方案血液透析患者肠道微生物群组成和微生物源尿毒症毒素含量的变化

全文:

INTRODUCTION

Interest in the potential role of intestinal dysbiosis in the development and progression of chronic kidney disease (CKD) has significantly increased over the last decade [1, 2]. Several experimental and clinical studies have demonstrated that CKD is associated with distinct qualitative and quantitative alterations in the intestinal microflora. These changes are accompanied by increased production and accumulation of uremic toxins, such as p-cresyl sulfate (PCS), indoxyl sulfate (IS), and trimethylamine-N-oxide (TMAO) [3, 4]. In contrast, patients with renal failure exhibit a reduction in short-chain fatty acids (SCFAs), which serve as a source of energy for enterocytes, maintain the integrity of the intestinal barrier, and have anti-inflammatory and anticarcinogenic effects [5]. The nature of changes in the intestinal microbial community can vary significantly depending on the etiology of renal failure and the degree of renal dysfunction. Individuals in the terminal stage of CKD receiving hemodialysis treatment exhibit the most pronounced changes [6].

Uremia can cause damage to the intestinal epithelial barrier, which can lead to the translocation of immunogenic bacterial products into the bloodstream. This can contribute to the development of chronic subclinical inflammation, CKD progression, and associated cardiovascular, metabolic, and other complications [7]. Therefore, intestinal dysbiosis should be considered an independent risk factor for adverse outcomes in individuals with severe renal dysfunction.

Studies on the relative composition and abundance of intestinal bacteria and their potential relationship with the levels of uremic toxins in the blood are insufficient. The data accumulated to date on the features of intestinal dysbacteriosis in CKD are highly heterogeneous [8]. Studies on the intestinal microbiota in our country are significantly limited because of the high cost and low availability of modern metagenomic and proteomic techniques [9].

This study aimed to investigate changes in the composition of the intestinal microbiota and the content of uremic toxins of microbial origin in a Russian cohort of patients on program hemodialysis.

MATERIALS AND METHODS

The study included 80 patients (40 men and 40 women) with a median age of 62.5 (range, 51.3–69.8) years who underwent hemodialysis for a median of 52 (range, 21.5–120) months. The median urea clearance rate was 1.46 (range, 1.39–1.57). In the hemodialysis group, the causes of terminal renal failure (TRF) were type 2 diabetes mellitus (33.7%), chronic glomerulonephritis (28.8%), polycystic kidney disease (10%), tubulointerstitial nephritis (5%), type 1 diabetes mellitus (3.8%), and other diseases (18.7%). The patients were primarily from the Northwest region and did not adhere to any specific diets, except for limiting fluid intake and avoiding foods high in potassium and phosphorus, which is recommended for severe renal failure.

The control group consisted of 20 healthy individuals (10 men and 10 women) with a median age of 55 (range, 49.3–66.8) years, and they had no renal dysfunction. The groups were comparable in terms of sex, age, body mass index, and smoking status.

The exclusion criteria were as follows: presence of acute inflammatory and uncompensated chronic diseases, viral hepatitis, and enteropathies such as Crohn’s disease, nonspecific ulcerative colitis, and celiac disease; intake of antibiotics, laxatives, and pre- and probiotics; or surgeries on gastrointestinal tract (GIT) organs in the preceding 12 months.

To determine the state of colonic microbiocenosis, 1 g of fecal samples was examined. Deoxyribonucleic acid (DNA) was extracted from the bacterial fraction of feces using the DNA-sorbB kit (Next-Bio, Russia), amplification was performed by reverse-transcription polymerase chain reaction using the Colonoflor 16 Premium kit produced by Alfalab (Russia) with the help of the DT-prime detection amplifier produced by DNA-Technology (Russia). The manufacturer’s software was used to interpret the results.

