scholarly journals Characterization, functional analysis, and expression levels of three carbonic anhydrases in response to pH and saline–alkaline stresses in the ridgetail white prawn Exopalaemon carinicauda

2019 ◽  
Vol 24 (3) ◽  
pp. 503-515 ◽  
Author(s):  
Qianqian Ge ◽  
Jian Li ◽  
Jiajia Wang ◽  
Zhengdao Li ◽  
Jitao Li
2018 ◽  
Vol 109 ◽  
pp. 448-456 ◽  
Author(s):  
Yuying Sun ◽  
Jiquan Zhang ◽  
Fengge Song ◽  
Jing Wang ◽  
Zhenzhen Zhang ◽  
...  

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2424-2424
Author(s):  
Maria Roubelakis ◽  
Dimitra Zagoura ◽  
Ourania Trohatou ◽  
Pantelis Zotos ◽  
Vassiliki Bitsika ◽  
...  

Abstract Human mesenchymal stem cells (hMSCs) constitute a population of multipotent stem cells, easily expanded in culture and able to differentiate into many lineages. These features render MSCs a very attractive tool for developing new strategies for clinical applications based on cell therapy. So far, the most common sources of MSCs have been the bone marrow (BM) and the umbilical cord blood (UCB). Our group has recently isolated MSCs from a novel source, such as the amniotic fluid (AF) and characterized them based on their phenotype, pluripotency, proliferation rate, differentiation potential and the generated for the first time proteomic profile (Stem Cells Dev.16:931, 2007). To further decipher the molecular mechanisms as they relate to the MSCs from the other two sources, in the present study we investigated the comparative post-transcriptional regulation mechanisms of MSCs from the three sources at the miRNA level. miRNAs are single-stranded RNA molecules 20–23 nt long, regulating gene expression by interacting with target mRNAs at specific sites of their 3′ UTR to induce either a cleavage of the message or inhibit its translation. More specifically, the objectives of the study were the detection of miRNA populations in AF, BM and UCB-MSCs, the validation of their expression levels using Real Time PCR, the generation of a new algorithm for the in silico detection of miRNA target-genes and the validation of miRNA binding on specific targets predicted by the algorithm application. Initially we identified 67 different species of miRNAs expressed in all three types of MSCs but at different levels in each source, using miRNA arrays (miRCURY™ LNA αrray v.8.1). We then further established and compared the miRNA profiles among the three sources. The data revealed a characteristic pattern of a set of key miRNAs, unique for each type of MSCs. The results were further validated for the characteristic expression levels of specific miRNAs in AF-MSCs, such as miR-21, miR-221, miR-222, miR-572, miR-210 and let-7d, employing Real Time PCR. For predicting mRNA targets of specific miRNAs, we developed a novel stand-alone application, designated GOmir, consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis, by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools and by providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir (by using up to four different databases) introduces, for the first time, miRNA predicted targets accompanied by full gene description, functional analysis and detailed gene ontology clustering. From the systematic miRNA array analysis, we detected higher expression levels of miR-21 and miR-100 in AF-MSCs compared to BM and UCB-MSCs. According to GOmir prediction, miR-21 and miR-100, are considered responsible for the regulation of key stem cell genes such as SOX-2 and FZD8, respectively, thus implying an important role on the self renewal of stem cells. To evaluate the predictive capacity of GOmir and the role of miR-21 in AF-MSCs in more detail, we performed functional studies using miR-21 antagonists and cloning strategies targeting for specific SOX-2 3′ UTR mRNA binding sites. These studies resulted in upregulation of the SOX-2 expression, providing the proof of principle for the validity of this combined approach. Thus, our data derived from this new strategy, are expected to clarify systematically the post-transcriptional regulation of MSCs from these different sources.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 3458-3458
Author(s):  
Ebru Coskun ◽  
Martin Neumann ◽  
Cornelia Schlee ◽  
Nicola Goekbuget ◽  
Dieter Hoelzer ◽  
...  

