West Azerbaijan Research Articles

Molecular examination for Coxiella burnetii and Brucella spp. infections in Iranian women experiencing spontaneous miscarriage

BackgroundSpontaneous miscarriage, a leading health concern globally, often occurs due to various factors, including infections. Among these, Coxiella burnetii and Brucella spp. may have adverse effects on pregnancy outcomes. While previous research has established a link between infections and spontaneous miscarriage, our study aimed specifically to investigate the presence of these two pathogens in abortion samples from women who experienced spontaneous miscarriages in Iran. Our study can add to the existing knowledge by focusing on Iran, a region with a high prevalence of C. burnetii and Brucella spp. As a result, it could provide a better understanding and unique insights into the relationship of these pathogens with spontaneous miscarriages in endemic regions.MethodsFrom March 2021 to March 2022, a total of 728 abortion samples (including placenta and cotyledon) were collected from 409 women who had experienced spontaneous miscarriages in the provinces of Tehran, Fars, and West Azerbaijan in Iran. The specimens included 467 Formalin-Fixed Paraffin-Embedded (FFPE) and 261 fresh frozen samples. After DNA extraction from abortion samples, the quantitative real-time PCR (qPCR) assay targeted a specific fragment of the IS1111 and IS711 elements for molecular identification of C. burnetii and Brucella spp., respectively. Furthermore, the qPCR assay employing specific primers for different species was used to determine the species of Brucella.ResultsAmong the studied women, 1 out of 409 (0.24%) samples tested positive for Brucella spp., specifically Brucella melitensis. There were no positive specimens for C. burnetii.ConclusionsOur study contributes to understanding the potential involvement of Brucella species in spontaneous infectious abortion within endemic regions. The identification of B. melitensis in this study highlights the need for further research in this area. However, while our results suggest a relatively low or zero identification of these pathogens in our sample population, this does not rule out the possibility of undetected infections. Therefore, it is critical to acknowledge the limitations of the molecular techniques used (qPCR), which may have potential limitations such as sensitivity and specificity. Moreover, because 64.15% of our samples were FFPE, the sensitivity of the qPCR test may be reduced. These raise concerns about the accuracy of the reported prevalence rates and the potential for false positives or negatives.

Using Machine Learning Algorithms in Determining the Stage of Breast Cancer from Pathology Reports

Introduction: After a cancer diagnosis, the most important thing is to determine the stage and grade of the cancer. Pathology reports are the main source for cancer staging, but they do not contain all the information needed for the staging. However, the text of these reports is sometimes the only available information. We were interested in knowing whether text mining methods can be used to predict staging only from pathology reports.Material and Methods: A total of 698 pathology reports of breast cancer cases and their TNM staging collected from multiple centers in West Azerbaijan Province, Iran were used for this study. After preparing the semi-structured reports, the texts of the reports were imported into a program written by Python V3. Three machine learning algorithms of Logistic Regression, SVM, and Naïve Bayes and a simple pipeline were used for the purpose of text mining. The performance of the algorithms was evaluated in terms of accuracy, precision, recall, and F1 score.Results: The Naïve Bayes algorithm achieved excellent results and a value rate of higher than 91% in all evaluation criteria (accuracy, precision, recall and F1 score). This means that the Naïve Bayes algorithm could classify the reports with high efficiency and its predictions were more correct than the other two algorithms. Naïve Bayes also outperformed SVM and Logistic Regression in terms of accuracy, recall and F1 score. In addition, Naïve-Bayes showed faster inference due to its simplicity and lower computational and training time.Conclusion: We suggest using the proposed design in this study for predicting breast cancer staging, where there is a need but not all necessary information except pathology reports. This method may not be a useful for clinical management of cancer patients, but it can be safely used for epidemiological estimations.