A comparative analysis was conducted on the composition of the intestinal microbiota using both qualitative (frequency of deviation from reference values) and quantitative criteria (magnitude of change in the trait). The degree of change in the investigated indicator was considered in the statistical analysis. For example, if the abundance of Escherichia coli was 3 × 10⁵ colony-forming units (CFU)/mL, 5 were considered for analysis. The total microbial content was compared between groups without considering cases with unknown microorganism counts, mainly due to a decrease in bacterial abundance below the sensitivity threshold of the technique.

Liquid chromatography/mass spectrometry was used to determine trimethylamine (TMA) and its metabolite TMAO in the serum. The Shimadzu-8060 system in combination with a Shimadzu LC-30AD liquid chromatograph (Japan) was employed for this purpose.

The serum concentrations of PCS and IS were determined using an enzyme immunoassay following the instructions of a commercial kit from Cloud-Clone Corp. (USA). The analysis was performed on a Victor X5 tablet analyzer by PerkinElmer Inc. (USA).

Data were statistically processed using the SPSS Statistics 26 program. To account for the small number of observations in the control group, all parameter numerical values are presented as median (Me) and interquartile range (Q25–Q75). Qualitative characteristics are presented as the absolute number and proportion of the total number (in %). The Mann – Whitney criterion was used to compare groups based on quantitative indicators. Qualitative variables were compared using Pearson’s chi-square test and Fisher’s exact test. A value of p < 0.05 was considered statistically significant.

The study was approved by the local ethical committee of the Kirov Military Medical Academy (Protocol No. 262 of April 26, 2022).

RESULTS AND DISCUSSION

The results of the comparative analysis of the composition of intestinal microbiota in both groups are presented in Tables 1 and 2. The analysis revealed that the total number of intestinal bacteria increased in 5 (6.3%) patients on hemodialysis, and the number of microbial cells decreased in 2 (2.5%). No deviations in this indicator were observed in the control group. No significant differences in the total number of bacteria were found between the groups. The abundance of Lactobacillus spp. and Bifidobacterium spp. decreased in 35 (43.8%) and 24 (30%) patients on hemodialysis, respectively. A combined violation was found in 19 (23.8%) patients. In contrast, only 1 (5%) case of similar abnormalities was recorded in the control group. A significant reduction in the absolute number of intestinal bifidobacteria and lactobacilli was noted in the hemodialysis group.

 

Table 1. Total number of representatives of the intestinal microbiota in both groups

Таблица 1. Общая численность некоторых представителей кишечной микробиоты у пациентов обеих групп

Indicator	Reference values	Hemodialysis group	Control group	р
Total bacterial mass	1011–1013	11 (10–12)	10.5 (10–11)	= 0.073
Lactobacillus spp.	107–108	6 5–7)	8 (7–8)	< 0.001
Bifidobacterium spp.	109–1010	8 (7–9)	9 (8–10)	= 0.014
Escherichia coli	106–108	6 (5–6)	7 (6–8)	< 0.001
Bacteroides spp.	109–1012	10 (10–11)	10 (9–11)	= 0.213
Faecalibacterium prausnitzii	108–1011	7 (9–10)	10 (9–10.75)	= 0.046
Eubacterium rectale	108–1011	6 (5–8)	10 (9–11)	< 0.001
Roseburia inulinivorans	108–1010	7 (6–9)	9 (8.25–10)	< 0.001
Bacteroides thetaomicron	–†	7.5 (7–9)	10 (9–10.75)	< 0.001
Akkermansia muciniphila	≤ 1011	8 (6.25–10)	10 (9–10)	< 0.001
Enterococcus spp.	≤ 108	7 (6–9)	6.5 (5.75–7.25)	= 0.037§
Blautia spp.	108–1011	8 (7–9)	8 (7–9)	= 0.536¥
Prevotella spp.	≤ 1011	7 (6–9)	9 (8–10)	= 0.005
Methanobrevibacter smithii	≤ 1010	7.5 (6–9)	9 (7.25–10)	= 0.036
Ruminococcus spp.	≤ 1011	7 (6–8)	9 (8–10)	= 0.001€
Relationship between Bacteroides spp. and Faecalibacterium prausnitzii (Bfr/Fprau)	0.01–100	9.95 (3.63–54.25)	4.25 (2.54–9.5)	= 0.011

