Bifidobacteria are a prominent type of bacteria that have garnered significant research attention for their exceptional probiotic properties and capacity to produce exopolysaccharides (EPSs). These compounds exhibit diverse physical, chemical, and biological characteristics, prompting numerous investigations into their potential applications. Researchers have noted their beneficial effects as immune modulators within the host's body across various industries. Extensive research has been conducted on the immunomodulatory effects of bifidobacteria-derived EPSs, with emerging engineering strategies aimed at enhancing their immune-modulating capabilities. Understanding the structure, physicochemical properties, and biological activities of these compounds is crucial for their effective utilization across different industries. Our review encompassed numerous studies exploring and its metabolites, including EPSs, across various sectors, drawing from diverse databases. The distinctive properties of EPSs have spurred investigations into their applications, revealing their potential to bolster the immune system, combat inflammation, and treat various ailments. Additionally, these compounds possess antioxidant and antimicrobial properties, making them suitable for incorporation into a range of products spanning food, health, and medicine.
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http://dx.doi.org/10.3389/fmicb.2024.1396308 | DOI Listing |
Cell Commun Signal
January 2025
Dongguan Key Laboratory of Stem Cell and Regenerative Tissue Engineering, The First Dongguan Affiliated Hospital, School of Basic Medical Sciences, Guangdong Medical University, Dongguan, 523808, China.
The prevalence of obesity and osteoporosis (OP) represents a significant public health concern on a global scale. A substantial body of evidence indicates that there is a complex relationship between obesity and OP, with a correlation between the occurrence of OP and obesity. In recent years, sirtuins have emerged as a prominent area of interest in the fields of aging and endocrine metabolism.
View Article and Find Full Text PDFBMC Med Res Methodol
January 2025
Department of Computer Science and Engineering, School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran.
Time-to-event data are very common in medical applications. Regression models have been developed on such data especially in the field of survival analysis. Kernels are used to handle even more complicated and enormous quantities of medical data by injecting non-linearity into linear models.
View Article and Find Full Text PDFCommun Biol
January 2025
Department of Chemistry, Merkert Chemistry Center, Boston College, Chestnut Hill, MA, USA.
Pseudouridine (Ψ) is an abundant RNA chemical modification that plays critical biological functions. Current Ψ detection methods are limited in identifying Ψs at base-resolution in U-rich sequence contexts, where Ψ occurs frequently. Here we report "Mut-Ψ-seq" that utilizes the classic N-cyclohexyl N'-(2-morpholinoethyl)carbodiimide (CMC) agent and an evolved reverse transcriptase ("RT-1306") for Ψ mapping at base-resolution.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Oncology, The First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian, 116011, China.
Lung cancer, particularly adenocarcinoma, ranks high in morbidity and mortality rates worldwide, with a relatively low five-year survival rate. To achieve precise prognostic assessment and clinical intervention for patients, thereby enhancing their survival prospects, there is an urgent need for more accurate stratification schemes. Currently, the TNM staging system is predominantly used in clinical practice for prognostic evaluation, but its accuracy is constrained by the reliance on physician experience.
View Article and Find Full Text PDFSci Rep
January 2025
College of Energy and Transportation Engineering, Inner Mongolia Agricultural University, Hohhot, 010010, China.
In the face of forest fire emergencies, fast and efficient dispatching of rescue vehicles is an important means of mitigating the damage caused by forest fires, and is an effective method of avoiding secondary damage caused by forest fires, minimizing the damage caused by forest fires to the ecosystem, and mitigating the losses caused by economic development. this paper takes the actual problem as the starting point, constructs a reasonable mathematical model of the problem, for the special characteristics of the emergency rescue vehicle scheduling problem of forest fires, taking into account the actual road conditions in the northern pristine forest area, through the analysis of the cost of paths between the forest area and the highway, to obtain the least obstructed rescue paths, to narrow the gap between the theoretical model and the problem of the actual. Improvement of ordinary genetic algorithm, design of double population strategy selection operation, the introduction of chaotic search initialization population, to improve the algorithm's solution efficiency and accuracy, through the northern pristine forest area of Daxing'anling real forest fire cases and generation of large-scale random fire point simulation experimental test to verify the effectiveness of the algorithm, to ensure that the effectiveness and reasonableness of the solution to the problem of forest fire emergency rescue vehicle scheduling program.
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