features were ultimately limited to four features for type, six features for grade, six features for DMI, four features for LVSI, and eight features for LNM for the nomogram models. The AUC of the nomogram model combining ADC value and radiomic features in the training and validation cohorts was 0.851 and 0.867 for type, 0.959 and 0.880 for grade, 0.839 and 0.766 for DMI, 0.816 and 0.746 for LVSI, and 0.910 and 0.897 for LNM.
The nomogram models of ADC value combined with radiomic features were associated with the type, grade, DMI, LVSI, and LNM of EC, and provide an effective, non-invasive method to evaluate preoperative risk stratification for EC.
The nomogram models of ADC value combined with radiomic features were associated with the type, grade, DMI, LVSI, and LNM of EC, and provide an effective, non-invasive method to evaluate preoperative risk stratification for EC.