Molecular estimation of alteration in intestinal microbial composition in Hashimoto's thyroiditis patients

The gut microbiota has a crucial effect on human health and physiology. Hypothyroid Hashimoto’s thyroiditis (HT) is an autoimmune disorder manifested with environmental and genetic factors. However, it is hypothesized that intestinal microbes might play a vital role in the pathogenesis of HT. The aim of current was to investigate and characterize the gut microbial composition of HT patients both quantitatively and qualitatively. The fecal samples from 29 HT patients and 12 healthy individuals were collected. The PCR-DGGE targeted V3 site of 16S rRNA gene and real time PCR for Bifidobacterium Lactobacillus, Bacteroides vulgatus and Clostridium leptum were performed. Pyrosequencing of 16S rRNA gene with V4 location was performed on 20 randomly selected samples. The comparative analysis of diversity and richness indices revealed diversification of gut microbiota in HT as compared to control. The statistical data elucidate the alterations in phyla of HT patients which was also affirmed at the family level. We observed the declined abundance of Prevotella_9 and Dialister, while elevated genera of the diseased group included Escherichia-Shigella and Parasutterella. The alteration in gut microbial configuration was also monitored at the species level, which showed an increased abundance of E. coli in HT. Therefore, the current study is in agreement with the hypothesis that HT patients have intestinal microbial dysbiosis. The taxa statistics at species-level along with each gut microbial community were modified in HT. Thus, the current study may offer the new insights into the treatment of HT patients, disease pathway, and mechanism

Early detection of Pseudomonas aeruginosa – comparison of conventional versus molecular (PCR) detection directly from adult patients with cystic fibrosis (CF)

BACKGROUND: Pseudomonas aeruginosa (PA) is the most important bacterial pathogen in patients with cystic fibrosis (CF) patients. Currently, routine bacteriological culture on selective/non- selective culture media is the cornerstone of microbiological detection. The aim of this study was to compare isolation rates of PA by conventional culture and molecular (PCR) detection directly from sputum. METHODS: Adult patients (n = 57) attending the regional adult CF centre in Northern Ireland, provided fresh sputum following airways clearance exercise. Following processing of the specimen with sputasol (1:1 vol), the specimen was examined for the presence of PA by plating onto a combination of culture media (Pseudomonas isolation agar, Blood agar & McConkey agar). In addition, from the same specimen, genomic bacterial DNA was extracted (1 ml) and was amplified employing two sequence-specific targets, namely (i) the outer membrane protein (oprL) gene locus and (ii) the exotoxin A (ETA) gene locus. RESULTS: By sputum culture, there were 30 patients positive for PA, whereas by molecular techniques, there were 35 positive patients. In 39 patients (22 PA +ve & 17 PA -ve), there was complete agreement between molecular and conventional detection and with both PCR gene loci. The oprL locus was more sensitive than the ETA locus, as the former was positive in 10 more patients and there were no patients where the ETA was positive and the oprL target negative. Where a PCR +ve/culture -ve result was recorded (10 patients), we followed these patients and recorded that 5 of these patients converted to being culture-positive at times ranging from 4–17 months later, with a mean lag time of 4.5 months. CONCLUSIONS: This study indicates that molecular detection of PA in sputum employing the oprL gene target, is a useful technique in the early detection of PA, gaining on average 4.5 months over conventional culture. It now remains to be established whether aggressive antibiotic intervention at this earlier stage, based on PCR detection, has any significant benefits on clinical outcome

Pediatric intensive care unit treatment alters the diversity and composition of the gut microbiota and antimicrobial resistance gene expression in critically ill children

IntroductionCommon critical illnesses are a growing economic burden on healthcare worldwide. However, therapies targeting the gut microbiota for critical illnesses have not been developed on a large scale. This study aimed to investigate the changes in the characteristics of the gut microbiota in critically ill children after short-term pediatric intensive care unit (PICU) treatments.MethodsAnal swab samples were prospectively collected from March 2021 to March 2022 from children admitted to the PICU of Xinhua Hospital who received broad-spectrum antibiotics on days 1 (the D1 group) and 7 (the D7 group) of the PICU treatment. The structural and functional characteristics of the gut microbiota of critically ill children were explored using metagenomic next-generation sequencing (mNGS) technology, and a comparative analysis of samples from D1 and D7 was conducted.ResultsAfter 7 days of PICU admission, a significant decrease was noted in the richness of the gut microbiota in critically ill children, while the bacterial diversity and the community structure between groups remained stable to some extent. The relative abundance of Bacilli and Lactobacillales was significantly higher, and that of Campylobacter hominis was significantly lower in the D7 group than in the D1 group. The random forest model revealed that Prevotella coporis and Enterobacter cloacae were bacterial biomarkers between groups. LEfSe revealed that two Gene Ontology entries, GO:0071555 (cell wall organization) and GO:005508 (transmembrane transport), changed significantly after the short-term treatment in the PICU. In addition, 30 KEGG pathways were mainly related to the activity of enzymes and proteins during the processes of metabolism, DNA catabolism and repair, and substance transport. Finally, 31 antimicrobial resistance genes had significantly different levels between the D7 and D1 groups. The top 10 up-regulated genes were Erm(A), ErmX, LptD, eptB, SAT-4, tetO, adeJ, adeF, APH(3′)-IIIa, and tetM.ConclusionThe composition, gene function, and resistance genes of gut microbiota of critically ill children can change significantly after short PICU treatments. Our findings provide a substantial basis for a better understanding of the structure and function of gut microbiota and their role in critical illnesses

