63 research outputs found
THE ROLE OF INFORMATION FOR GLOBAL MARKETING - EDUCATIONAL AND PRACTICAL ASPECTS
The selection of company strategy for international market appearance is an essential part of implementation the global marketing. Given the fact that this process is influenced by a diverse range of factors, it is necessary to research and report frequently about the dynamics. The research of market environment is one of the most essential company activities. Information is the base of the market assessment as an opportunity to company entry, as well as for establishing a balance between the marketing-mix tactics in accordance with specific conditions set out by the local markets. Some of the huge problems in the transition economies are closely connected with education and practice connected to the global marketing issues. It is very significant to understand that marketing is not only a theory, but also an amount of knowledge created and carried through the experience in the business practice. The low level of theoretical and practical knowledge of this problematic is a serious flaw in global assessment process, especially in relation to local countries and regions, including the specific marketing functions of the company. The initial step should be implementation of theoretical and practical knowledge in the process of the companyβs information needs definition, and then to carry out further implementation of other phases of the process. The transition of economic and political system in Macedonia created favorable circumstances on education that sought to understand and employ the market system logic. The fundamental goals have been to achieve reflective, practical and analytical skills for those involved in management or marketing and for those who want a better understanding of the nature and process of management and marketing within broader contexts.Information; Management; Marketing; Education; Institution; Globalization.
THE ROLE OF MARKETING IN SMEβS DEVELOPMENT IN REPUBLIC MACEDONIA
The SME's currently need to upgrade their knowledge and skills to respond the complex market needs, in order to make their position and competitiveness on the market. There is a very close connection among marketing orientation and the level of development of small business. Among other macro and institutional factors, marketing has become one of the most important for SME's development. To be competitive means to create optimal marketing mix by using the four marketing instruments: product, place, promotion and price (4P). The situation of SME's in the Republic of Macedonia is characterized by disturbances in their development through the period of transition. The reasons for such situation are focused mainly on the highest (macro) level, but there are still some opinions that firms are not very innovative or creative in implementing the real marketing concept in practice. The owners or managers in this SME's are not aware or educated in the sphere of marketing and the possibilities for implementation of business activities. Responding to the consumer needs should be a base for creating the whole strategy and the process of consumer satisfaction has to be an indicator for the development small business. This should be a base for creating the contemporary relationship management concept in order to make a real business strategy for positioning the SMEβs in order to increase the completeness on the market.Marketing orientation; SMEβs development; Marketing concept; Promotion; Integrated communication
Level of Education and Health Status of the Different Social Groups: Case Study Macedonia