Note: ^† — any amount is acceptable; ^§ — value calculated for 54 patients in the study group and 10 in the control group wherein the exact content of Enterococcus spp. was determined; ^¥ — value calculated for 44 patients in the study group and 18 in the control group wherein the exact content of Blautia spp. was determined; ^€ — value calculated for 54 patients in the study group and 17 in the control group wherein the exact content of Ruminococcus spp. was determined.

Примечание: ^† — допустимо любое количество; ^§ — значение рассчитано для 54 пациентов ОГ и 10 лиц КГ, у которых определено точное содержание Enterococcus spp.; ^¥ — значение рассчитано для 44 пациентов ОГ и 18 лиц КГ, у которых определено точное содержание Blautia spp.; ^€ — значение рассчитано для 54 пациентов ОГ и 17 лиц КГ, у которых определено точное содержание Ruminococcus spp.

 

Table 2. Frequency of occurrence of clinically significant changes in the composition of the intestinal microbiota in both groups, abs. (%)

Таблица 2. Частота встречаемости клинически значимых изменений состава кишечной микробиоты у пациентов обеих групп, абс. (%)

Indicator	Hemodialysis group	Control group	р
Total bacterial mass, > 1013	5 (6.3)	0	= 0.58
Total bacterial mass, < 1011	2 (2.5)	0	= 1.0
Lactobacillus spp. < 106	35 (43.8)	1 (5)	= 0.001
Bifidobacterium spp. < 108	24 (30)	1 (5)	= 0.021
Escherichia coli < 105	8 (10)	0	= 0.352
Bacteroides spp. > 1012	12 (15)	1 (5)	= 0.456
Faecalibacterium prausnitzii < 107	18 (22.5)	0	= 0.02
Eubacterium rectale < 106	30 (37.5)	2 (10)	= 0.018
Roseburia inulinivorans < 108	21 (26.3)	3 (15)	= 0.387
Escherichia coli enteropathogenic > 104	4 (5)	0	= 0.581
Enterococcus spp. > 108	15 (18.8)	1 (5)	= 0.183
Klebsiella pneumoniae > 104	6 (7.5)	0	= 0.597
Klebsiella oxytoca > 104	1 (1.3)	0	= 1.0
Candida spp. > 104	2 (2.5)	0	= 1.0
Staphylococcus aureus > 104	1 (1.3)	0	= 1.0
Acinetobacter spp. > 106	2 (2.5)	0	= 1.0
Clostridium difficile	4 (5)	0	= 0.581
Clostridium perfringens	4 (5)	0	= 0.581
Proteus vulgaris/mirabilis > 104	2 (2.5)	0	= 1.0
Citrobacter spp. > 104	3 (3.8)	0	= 1.0
Enterobacter spp. > 104	6 (7.5)	0	= 0.597
Fusobacterium nucleatum	11 (13.8)	2 (10)	= 1.0
Streptococcus spp. > 108	0	0	–
Parvimonas micra > 104	4 (5)	1 (5)	= 1.0
Blautia spp. < 107	46 (57.5)	2 (10)	< 0.001
Methanobrevibacter smithii < 105	19 (23.8)	3 (15)	= 0.551
Methanobrevibacter smithii > 1010	7 (8.8)	0	= 0.339
Methanosphaera stadmanae > 106	18 (22.5)	0	= 0.02
Ruminococcus spp. < 105	26 (32.5)	3 (15)	= 0.17
Salmonella spp.	0	0	–
Shigella spp.	0	0	–
Relationship between Bacteroides spp. and Faecalibacterium prausnitzii (Bfr/Fprau) > 100	13 (16.3)	0	= 0.065

 

In patients undergoing hemodialysis, the total population of E. coli decreased, and in 8 (10%) patients, its content in fecal samples was <10⁵ CFU/mL. In addition, enteropathogenic strains of E. coli were detected in 6 (7.5%) patients with TRF, of which in 4 (5%), its titer exceeded the clinically significant threshold of 10⁴ CFU/mL. The percentage of patients with TRF and elevated Bacteroides spp. titers (15%) was slightly higher than that of relatively healthy volunteers (5%). However, no significant differences in the total number of Bacteroides spp. were found between the two groups.

