Isolated Sacral Vertebral Hydatid Cyst Presenting with Pathological Fracture

Mohakud, Sudipta; Ray, Biswadeep; Naik, Suprava; Deep, Nerbadyswari

doi:10.1055/s-0039-1695700

Cited by 3 publications

(2 citation statements)

References 3 publications

(5 reference statements)

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“…The relative abundance curve was used to reflect species diversity and abundance of samples. Alpha-diversity indexes, including Chao1, ACE, observed species and goods Coverage were compared to analysis the species richness and uniformity 13 . Beta-diversity analysis was used to evaluate the species complexity among different groups.…”

Section: Methodsmentioning

confidence: 99%

Combined analysis of 16S rDNA sequencing and metabolomics to find biomarkers of drug-induced liver injury

He,

Liu,

Wang

et al. 2023

Sci Rep

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Drug induced liver injury (DILI) is a kind of liver dysfunction which caused by drugs, and gut microbiota could affect liver injury. However, the relationship between gut microbiota and its metabolites in DILI patients is not clear. The total gut microbiota DNA was extracted from 28 DILI patient and 28 healthy control volunteers (HC) and 16S rDNA gene were amplified. Next, differentially metabolites were screened. Finally, the correlations between the diagnostic strains and differentially metabolites were studied.The richness and uniformity of the bacterial communities decreased in DILI patients, and the structure of gut microbiota changed obviously. Enterococcus and Veillonella which belong to Firmicutes increased in DILI, and Blautia and Ralstonia which belong to Firmicutes, Dialister which belongs to Proteobacteria increased in HC. In addition, these diagnostic OTUs of DILI were associated with the DILI damage mechanism. On the other hands, there were 66 differentially metabolites between DILI and HC samples, and these metabolites were mainly enriched in pyrimidine metabolism and steroid hormone biosynthesis pathways. Furthermore, the collinear network map of the key microbiota-metabolites were constructed and the results indicated that Cortodoxone, Prostaglandin I1, Bioyclo Prostaglandin E2 and Anacardic acid were positively correlated with Blautia and Ralstonia, and negatively correlated with Veillonella.This study analyzed the changes of DILI from the perspective of gut microbiota and metabolites. Key strains and differentially metabolites of DILI were screened and the correlations between them were studied. This study further illustrated the mechanism of DILI.

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Section: Methodsmentioning

confidence: 99%

Combined analysis of 16S rDNA sequencing and metabolomics to find biomarkers of drug-induced liver injury

He,

Liu,

Wang

et al. 2023

Sci Rep

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“…The differential diagnoses are chordoma, giant cell tumours, enchondroma, chondrosarcoma, aneurysmal bone cyst, metastases and rarely hydatid cysts in endemic areas. 1 , 4 , 5 …”

Section: Commentmentioning

confidence: 99%

Large Intraosseous Haemangioma of the Sacral Vertebra

Deep¹,

Mohakud²,

Jain³

et al. 2023

Sultan Qaboos Univ Med J

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Multi-omics analysis of the biological mechanism of the pathogenesis of non-alcoholic fatty liver disease

Lin,

Zhang,

Liu

et al. 2024

Front. Microbiol.

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BackgroundNon-alcoholic fatty liver disease (NAFLD) is a type of liver metabolic syndrome. Employing multi-omics analyses encompassing the microbiome, metabolome and transcriptome is crucial for comprehensively elucidating the biological processes underlying NAFLD.MethodsHepatic tissue, blood and fecal samples were obtained from 9 NAFLD model mice and 8 normal control mice. Total fecal microbiota DNA was extracted, and 16S rRNA was amplified, to analyze alterations in the gut microbiota (GM) induced by NAFLD. Subsequently, diagnostic strains for NAFLD were screened, and their functional aspects were examined. Differential metabolites and differentially expressed genes were also screened, followed by enrichment analysis. Correlations between the differential microbiota and metabolites, as well as between the DEGs and differential metabolites were studied. A collinear network involving key genes-, microbiota-and metabolites was constructed.ResultsIleibacterium and Ruminococcaceae, both belonging to Firmicutes; Olsenella, Duncaniella and Paramuribaculum from Bacteroidota; and Bifidobacterium, Coriobacteriaceae_UCG_002 and Olsenella from Actinobacteriota were identified as characteristic strains associated with NAFLD. Additionally, differentially expressed metabolites were predominantly enriched in tryptophan, linoleic acid and methylhistidine metabolism pathways. The functions of 2,510 differentially expressed genes were found to be associated with disease occurrence. Furthermore, a network comprising 8 key strains, 14 key genes and 83 key metabolites was constructed.ConclusionThrough this study, we conducted a comprehensive analysis of NAFLD alterations, exploring the gut microbiota, genes and metabolites of the results offer insights into the speculated biological mechanisms underlying NAFLD.

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Isolated Sacral Vertebral Hydatid Cyst Presenting with Pathological Fracture

Cited by 3 publications

References 3 publications

Combined analysis of 16S rDNA sequencing and metabolomics to find biomarkers of drug-induced liver injury

Combined analysis of 16S rDNA sequencing and metabolomics to find biomarkers of drug-induced liver injury

Large Intraosseous Haemangioma of the Sacral Vertebra

Multi-omics analysis of the biological mechanism of the pathogenesis of non-alcoholic fatty liver disease

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