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FEDERAL STATE-FUNDED EDUCATIONAL INSTITUTION FOREIGN ECONOMIC ASSOCIATION TGMU OF MINISTRY OF HEALTH OF THE RUSSIAN FEDERATION
Primorsky Territory
OGRN: 1022501895877
TIN: 2538017661
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OKVED2 85.22 Total: 13
Higher education
Monitoring Notes Reports Contact information
94
Reliability Score
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Chancellor
Shumatov Valentin Borisovich
29
years
Established
January 17, 1996
City Vladivostok
Revenue
No data
513
Connections
+1 last week
Employees
No data

Litigation

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Stats Over Time

Participation Total number of cases For the last year
Plaintiff
26 cases (▒▒▒▒▒ ₽) 1 case (▒▒▒▒▒ ₽)
Defendant
24 cases (▒▒▒▒▒ ₽) 1 case (▒▒▒▒▒ ₽)
Third party
7 cases (▒▒▒▒▒ ₽) 0 cases (▒▒▒▒▒ ₽)
Other party
2 cases (▒▒▒▒▒ ₽) 0 cases (▒▒▒▒▒ ₽)

Positive outcome — ▒▒%

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Negative outcome — ▒▒%

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Under consideration — ▒%

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Undefined — ▒▒%

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Type of dispute

%
Administrative
%
Civil
%
Bankruptcy-related
%
Other
×
Claim amount
×
Type of dispute
×
Outcome of case
×

Current cases

As plaintiff (1)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
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Defendant
Instance
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As defendant (1)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
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Plaintiff
Defendant
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Completed cases

As plaintiff (25)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
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Plaintiff
Defendant
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As defendant (23)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
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Plaintiff
Defendant
Instance
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As third party (7)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
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As other party (2)
Claims amount: ▒▒▒▒▒ ₽
Date/Number
Complexity
Object
Plaintiff
Defendant
Instance
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Data sources Information about company arbitration cases is collected from public sources.

Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.

If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!

Data sources Information about company arbitration cases is collected from public sources.

Accurate binding to a company can be created only if the information source contains its TIN and OGRN values. If identification details are not specified, the binding is created by using linguistic algorithms. Although these algorithms are being constantly improved, some information may be absent.

If you have noticed an error or lack of information, please let us know about it. Let's improve Seldon.Basis together!

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