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The phi027 bacteriophage influences physiology and virulence of the lysogenic strain of Clostridioides difficile
Abstract Clostridioides difficile, the causative agent of C. difficile infections (CDI), can be naturally infected by bacterial viruses known as bacteriophages. All characterized bacteriophages of this bacterium are temperate, meaning that upon infection their genetic material integrates and replicates with host’s genome. Such lysogenic strains can exhibit altered physiology and virulence, which in turn can be an important factor for epidemiology of CDI. In this study we characterized the phiCDKH02 bacteriophage infecting clinical isolates of C. difficile belonging to hypervirulent ribotypes 027 and 176. The bacteriophage was found to be identical to phi027. To get some insight into the role of this bacteriophage in physiology of its host and interaction with human colon cells, we made use of CRISPR-Cpf1 technology to cure the lysogenic C. difficile of the prophage. The prophage-free strain exhibited altered sporulation efficiency, lowered adhesion and decreased cytopathic effects towards human colon cells associated with decreased production of TcdB. These results emphasize importance of prophages in shaping virulence of C. difficile.
Daily briefing: Immune cell ‘spies’ give the brain information about the gut
Association among isometric hip strength, hip joint stiffness, and dynamic Knee Valgus in jump-landing tasks
Lower water-soluble vitamins and higher homocysteine are associated with neurodegenerative diseases
Abstract Evidence of the effects of water-soluble vitamins (e.g., B vitamins, vitamin C, and total folate) on cognitive function in patients with neurodegenerative diseases is mixed. Furthermore, the relationships among homocysteine (Hcy) metabolism, water-soluble vitamins, and cognitive impairment remain unclear. Therefore, we aimed to investigate the role of the levels of water-soluble vitamins [e.g., vitamins B1, B2, B3, B5, B6, 5-methyltetrahydrofolate (5mTHF), B12, and C and total folate] and Hcy in dementia progression in patients with neurodegenerative diseases. In this retrospective cohort study, we enrolled 280 healthy controls and 646 patients with a neurodegenerative disease. Patients were classified into a Parkinson’s disease (PD) group (n = 312), Alzheimer’s disease (AD) group (n = 219), or other dementia group (n = 115) according to pathological features. The other dementia group comprised 25 patients with frontotemporal dementia, 38 with Lewy body dementia, 34 with vascular dementia, and 18 with semantic dementia. Serum vitamins (i.e., B1, B2, B3, B5, VB6, 5mTHF, and C) were measured via liquid chromatography-mass spectrometry/mass spectrometry. Total Hcy, vitamin B12 and total folate levels were measured using commercial electrochemiluminescence immunoassays. The serum levels of vitamins B1, B2, B5, B6, 5mTHF, and C were lower in all patient groups than in the control group. The logistic regression results revealed that lower levels of serum vitamins B2, B6, 5mTHF, and B12 were associated with a higher risk of dementia in PD patients, and higher Hcy levels and lower serum vitamin B6 and 5mTHF levels were associated with a higher risk of AD-related cognitive impairment. In addition, the level of vitamins was positively correlated with neuropsychological assessment scores and negatively correlated with Hcy level and stage of dementia. The levels of several water-soluble vitamins are lower in dementia patients. Moreover, lower levels of water-soluble vitamins and higher levels of Hcy increased odds ratios for having neurodegenerative diseases or cognitive impairment. These findings suggest that estimating water-soluble vitamin levels in older adults may be valuable given that they may help improve cognitive function.
How the natural world is inspiring the robot eyes of the future
Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM
Demonstration of accurate ID-VG characteristics modeling in SiC mosfets using separated artificial neural networks with small training dataset
Genome-wide investigation of cytokinin oxidase/dehydrogenase (CKX) family genes in Brassica juncea with an emphasis on yield-influencing CKX
Black Death bacterium has become less lethal after genetic tweak
Identification of transarterial chemoembolization candidates in advanced hepatocellular carcinoma patients classified solely by performance status 1: a multicenter retrospective study
Formation of the high pressure jeffbenite phase from glass at ambient pressure
R-CKGAT: a recommendation algorithm based on scientific fitness knowledge graph
Singapore’s fight to save its green spaces from development
Analyzing the effect of physical exercise on subjective well-being of university students using the chain mediation model
The history and future of resting-state functional magnetic resonance imaging
Osprey optimization algorithm for distributed generation integration in a radial distribution system for power loss reduction
Exploring the role of energy transition in shaping the CO2 emissions pattern in China’s power sector
Blockchain based electronic educational document management with role-based access control using machine learning model
Abstract The emergence of digital technology has led to a significant increase in the importance of educational credential storage, exchange, and verification for organisations, enterprises, and universities. Academic record forgery, record misuse, credential data tampering, time-consuming verification procedures, ownership and control difficulties, and other problems plague the education sector. Machine learning (ML) and blockchain, two of the most disruptive methods, have replaced traditional techniques in the education sector with highly technological and efficient ways. Our study aims to propose a novel electronic educational document management technique using a blockchain-based fuzzy feed-forward convolutional temporal neural network that detects malicious users. Here, the training is carried out based on NLP analysis in document word weight indexing. This document management access control is based on role-based access with simulated remora swarm optimisation. In order to identify malicious users, this suggested system logs access requests on the blockchain and authenticated users. The findings demonstrate that this suggested architecture performs as intended in every case. The experimental analysis is based on a malicious user detection dataset regarding Prediction accuracy, Mean average precision, F-measure, Latency, QoS, Contract execution time, and Throughput. Based on dataset feature analysis, the proposed B-FCTNN_SRSO achieved a prediction accuracy of 98%, a mean average precision (MAP) of 95%, and an F1 score of 97%, with a latency of 96%. Additionally, based on blockchain security analysis, the B-FCTNN_SRSO attained a QoS of 97%, a precision of 94%, and a throughput of 96%.