The educational level is an important indicator within the socioeconomical status for health evaluation and a powerful instrument in promotion of populationβs health. In 2000 a study conducted in R. Macedonia, in 15 municipalities with different gross national product per capita, encompassing 1129 examinees older than 18 years. The results of the conducted research showed statistically significant association of the educational level with the morbidity. Higher morbidity emerges in persons that are illiterate (78,57%) and in those who have completed only 1-3 elementary school grades (77,08%). There is also an interaction between the mortality and the educational level. Persons with lower educational level have higher mortality rate. What kind of interaction is there between the educational level and the positive health? People with lower educational level are more susceptible to diseases; they are less informed which leads to a poor health. Morbidity and mortality rates are lower in people with higher educational level, who also have high level of self-informing that augments their health awareness and culture, leading towards positive health. According to many research studies, the mechanisms that link education to positive health are the employment and self-satisfaction with the job, healthy lifestyle, psycho-social resources etc. There is a mutual negative effect between poverty and lack of education that provides skills and information needed for managing the stress situations life brings with itself. Education, employment and incomes increase the capacity of self-control, and that condition strengthen the health in relation to the environment The social support, which is most frequent in persons with higher educational level, promotes health and decreases mortality through physiological mechanisms of the environment. People with higher educational level most likely will look for preventive health care (yearly check-ups for health control, immunization and other preventive examinations) and will probably not abuse alcohol and drugs. Preparation of various programs for applying the health education will contribute in the process of directing the individual to correct behavior that leads towards positive health, opposite the hostile influences of the social environment, which leads to bad quality in health (based on the education)
Discovering Strategic Behaviour of Multi-Agent Systems in Adversary Settings
Can specific behaviour strategies be induced from low-level observations of two adversary groups of agents with limited domain knowledge? This paper presents a domain-independent Multi-Agent Strategy Discovering Algorithm (MASDA), which discovers strategic behaviour patterns of a group of agents under the described conditions. The algorithm represents the observed multi-agent activity as a graph, where graph connections correspond to performed actions and graph nodes correspond to environment states at action starts. Based on such data representation, the algorithm applies hierarchical clustering and rule induction to extract and describe strategic behaviour. The discovered strategic behaviour is represented visually as graph paths and symbolically as rules. MASDA was evaluated on RoboCup. Both soccer experts and quantitative evaluation confirmed the relevance of the discovered behaviour patterns
ΠΠΠ’ΠΠ€ΠΠ ΠΠ’Π ΠΠ ΠΠΠΠΠ§ΠΠΠ’Π ΠΠΠΠ¦ΠΠΠ’Π£ΠΠΠΠΠΠ¦ΠΠΠ ΠΠ ΠΠΠΠ¦ΠΠΠ’Π (Π‘Π ΠΠΠ‘ΠΠΠΠ ΠΠ‘ΠΠ Π’ ΠΠ Π€Π ΠΠΠΠΠΠ’Π Π‘Π ΠΠΠΠ§ΠΠΠ Π‘Π’Π ΠΠ ΠΠ ΠΠΠΠΠΠΠΠ‘ΠΠΠΠ’ Π ΠΠ Π Π£Π‘ΠΠΠΠ’ ΠΠΠΠΠ)
