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PURPOSE: The characteristics of saliva and intestinal microbial community in children with high caries and no caries were analyzed by 16S rDNA high-throughput sequencing. METHODS: Among 431 children aged 3-5 years old in Zunyi City who were investigated previously by our team, 25 children in the high caries group and the same in the caries-free group were selected for fecal and saliva samples. 16S rDNA high-throughput sequencing was used to analyze the bacterial flora structure of the samples and identify the species with different relative abundance at the species level. SPSS 18.0 software package was used for data analysis. RESULTS: The diversity of intestinal flora in the high caries group was higher than that in the caries-free group, and the difference was statistically significant(Pï¼0.05). The diversity of salivary flora in the high caries group was more than that in the caries-free group, with no significant difference(Pï¼0.05). At phylum level,there was no significant difference in intestinal and salivary flora between children with high caries and children without caries. At gene level, Blautia, [Eubacterium] hallii group and [Eubacterium] eligens group in the intestine of caries-free group were significantly higher than those of high caries group(Pï¼0.05), while Parasutterella and Christensenellaceae R-7 group were significantly lower than those of high caries group(Pï¼0.05). At gene level, Peptostreptococcus in saliva of caries-free group was significantly higher than that in high caries group(Pï¼0.05). Dialister, Kingella, Escherichia-Shigella and Treponema in saliva of caries-free group were significantly lower than those in high caries group(Pï¼0.05). CONCLUSIONS: There are significant differences in species composition of intestinal flora but no in salivary flora between children with high caries and children without caries.
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Caries Dental , Microbioma Gastrointestinal , Secuenciación de Nucleótidos de Alto Rendimiento , ARN Ribosómico 16S , Saliva , Humanos , Saliva/microbiología , Caries Dental/microbiología , Preescolar , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , ARN Ribosómico 16S/genética , Microbioma Gastrointestinal/genética , Heces/microbiología , Eubacterium/genética , ADN Bacteriano/genética , ADN Ribosómico/genéticaRESUMEN
Background: Orthotopic models of lung cancer have been widely utilized, and the purpose of this study was to demonstrate the viability of our proposed modified modeling approach. Methods: A total of 50 female BALB/c mice were implanted with 1×1×1 mm fragments of a tumor sample into the left lung lobe. After 2 months of observation, the mice were humanely euthanized through CO2 inhalation. The macroscopic specimens were photographed, and the most representative neoplastic lesions were collected for histological analysis. Small-animal positron emission tomography/computed tomography (PET/CT) scans were conducted on 6 randomly selected mice. Results: Local tumor formation, ipsilateral thoracic tissue infiltration, the contralateral chest wall, right lung metastases, and distant kidney metastases were observed in these models. Overall, the tumor development and metastasis rates were 60.86% (28/46) and 57.14% (16/28), respectively. The 3 mice that had a small-animal PET/CT scan developed a local tumor, but no distant metastases were observed. Conclusions: This modified method was deemed reliable, reproducible, minimally invasive, straightforward, and comprehensible; it might serve as the foundation for developing patient-derived orthotopic xenografts of lung cancer.
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OBJECTIVE: Studies have shown that oral microbiota composition is altered in type 2 diabetes mellitus, implying that it is a potential biomarker for diabetes. This study aimed at constructing a noninvasive auxiliary diagnostic model for diabetes based on differences in the salivary microbial community. DESIGN: Salivary microbiota from 24 treatment-naive type 2 diabetes mellitus patients and 21 healthy populations were detected through 16S rRNA gene sequencing, targeting the V3/V4 region using the MiSeq platform. Salivary microbiome diversity and composition were analyzed so as to establish a diagnostic model for type 2 diabetes. RESULTS: Salivary microbiome for treatment-naive type 2 diabetes mellitus patients was imbalanced with certain taxa, including Slackia, Mitsuokella, Abiotrophia, and Parascardovia that being significantly dominant, while the abundance of Moraxella was high in healthy controls. Diabetic patients exhibited varying levels of Prevotella nanceiensis and Prevotella melaninogenica which were negatively correlated with glycosylated hemoglobin and fasting blood glucose levels, as well as fasting blood glucose levels, respectively. Based on differences in salivary microbiome composition between diabetic and healthy groups, we developed a diagnostic model that can be used for the auxiliary diagnosis of type 2 diabetes mellitus with an accuracy of 80 %. CONCLUSIONS: These findings elucidate on the differences in salivary microbiome compositions between type 2 diabetic and non-diabetic populations, and the diagnostic model provides a promising approach for the noninvasive auxiliary diagnosis of diabetes mellitus.
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Diabetes Mellitus Tipo 2 , Microbiota , Diabetes Mellitus Tipo 2/diagnóstico , Humanos , Prevotella , ARN Ribosómico 16S/genéticaRESUMEN
Human microbiome refers to the total microorganism genetic information of human body surface and internal, which is closely related to human health and disease. Oral and gut microbiomes are the most diverse microbial communities, which can interact and play a role in the development of the disease, and can reflect the health and disease state in real time. Type 2 diabetes mellitus is a metabolic disorder caused by both genetic and environmental factors. Recent research has shown a link between microbes and diabetes. This article reviewed the latest research on the changes of oral and gut microbiomes in type 2 diabetes mellitus patients, which expects to provide a reference for exploring the development of the disease model for prediction, diagnosis and prognosis of type 2 diabetes mellitus based on human microbiome characteristics.