Human Health, Environmental Comfort and Well-Being. Part 2. Ecological Comfort as a New and Strategic Factor in the Protection of Modern Human Health
- 作者: Suchkov S.V.1,2,3,4, Abe H.5, Murphy S.6,7, Smith D.8, Polyakova V.S.4, Scherman D.9,10,11, Glinushkin A.P.12, Barach P.13, Terentʼev A.O.12, Tan M.14, Suvorov A.N.15,16
-
隶属关系:
- Russian Academy of Natural Sciences
- Russian University of Medicine
- New York Academy of Sciences
- University of World Politics and Law
- Abe Cancer Clinic
- Massachusetts General Hospital (MGH)
- Harvard Medical School
- Mayo Clinic
- European Academy of Sciences
- National Center for Scientific Research (CNRS)
- Paris Descartes University
- Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences
- Wayne State University, School of Medicine
- NAKADA Geriatric Health and Welfare Facilities
- Institute of Experimental Medicine, Russian Academy of Sciences
- St. Petersburg State University
- 期: 卷 144, 编号 3 (2024)
- 页面: 314-334
- 栏目: Articles
- ##submission.dateSubmitted##: 02.02.2025
- ##submission.datePublished##: 18.12.2024
- URL: https://rjpbr.com/0042-1324/article/view/653200
- DOI: https://doi.org/10.31857/S0042132424030047
- EDN: https://elibrary.ru/PRWWWQ
- ID: 653200
如何引用文章
全文:
详细
Since the dawn of humanity, human beings have inherently sought a state of security, trying to make their existence as comfortable as possible. Accordingly, among the many factors affecting human health, comfort and well-being, the quality of the micro-environment and ecology, as well as the health care system and health-saving resources, are important. In this regard, environmental security, with its systemic nature, brings a significant contribution to the PPM model by optimizing the state of balance in the interrelationship of natural, anthropogenic, physiological and social processes. Accordingly, individualized nutrition and pharmacointervention for preventive and prophylactic purposes, being important tools for health preservation, represent an integrative approach aimed at understanding the interaction between nutrition and the environment within the formed or formed lifestyle. This review will consider the main components of human health protection, as well as their impact on the preservation of ecobiocenosis stability.
作者简介
S. Suchkov
Russian Academy of Natural Sciences; Russian University of Medicine; New York Academy of Sciences; University of World Politics and Law
编辑信件的主要联系方式.
Email: med_nika2000@mail.ru
Department of Clinical Allergology and Immunology
俄罗斯联邦, Moscow; Moscow; New York, USA; MoscowH. Abe
Abe Cancer Clinic
Email: med_nika2000@mail.ru
日本, Tokyo
S. Murphy
Massachusetts General Hospital (MGH); Harvard Medical School
Email: med_nika2000@mail.ru
美国, Boston, MA; Boston, MA
D. Smith
Mayo Clinic
Email: med_nika2000@mail.ru
美国, Rochester, MN
V. Polyakova
University of World Politics and Law
Email: med_nika2000@mail.ru
俄罗斯联邦, Moscow
D. Scherman
European Academy of Sciences; National Center for Scientific Research (CNRS); Paris Descartes University
Email: med_nika2000@mail.ru
Unité de Pharmacologie Chimique et Génétique d’Imagerie
比利时, Liège; Paris, France; Paris, FranceA. Glinushkin
Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences
Email: med_nika2000@mail.ru
俄罗斯联邦, Moscow
P. Barach
Wayne State University, School of Medicine
Email: mbikeeva@yandex.ru
俄罗斯联邦, Detroit, MI
A. Terentʼev
Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences
Email: mbikeeva@yandex.ru
俄罗斯联邦, Moscow
M. Tan
NAKADA Geriatric Health and Welfare Facilities
Email: mbikeeva@yandex.ru
日本, Nakada Tome Miyagi
A. Suvorov
Institute of Experimental Medicine, Russian Academy of Sciences; St. Petersburg State University
Email: mbikeeva@yandex.ru
Department of Microbiology
俄罗斯联邦, St. Petersburg; St. Petersburg参考
- Гнедых Н.Н. Роль стратегических карт в управлении человеческими ресурсами современного предприятия // Управление человеческими ресурсами – основа развития инновационной экономики. 2010. № 2. С. 226–230.
- Лебедев А.Н., Ковешников А.И. Концепция формирования общего экологического каркаса на территориях Орловской, Брянской и Калужской областей. http://science-bsea.bgita.ru/2008/les_2008/lebedev_koncepcia.htm
- Хуррамов И.А. Проблемы экологического образования и воспитания на примере мирового сообщества // Молодой ученый. 2012. № 11. С. 493–496.
