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Vezzoli A, Mrakic-Sposta S, Brizzolari A, Balestra C, Camporesi EM, Bosco G. Oxy-Inflammation in Humans during Underwater Activities. Int J Mol Sci 2024; 25:3060. [PMID: 38474303 DOI: 10.3390/ijms25053060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 02/22/2024] [Accepted: 03/01/2024] [Indexed: 03/14/2024] Open
Abstract
Underwater activities are characterized by an imbalance between reactive oxygen/nitrogen species (RONS) and antioxidant mechanisms, which can be associated with an inflammatory response, depending on O2 availability. This review explores the oxidative stress mechanisms and related inflammation status (Oxy-Inflammation) in underwater activities such as breath-hold (BH) diving, Self-Contained Underwater Breathing Apparatus (SCUBA) and Closed-Circuit Rebreather (CCR) diving, and saturation diving. Divers are exposed to hypoxic and hyperoxic conditions, amplified by environmental conditions, hyperbaric pressure, cold water, different types of breathing gases, and air/non-air mixtures. The "diving response", including physiological adaptation, cardiovascular stress, increased arterial blood pressure, peripheral vasoconstriction, altered blood gas values, and risk of bubble formation during decompression, are reported.
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Affiliation(s)
- Alessandra Vezzoli
- Institute of Clinical Physiology-National Research Council (CNR-IFC), 20142 Milano, Italy
- Department of Biomedical Sciences, University of Padova, 35131 Padova, Italy
| | - Simona Mrakic-Sposta
- Institute of Clinical Physiology-National Research Council (CNR-IFC), 20142 Milano, Italy
| | - Andrea Brizzolari
- Department of Biomedical Sciences, University of Padova, 35131 Padova, Italy
| | - Costantino Balestra
- Environmental, Occupational, Aging (Integrative) Physiology Laboratory, Haute Ecole Bruxelles-Brabant (HE2B), 1160 Brussels, Belgium
- Physical Activity Teaching Unit, Motor Sciences Department, Université Libre de Bruxelles (ULB), 1050 Brussels, Belgium
- DAN Europe Research Division (Roseto-Brussels), 1160 Brussels, Belgium
| | | | - Gerardo Bosco
- Department of Biomedical Sciences, University of Padova, 35131 Padova, Italy
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Gao X, Yin P, Ren Y, Yu L, Tian F, Zhao J, Chen W, Xue Y, Zhai Q. Predicting Personalized Diets Based on Microbial Characteristics between Patients with Superficial Gastritis and Atrophic Gastritis. Nutrients 2023; 15:4738. [PMID: 38004131 PMCID: PMC10675729 DOI: 10.3390/nu15224738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 11/04/2023] [Accepted: 11/07/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND gastritis is a common stomach disease with a high global incidence and can potentially develop into gastric cancer. The treatment of gastritis focuses on medication or diets based on national guidelines. However, the specific diet that can alleviate gastritis remains largely unknown. METHODS we propose a microbiota-directed dietary strategy that investigates potential food factors using microbial exogenous metabolites. Given the current lack of understanding of the repeatable characteristics of gastric microbiota, we conducted a meta-analysis to identify the features of gastric bacteria. Local samples were collected as validation cohorts. Furthermore, RevEcoR was employed to identify bacteria's exogenous metabolites, and FooDB was used to retrieve foods that can target specific bacteria. RESULTS Bacteroides, Weissella, Actinomyces, Atopobium, Oribacterium, Peptostreptococcus, and Rothia were biomarkers between superficial gastritis (SG) and atrophic gastritis (AG) (AG_N) without H. pylori infection, whereas Bacillus, Actinomyces, Cutibacterium, Helicobacter, Novosphingobium, Pseudomonas, and Streptococcus were signatures between SG and AG (AG_P) with H. pylori infection. According to the exogenous metabolites, adenosyloobalamin, soybean, common wheat, dates, and barley were regarded as potential candidates for AG_N treatment, while gallate was regarded as a candidate for AG_P treatment. CONCLUSIONS this study firstly profiled the gastric microbiota of AG and SG with or without H. pylori and provided a recommended diet for global AG according to exogenous metabolites.
