Features of the etiology of SARS-CoV-2–associated pneumonias in Primorsky territory

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BACKGROUND

Viral pneumonias associated with SARS-CoV-2 have exacerbated multiple challenges in routine clinical practice, including the criteria for initiating etiotropic therapy. During the COVID-19 pandemic in the Russian Federation, specialists revised more than ten versions of clinical guidelines for the diagnosis and treatment of this disease [1]. Studies have demonstrated that antibiotics are ineffective against pneumonias of viral etiology; nevertheless, clinicians continued to prescribe them for various reasons [1]. The use of antibacterial agents requires clear clinical justification. To ensure appropriate prescription of antibacterial therapy in patients with SARS-CoV-2 infection, additional diagnostic evaluation is necessary to confirm the presence of bacterial co-infection. It is also essential to consider data on regional characteristics of the population microbiota and patterns of antimicrobial resistance [2]. However, in many cases, antibacterial therapy was prescribed without taking into account the most prevalent Gram-positive or Gram-negative microorganisms and their biological properties [3]. A major concern has also been the widespread use of antibacterial agents in patients with viral infections in the absence of evidence of bacterial infection [4]. This situation was further aggravated during the coronavirus pandemic due to the extensive use of antibacterial drugs, including self-medication without medical supervision. In addition, published data indicate changes in the regional composition of the accompanying microbiota in the context of ongoing coronavirus infection [5].

AIM

To perform an epidemiologic analysis of SARS-CoV-2 infection morbidity in Primorsky territory during 2021–2023, to conduct a comparative analysis of the etiologic distribution of pneumonia in patients with COVID-19, and to assess antimicrobial resistance of the lower respiratory tract microbiota.

METHODS

Study Design

We conducted a retrospective cohort study based on archived medical records from the infectious diseases department of Regional Clinical Hospital No. 2 (Vladivostok, Russia). The analysis included 6491 medical records of patients with confirmed coronavirus disease (COVID-19) who were hospitalized between 2021 and 2023.

Eligibility Criteria

Inclusion criteria:

• Men and women aged ≥18 years hospitalized for inpatient treatment;
• SARS-CoV-2 infection confirmed based on polymerase chain reaction (PCR) testing of oropharyngeal and/or nasopharyngeal swabs;
• Radiologic signs of pneumonia identified by computed tomography (CT) at hospital admission;
• Moderate or severe course of the disease;
• Plasma C-reactive protein concentration >10 mg/L;
• Body temperature ≥38 °C;
• Availability of cytological and microbiological sputum examination results with determination of antimicrobial resistance of isolated pathogens;
• Availability of clinical and biochemical blood test results;
• Administration of standard antiviral and antibacterial therapy in accordance with the version of the interim clinical guidelines for the prevention, diagnosis, and treatment of coronavirus infection [6].

Exclusion criteria:

• Use of antibacterial agents within six months before hospital admission.

Study Setting

The study was conducted in the Department of Infectious Diseases of Regional Clinical Hospital No. 2 (Vladivostok, Russia).

Study Duration

The study was performed retrospectively using archived medical records of patients with confirmed COVID-19 who received inpatient treatment between 2021 and 2023.

Intervention

Biological material for microbiological analysis was collected from patients within 48 hours after hospital admission. Sputum samples were examined using a classical quantitative bacteriological method: sputum was diluted in series to a concentration of 10⁷ and cultured on differential diagnostic media to determine the spectrum of major pathogens. Mycoplasma pneumoniae was detected using the AmpliSens^® Mycoplasma pneumoniae test system (Central Research Institute of Epidemiology, Russia). Legionella spp. were identified by an immunochromatographic assay with detection of Legionella antigen in urine. For the identification of acid-fast mycobacteria, sputum samples from each patient were stained three times using the Ziehl–Neelsen method. All isolates were analyzed using the BD Phoenix™ M50 system (Becton Dickinson, USA) for microorganism identification and determination of antimicrobial susceptibility to a broad range of antibacterial agents. A score value ≥2.2 was considered indicative of reliable species-level identification. Antimicrobial resistance was assessed using the disk diffusion method, with interpretation of results in accordance with the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines (version 8.0). When necessary, additional analysis was performed using the VITEK^® 2 Compact microbiological analyzer (bioMérieux SA, France).