In the hemodialysis group, the total number of microorganisms that produce butyrate and other SCFAs, including Faecalibacterium prausnitzii, Eubacterium rectale, and Roseburia inulinivorans, significantly decreased. The content of Faecalibacterium prausnitzii was reduced in 18 (22.5%) patients on hemodialysis, Eubacterium rectale in 30 (37.5%), and Roseburia inulinivorans in 21 (26.3%), relative to normal values. Patients undergoing hemodialysis exhibited higher Bacteroides spp./Faecalibacterium prausnitzii ratio (9.95 [3.63–54.24]) than those not receiving treatment (4.25 [2.54–9.5], p = 0.011). An increase in this index may indicate an anaerobic imbalance in the intestinal microflora, with values >100 indicating clinically significant disorders. Such abnormalities were observed in 13 (16.3%) patients in the hemodialysis group.

Patients undergoing hemodialysis exhibited a significant reduction in the abundance of Bacteroides thetaomicron, a bacterium that possesses anti-inflammatory properties and contributes to the barrier function of the intestinal mucosa. The population of Akkermansia muciniphila, which breaks down mucin to produce beneficial products such as SCFAs, was also reduced. These metabolites regulate the abundance of other beneficial bacterial species and play a role in the immune modulation of the intestinal wall. The intestinal microbiota profile of patients on hemodialysis was characterized by an increased colonization of enterococci. Excessive content of enterococci (>10⁸ CFU/mL) was detected in 15 (18.8%) patients in the hemodialysis group and 1 (5%) in the control group. These patients also showed a predominance of Enterococcus spp. over Escherichia coli, which is considered a sign of dysbiosis and can often have pathological consequences. Representatives of opportunistic flora were detected in fecal samples of patients undergoing hemodialysis and in some cases in clinically significant titers. Thus, Fusobacterium nucleatum was detected in 11 (13.8 %) patients, Klebsiella pneumoniae in 6 (7.5 %), Enterobacter spp. in 6 (7.5 %), Clostridium perfringens in 4 (5 %), Clostridium difficile in 4 (5 %), Citrobacter spp. in 3 (3.8%), Candida spp. in 2 (2.5%), Proteus vulgaris/mirabilis in 2 (2.5%), Klebsiella oxytoca in 1 (1.3%), Staphylococcus aureus in 1 (1.3%), and Acinetobacter spp. in 2 (2.5%) of the hemodialysis group. This was in contrast to the control group, where bacterial infections were practically not observed among healthy individuals.

Streptococcus spp. microorganisms were detected in fecal samples from 45 (56.3%) patients in the hemodialysis group and 5 (25%) in the control group. However, none of the patients had titers exceeding the clinically significant threshold of 10⁸ CFU/mL. In both groups, the frequency of Parvimonas micra detection in fecal samples with clinically significant titers was 5%. Detection of this obligate anaerobic bacterium in amounts >10⁴ CFU/mL is considered an early marker of large-intestine carcinogenesis. In the hemodialysis group, 57.5% of the patients had a decreased abundance of Blautia spp., a resident anaerobic bacterium that synthesizes acetate and exerts a protective effect on pathogen introduction. Two (10%) similar cases were noted in the control group.