This article illustrates how important role metaphor plays in understanding a phenomenon as complex as the nature of emotion and how the human body influences the conceptualization of emotion. A lot of emotion metaphors are biologically rooted and based on physiologically conditioned responses to various stimuli. Well-known example of such biologically-based linguistic metaphor is fear is cold. The purpose of this article is to make a comparison of the metaphorical models applied on idioms denotiong fear in Macedonin and Russian language following the similar studies made for other Slavic languages
ΠΠ°ΡΡΠ΅ΡΡΠΈ Π±Π°ΠΊΡΠ΅ΡΠΈΡΠΊΠΈ ΠΈΠ·ΠΎΠ»Π°ΡΠΈ ΠΎΠ΄ ΠΏΡΠΈΠΌΠ΅ΡΠΎΡΠΈ ΠΎΠ΄ ΡΠ°Π½ΠΈ β ΡΡΠΈΠ³ΠΎΠ΄ΠΈΡΠ½Π° ΡΡΡΠ΄ΠΈΡΠ°
Aim: The aim of our study was to determine the most common bacteria isolated from wound samples and tΠΎ compare the frequency of the resistant bacteria isolated over a 3-year period. Material and methods: During a three years period (2017-2019) a total of 11 863 wound samples (wound swabs, punctuates, exudates, tissue, etc.) were obtained from the hospitalized patients in the University Clinics of the ,,Mother Theresaβ campus, the City hospital ,,8th Septemberβ and the University Clinic for surgical diseases ,,St. Naum Ohridskiβ in Skopje. All samples were processed at the Institute of Microbiology and Parasitology, Faculty of Medicine, Skopje. They were examined by standard microbiology techniques. Identification and susceptibility of microorganisms were done by both standard methods and automatized Vitek 2 system. Results: Out of a total number of samples, which was 3 463 in 2017, 4 127 in 2018 and 4 273 in 2019, positive were 2 068 (60%), 2 302 (55.8%) and 2 387 (55.9%), respectively. From the total of aerobes/facultative anaerobes (2 758, 2 949 and 3 279 in three consecutive years, 2017, 2018 and 2019, respectively), Staphylococcus aureus was the most predominant isolate (19.5%, 16.6%, 16.9%) followed by Enterococcus spp (16%, 16%, 16.7%), Pseudomonas aeruginosa (12%, 13%, 12.7%) and E. coli (10%, 10.4%, 10.7%). Considering anaerobic bacteria, the percentage of Gram positive anaerobes (Peptostreptococcus) has decreased from 33% to 18% out of a total number of anaerobes, unlike Gram negative anaerobes in which the increasing percentage was mostly observed in bacteria of the genus Bacteroides (from 39% to 45%). The percentage of the resistant strains of MRSA, CNS-MR and VRE was almost the same in that period. In Gram-negatives the percentage of ESBL-positive isolates of E. coli and Enterobacter spp. increased consecutively from 2017 to 2019. The increase in the percentage of resistant strains was more noticeable in ESBL-positive isolates of Klebsiella pneumonia between 2017 and 2018, but in 2019 a percentage decrease can be observed. Considering carbapenem-resistant (CR) Enterobacterales, an increase in the resistance was noticeable in K. pneumonia. The increase in the percentage of resistant strains in Enterobacter spp. between 2017 and 2018, as well as the decrease between 2018 and 2019 was statistically significant. The percentage of CR-isolates of Pseudomonas aeruginosa was from 30% to 38% and for Acinetobacter spp. this percentage was from 81% to 85%. Conclusion: The knowledge of the most commonly isolated bacterial pathogens, especially the presence of resistant bacteria, is crucial and should be continuously monitored in order to understand, construct and update effective treatment algorithms and guidelines.Π¦Π΅Π»: Π¦Π΅Π» Π½Π° ΡΡΡΠ΄ΠΈΡΠ°ΡΠ° Π΅ Π΄Π° ΡΠ΅ Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠ°Π°Ρ Π½Π°ΡΡΠ΅ΡΡΠΈΡΠ΅ Π±Π°ΠΊΡΠ΅ΡΠΈΠΈ ΠΈΠ·ΠΎΠ»ΠΈΡΠ°Π½ΠΈ ΠΎΠ΄ ΠΏΡΠΈΠΌΠ΅ΡΠΎΡΠΈ ΠΎΠ΄ ΡΠ°Π½ΠΈ ΠΈ Π΄Π° ΡΠ΅ ΡΠΏΠΎΡΠ΅Π΄ΠΈ ΠΏΡΠΎΡΠ΅Π½ΡΠΎΡ Π½Π° ΡΠ΅Π·ΠΈΡΡΠ΅Π½ΡΠ½ΠΈ Π±Π°ΠΊΡΠ΅ΡΠΈΠΈ Π²ΠΎ ΡΡΠΈΠ³ΠΎΠ΄ΠΈΡΠ½ΠΈΠΎΡ ΠΏΠ΅ΡΠΈΠΎΠ΄. ΠΠ°ΡΠ΅ΡΠΈΡΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ: ΠΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄ ΠΎΠ΄ ΡΡΠΈ Π³ΠΎΠ΄ΠΈΠ½ΠΈ (2017-2019) Π±Π΅Π° Π·Π΅ΠΌΠ΅Π½ΠΈ Π²ΠΊΡΠΏΠ½ΠΎ 11 863 ΠΏΡΠΈΠΌΠ΅ΡΠΎΡΠΈ ΠΎΠ΄ ΡΠ°Π½ΠΈ (Π±ΡΠΈΡΠ΅Π²ΠΈ, ΠΏΡΠ½ΠΊΡΠ°ΡΠΈ, Π΅ΠΊΡΡΠ΄Π°ΡΠΈ, ΡΠΊΠΈΠ²ΠΎ ΠΈ Π΄Ρ.) ΠΎΠ΄ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈ Ρ
ΠΎΡΠΏΠΈΡΠ°Π»ΠΈΠ·ΠΈΡΠ°Π½ΠΈ Π²ΠΎ Π£Π½ΠΈΠ²Π΅ΡΠ·ΠΈΡΠ΅ΡΡΠΊΠΈΡΠ΅ ΠΊΠ»ΠΈΠ½ΠΈΠΊΠΈ Π²ΠΎ ΠΊΠ°ΠΌΠΏΡΡΠΎΡ ,,ΠΠ°ΡΠΊΠ° Π’Π΅ΡΠ΅Π·Π°β, ΠΡΠ°Π΄ΡΠΊΠ°ΡΠ° Π±ΠΎΠ»Π½ΠΈΡΠ° ,,8. Π‘Π΅ΠΏΡΠ΅ΠΌΠ²ΡΠΈβ Π£Π½ΠΈΠ²Π΅ΡΠ·ΠΈΡΠ΅ΡΡΠΊΠ°ΡΠ° ΠΊΠ»ΠΈΠ½ΠΈΠΊΠ° Π·Π° Ρ
ΠΈΡΡΡΡΠΊΠΈ Π±ΠΎΠ»Π΅ΡΡΠΈ ,,Π‘Π². ΠΠ°ΡΠΌ ΠΡ
ΡΠΈΠ΄ΡΠΊΠΈβ Π²ΠΎ Π‘ΠΊΠΎΠΏΡΠ΅. Π‘ΠΈΡΠ΅ ΠΏΡΠΈΠΌΠ΅ΡΠΎΡΠΈ Π±Π΅Π° ΠΎΠ±ΡΠ°Π±ΠΎΡΠ΅Π½ΠΈ Π½Π° ΠΠ½ΡΡΠΈΡΡΡΠΎΡ Π·Π° ΠΌΠΈΠΊΡΠΎΠ±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ° ΠΈ ΠΏΠ°ΡΠ°Π·ΠΈΡΠΎΠ»ΠΎΠ³ΠΈΡΠ°, ΠΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈ ΡΠ°ΠΊΡΠ»ΡΠ΅Ρ, Π‘ΠΊΠΎΠΏΡΠ΅. ΠΠ° ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠ° Π±Π΅Π° ΠΊΠΎΡΠΈΡΡΠ΅Π½ΠΈ ΡΡΠ°Π½Π΄Π°ΡΠ΄Π½ΠΈ ΠΌΠΈΠΊΡΠΎΠ±ΠΈΠΎΠ»ΠΎΡΠΊΠΈ ΡΠ΅Ρ
Π½ΠΈΠΊΠΈ. ΠΠ΄Π΅Π½ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡΠ°ΡΠ° Π½Π° Π±Π°ΠΊΡΠ΅ΡΠΈΠΈΡΠ΅, ΠΊΠ°ΠΊΠΎ ΠΈ ΠΎΠ΄ΡΠ΅Π΄ΡΠ²Π°ΡΠ΅ Π½Π° Π½ΠΈΠ²Π½Π°ΡΠ° ΠΎΡΠ΅ΡΠ»ΠΈΠ²ΠΎΡΡ ΠΊΠΎΠ½ Π°Π½ΡΠΈΠΌΠΈΠΊΡΠΎΠ±Π½ΠΈ ΡΡΠ΅Π΄ΡΡΠ²Π° Π±Π΅ΡΠ΅ Π½Π°ΠΏΡΠ°Π²Π΅Π½Π° ΡΠΎ ΡΡΠ°Π½Π΄Π°ΡΠ΄Π½ΠΈ ΠΈ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·ΠΈΡΠ°Π½ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ (Vitek 2- ΡΠΈΡΡΠ΅ΠΌ). Π Π΅Π·ΡΠ»ΡΠ°ΡΠΈ: ΠΠ΄ Π²ΠΊΡΠΏΠ½ΠΈΠΎΡ Π±ΡΠΎΡ Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠΎΡΠΈ ΠΊΠΎΡ ΠΈΠ·Π½Π΅ΡΡΠ²Π°ΡΠ΅ 3 463 Π²ΠΎ 2017, 4 127 Π²ΠΎ 2018 ΠΈ 4 273 Π²ΠΎ 2019 Π³ΠΎΠ΄., ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΠΈ Π±Π΅Π° 2 068 (60%), 2 302 (55,8%) ΠΈ 2 387 (55,9%), ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Π½ΠΎ. ΠΠ΄ Π²ΠΊΡΠΏΠ½ΠΈΠΎΡ Π±ΡΠΎΡ Π°Π΅ΡΠΎΠ±ΠΈ/ΡΠ°ΠΊΡΠ»ΡΠ°ΡΠΈΠ²Π½ΠΎ Π°Π½Π°Π΅ΡΠΎΠ±ΠΈ (2 758, 2 949 ΠΈ 3 279 Π²ΠΎ ΡΡΠΈ ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Π½ΠΈ Π³ΠΎΠ΄ΠΈΠ½ΠΈ, 2017, 2018 ΠΈ 2019 Π³ΠΎΠ΄.), Π½Π°ΡΡΠ΅ΡΡΠΎ ΠΈΠ·ΠΎΠ»ΠΈΡΠ°Π½Π° Π±Π΅ΡΠ΅ Π±Π°ΠΊΡΠ΅ΡΠΈΡΠ°ΡΠ° Staphylococcus aureus (19,5%, 16,6% ΠΈ 16,9%), ΠΏΠΎΡΠΎΠ° Enterococcus spp (16%, 16% ΠΈ 16,7%), Pseudomonas aeruginosa (12%, 13% ΠΈ 12,7%) ΠΈ E. coli (10%, 10,4% ΠΈ 10,7%). ΠΠ΄ Π°Π½Π°Π΅ΡΠΎΠ±Π½ΠΈΡΠ΅ Π±Π°ΠΊΡΠ΅ΡΠΈΠΈ, Π±Π΅ΡΠ΅ Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠ°Π½ΠΎ Π½Π°ΠΌΠ°Π»ΡΠ²Π°ΡΠ΅ Π½Π° ΠΏΡΠΎΡΠ΅Π½ΡΠΎΡ Π½Π° ΠΡΠ°ΠΌ-ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΠΈΡΠ΅ Π°Π½Π°Π΅ΡΠΎΠ±ΠΈ (Peptostreptococcus) ΠΎΠ΄ 33% Π½Π° 18%, ΠΎΠ΄ Π²ΠΊΡΠΏΠΈΠΎΡ Π±ΡΠΎΡ Π½Π° Π°Π½Π°Π΅ΡΠΎΠ±ΠΈ, Π·Π° ΡΠ°Π·Π»ΠΈΠΊΠ° ΠΎΠ΄ ΠΡΠ°ΠΌ-Π½Π΅Π³Π°ΡΠΈΠ²Π½ΠΈΡΠ΅ Π°Π½Π°Π΅ΡΠΎΠ±ΠΈ ΠΊΠ°Π΄Π΅ Π±Π΅ΡΠ΅ Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠ°Π½ΠΎ Π·Π³ΠΎΠ»Π΅ΠΌΡΠ²Π°ΡΠ΅ Π½Π° ΡΠΎΡ ΠΏΡΠΎΡΠ΅Π½Ρ, ΠΎΡΠΎΠ±Π΅Π½ΠΎ ΠΊΠ°Ρ Π±Π°ΠΊΡΠ΅ΡΠΈΠΈΡΠ΅ ΠΎΠ΄ ΡΠΎΠ΄ΠΎΡ Bacteroides (ΠΎΠ΄ 39% Π½Π° 45%). ΠΡΠΎΡΠ΅Π½ΡΠΎΡ Π½Π° ΡΠ΅Π·ΠΈΡΡΠ΅Π½ΡΠ½ΠΈ ΡΠΎΠ΅Π²ΠΈ (MRSA, CNS-MR ΠΈ VRE) Π±Π΅ΡΠ΅ ΡΠ΅ΡΠΈΡΠΈ ΠΈΠ΄Π΅Π½ΡΠΈΡΠ΅Π½ Π²ΠΎ ΠΈΡΠΏΠΈΡΡΠ²Π°Π½ΠΈΠΎΡ ΠΏΠ΅ΡΠΈΠΎΠ΄. ΠΠ°Ρ ΠΡΠ°ΠΌ-Π½Π΅Π³Π°ΡΠΈΠ²Π½ΠΈΡΠ΅ Π±Π°ΠΊΡΠ΅ΡΠΈΠΈ, Π±Π΅ΡΠ΅ Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠ°Π½ΠΎ Π·Π³ΠΎΠ»Π΅ΠΌΡΠ²Π°ΡΠ΅ Π½Π° ΠΏΡΠΎΡΠ΅Π½ΡΠΎΡ Π½Π° ESBL-ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΠΈ ΠΈΠ·ΠΎΠ»Π°ΡΠΈ Π½Π° E. coli ΠΈ Enterobacter spp. Π²ΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄ΠΎΡ ΠΎΠ΄ 2017 Π΄ΠΎ 2019, Π° ΠΊΠ°Ρ Klebsiella pneumoniaΠ΅ Π²ΠΎ ΠΏΠ΅ΡΠΈΠΎΠ΄ΠΎΡ ΠΎΠ΄ 2017 ΠΈ 2018 ΠΈΠΌΠ°ΡΠ΅ Π·Π³ΠΎΠ»Π΅ΠΌΡΠ²Π°ΡΠ΅, Π° Π²ΠΎ 2019 Π½Π°ΠΌΠ°Π»ΡΠ²Π°ΡΠ΅ Π½Π° ΡΠΎΡ ΠΏΡΠΎΡΠ΅Π½Ρ. ΠΠΎ ΠΎΠ΄Π½ΠΎΡ Π½Π° ΠΊΠ°ΡΠ±Π°ΠΏΠ΅Π½Π΅ΠΌ-ΡΠ΅Π·ΠΈΡΡΠ΅Π½ΡΠ½ΠΈΡΠ΅ (CR) Π΅Π½ΡΠ΅ΡΠΎΠ±Π°ΠΊΡΠ΅ΡΠΈΠΈ, ΠΊΠ°Ρ Π. pneumoniae Π±Π΅ΡΠ΅ Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠ°Π½ΠΎ Π·Π³ΠΎΠ»Π΅ΠΌΡΠ²Π°ΡΠ΅ Π½Π° ΠΏΡΠΎΡΠ΅Π½ΡΠΎΡ Π½Π° ΡΠ΅Π·ΠΈΡΡΠ΅Π½ΡΠ½ΠΈ ΠΈΠ·ΠΎΠ»Π°ΡΠΈ Π²ΠΎ ΡΠΈΡΠ΅ ΡΡΠΈ Π³ΠΎΠ΄ΠΈΠ½ΠΈ, Π΄ΠΎΠ΄Π΅ΠΊΠ°, ΠΏΠ°ΠΊ, ΠΊΠ°Ρ Enterobacter spp. ΡΠΎΡ ΠΏΡΠΎΡΠ΅Π½ΡΠΎΡ Π±Π΅ΡΠ΅ ΠΏΠΎΠ²ΠΈΡΠΎΠΊ ΠΌΠ΅ΡΡ 2017 ΠΈ 2018, Π° Π²ΠΎ 2019 Π³ΠΎΠ΄. ΡΡΠ°ΡΠΈΡΡΠΈΡΠΊΠΈ Π·Π½Π°ΡΠ°ΡΠ½ΠΎ ΠΏΠΎΠ½ΠΈΠ·ΠΎΠΊ. ΠΡΠΎΡΠ΅Π½ΡΠΎΡ Π½Π° CR- ΠΈΠ·ΠΎΠ»Π°ΡΠΈ Π½Π° Pseudomonas aeruginosa Π±Π΅ΡΠ΅ ΠΏΠΎΠΌΠ΅ΡΡ 30% ΠΈ 38%, Π° Π·Π° Acinetobacter spp. ΠΎΠ²ΠΎΡ ΠΏΡΠΎΡΠ΅Π½Ρ Π±Π΅ΡΠ΅ ΠΌΠ΅ΡΡ 81% ΠΈ 85%. ΠΠ°ΠΊΠ»ΡΡΠΎΠΊ: ΠΠΎΡΡΠ΅Π±Π½ΠΎ Π΅ ΠΊΠΎΠ½ΡΠΈΠ½ΡΠΈΡΠ°Π½ΠΎ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΡΠ°ΡΠ΅ Π½Π° Π½Π°ΡΡΠ΅ΡΡΠΎ ΠΈΠ·ΠΎΠ»ΠΈΡΠ°Π½ΠΈΡΠ΅ Π±Π°ΠΊΡΠ΅ΡΠΈΠΈ ΠΎΠ΄ ΠΏΡΠΈΠΌΠ΅ΡΠΎΡΠΈΡΠ΅ ΠΎΠ΄ ΡΠ°Π½ΠΈ, ΠΎΡΠΎΠ±Π΅Π½ΠΎ ΠΏΡΠΈΡΡΡΡΠ²ΠΎΡΠΎ Π½Π° ΡΠ΅Π·ΠΈΡΡΠ΅Π½ΡΠ½ΠΈ Π±Π°ΠΊΡΠ΅ΡΠΈΠΈ, ΡΠΎ ΡΠ΅Π» ΠΏΡΠΈΠΌΠ΅Π½Π° Π½Π° ΡΠΎΠΎΠ΄Π²Π΅ΡΠ½ΠΈ Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈ ΠΈ Π²ΠΎΠ΄ΠΈΡΠΈ Π·Π° Π΅ΡΠ΅ΠΊΡΠΈΠ²Π΅Π½ ΡΡΠ΅ΡΠΌΠ°Π½ Π½Π° ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈΡΠ΅ Π½Π° ΡΠ°Π½ΠΈ.  
ΠΠ²Π°Π»ΡΠ°ΡΠΈΡΠ° Π½Π° (1,3)--d-Π³Π»ΠΈΠΊΠ°Π½ Π΅ΡΠ΅Ρ Π²ΠΎ Π΄ΠΈΡΠ°Π³Π½ΠΎΠ·Π° Π½Π° ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ ΡΠΎ Πspergillus
Invasive fungal infections caused by Aspergillus are a significant problem in immunocompromised and critically ill patients and associated with increased morbidity and mortality. Early diagnosis of invasive aspergillosis is still a big clinical and diagnostic challenge. Conventional methods are not sensitive enough, and therefore, there is a need for rapid, more sensitive methods for early diagnosis of invasive fungal infections with Aspergillus. The aim of this study was to evaluate the diagnostic performance, sensitivity and specificity of serological panfungal (1,3)-b-D-glucan marker compared to conventional method for diagnosis of invasive fungal infections with Aspergillus. Material and methods: Specimens of 125 patients divided into 4 groups (group I - immune deficiency, group II - prolonged ICU stay, group III - chronic aspergillosis, group IV - cystic fibrosis), classified according to clinical diagnosis and EORTC/MSG criteria, were analyzed at the Institute of Microbiology and Parasitology, with conventional and serological methods, during a period of two years. Results: A total of 71 isolates of Aspergillus were confirmed in this study. Four isolates were recovered from bloodculture of patients with primary immune deficiency. With BAL culture, Aspergillus was detected in the group of chronic aspergillosis (63.33%), followed by the groups of cystic fibrosis (56.67%), primary immune deficiency (51.43%), and the group with prolonged ICU stay (43.33%). Sensitivity and specificity of BAL culture were: 64.29% and 100%, 59.09% and 100%, 54.55% and 12.5%, 100% and 54.17%, in I, II, III and IV group, respectively. In 79.1% (53/67) from positive BAL cultures in all groups, A. fumigatus was confirmed, of which, 32.1% (17/53) in group III, followed by group I β 26.42% (14/53) and group IV β 26.42% (14/53), and 15.1% (8/53) in group II. Other species confirmed in BAL were A. flavus 16.42% (11/67) and A.terreus 4.48% (3/67). Sensitivity and specificity of the serological panfungal (1,3)-b-D-glucan (BDG) marker were: 64.71% and 85.71%, 50% and 87.5%, 36.36% and 50%, in groups I, II and III, respectively. No positive findings of the panfungal (1,3)-b-D-glucan (BDG) marker were found in the group with cystic fibrosis. Conclusion: The results obtained in this study have demonstrated that a positive (1,3)-b-D-glucan assay highlights the value of this test as a diagnostic adjunct in the serodiagnosis of invasive fungal infections with Aspergillus, and along with the results from conventional mycological investigation, helped in reaching a timely antifungal treatment with a favorable clinical outcome.