Main Study Outcome

Determination of the incidence and trends of pneumonia among patients hospitalized with laboratory-confirmed SARS-CoV-2 infection between 2021 and 2023.

Additional Study Outcomes

Assessment of the etiologic distribution of bacterial and fungal superinfections in patients with pneumonia associated with COVID-19. Evaluation of antimicrobial resistance profiles of the leading bacterial pathogens isolated from sputum samples of hospitalized patients.

Ethics Approval

The study was approved by the Local Ethics Committee of the Regional Clinical Hospital No. 2 (Minutes No. 2/1 dated June 1, 2021). Prior to inclusion in the study, all participants voluntarily provided an informed consent form approved as part of the study protocol by the Ethics Committee.

Statistical Analysis

No a priori sample size calculation was performed.

Statistical analysis was conducted using descriptive statistics with STATISTICA version 12.5 (StatSoft, USA) and Microsoft Excel 2010 (Windows 10; Microsoft, USA).

RESULTS

Participants

The study included 6491 medical records of patients with laboratory-confirmed coronavirus infection.

Primary Results

During the analyzed period, the number of hospitalizations at the infectious disease hospital fluctuated with periodic increases and decreases (Table 1), reflecting the overall epidemiologic situation of coronavirus infection in the Russian Federation and Primorsky territory. In 2021, a bimodal increase in hospitalizations of patients with coronavirus infection was observed. The first rise occurred during the winter months, followed by a decrease in hospitalizations in spring and a more pronounced increase in summer and autumn. A similar pattern was observed in the incidence of pneumonia. Notably, among hospitalized patients, more than 80% of pneumonia cases were diagnosed in June, November, and December.

 

Table 1. Distribution of patients with SARS-CoV-2–associated coronavirus infection and patients with pneumonia

Months	2021			2022			2023
	COVID-19, n	Pneumonia		COVID-19, n	Pneumonia		COVID-19, n	Pneumonia
		n	%		n	%		n	%
January	240	174	72.5	172	161	93.6	224	142	63.4
February	127	101	79.5	188	142	75.5	272	135	49.6
March	76	51	67.1	73	63	86.3	269	118	43.9
April	98	67	68.4	130	83	63.8	187	85	45.5
May	222	164	73.8	76	42	55.2	119	59	49.8
June	254	209	82.3	93	46	49.5	72	41	56.9
July	302	234	77.5	202	60	29.7	53	26	49.1
August	277	217	78.3	252	81	32.1	53	31	58.5
September	203	162	79.8	237	86	36.3	137	68	49.6
October	299	240	80.3	135	69	51.1	166	86	51.8
November	324	276	85.2	173	61	35.3	217	114	52.5
December	217	193	88.9	196	66	33.7	164	57	34.7
Total	2639	2088	79.1	1919	874	45.5	1933	962	49.8

 

In 2022, the situation changed. First, the overall number of hospitalized patients decreased. Second, beginning in spring, the proportion of diagnosed pneumonia cases declined to 30%–40%, reaching a minimum in July (29.7%). However, at the end of 2022 and during the first months of 2023, a renewed increase in hospitalizations due to coronavirus infection was recorded, along with an increase in the proportion of pneumonia cases to 63.4% of all hospitalizations. The highest number of hospitalized patients and verified pneumonia cases was registered in 2021, followed by a marked decline in these indicators in 2022–2023. Among hospitalized patients during 2021–2023, moderate severity of coronavirus infection predominated (Table 2), accounting for 59.8% of cases in 2021 and increasing to 74.8% in 2022. The highest proportion of severe and extremely severe cases was observed in 2021 (41.1%), whereas the lowest was recorded in 2022 (25.2%).

 

Table 2. Distribution of patients with SARS-CoV-2–associated coronavirus infection by disease severity

Severity	2021, n	%	2022, n	%	2023, n	%
Moderate	1579	59.8	1436	74.8	1315	68.0
Severe	728	27.6	310	16.2	436	22.5
Critical	332	13.5	173	9.0	182	9.5
Total:	2639		1919		1933

 

The clinical presentation of coronavirus infection in hospitalized patients was characterized by moderate and severe disease forms, a high incidence of pneumonia with respiratory failure, development of acute respiratory distress syndrome (ARDS), and a substantial number of fatal outcomes.

Analysis of pathogens isolated from sputum samples of patients with pneumonia revealed marked etiologic polymorphism. In 2021, pneumonia cases were predominantly of viral origin, and a microbial pathogen was detected in only one-third of cases. In contrast, during 2022–2023, a substantial increase in virus–bacterial co-infections was observed (up to 60%), along with a rising frequency of opportunistic microorganisms (Candida, Mycoplasma). The highest number of such viral–microbial associations was recorded during the spring and autumn periods. Over the study period, the composition of sputum bacterial microbiota changed. In 2021–2022, Gram-positive flora predominated, whereas in 2023, an equal distribution of Gram-positive and Gram-negative microorganisms was observed (Table 3). Since 2022, the disease structure has demonstrated the emergence and a subsequent >6-fold increase in the proportion of various Candida species.

 

Table 3. Distribution of microorganisms isolated from the sputum microbiota of patients with SARS-CoV-2–associated pneumonia

Microorganisms	2021, n	2022, n	2023, n	Total:
Non-fermenting bacteria
Pseudomonas aeruginosa	25	14	12	51
Burkholderia cepacia	25	-	-	25
Acinetobacter baumannii	8	-	13	21
Total:	58	14	25	97
Gram-negative bacteria
Klebsiella aerogenes	58	25	28	111
Klebsiella pneumoniae	43	34	65	142
Klebsiella oxytoca	6	1	-	7
Escherichia coli	40	32	72	144
Enterobacter cloacae	-	22	63	85
Proteus mirabilis	17	26	10	53
Total:	164	140	238	542
Gram-positive bacteria
Staphylococcus epidermidis	147	102	50	299
MRSA, %	52.7	4.6	7.5	-
Streptococcus pyogenes	113	63	71	247
Streptococcus pneumoniae	76	58	51	185
Streptococcus, beta-haemolytic	42	7	2	51
Enterococcus faecium	42	32	4	78
Enterococcus faecalis	27	20	11	58
Staphylococcus aureus	36	13	24	73
Streptococcus viridans, alpha-haemolytic	-	15	10	25
Staphylococcus saprophyticus	10	13	31	54
Streptococcus agalactiae	2	13	-	15
BLRSA, %	48.3	77.2	37.6	-
Total:	495	336	254	1085
Yeast-like fungi
Candida krusei	-	16	76	92
Candida albicans	-	11	70	81
Candida glabrata	-	8	31	39
Candida tropicalis	-	-	16	16
Total:	-	35	193	228

 

Among Gram-positive microorganisms isolated from sputum, S. epidermidis (27.6%) and streptococci, Streptococcus pyogenes (22.8%) and S. pneumoniae (17.1%), were most frequently identified. In 2023, the detection rate of S. epidermidis decreased threefold, and that of S. pyogenes decreased 1.5-fold, whereas the frequency of S. pneumoniae isolation remained relatively stable across all years.

Among Gram-negative pathogens, representatives of Escherichia coli (22.5%) and Klebsiella pneumoniae (22.2%) predominated. The annual number of isolates of these pathogens increased, reaching 30.3% and 27.3%, respectively, in 2023. In addition, non-fermenting Gram-negative bacteria, including Pseudomonas aeruginosa and Acinetobacter baumannii, were detected.

Fungi are often part of the human microbiome. In the analyzed sputum samples, C. albicans (35.5%) and C. krusei (40.3%) were most frequently identified, with the highest prevalence recorded in 2023. All sputum samples were additionally tested for M. pneumoniae, which was detected in 27.6% of cases. Legionella spp. were not identified in any of the samples.

Bacterial pathogens demonstrated resistance to the major classes of antibacterial agents (Table 4). The proportion of methicillin-resistant Staphylococcus aureus (MRSA) was 52.7% in 2021 and sharply declined to 4.6% in 2022, likely reflecting the widespread use of antibacterial agents during the early phase of the COVID-19 pandemic. Analysis of multidrug-resistant pathogens showed that the proportion of microorganisms resistant to beta-lactams and carbapenems ranged from 37.7% to 77.2%. The highest resistance of Staphylococcus species to penicillins was observed in 2022 (71.8%), followed by a twofold decrease by 2023. Resistance to aminoglycosides reached 44.3% in 2023; to macrolides, 36.3% in 2021 (with a subsequent decline); to fluoroquinolones, 20.2% in 2021 (also decreasing by 2023); and to glycopeptides, 36.3% in 2021. Overall, resistance patterns of Staphylococcus species to individual antibacterial classes varied over time.