The dietary pattern of most patients on dialysis, which includes a reduced intake of plant foods (particularly fiber), may be responsible for the significant reduction in the abundance of Prevotella spp. Lower abundance levels of this genus may also be associated with atrophic gastritis and gastric cancer. In addition, the total counts of Methanobrevibacter smithii decreased in the hemodialysis group, and the content of this methane-forming anaerobic microorganism in the hemodialysis group had a multidirectional characteristics. In 7 (8.8%) patients with TRF, M. smithii was detected in a titer > 10¹⁰ CFU/mL, a finding previously observed in individuals with obesity. However, 23 (28.8%) patients showed a decrease in M. smithii < 10⁵ CFU/mL, which may contribute to the activation of fermentation and putrefaction in the intestines. In addition, 18 (22.5%) patients with TRF showed an increase in the titer of Methanosphaera stadmanae, another representative of the archaea domain. No abnormalities were observed in the control group. M. stadmanae is thought to stimulate local immune reactions and the synthesis of proinflammatory cytokines, contributing to inflammation development.

In the hemodialysis group, 32.5% of the patients had decreased abundance of Ruminococcus spp. compared with 15% in the control group. The total content of Ruminococcus spp. in the hemodialysis group was significantly lower than that in the control group, even when excluding individuals with titers < 10⁵ CFU/mL. These changes may result from a deficiency of dietary proteins, essential amino acids, and microelements. However, some bacteria in this genus, such as R. torques, produce butyrate. Pathogenic strains of Salmonella spp. and Shigella spp. were not found in either group.

Changes in the composition of intestinal microbiota in the hemodialysis group led to a significant increase in the blood concentration levels of uremic toxins of microbial origin. Compared with individuals with normal renal function, patients on hemodialysis had a 22-fold increase in TMA levels, 23-fold increase in TMAO levels, 21-fold increase in IS levels, and 5-fold increase in PCS levels (Table 3).

 

Table 3. Serum levels of uremic toxins of microbial origin in both groups

Таблица 3. Сывороточный уровень уремических токсинов микробного происхождения у пациентов обеих групп

Uremic toxin	Hemodialysis group	Control group	р <
Trimethylamine, ng/mL	153.8 (95.7–283.1)	7.1 (4.3–13.1)	0.001
Trimethylamine-N-oxide, ng/mL	5223.3 (3389.3–9445.7)	227.1 (140.4–34)	0.001
Indoxyl sulfate, μmol/L	2.1 (1.4–3)	0.1 (0–0.3)	0.001
P-cresyl sulfate, ng/mL	33.6 (19.1–50.6)	6.4 (4.0–9.2)	0.001

 

For the first time in Russian patients on hemodialysis, we have studied the peculiarities of changes in intestinal microbiocenosis. This includes both the composition of the intestinal microbiota and uremic toxins of microbial origin, such as TMA, TMAO, IS, and PCS, in the blood. In patients with TRF, multidirectional changes in the content of obligate representatives of intestinal microflora, with signs of anaerobic imbalance, were noted. Specifically, increased colonization of enterococci is combined with a decrease in the abundance of E. coli, ruminococci, and various SCFA-producing bacteria. The total number of microbial cells remains unchanged. Furthermore, patients undergoing hemodialysis often exhibit increased levels of opportunistic and pathogenic microorganisms and an altered microbiome associated with systemic metabolic disorders, inflammation, and gastrointestinal carcinogenesis. Intestinal dysbiosis, in one form or another, was diagnosed in all patients undergoing hemodialysis.

The data generally agree with earlier studies, revealing that stool samples from patients on hemodialysis contain significantly lower counts of Lactobacillaceae and Prevotellaceae families and 100 times higher counts of Enterobacteriaceae and Enterococci than in age-, sex-, and ethnicity-matched healthy volunteers [10]. Individuals with advanced CKD stages have also been observed to have increased counts of Eggerthella lenta from the Actinobacteria genus, Fusobacterium nucleatum from the Fusobacteriota genus, and Alistipes shahii from the Bacteroidetes genus [11]. According to J. Zhao, X. Ning, B. Liu, et al. [12], patients with TRF have higher counts of Proteobacteria and Streptococcus and Fusobacterium genera and lower counts of Prevotella, Coprococcus, Megamonas, and Faecalibacterium.