Β ΠΠ½Π²Π°Π·ΠΈΠ²Π½ΠΈΡΠ΅ ΡΡΠ½Π³Π°Π»Π½ΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ ΡΠΎ Aspergillus ΠΏΡΠ΅ΡΡΡΠ°Π²ΡΠ²Π°Π°Ρ ΡΠ΅ΡΠΈΠΎΠ·Π΅Π½ ΠΏΡΠΎΠ±Π»Π΅ΠΌ ΠΊΠ°Ρ ΠΈΠΌΡΠ½ΠΎΠΊΠΎΠΌΠΏΡΠΎΠΌΠΈΡΠΈΡΠ°Π½ΠΈΡΠ΅ Π»ΠΈΡΠ° ΠΈ ΠΊΡΠΈΡΠΈΡΠ½ΠΎ Π±ΠΎΠ»Π½ΠΈΡΠ΅ Π»ΠΈΡΠ°, ΠΈ ΡΠ΅ Π°ΡΠΎΡΠΈΡΠ°Π½ΠΈ ΡΠΎ Π·Π³ΠΎΠ»Π΅ΠΌΠ΅Π½ ΠΌΠΎΡΠ±ΠΈΠ΄ΠΈΡΠ΅Ρ ΠΈ ΠΌΠΎΡΡΠ°Π»ΠΈΡΠ΅Ρ. Π Π°Π½Π° Π΄ΠΈΡΠ°Π³Π½ΠΎΠ·Π° Π½Π° ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½Π°ΡΠ° Π°ΡΠΏΠ΅ΡΠ³ΠΈΠ»ΠΎΠ·Π° Π΅ ΡΡ ΡΡΡΠ΅ Π³ΠΎΠ»Π΅ΠΌ ΠΊΠ»ΠΈΠ½ΠΈΡΠΊΠΈ ΠΈ Π΄ΠΈΡΠ°Π³Π½ΠΎΡΡΠΈΡΠΊΠΈ ΠΏΡΠ΅Π΄ΠΈΠ·Π²ΠΈΠΊ. ΠΠΎΠ½Π²Π΅Π½ΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈ Π½Π΅ ΡΠ΅ Π΄ΠΎΠ²ΠΎΠ»Π½ΠΎ ΡΠ΅Π½Π·ΠΈΡΠΈΠ²Π½ΠΈ, ΠΈ Π·Π°ΡΠ°Π΄ΠΈ ΡΠΎΠ°, ΡΠ΅ Π½Π°ΠΌΠ΅ΡΠ½ΡΠ²Π° ΠΏΠΎΡΡΠ΅Π±Π° Π·Π° Π±ΡΠ·ΠΈ ΠΈ ΠΏΠΎΡΠ΅Π½Π·ΠΈΡΠΈΠ²Π½ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ Π·Π° ΡΠ°Π½Π° Π΄ΠΈΡΠ°Π³Π½ΠΎΠ·Π° Π½Π° ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΠΈ ΡΡΠ½Π³Π°Π»Π½ΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ ΡΠΎ Aspergillus. Π¦Π΅Π»ΡΠ° Π½Π° ΠΎΠ²Π°Π° ΡΡΡΠ΄ΠΈΡΠ° Π±Π΅ΡΠ΅ Π΄Π° ΡΠ΅ Π΅Π²Π°Π»ΡΠΈΡΠ° Π΄ΠΈΡΠ°Π³Π½ΠΎΡΡΠΈΡΠΊΠΈΠΎΡ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½Ρ, ΡΠ΅Π½Π·ΠΈΡΠΈΠ²Π½ΠΎΡΡΠ° ΠΈ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΠ° Π½Π° ΡΠ΅ΡΠΎΠ»ΠΎΡΠΊΠΈΠΎΡ ΠΏΠ°Π½ΡΡΠ½Π³Π°Π»Π΅Π½ ΠΌΠ°ΡΠΊΠ΅Ρ (1,3)-b-D-Π³Π»ΠΈΠΊΠ°Π½ ΡΠΏΠΎΡΠ΅Π΄Π΅Π½ΠΎ ΡΠΎ ΠΊΠΎΠ½Π²Π΅Π½ΡΠΈΠΎΠ½Π°Π»Π½ΠΈΠΎΡ ΠΌΠ΅ΡΠΎΠ΄ Π·Π° Π΄ΠΈΡΠ°Π³Π½ΠΎΠ·Π° Π½Π° ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΠΈΡΠ΅ ΡΡΠ½Π³Π°Π»Π½ΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ ΡΠΎ Aspergillus. ΠΠ°ΡΠ΅ΡΠΈΡΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ: ΠΡΠΈΠΌΠ΅ΡΠΎΡΠΈ ΠΎΠ΄ 125 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈ, ΠΏΠΎΠ΄Π΅Π»Π΅Π½ΠΈ Π²ΠΎ 4 Π³ΡΡΠΏΠΈ (Π³ΡΡΠΏΠ° I - ΠΈΠΌΡΠ½ Π΄Π΅ΡΠΈΡΠΈΡ, Π³ΡΡΠΏΠ° II - ΠΏΡΠΎΠ»ΠΎΠ½Π³ΠΈΡΠ°Π½ ΠΏΡΠ΅ΡΡΠΎΡ Π²ΠΎ ΠΠΠ, Π³ΡΡΠΏΠ° III - Ρ