Label-free visualization of carbapenemase activity in living bacteria

Evaluating enzyme activity intracellularly on natural substrates is a significant experimental challenge in biomedical research. We report a label‐free method for real‐time monitoring of the catalytic behavior of class A, B, and D carbapenemases in live bacteria based on measurement of heat changes. By this means, novel biphasic kinetics for class D OXA‐48 with imipenem as substrate is revealed, providing a new approach to detect OXA‐48‐like producers. This in‐cell calorimetry approach offers major advantages in the rapid screening (10 min) of carbapenemase‐producing Enterobacteriaceae from 142 clinical bacterial isolates, with superior sensitivity (97 %) and excellent specificity (100 %) compared to conventional methods. As a general, label‐free method for the study of living cells, this protocol has potential for application to a wider range and variety of cellular components and physiological processes

Gut-Thyroid axis: How gut microbial dysbiosis associated with euthyroid thyroid cancer

Thyroid cancer in humans has a fast-growing prevalence, with the most common lethal endocrine malignancy for unknown reasons. The current study was aimed to perform qualitative and quantitative investigation and characterization of the gut bacterial composition of euthyroid thyroid cancer patients. The fecal samples were collected from sixteen euthyroid thyroid cancer patients and ten from healthy subjects. The PCR-DGGE was conducted by targetting the V3 region of 16S rRNA gene, as well as real-time PCR for Bacteroides vulgatus, E.coli Bifidobacterium, Clostridium leptum and Lactobacillus were carried. High-throughput sequencing of V3+V4 region of 16S rRNA gene was performed on Hiseq 2500 platform on 20 (10 healthy & 10 diseased subjects) randomly selected fecal samples. The richness indices and comparative diversity analysis showed significant gut microbial modification in euthyroid thyroid cancer than control. At phylum level, there was significant enrichment of Firmicutes, Verrucomicrobia, while a significant decrease in Bacteroidetes was detected in the experimental group. At family statistics, significant high levels of Ruminococcaceae and Verrucomicrobiaceae, while the significant lower abundance of Bacteroidaceae, Prevotellaceae, Porphyromonadaceae, and Alcaligenaceae was after observed. It also found that the significantly raised level of Escherichia-Shigella, Akkermansia [Eubacterium]_coprostanoligenes, Dorea, Subdoligranulum, and Ruminococcus_2 genera, while significantly lowered genera of the patient group were Prevotella_9, Bacteroides and Klebsiella. The species-level gut microbial composition showed a significantly raised level of Escherichia coli in euthyroid thyroid cancer. Thus, this study reveals that euthyroid thyroid cancer patients have significant gut microbial dysbiosis. Moreover, Statistics (P<0.05) of each gut microbial taxa were significantly changed in euthyroid thyroid cancer patients. Therefore, the current study may propose new approaches to understanding thyroid cancer patients' disease pathways, mechanisms, and treatment

Application of PCR and DNA sequencing based molecular diagnosis in infectious diseases

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NN-Based Parallel Model Predictive Control for a Quadrotor UAV

A novel neural network (NN)-based parallel model predictive control (PMPC) method is proposed to deal with the tracking problem of the quadrotor unmanned aerial vehicles (Q-UAVs) system in this article. It is well known that the dynamics of Q-UAVs are changeable while the system is operating in some specific environments. In this case, traditional NN-based MPC methods are not applicable because their model networks are pre-trained and kept constant throughout the process. To solve this problem, we propose the PMPC algorithm, which introduces parallel control structure and experience pool replay technology into the MPC method. In this algorithm, an NN-based artificial system runs in parallel with the UAV system to reconstruct its dynamics model. Furthermore, the experience replay technology is used to maintain the accuracy of the reconstructed model, so as to ensure the effectiveness of the model prediction algorithm. Furthermore, a convergence proof of the artificial system is also given in this paper. Finally, numerical results and analysis are given to demonstrate the effectiveness of the PMPC algorithm