The intestinal bacterium Akkermansia, belonging to the Verrucomicrobia genus, plays a crucial role in maintaining the intestinal barrier function and mucus density. It also participates in the utilization of hydrogen sulfide and supports the growth of SCFA-producing bacteria by providing them with carbon, nitrogen, and energy from mucus decomposition [13]. A study of fecal microbial communities revealed a reduction in the abundance of the probiotic bacteria Akkermansia in patients with CKD compared with healthy controls [14].

Several studies have shown that Roseburia levels decrease in patients with late CKD stages, including patients on hemodialysis [6]. Roseburia is one of the main producers of butyric acid (butyrate) in the colon. Its content is also reduced in various inflammatory and metabolic diseases [15].

Q. Hu, K. Wu, W. Pan, et al. [16] found that the predominance of Ruminococcus gnavus at the delivery level could be distinguished between patients with early-stage CKD and healthy controls. In patients with Crohn’s disease, R. gnavus promotes intestinal wall inflammation by producing inflammatory polysaccharides such as glucoramnan. These polysaccharides induce the secretion of the inflammatory cytokine tumor necrosis factor-alpha by dendritic cells [17]. In contrast, the abundance of Ruminococcus spp. significantly in the hemodialysis group compared with the control group. A possible explanation for these contradictions is the peculiarities of the methodology used to assess the composition of the intestinal microbiota, which allows for determining the total number of all ruminococci, rather than individual representatives of this genus, as they have antagonistic properties.

Data on the peculiarities of intestinal dysbacteriosis in Russian patients undergoing hemodialysis are limited. Only one paper in the available literature, authored by I.V. Belova, A.E. Khrulev, A.G. Tochilina et al., addressed this topic. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry revealed dysbiotic changes in the intestinal microbiocenosis of 62 patients on maintenance hemodialysis, which were characterized by a complete absence or suppression of lacto- and bifidoflora and a higher count and species diversity of Bacteroides, Clostridium, Collinsella, Eggerthella, and some other microorganisms.

Intestinal dysbacteriosis in the hemodialysis group was found to be associated with a significant increase in serum levels of IS, PCS, and TMA (TMAO). The accumulation of these compounds in the body is attributed to a decrease in their renal excretion and the involvement of dysbiotic intestinal microflora [3]. J. Wong, Y.M. Piceno, T.Z. DeSantis, et al. [5] confirmed that microorganisms with enzymes involved in the synthesis of uremic toxins (such as urease, uricase, and tryptophanase) were prevalent among the bacteria in individuals with TRF. Furthermore, in CKD, the bacterial composition shifts toward proteolytic bacterial species that produce protease. This shift is associated with inflammation and increased permeability of the intestinal wall. In addition, the abundance of saccharolytic bacteria, which break down sugars and produce fermentation products necessary for the synthesis of SCFAs, decreases [12, 19].

In the systemic circulation, uremic toxins of microbial origin can induce inflammation through various molecular mechanisms and signaling pathways and have direct pathogenic effects on various cell types. This contributes to the development and progression of cardiovascular, neurological, mineral-bone, alimentary, and other complications in patients with CKD [20].

This study has limitations. The number of participants may have been insufficient to extrapolate the identified features of intestinal dysbiosis to the entire population of patients receiving hemodialysis because of the huge interindividual variability of the intestinal microbiome. The influence of individual dietary habits, medications, and other factors that have previously shown a significant effect on the composition of the intestinal microbiota cannot be excluded.

Moreover, the primary pathology that caused TRF may have a greater effect on intestinal dysbiosis than severe renal dysfunction and the need for dialysis. Furthermore, this study had limited ability to analyze the full spectrum of intestinal microorganisms because we were only able to assess the contents of certain microorganisms. Although full-genome sequencing is the preferred method for such studies, our findings can serve as a foundation for future research in this field.

