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1.
J Cell Physiol ; 230(11): 2634-9, 2015 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-25899830

RESUMO

Connective Tissue Growth Factor (CCN2/CTGF) and Nephroblastoma Overexpressed (CCN3/NOV) execute key functions within the hematopoietic compartment. Both are abundant in the bone marrow stroma, which is a niche for hematopoiesis and supports marrow function. Roles for 1,25-dihydroxyvitamin D3 (calcitriol) and all-trans retinoic acid in the bone marrow have also been elucidated. Interestingly, some of the annotated roles of these vitamins overlap with established functions of CCN2 and CCN3. Yet, no factor has been identified that unifies these observations. In this study, we report the regulation of the CTGF and NOV genes by Myeloid Zinc Finger-1 (MZF-1), a hematopoietic transcription factor. We show the interaction of MZF-1 with the CTGF and NOV promoters in several cell types. Up-regulation of MZF-1 via calcitriol and vitamin A induces expression of CTGF and NOV, implicating a role for these vitamins in the functions of these two genes. Lastly, knockdown of MZF1 reduces levels of CTGF and NOV. Collectively, our results argue that MZF-1 regulates the CTGF and NOV genes in the hematopoietic compartment, and may be involved in their respective functions in the stroma.


Assuntos
Fator de Crescimento do Tecido Conjuntivo/biossíntese , Hematopoese/genética , Fatores de Transcrição Kruppel-Like/genética , Proteína Sobre-Expressa em Nefroblastoma/biossíntese , Medula Óssea/metabolismo , Calcitriol/metabolismo , Fator de Crescimento do Tecido Conjuntivo/genética , Regulação da Expressão Gênica , Humanos , Fatores de Transcrição Kruppel-Like/metabolismo , Proteína Sobre-Expressa em Nefroblastoma/genética , RNA Mensageiro/biossíntese , RNA Mensageiro/genética , Tretinoína/metabolismo
2.
PLoS One ; 11(12): e0167370, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-28005908

RESUMO

Research on the human microbiome, the microbiota that live in, on, and around the human person, has revolutionized our understanding of the complex interactions between microbial life and human health and disease. The microbiome may also provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death. Current methods of estimating PMI for cadavers discovered in uncontrolled, unstudied environments have substantial limitations, some of which may be overcome through the use of microbial indicators. In this project, we sampled the microbiomes of decomposing human cadavers, focusing on the skin microbiota found in the nasal and ear canals. We then developed several models of statistical regression to establish an algorithm for predicting the PMI of microbial samples. We found that the complete data set, rather than a curated list of indicator species, was preferred for training the regressor. We further found that genus and family, rather than species, are the most informative taxonomic levels. Finally, we developed a k-nearest- neighbor regressor, tuned with the entire data set from all nasal and ear samples, that predicts the PMI of unknown samples with an average error of ±55 accumulated degree days (ADD). This study outlines a machine learning approach for the use of necrobiome data in the prediction of the PMI and thereby provides a successful proof-of- concept that skin microbiota is a promising tool in forensic death investigations.


Assuntos
Microbiota , Pele/microbiologia , Bactérias/genética , Bactérias/isolamento & purificação , Cadáver , DNA Bacteriano/genética , DNA Bacteriano/metabolismo , Patologia Legal , Humanos , Aprendizado de Máquina , Mudanças Depois da Morte , Fatores de Tempo
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