- Athanasios A., Charalampos V., Vasileios T., Ashraf G.M. Protein-protein interaction (PPI) network: recent advances in drug discovery // Curr. Drug Metab. 2017. V. 18 (1). P. 5–10. https://doi.org/10.2174/138920021801170119204832
- Bano R., Gupta S., Shekhar C. Translational research in biomedical sciences in India: Challenges, observations and national perspectives // Indian J. Med. Res. 2020. V. 152 (4). P. 335–341.
- Bebek G. Identifying gene interaction networks // Meth. Mol. Biol. 2012. V. 850. P. 483–494. https://doi.org/10.1007/978-1-61779-555-8_26
- Bludau I., Aebersold R. Proteomic and interactomic insights into the molecular basis of cell functional diversity // Nat. Rev. Mol. Cell Biol. 2020. V. 21 (6). P. 327–340. https://doi.org/10.1038/s41580-020-0231-2
- Chaudhary N., Kumar V., Sangwan P. et al. Personalized nutrition and -omics // Comp. Foodomics. 2020. P. 495–507. https://doi.org/10.1016/B978-0-08-100596-5.22880-1
- Chen S.J., Lia D.L., Chen C.H. et al. Construction and analysis of protein-protein interaction network of heroin use disorder // Sci. Rep. 2019. V. 9. P. 4980. https://doi.org/10.1038/s41598-019-41552-z
- Choi R.Y., Coyner A.S., Kalpathy-Cramer J. et al. Introduction to machine learning, neural networks, and deep learning // Transl. Vis. Sci. Technol. 2020. V. 9 (2). P. 14. https://doi.org/10.1167/tvst.9.2.14
- Conte F., Fiscon G., Licursi V. et al. A paradigm shift in medicine: A comprehensive review of network-based approaches // Biochim. Biophys. Acta Gene Regul. Mech. 2020. V. 1863 (6). P. 194416. https://doi.org/10.1016/j.bbagrm.2019.194416
- Costanzo M., Vandersluis B., Koch E.N. et al. A global genetic interaction network maps a wiring diagram of cellular function // Science. 2016. V. 353 (6306). https://doi.org/10.1126/science.aaf1420
- Cui T., El Mekkaoui K., Reinvall J. et al. Gene–gene interaction detection with deep learning // Comm. Biol. 2022. V. 5 (1238). https://doi.org/10.1038/s42003-022-04186-y
- Cusick M.E., Klitgord N., Vidal M., Hill D.E. Interactome: gateway into systems biology // Hum. Mol. Genet. 2005. V. 14 (2). P. R171–R181.
- Di Renzo L., Gualtieri P., Romano L. et al. Role of personalized nutrition in chronic-degenerative diseases // Nutrients. 2019. V. 11 (8). P. 1707. https://doi.org/10.3390/nu11081707
- Fang Z., Chen L. Personalized prediction of human diseases with single-sample dynamic network biomarkers // Biomark. Med. 2020. V. 14 (8). P. 615–620. https://doi.org/10.2217/bmm-2020-0066
- Ferguson L.R., De Caterina R., Görman U. et al. Guide and position of the international society of nutrigenetics/nutrigenomics on personalised nutrition: Part 1 – fields of precision nutrition // J. Nutr. Nutrigenom. 2016. V. 9 (1). P. 12–27. https://doi.org/10.1159/000445350
- Fernandez M.A., Raine K.D. Digital food retail: public health opportunities // Nutrients. 2021. V. 13 (11). P. 3789. https://doi.org/10.3390/nu13113789
- Fu B. Preface for special issue, ecotechnologies for controlling non-point source pollution and protecting aquatic ecosystem (ENPE-2017) // Sci. Tot. Environ. 2018. V. 618. P. 1032. https://doi.org/10.1016/j.scitotenv.2017.09.085
- Ghadie M.A., Coulombe-Huntington J., Xia Y. Interactome evolution: insights from genome-wide analyses of protein-protein interactions // Curr. Opin. Struct. Biol. 2018. V. 50. P. 42–48. https://doi.org/10.1016/j.sbi.2017.10.012
- Goh K.I., Cusick M.E., Valle D. et al. The human disease network // PNAS USA. 2007. V. 104 (21). P. 8685–8690.
- Huttlin E.L., Bruckner R.J., Paulo J.A. et al. Architecture of the human interactome defines protein communities and disease networks // Nature. 2017. V. 545 (7655). P. 505–509.