 

Table 4. Distribution of major antibiotic-resistant microbial groups isolated from the sputum microbiota of patients with SARS-CoV-2–associated pneumonia

Antibiotic class	year	Genus of microorganisms
		Staphylococcus, %	Klebsiella, %	Escherichia + Enterobacter, %	Pseudomonas, %	Streptococcus, %	Enterococcus, %
Cephalosporins 3rd generation	2021	2.1	32.7	53.8	65.3	38.3	15.9
	2022	26.6	86.6	61.1	57.1	13.2	22.6
	2023	1.9	44.0	21.1	-	6.3	-
Cephalosporins 4th generation	2021	-	48.6	6.1	15.3	-	-
	2022	-	5.0	-	-	-	-
	2023	0.9	3.2	-	-	-	-
Aminoglycosides	2021	36.8	37.3	29.2	15.3	3.5	37.6
	2022	26.6	53.3	51.8	21.4	16.9	39.6
	2023	44.3	54.8	51.8	-	1.3	6.6
Macrolides	2021	36.3	26.1	41.5	-	29.2	10.1
	2022	30.5	5.0	12.9	7.1	15.7	18.8
	2023	1.9	-	-	-	5.6	-
Glycopeptides	2021	36.3	4.6	-	3.8	28.4	27.5
	2022	34.3	-	-	-	34.6	47.1
	2023	-	-	-	-	2.5	6.6
Tetracyclines	2021	18.7	-	-	-	-	31.8
	2022	8.6	-	-	-	1.2	13.2
	2023	-	-	-	-	-	-
Penicillins	2021	7.8	23.3	10.7	7.6	60.0	65.2
	2022	71.8	1.6	55.5	21.4	36.4	56.6
	2023	38.6	67.7	79.5	8.3	20.0	20.0
Fluoroquinolones	2021	20.2	35.5	13.8	19.2	32.4	55.1
	2022	12.5	26.6	20.3	28.5	23.2	41.5
	2023	17.9	48.3	65.6	50.0	23.1	33.3
Carbapenems	2021	9.8	18.6	23.1	15.3	17.3	5.7
	2022	6.3	10.0	18.5	28.5	8.1	3.7
	2023	5.6	46.2	64.9	41.6	5.6	40.0
Lincosamides	2021	-	-	-	-	-	4.3
	2022	-	-	-	-	-	-
		38.6	-	-	-	16.8	-

 

Streptococcus species demonstrated heterogeneous resistance profiles across major antibacterial classes. Resistance to third-generation cephalosporins decreased from 38.3% in 2021 to 6.3% in 2023. The highest proportion of glycopeptide-resistant strains was observed in 2022 (34.6%), whereas resistance to macrolides peaked at 29.2% in 2021. Penicillin resistance was 60.0% in 2021 but declined to 20.0% by 2023. Resistance to fluoroquinolones was higher than that observed in Staphylococcus species, reaching 32.4%.

Enterococcus species exhibited high resistance to penicillin antibiotics, with a rate of 65.2% in 2021, followed by a threefold decrease by 2023. Resistance to fluoroquinolones was 55.1% in 2021 and persisted throughout 2022–2023. Additionally, resistance to glycopeptides reached 47.1% in 2022, and resistance to aminoglycosides was 39.6% in 2022, decreasing to 6.6% in 2023. Notably, a marked increase in carbapenem resistance was observed in this group, reaching 40.0% in 2023. Overall, Gram-positive bacteria exhibited the highest resistance to penicillins and fluoroquinolones.

Klebsiella species demonstrated the highest resistance to third- and fourth-generation cephalosporins (86.6% and 48.6%, respectively). In 2023, an increase in strain resistance was observed to the following antibiotic classes: aminoglycosides at 54.8%, penicillins at 67.7%, fluoroquinolones at 48.3%, and carbapenems at 46.2%.