ΡΠΎΠ½ΠΈΡΠ½Π° Π°ΡΠΏΠ΅ΡΠ³ΠΈΠ»ΠΎΠ·Π°, Π³ΡΡΠΏΠ° IV - ΡΠΈΡΡΠΈΡΠ½Π° ΡΠΈΠ±ΡΠΎΠ·Π°), ΠΈ ΠΊΠ»Π°ΡΠΈΡΠΈΡΠΈΡΠ°Π½ΠΈ ΡΠΏΠΎΡΠ΅Π΄ ΠΊΠ»ΠΈΠ½ΠΈΡΠΊΠ°ΡΠ° Π΄ΠΈΡΠ°Π³Π½ΠΎΠ·Π° ΠΈ EORTC/MSG ΠΊΡΠΈΡΠ΅ΡΠΈΡΠΌΠΈΡΠ΅, Π±Π΅Π° Π°Π½Π°Π»ΠΈΠ·ΠΈΡΠ°Π½ΠΈ Π½Π° ΠΠ½ΡΡΠΈΡΡΡΠΎΡ Π·Π° ΠΌΠΈΠΊΡΠΎΠ±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ° ΠΈ ΠΏΠ°ΡΠ°Π·ΠΈΡΠΎΠ»ΠΎΠ³ΠΈΡΠ°, ΡΠΎ ΠΊΠΎΠ½Π²Π΅Π½ΡΠΈΠΎΠ½Π°Π»Π½ΠΈ ΠΈ ΡΠ΅ΡΠΎΠ»ΠΎΡΠΊΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ, Π²ΠΎ ΡΠ΅ΠΊ Π½Π° Π΄Π²Π΅-Π³ΠΎΠ΄ΠΈΡΠ΅Π½ ΠΏΠ΅ΡΠΈΠΎΠ΄. Π Π΅Π·ΡΠ»ΡΠ°ΡΠΈ: ΠΠΊΡΠΏΠ½ΠΎ 71 ΠΈΠ·ΠΎΠ»Π°Ρ Π½Π° Aspergillus Π±Π΅Π° ΠΏΠΎΡΠ²ΡΠ΄Π΅Π½ΠΈ Π²ΠΎ ΠΎΠ²Π°Π° ΡΡΡΠ΄ΠΈΡΠ°. Π§Π΅ΡΠΈΡΠΈ ΠΈΠ·ΠΎΠ»Π°ΡΠΈ Π±Π΅Π° Π΄ΠΎΠΊΠ°ΠΆΠ°Π½ΠΈ Π²ΠΎ Ρ
Π΅ΠΌΠΎΠΊΡΠ»ΡΡΡΠ°, ΠΊΠ°Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΈ ΡΠΎ ΠΏΡΠΈΠΌΠ°ΡΠ΅Π½ ΠΈΠΌΡΠ½ Π΄Π΅ΡΠΈΡΠΈΡ. Π‘ΠΎ ΠΊΡΠ»ΡΡΡΠ° Π½Π° ΠΠΠ, Aspergillus Π½Π°ΡΡΠ΅ΡΡΠΎ Π±Π΅ΡΠ΅ Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠ°Π½ Π²ΠΎ Π³ΡΡΠΏΠ°ΡΠ° Π½Π° Ρ
ΡΠΎΠ½ΠΈΡΠ½Π° Π°ΡΠΏΠ΅ΡΠ³ΠΈΠ»ΠΎΠ·Π° (63,33%), ΠΏΠΎ ΡΡΠΎ ΡΠ»Π΅Π΄ΡΠ²Π°Π° Π³ΡΡΠΏΠΈΡΠ΅ ΡΠΎ ΡΠΈΡΡΠΈΡΠ½Π° ΡΠΈΠ±ΡΠΎΠ·Π° (56,67%), ΠΏΡΠΈΠΌΠ°ΡΠ΅Π½ ΠΈΠΌΡΠ½ Π΄Π΅ΡΠΈΡΠΈΡ (51,43%), ΠΈ Π³ΡΡΠΏΠ°ΡΠ° Π»ΠΈΡΠ° ΡΠΎ ΠΏΡΠΎΠ»ΠΎΠ½Π³ΠΈΡΠ°Π½ ΠΏΡΠ΅ΡΡΠΎΡ Π²ΠΎ Π΅Π΄ΠΈΠ½ΠΈΡΠΈΡΠ΅ Π·Π° ΠΈΠ½ΡΠ΅Π½Π·ΠΈΠ²Π½ΠΎ Π»Π΅ΠΊΡΠ²Π°ΡΠ΅ (43,33%). Π‘Π΅Π½Π·ΠΈΡΠΈΠ²Π½ΠΎΡΡΠ° ΠΈ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΠ° Π½Π° ΠΊΡΠ»ΡΡΡΠΈΡΠ΅ Π½Π° ΠΠΠ Π±Π΅Π°: 64,29% ΠΈ 100%, 59,09% ΠΈ 100%, 54,55% ΠΈ 12,5%, 100% ΠΈ 54,17%, Π²ΠΎ I, II, III ΠΈ IV Π³ΡΡΠΏΠ°, ΡΠΎΠΎΠ΄Π²Π΅ΡΠ½ΠΎ. ΠΠΎ 79,1% (53/67) ΠΎΠ΄ ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΠΈΡΠ΅ ΠΊΡΠ»ΡΡΡΠΈ Π½Π° ΠΠΠ Π²ΠΎ ΡΠΈΡΠ΅ Π³ΡΡΠΏΠΈ, Π±Π΅ΡΠ΅ Π΄ΠΎΠΊΠ°ΠΆΠ°Π½ A.fumigatus, ΠΎΠ΄ ΠΊΠΎΠΈ, 32,1% (17/53) ΠΎΠ΄ Π³ΡΡΠΏΠ° III, ΠΏΠΎΡΠΎΠ° 26,42 % (14/53) ΠΎΠ΄ Π³ΡΡΠΏΠ° I ΠΈ 26,42% (14/53) ΠΎΠ΄ Π³ΡΡΠΏΠ° IV, ΠΊΠ°ΠΊΠΎ ΠΈ 15,1% (8/53) ΠΎΠ΄ Π³ΡΡΠΏΠ° II. ΠΡΡΠ³ΠΈ ΡΠΏΠ΅ΡΠΈΠ΅ΡΠΈ ΠΏΠΎΡΠ²ΡΠ΄Π΅Π½ΠΈ Π²ΠΎ ΠΠΠ Π±Π΅Π° A.flavus 16,42% (11/67) ΠΈ A.terreus 4,48% (3/67). Π‘Π΅Π½Π·ΠΈΡΠΈΠ²Π½ΠΎΡΡΠ° ΠΈ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΠ° Π½Π° ΡΠ΅ΡΠΎΠ»ΠΎΡΠΊΠΈΠΎΡ ΠΏΠ°Π½ΡΡΠ½Π³Π°Π»Π΅Π½ (1,3)-b-D-Π³Π»ΠΈΠΊΠ°Π½ (BDG) ΠΌΠ°ΡΠΊΠ΅Ρ Π±Π΅Π°: 64,71% ΠΈ 85,71%, 50% ΠΈ 87,5%, 36,36% ΠΈ 50%, Π²ΠΎ Π³ΡΡΠΏΠΈΡΠ΅ I, II ΠΈ III, ΡΠΎΠΎΠ΄Π²Π΅ΡΠ½ΠΎ. ΠΠ΅ Π±Π΅Π° Π΄Π΅ΡΠ΅ΠΊΡΠΈΡΠ°Π½ΠΈ ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΠΈ Π½Π°ΠΎΠ΄ΠΈ ΠΎΠ΄ ΠΏΠ°Π½ΡΡΠ½Π³Π°Π»Π½ΠΈΠΎΡ (1,3)-b-D-Π³Π»ΠΈΠΊΠ°Π½ (BDG) ΠΌΠ°ΡΠΊΠ΅Ρ Π²ΠΎ Π³ΡΡΠΏΠ°ΡΠ° ΡΠΎ ΡΠΈΡΡΠΈΡΠ½Π° ΡΠΈΠ±ΡΠΎΠ·Π°. ΠΠ°ΠΊΠ»ΡΡΠΎΠΊ: Π Π΅Π·ΡΠ»ΡΠ°ΡΠΈΡΠ΅ ΠΎΠ΄ ΠΎΠ²Π°Π° ΡΡΡΠ΄ΠΈΡΠ° ΠΏΠΎΠΊΠ°ΠΆΠ°Π° Π΄Π΅ΠΊΠ° ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π΅Π½ Π½Π°ΠΎΠ΄ Π½Π° (1,3)-b-D-Π³Π»ΠΈΠΊΠ°Π½ ΡΠ° ΠΈΡΡΠ°ΠΊΠ½ΡΠ²Π° Π²ΡΠ΅Π΄Π½ΠΎΡΡΠ° Π½Π° ΠΎΠ²ΠΎΡ ΡΠ΅ΡΡ ΠΊΠ°ΠΊΠΎ Π΄ΠΈΡΠ°Π³Π½ΠΎΡΡΠΈΡΠΊΠΎ Π½Π°Π΄ΠΎΠΏΠΎΠ»Π½ΡΠ²Π°ΡΠ΅ Π²ΠΎ ΡΠ΅ΡΠΎΠ΄ΠΈΡΠ°Π³Π½ΠΎΠ·Π°ΡΠ° Π½Π° ΠΈΠ½Π²Π°Π·ΠΈΠ²Π½ΠΈΡΠ΅ ΡΡΠ½Π³Π°Π»Π½ΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ ΡΠΎ Aspergillus, ΠΈ Π·Π°Π΅Π΄Π½ΠΎ ΡΠΎ ΡΠ΅Π·ΡΠ»ΡΠ°ΡΠΈΡΠ΅ ΠΎΠ΄ ΠΊΠΎΠ½Π²Π΅Π½ΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡΠ΅ ΠΌΠΈΠΊΠΎΠ»ΠΎΡΠΊΠΈ ΠΈΡΠΏΠΈΡΡΠ²Π°ΡΠ°, ΠΏΠΎΠΌΠ°Π³Π°Π°Ρ Π²ΠΎ Π½Π°Π²ΡΠ΅ΠΌΠ΅Π½Π° ΠΏΡΠΈΠΌΠ΅Π½Π° Π½Π° Π°Π½ΡΠΈΡΡΠ½Π³Π°Π»Π½Π° ΡΠ΅ΡΠ°ΠΏΠΈΡΠ°, ΠΈ ΠΏΠΎΡΡΠΈΠ³Π½ΡΠ²Π°ΡΠ΅ ΠΏΠΎΠ²ΠΎΠ»Π΅Π½ ΠΊΠ»ΠΈΠ½ΠΈΡΠΊΠΈ ΠΈΡΡ
ΠΎΠ΄.
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