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Affiliation(s)
- Xiaoxiang Gao
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (X.G.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Pingping Yin
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (X.G.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Yilin Ren
- Department of Gastroenterology, Affiliated Hospital of Jiangnan University, Wuxi 214122, China
| | - Leilei Yu
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (X.G.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Fengwei Tian
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (X.G.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Jianxin Zhao
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (X.G.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
| | - Wei Chen
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (X.G.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
- National Engineering Research Center for Functional Food, Jiangnan University, Wuxi 214122, China
| | - Yuzheng Xue
- Department of Gastroenterology, Affiliated Hospital of Jiangnan University, Wuxi 214122, China
| | - Qixiao Zhai
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi 214122, China; (X.G.)
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, China
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Zhou Q, Chen Y, Liu G, Qiao P, Tang C. A preliminary study of the salivary microbiota of young male subjects before, during, and after acute high-altitude exposure. PeerJ 2023; 11:e15537. [PMID: 37397022 PMCID: PMC10312199 DOI: 10.7717/peerj.15537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 05/19/2023] [Indexed: 07/04/2023] Open
Abstract
Background The microbial community structure in saliva differs at different altitudes. However, the impact of acute high-altitude exposure on the oral microbiota is unclear. This study explored the impact of acute high-altitude exposure on the salivary microbiome to establish a foundation for the future prevention of oral diseases. Methods. Unstimulated whole saliva samples were collected from 12 male subjects at the following three time points: one day before entering high altitude (an altitude of 350 m, pre-altitude group), seven days after arrival at high altitude (an altitude of 4,500 m, altitude group) and seven days after returning to low altitude (an altitude of 350 m, post-altitude group). Thus, a total of 36 saliva samples were obtained. 16S rRNA V3-V4 region amplicon sequencing was used to analyze the diversity and structure of the salivary microbial communities, and a network analysis was employed to investigate the relationships among salivary microorganisms. The function of these microorganisms was predicted with a Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis. Results In total, there were 756 operational taxonomic units (OTUs) identified, with 541, 613, and 615 OTUs identified in the pre-altitude, altitude, and post-altitude groups, respectively. Acute high-altitude exposure decreased the diversity of the salivary microbiome. Prior to acute high-altitude exposure, the microbiome mainly consisted of Proteobacteria, Firmicutes, Bacteroidetes, Fusobacteria, and Actinobacteria. After altitude exposure, the relative abundance of Streptococcus and Veillonella increased, and the relative abundance of Prevotella, Porphyromonas, and Alloprevotella decreased. The relationship among the salivary microorganisms was also affected by acute high-altitude exposure. The relative abundance of carbohydrate metabolism gene functions was upregulated, while the relative abundance of coenzyme and vitamin metabolism gene functions was downregulated. Conclusion Rapid high-altitude exposure decreased the biodiversity of the salivary microbiome, changing the community structure, symbiotic relationships among species, and abundance of functional genes. This suggests that the stress of acute high-altitude exposure influenced the stability of the salivary microbiome.