Among Pseudomonas species, the highest resistance was observed to third-generation cephalosporins (65.3%) in 2021. By 2023, resistance to fluoroquinolones and carbapenems reached 50.0% and 41.6%, respectively. Escherichia and Enterobacter species also exhibited resistance to third-generation cephalosporins (61.1% in 2022) and aminoglycosides (51.8% in 2022–2023). In 2023, an increase in resistance to penicillins, fluoroquinolones, and carbapenems was observed (79.5%, 65.6%, and 64.9%, respectively). Overall, the major Gram-negative bacteria demonstrated the highest resistance to third-generation cephalosporins, fluoroquinolones, and carbapenems. The obtained data are quite expected, since these antibacterial drug classes are used in the treatment of patients with signs of bacterial lung tissue involvement.

DISCUSSION

Summary of Primary Results

In this study, we identified the characteristics and temporal trends of the sputum microbial landscape in patients with coronavirus infection in Primorsky territory. In 2021, Gram-positive flora predominated in sputum samples from patients with pneumonia, whereas by 2023 an increase in the proportion of Gram-negative bacteria was observed, along with a rise in the number of fungal species and M. pneumoniae. The predominant Gram-positive bacteria in the region exhibited the highest resistance to penicillins and fluoroquinolones. Among Gram-negative bacteria, resistance was most commonly observed to third-generation cephalosporins, fluoroquinolones, and carbapenems.

Discussion of the Study Results

The analysis revealed periodic increases in the number of hospitalized patients with coronavirus infection throughout the year. Each analyzed period differed, and no consistent monthly patterns were identified in the trends of the total number of cases or pneumonia incidence. This situation was consistent with global and Russian trends in morbidity and can be explained by the emergence of new SARS-CoV-2 variants [7]. The emergence of novel strains was invariably accompanied by surges in incidence. For example, in 2021, the increase in morbidity was associated with the spread of the Delta variant, during which patients were predominantly diagnosed with viral pneumonia [7]. Sputum samples were dominated by Gram-positive bacteria exhibiting high levels of antibiotic resistance. The use of hydroxychloroquine and azithromycin as etiotropic therapy for coronavirus infection, in accordance with temporary methodological guidelines, further aggravated the situation. Additionally, patients frequently started uncontrolled self-medication with antibiotics at the onset of viral infection symptoms. When commonly used medications were unavailable in pharmacies, the population resorted to reserve antibiotics.

In 2022, the situation changed with the initiation of mass vaccination. Updated methodological guidelines also introduced more specific antiviral drugs, whereas indications for antibacterial therapy were restricted to cases with confirmed bacterial pneumonia. At the same time, the Omicron variant became dominant, which was more frequently associated with viral–bacterial pneumonia. With continued widespread antibiotic use, the development of immunosuppression in patients, and the presence of Gram-positive and Gram-negative flora in approximately equal proportions, the situation was further complicated by the detection of opportunistic microorganisms, including yeast-like fungi and M. pneumoniae, in one-third of patients. Subsequently, alongside the introduction of new antiviral drugs and large-scale vaccination, mutational changes in the viral genome occurred. These changes contributed to a relatively mild course of coronavirus infection in most young and middle-aged patients. Severe disease was more often observed in patients older than 65 years. In immunocompromised patients, pneumonia frequently involved multiple bacterial pathogens, including opportunistic microorganisms such as Candida spp. and M. pneumoniae.

Microbiological monitoring of the sputum microbial landscape in patients with coronavirus infection in Primorsky territory demonstrated a shift from the predominance of Gram-positive flora in 2021 to an increased proportion of Gram-negative bacteria in 2023, along with the emergence of fungal species and M. pneumoniae, which is consistent with findings from other studies [4, 8]. According to our results, the detection rate of Candida spp. in Primorsky territory was higher than that reported in other regions of the Russian Federation, reaching 27.2% in 2023. This may be attributable to the high proportion of hospitalized patients with hematologic and oncologic diseases, as well as patients with chronic kidney disease receiving maintenance hemodialysis at Regional Clinical Hospital No. 2. SARS-CoV-2 further complicated the situation through its immunosuppressive effects during the acute phase of illness, facilitating the development of bacterial pneumonia caused by pathogens resistant to first-line antibacterial agents and the predominance of opportunistic flora in sputum. In certain years, the proportion of MRSA reached 52.7%, and strains resistant to most antibacterial agents accounted for up to 77.2%. Increasing antibiotic resistance among major pneumonia pathogens in patients with coronavirus infection has been reported worldwide and is driven by a range of direct and indirect factors [9–11]. Severe coronavirus infection requiring intensive care is thought to increase the risk of secondary infection or activation of opportunistic flora, including infection with hospital-acquired strains. Therefore, the selection of antibacterial therapy for bacterial coinfection in the setting of viral disease should take regional characteristics into account. In Primorsky territory, based on resistance profile analyses, effective empirical therapy should include fourth-generation cephalosporins and macrolides.