Abstract Abstract 3458 Introduction: Early T-cell precursor acute lymphoblastic leukemia (ETP-ALL) has been identified as high-risk subgroup in pediatric acute T-lymphoblastic leukemia (T-ALL). ETP-ALLs originate from early thymic progenitors that retain stem cell features and are characterized by a specific immunophenotype and by a specific gene expression profile. Recently, we have characterized ETP-ALL as subgroup of early T-ALL in adults. To unravel the underlying mechanisms for the aberrant and distinct gene expression profile in ETP-ALL we now explored the expression of microRNAs (miRNAs) as gene regulators in ETP-ALL and further investigated their functional role in acute leukemia. Patients and methods: We screened expression levels of 667 miRNAs in newly diagnosed T-ALL patients (n=14: ETP-ALL n=8, non-ETP early T-ALL n=3, thymic T-ALL n=3) and 2 healthy controls (CD3 selected T cells) using a Taqman Low Density Array (TLDA; Applied Biosystems). The expression levels of miR-221 and miR-222 were validated in a large cohort of adult T-ALL (n=178: ETP-ALL n=66 and typical T-ALL n=112 including early-, thymic-, and mature T-ALLs) and healthy controls (n=6) by real-time-PCR (Taqman microRNA assays; Applied Biosystems). These patients were enrolled on the GMALL study 07/03. Functional analysis was performed by AMAXA transfection of pSUPER vector containing the miR-221 and miR-222 DNA sequences in Jurkat (T-lineage ALL) and KG1a (AML) cells. Viability was determined by cell proliferation reagent WST-1, and BrdU ELISA. Apoptosis was measured by annexin-V/7AAD staining with subsequent flow cytometric analysis. Results: In our screen 229 (34%) of the 667 miRNAs represented by the TLDA were expressed at detectable levels in at least two-thirds of the T-ALL samples and the controls. Of these we identified 55 miRNAs to be differentially expressed in T-ALL samples compared to healthy controls: 49 miRNAs were upregulated and 6 miRNAs were downregulated in the patient samples. Of these, miR-221 and miR-222 were the only miRNAs significantly upregulated in the ETP-ALL compared to the combined early and thymic T-ALL subgroups (8.0-fold, P<0.01; 5.0-fold, P<0.01, respectively). Therefore, we further validated miR-221 and miR-222 expression in a larger set of 178 T-ALL samples and observed a 3.3-fold higher expression of miR-221 (P<0.0001) and 3.9-fold higher expression of miR-222 (P<0.0001) in ETP-ALL (n=66) compared to typical T-ALL (n=112). For the correlation of miR-221 and miR-222 expression with molecular features, samples were divided into groups (low and high) according to the median of the miRNA expression levels. High miR-222 expression was associated with an immature phenotype of early T-ALL (P<0.01) and cell surface expression of CD34 (mean: 32%) compared to low miR-222 expressers (mean: 8%; P<0.01). Moreover, high miR-222 expression was associated with expression of myeloid markers CD33 (mean: 23% compared to 4% in low miRNA expressers, P<0.01) and CD13 (mean: 18% vs. 4%, P<0.01). Similar results were obtained for miR-221. In vitro studies revealed that overexpression of miR-222 inhibited proliferation of Jurkat (58% reduction of proliferation compared to cells transfected with the empty vector, P<0.001) and KG1a cells (50% reduction of proliferation compared to control cells, P<0.01) determined by WST-1. A reduction of the DNA synthesis was detected by BrdU incorporation after miR-222 overexpression in Jurkat (37% reduction compared to control cells) and in KG1a cells (54% reduction compared to control cells). Overexpression of miR-222 induced a 1.3- (P=0.02) and 3.0-fold (P<0.01) increase in apoptosis in Jurkat and KG1a cells, respectively. No significant changes were observed for miR-221 transfected cells in these functional assays. Conclusion: In summary, our study revealed aberrant expression of miRNAs in ETP-ALL, with miR-221 and miR-222 as the most overexpressed miRNAs. Functional analysis demonstrated that miR-222 impaired the proliferation and induced apoptosis, indicating a potential role for miR-222 in acute leukemia. Importantly, miR-222 targets such as the proto-oncogene c-KIT and the ETS1oncogene are contained in the gene expression profile of ETP-ALL. Thus, aberrant expression of miR-222 may directly impact leukemogenesis by altering expression of key oncogenes in acute leukemia. Disclosures: Goekbuget: Micromet: Consultancy.


2003 ◽  
Vol 19 (3) ◽  
pp. 164-174 ◽  
Author(s):  
Stephen N. Haynes ◽  
Andrew E. Williams

Summary: We review the rationale for behavioral clinical case formulations and emphasize the role of the functional analysis in the design of individualized treatments. Standardized treatments may not be optimally effective for clients who have multiple behavior problems. These problems can affect each other in complex ways and each behavior problem can be influenced by multiple, interacting causal variables. The mechanisms of action of standardized treatments may not always address the most important causal variables for a client's behavior problems. The functional analysis integrates judgments about the client's behavior problems, important causal variables, and functional relations among variables. The functional analysis aids treatment decisions by helping the clinician estimate the relative magnitude of effect of each causal variable on the client's behavior problems, so that the most effective treatments can be selected. The parameters of, and issues associated with, a functional analysis and Functional Analytic Clinical Case Models (FACCM) are illustrated with a clinical case. The task of selecting the best treatment for a client is complicated because treatments differ in their level of specificity and have unequally weighted mechanisms of action. Further, a treatment's mechanism of action is often unknown.


1958 ◽  
Vol 3 (6) ◽  
pp. 158-160
Author(s):  
LAWRENCE SCHLESINGER

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