Background
The microbiota–gut–brain axis, especially the microbial tryptophan (Trp) biosynthesis and metabolism pathway (MiTBamp), may play a critical role in the pathogenesis of major depressive disorder (MDD). However, studies on the MiTBamp in MDD are lacking. The aim of the present study was to analyze the gut microbiota composition and the MiTBamp in MDD patients.
Methods
We performed shotgun metagenomic sequencing of stool samples from 26 MDD patients and 29 healthy controls (HCs). In addition to the microbiota community and the MiTBamp analyses, we also built a classification based on the Random Forests (RF) and Boruta algorithm to identify the gut microbiota as biomarkers for MDD.
Results
The Bacteroidetes abundance was strongly reduced whereas that of Actinobacteria was significantly increased in the MDD patients compared with the abundance in the HCs. Most noteworthy, the MDD patients had increased levels of Bifidobacterium, which is commonly used as a probiotic. Four Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologies (KOs) (K01817, K11358, K01626, K01667) abundances in the MiTBamp were significantly lower in the MDD group. Furthermore, we found a negative correlation between the K01626 abundance and the HAMD scores in the MDD group. Finally, RF classification at the genus level can achieve an area under the receiver operating characteristic curve of 0.890.
Conclusions
The present findings enabled a better understanding of the changes in gut microbiota and the related Trp pathway in MDD. Alterations of the gut microbiota may have the potential as biomarkers for distinguishing MDD patients form HCs.
Telomeres generally consist of short repeats of minisatellite DNA sequences and are useful in chromosome identification and karyotype analysis. To date, telomeres have not been characterized in the economically important brown seaweed Saccharina japonica, thus its full cytogenetic research and genetic breeding potential has not been realized. Herein, the tentative sequence of telomeres in S. japonica was identified by PCR amplification with primers designed based on the Arabidopsis-type telomere sequence (TTTAGGG) , which was chosen out of three possible telomeric repeat DNA sequences typically present in plants and algae. After PCR optimization and cloning, sequence analysis of the amplified products from S. japonica genomic DNA showed that they were composed of repeat units, (TTTAGGG) , in which the repeat number ranged from 15 to 63 (n = 46). This type of repeat sequence was verified by a Southern blot assay with the Arabidopsis-type telomere sequence as a probe. The digestion of S. japonica genomic DNA with the exonuclease Bal31 illustrated that the target sequence corresponding to the Arabidopsis-type telomere sequence was susceptible to Bal31 digestion, suggesting that the repeat sequence was likely located at the outermost ends of the kelp chromosomes. Fluorescence in situ hybridizations with the aforementioned probe provided the initial cytogenetic evidence that the hybridization signals were principally localized at both ends of S. japonica chromosomes. This study indicates that the telomeric repeat of the kelp chromosomes is (TTTAGGG) which differs from the previously reported (TTAGGG) sequence in Ectocarpus siliculosus through genome sequencing, thereby suggesting distinct telomeres in brown seaweeds.
Nuclear tandemly repeated ribosomal RNA genes (18S-5.8S-25S rDNA and 5S rDNA) have been proven to be excellent cytogenetic markers for karyotype analysis of various higher plants by using the fluorescence in situ hybridization (FISH) technique. To illustrate physical mapping of these rDNAs in brown seaweed, Saccharina japonica, chromosomes, an approximately 5400-bp transcription unit of 18S-5.8S-25S rDNA was assembled by cloning the 25S rDNA after paired-end sequencing of two screened clones from a bacterial artificial chromosome library of kelp gametophytes. In contrast to the conserved 18S-5.8S-25S rDNA and ITS1 in S. japonica, the 245-bp ITS2 was variable in sequence. The cloned 5S rDNA revealed that the 120-bp conserved coding region was separated by a diverse intergenic spacer sequence that were 250, 445, 905, or 1335 bp in length. On average, the 18S-5.8S-25S rDNA of kelp female and male gametophytes had 45 and 41 copies per haploid genome, respectively, as detected by quantitative real-time PCR, whereas the 5S rDNA had 2590 and 2648 copies, respectively. Southern hybridization with labeled probes of 18S rDNA or 5S rDNA demonstrated that kelp gametophytes possessed only one locus each of the 18S-5.8S-25S or 5S rDNAs. This was further confirmed by FISH analysis using the same labeled probes, thus illustrating that 18S-5.8S-25S rDNA is located at the intercalary region of chromosome 23, whereas 5S rDNA at the sub-telomeric region of chromosomes 27. The localization of these rDNAs using the FISH technique has facilitated the identification of individual chromosomes and karyotype analysis of this kelp.
Background
Acute cholangitis is a severe inflammatory disease associated with an infection of the biliary system, which can lead to complications and adverse outcomes. The existing nomogram-based risk assessment methods largely rely on a limited set of clinical features and laboratory indicators, and are mostly constructed using univariable models, which have limitations in predicting the severity. This study aims to develop a nomogram-based model that integrates multiple variables to improve risk prediction for acute cholangitis.
Methods
Data were retrospectively collected from 152 patients with acute cholangitis who attended the People’s Hospital of Jiangsu University between January 2019 and March 2022, and were graded as having mild to moderate versus severe cholangitis according to the 2018 Tokyo guidelines. Univariate and multivariate analyses were employed to discern independent risk factors associated with severe acute cholangitis, which were subsequently integrated into a nomogram model. The efficacy of the model was appraised by leveraging Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA).
Results
Aspartate to alanine transaminase ratio (Transaminase ratio or TR), Neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP), and D-dimer (DD) levels were independent risk factors for severe acute cholangitis. A nomogram model was constructed based on these 4 risk factors. ROC and calibration curves were well differentiated and calibrated. DCA had a high net gain in the range of 7% to 83%. The above model was tested internally. According to the nomogram model when patients using characteristic curve critical values were divided into a low-risk group and a high-risk group, the incidence in the high-risk group was significantly higher than in the low-risk group.
Conclusion
This nomogram model may provide clinicians with an effective tool to predict the potential risk of severe acute cholangitis in patients and guide informed intervention measures and treatment decisions.
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