CONCLUSION

Thus, the microbial landscape of sputum in patients with pneumonia associated with coronavirus infection in Primorsky territory has characteristic features that should be taken into account when selecting treatment.

ADDITIONAL INFORMATION

Author contributions: S.A. Sokotun: resources, writing—original draft, writing—review & editing, visualization; A.O. Mikhailov: resources, writing—original draft; A.I. Simakova, N.G. Plekhova, S.N. Beniova: writing—review & editing; E.P. Chirkova, A.A. Savinov: formal analysis; I.O. Belevich: formal analysis. All the authors approved the version of the manuscript to be published and agreed to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Ethics approval: The study was approved by the Local Ethics Committee of Regional Clinical Hospital No. 2 (Minutes No. 2/1 dated June 1, 2021). All study participants signed the informed consent form prior to enrollment; the consent form was approved by the ethics committee as part of the study protocol.

Funding sources: No funding.

Disclosure of interests: The authors have no relationships, activities, or interests for the last three years related to for-profit or not-for-profit third parties whose interests may be affected by the content of the article.

Statement of originality: No previously published material was used in this work.

Data availability statement: The editorial policy regarding data sharing does not apply to this work.

Generative AI: No generative artificial intelligence technologies were used to prepare this article.

Provenance and peer review: This paper was submitted unsolicited and reviewed following the standard procedure. The peer review process involved three members of the editorial board.

About the authors

Svetlana A. Sokotun

Pacific State Medical University

Author for correspondence.
Email: sokotun.s@mail.ru
ORCID iD: 0000-0003-3807-3259
SPIN-code: 8744-2166

MD, Cand. Sci. (Medicine), Assistant Professor

Russian Federation, 2 Ostryakova ave, Vladivostok, 690002

Aleksandr O. Mikhaylov

Pacific State Medical University

Email: mao1991@mail.ru
ORCID iD: 0000-0002-2719-3629
SPIN-code: 1469-9086

MD, Cand. Sci. (Medicine), Assistant Professor

Russian Federation, 2 Ostryakova ave, Vladivostok, 690002

Anna I. Simakova

Pacific State Medical University

Email: anna-inf@yandex.ru
ORCID iD: 0000-0002-3334-4673
SPIN-code: 3563-7054

MD, Dr. Sci. (Medicine), Assistant Professor

Russian Federation, 2 Ostryakova ave, Vladivostok, 690002

Natalia G. Plekhova

Pacific State Medical University

Email: pl_nat@hotmail.com
ORCID iD: 0000-0002-8701-7213
SPIN-code: 2685-9578

Dr. Sci. (Biology), Assistant Professor

Russian Federation, 2 Ostryakova ave, Vladivostok, 690002

Svetlana N. Beniova

Regional Clinical Hospital № 2, Vladivostok

Email: snbeniova@mail.ru
ORCID iD: 0000-0002-8099-1267
SPIN-code: 9715-7742

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Vladivostok

Еlena P. Chirkova

Regional Clinical Hospital № 2, Vladivostok

Email: chirkova_ep@kkb2.ru
ORCID iD: 0009-0008-1263-4322
SPIN-code: 4568-0711
Russian Federation, Vladivostok

Andrey A. Savinov

Regional Clinical Hospital № 2, Vladivostok

Email: savinov.andrey28rus@mail.ru
ORCID iD: 0009-0001-9284-3296
Russian Federation, Vladivostok

Ivan O. Belevich

Pacific State Medical University

Email: belevich_1998@mail.ru
ORCID iD: 0009-0001-9480-2199
Russian Federation, 2 Ostryakova ave, Vladivostok, 690002

References

Supplementary files