- Jiang T., Gradus J.L., Rosellini A.J. Supervised machine learning: a brief primer // Behav. Ther. 2020. V. 51 (5). P. 675–687. https://doi.org/10.1016/j.beth.2020.05.002
- Kaiser R.H., Chase H.W., Phillips M.L. et al. Dynamic resting-state network biomarkers of antidepressant treatment response // Biol. Psychiatry. 2022. V. 92 (7). P. 533–542. https://doi.org/10.1016/j.biopsych.2022.03.020
- Karimizadeh E., Sharifi-Zarchi A., Nikaein H. et al. Analysis of gene expression profiles and protein-protein interaction networks in multiple tissues of systemic sclerosis // BMC Med. Genom. 2019. V. 12. P. 199. https://doi.org/10.1186/s12920-019-0632-2
- Lage K. Protein-protein interactions and genetic diseases: The interactome // Biochim. Biophys. Acta. 2014. V. 1842 (10). P. 1971–1980.
- Lin J.S., Lai E.M. Protein-protein interactions: yeast two-hybrid system // Bacterial protein secretion systems / Eds L. Journet, E. Cascales. N.Y.: Humana Press, 2017. V. 1615. P. 177–187. https://doi.org/10.1007/978-1-4939-7033-9_14
- Marcum J.A. Nutrigenetics/nutrigenomics, personalized nutrition, and precision healthcare // Curr. Nutr. Rep. 2020. V. 9 (4). P. 338–345. https://doi.org/10.1007/s13668-020-00327-z
- Matthews D.E., Norman K. Editorial: Biomarkers in nutritional research // Curr. Opin. Clin. Nutr. Metab. Care. 2021. V. 24 (5). P. 393–394. https://doi.org/10.1097/MCO.0000000000000769
- Osada J. Nutrition genomics // Int. J. Mol. Sci. 2023. V. 24 (7). P. 6490. https://doi.org/10.3390/ijms24076490
- Plewczyński D., Ginalski K. The interactome: predicting the protein-protein interactions in cells // Cell Mol. Biol. Lett. 2009. V. 14 (1). P. 1–22.
- Przytycka T.M., Singh M., Slonim D.K. Toward the dynamic interactome: it’s about time // Brief Bioinform. 2010. V. 11 (1). P. 15–29.
- Safari-Alighiarloo N., Taghizadeh M., Rezaei-Tavirani M. et al. Protein-protein interaction networks (PPI) and complex diseases // Gastroenterol. Hepatol. Bed. Bench. 2014. V. 7 (1). P. 17–31.
- Silverbush D., Sharan R. A systematic approach to orient the human protein-protein interaction network // Nat. Commun. 2019. V. 10. P. 3015. https://doi.org/10.1038/s41467-019-10887-6
- Suchkov S.V. Personalized and precision medicine as a new model of the healthcare services // V Russ. Congress of laboratory medicine, September 12, 2019.
- Taguchi Y.H. Bioinformatic tools for epitranscriptomics // Am. J. Physiol. Cell Physiol. 2023. V. 324 (2). P. C447–C457. https://doi.org/10.1152/ajpcell.00437.2022
- Taylor I.W., Linding R., Warde-Farley D. et al. Dynamic modularity in protein interaction networks predicts breast cancer outcome // Nat. Biotechnol. 2009. V. 27 (2). P. 199–204.
- Tenenbaum J.D. Translational bioinformatics: past, present, and future // Genom. Proteom. Bioinform. 2016. V. 14 (1). P. 31–41.
- Vidal M., Cusick M.E., Barabasi A.L. Interactome networks and human disease // Cell. 2011. V. 144 (6). P. 986–998.
- Vimaleswaran K.S., Le Roy C.I., Claus S.P. Foodomics for personalized nutrition: how far are we? // Curr. Opin. Food Sci. 2015. V. 4. P. 129–135.
- Voevodin D.A., Rozanova G.N., Poddubikov A.V., Mikhailova N.A. Microbiocenosis, immune system and heredity // Zh. Mikrobiol. Epidemiol. Immunobiol. 2017. V. (2). P. 116–126.
- Ung M.H., Liu C.C., Cheng C. Integrative analysis of cancer genes in a functional interactome // Sci. Rep. 2016. V. 6. P. 29228.
- Wiredja D., Bebek G. Identifying gene interaction networks // Meth. Mol. Biol. 2017. V. 1666. P. 539–556. https://doi.org/10.1007/978-1-4939-7274-6_27
补充文件