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Affiliation(s)
- Qian Zhou
- The fifth Clinical Medical College of Anhui Medical University, Clinical College of Anhui Medical University, Beijing, China
- Department of Stomatology, PLA Strategic Support Force Medical Center, Beijing, China
| | - Yuhui Chen
- Department of Stomatology, PLA Strategic Support Force Medical Center, Beijing, China
| | - Guozhu Liu
- The 32183 Military Hospital of PLA, Baicheng, Jilin, China
| | - Pengyan Qiao
- Department of Stomatology, PLA Strategic Support Force Medical Center, Beijing, China
| | - Chuhua Tang
- The fifth Clinical Medical College of Anhui Medical University, Clinical College of Anhui Medical University, Beijing, China
- Department of Stomatology, PLA Strategic Support Force Medical Center, Beijing, China
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Lu YT, Wang SH, Liou ML, Lee CY, Li YX, Lu YC, Hsin CH, Yang SF, Chen YY, Chang TH. Microbiota dysbiosis in odontogenic rhinosinusitis and its association with anaerobic bacteria. Sci Rep 2022; 12:21023. [PMID: 36470924 PMCID: PMC9722704 DOI: 10.1038/s41598-022-24921-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
Odontogenic rhinosinusitis is a subtype of rhinosinusitis associated with dental infection or dental procedures and has special bacteriologic features. Previous research on the bacteriologic features of odontogenic rhinosinusitis has mainly used culture-dependent methods. The variation of microbiota between odontogenic and nonodontogenic rhinosinusitis as well as the interplay between the involved bacteria have not been explored. Therefore, we enrolled eight odontogenic rhinosinusitis cases and twenty nonodontogenic rhinosinusitis cases to analyze bacterial microbiota through 16S rRNA sequencing. Significant differences were revealed by the Shannon diversity index (Wilcoxon test p = 0.0003) and PERMANOVA test based on weighted UniFrac distance (Wilcoxon test p = 0.001) between odontogenic and nonodontogenic samples. Anaerobic bacteria such as Porphyromonas, Fusobacterium, and Prevotella were significantly dominant in the odontogenic rhinosinusitis group. Remarkably, a correlation between different bacteria was also revealed by Pearson's correlation. Staphylococcus was highly positively associated with Corynebacterium, whereas Fusobacterium was highly negatively correlated with Prophyromonas. According to our results, the microbiota in odontogenic rhinosinusitis, predominantly anaerobic bacteria, was significantly different from that in nonodontogenic rhinosinusitis, and the interplay between specific bacteria may a major cause of this subtype of rhinosinusitis.
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Affiliation(s)
- Yen-Ting Lu
- grid.411641.70000 0004 0532 2041Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan ,grid.452771.2Department of Otolaryngology, St. Martin De Porres Hospital, Chiayi, Taiwan ,grid.411645.30000 0004 0638 9256Department of Otolaryngology, Chung Shan Medical University Hospital, Taichung, Taiwan ,grid.411641.70000 0004 0532 2041School of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Shao-Hung Wang
- grid.412046.50000 0001 0305 650XDepartment of Microbiology, Immunology and Biopharmaceuticals, National Chiayi University, Chiayi, Taiwan
| | - Ming-Li Liou
- grid.413051.20000 0004 0444 7352Department of Medical Laboratory Science and Biotechnology, Yuanpei University, Hsinchu City, Taiwan
| | - Cheng-Yang Lee
- grid.412896.00000 0000 9337 0481Office of Information Technology, Taipei Medical University, Taipei City, Taiwan
| | - Yu-Xuan Li
- grid.412896.00000 0000 9337 0481Office of Information Technology, Taipei Medical University, Taipei City, Taiwan
| | - Ying-Chou Lu
- grid.452771.2Department of Otolaryngology, St. Martin De Porres Hospital, Chiayi, Taiwan
| | - Chung-Han Hsin
- grid.411641.70000 0004 0532 2041Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan ,grid.411645.30000 0004 0638 9256Department of Otolaryngology, Chung Shan Medical University Hospital, Taichung, Taiwan ,grid.411641.70000 0004 0532 2041School of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Shun-Fa Yang
- grid.411641.70000 0004 0532 2041Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan ,grid.411645.30000 0004 0638 9256Department of Medical Research, Chung Shan Medical University Hospital, Taichung, Taiwan
| | - Yih-Yuan Chen
- grid.412046.50000 0001 0305 650XDepartment of Biochemical Science and Technology, National Chiayi University, Chiayi, Taiwan
| | - Tzu-Hao Chang
- grid.412897.10000 0004 0639 0994Clinical Big Data Research Center, Taipei Medical University Hospital, Wu-Hsing Street, Taipei City, 110 Taiwan ,grid.412896.00000 0000 9337 0481Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
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