CONCLUSIONS

1. Patients receiving hemodialysis have pronounced changes in gut microflora accompanied by a significant increase in the blood concentrations of uremic toxins of microbial origin, such as IS, PCS, and TMA (TMAO).
2. The results suggest the need for further research into the characteristics of intestinal dysbacteriosis in patients with kidney disease.
3. Improved understanding of the metabolic interactions between the intestinal microbiota and the body may facilitate the development of new personalized treatment approaches focused on correcting dysbiosis and reducing the concentration of uremic toxins of microbial origin. This could have a significant effect on improving the outcomes of patients with CKD, including those receiving hemodialysis.

ADDITIONAL INFORMATION

Authors’ contribution. Thereby, all authors made a substantial contribution to the conception of the study, acquisition, analysis, interpretation of data for the work, drafting and revising the article, final approval of the version to be published and agree to be accountable for all aspects of the study.

The contribution of each author. M.O. Pyatchenkov — general concept development, research design, article writing; E.V. Shcherbakov — collection and statistical processing of material; A.E. Trandina — enzyme immunoassay; R.I. Glushakov — literature review, article editing; K.A. Leonov — chromatographic analysis; V.I. Kazey — data analysis, content analysis.

Competing interests. The authors declare that they have no competing interests.

Funding source. This study was not supported by any external sources of funding.

ДОПОЛНИТЕЛЬНАЯ ИНФОРМАЦИЯ

Вклад авторов. Все авторы внесли существенный вклад в разработку концепции, проведение исследования и подготовку статьи, прочли и одобрили финальную версию перед публикацией.

Вклад каждого автора. М.О. Пятченков — разработка общей концепции, дизайн исследования, написание статьи; Е.В. Щербаков — сбор и статистическая обработка материала; А.Е. Трандина — иммуноферментный анализ; Р.И. Глушаков — обзор литературы, редактирование статьи; К.А. Леонов — хроматографический анализ; В.И. Казей — анализ данных, контент-анализ.

Конфликт интересов. Авторы декларируют отсутствие явных и потенциальных конфликтов интересов, связанных с публикацией настоящей статьи.

Источник финансирования. Авторы заявляют об отсутствии внешнего финансирования при проведении исследования.

作者简介

Mikhail O. Pyatchenkov

Kirov Military Medical Academy

编辑信件的主要联系方式.
Email: pyatchenkovMD@yandex.ru
ORCID iD: 0000-0002-5893-3191
SPIN 代码: 5572-8891

MD, Cand. Sci. (Med.)

俄罗斯联邦, Saint Petersburg

Evgeniy V. Sherbakov

Kirov Military Medical Academy

Email: evgenvmeda@mail.ru
ORCID iD: 0000-0002-3045-1721
SPIN 代码: 6337-6039
俄罗斯联邦, Saint Petersburg

Alexandra E. Trandina

Kirov Military Medical Academy

Email: sasha-trandina@rambler.ru
ORCID iD: 0000-0003-1875-1059
SPIN 代码: 6089-3495
俄罗斯联邦, Saint Petersburg

Ruslan I. Glushakov

Kirov Military Medical Academy

Email: glushakoffruslan@yandex.ru
ORCID iD: 0000-0002-0161-5977
SPIN 代码: 6860-8990

MD, Dr. Sci. (Med.)

俄罗斯联邦, Saint Petersburg

Klim A. Leonov

Exacte Labs

Email: pyatchenkovMD@yandex.ru
ORCID iD: 0000-0003-4268-1724

MD, Cand. Sci. (Chem.)

俄罗斯联邦, Moscow

Vasily I. Kazey

Exacte Labs

Email: pyatchenkovMD@yandex.ru
ORCID iD: 0000-0003-2032-6289
SPIN 代码: 6253-0211

MD, Cand. Sci. (Biol.)

俄罗斯联邦, Moscow

参考

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