The effect of educational intervention on efficacy of 1% permethrin shampoo and 4% dimeticone lotion to treat head lice infestation using propensity score matching (PSM)

BackgroundHead lice are a main public health problem and the most important human ectoparasites and the use of pediculicides is the most common way to control it. One of the possible causes of treatment failure is the lack of improper application of pediculicide. The aim of this study was to assess the effect of education on efficacy of 1% permethrin or 4% dimeticone lotion to treat head lice infestation.MethodsThis quasi-experimental study included 100 individuals with head lice infestation from comprehensive urban health centers in Ardabil as the intervention group, and 400 individuals from East Azerbaijan and West Azerbaijan provinces as the control group, from April to March 2019. The data collection tools included a demographic questionnaire and an examination recording sheet, which documented the presence of adult lice or nits. Due to the inability to perform random assignment and control for numerous observed covariates, propensity score matching (PSM) was used.ResultsThe outcome of treatment included elimination of head lice infestation on is 7, and in the case of recurrence, it was considered on days 14 and 30 after treatment. The results showed that the educational intervention program had a significant positive effect on the efficacy of both treatments. The likelihood of improvement was approximately three times greater in the intervention group compared to the control group.ConclusionParticipants who received the training intervention (OR = 3.29; CI 95%: 2.21–4.88) were more likely to have a successful treatment than control group. In the case of providing proper training on the use of pediculicides and observing hygiene tips to patients with pediculosis, could help to successful treatment of pediculosis.

Socio-demographic Determinants of Infertility: A Study in Four Selected Provinces of Iran

Objectives: Infertility is one of the reproductive health issues that not only affects infertile couple’s life, but it is a matter of demographic concerns on a vast scale. This study aims to examine the impact of socio-demographic factors on the incidence of infertility. Materials and Methods: We used data from our cross-sectional fertility survey conducted in 2017 in four selected provinces of Iran including Gilan, West Azarbaijan, Sistan and Baluchistan, and Yazd. Using a structured questionnaire, 4088 women of reproductive age were interviewed in the survey for their reproductive life history as well as their socio-demographic and economic condition. Bivariate (chi-square test), and multivariate (Multiple Logistic Regression) analyses are applied to the data to meet the aim of the study. P values less than 0.05 are considered statistically significant where differentials are tested. Results: The prevalence of current infertility according to clinical definition varied from 7.4% in Yazd, 8.6% in West Azerbaijan, 12.4% in Gilan, and 22.3% in Sistan and Baluchistan. Logistic regression analysis revealed a significant association between infertility and the age and age at marriage of women. Controlling for other socio-demographic variables probability of being infertile increases as women get married at an older age. In addition, women who lived in a household with the lowest socio-economic conditions were 80 percent more likely to experience infertility compared to those living in households with the highest socio-economic conditions. Living in Sistan and Baluchistan was also a strong predictor of infertility in the study resulting in a high odds ratio (3.050) compared with women living in Yazd province Conclusions: Women’s age and age at marriage are the most important demographic characteristics in explaining infertility and having a lower socio-economic condition trigger it. Since the age of marriage is increasing in Iran, it may affect primary infertility where childbearing is postponed to the late 30s and early 40s.

Predicting Cyanide Degradability and Destruction Using Artificial Neural Networks: A Case Study in West Azerbaijan, Iran”

ABSTRACT The presence of cyanide compounds in soil can lead to the formation and evaporation of hydrogen cyanide (HCN), while some of these compounds can undergo conversion by microorganisms present in the soil. However, high concentrations of cyanide can be toxic to soil microorganisms. During the gold extraction of mines, sodium cyanide (NaCN) solution is commonly used which results in a significant amount of cyanide waste that is regarded as an environmental pollutant. Previous studies have proposed physical, chemical, and biological methods to eliminate cyanide, but they have not achieved optimal efficiency. Unfortunately, the potential of artificial intelligence (AI) in this domain has been overlooked. Artificial Neural Network (ANN) models, specifically the multilayer perceptron (MLP) and simple linear regression, can significantly enhance and expedite the cyanide remediation process due to their remarkable predictive capabilities. In this study, an MLP and simple linear regression were employed to predict the biodegradation procedures of cyanide in soil. The study focused on cyanide waste generated by gold extraction factories and utilized environmental factors such as initial waste cyanide concentration, pH, soil and environmental temperature, humidity, chloride concentration, alkaline, electrical conductivity, precipitation, evaporation intensity, cyanide concentration, and initial pH as input data for the artificial neural network. The results of the MLP model revealed that electrical conductivity is the most influential factor in predicting the cyanide rate and initial pH of the waste soil. Conversely, the results of the simple linear regression indicated that the variables with the greatest impact on cyanide concentration are electrical conductivity (0.881), time (0.862), and alkalinity (0.724). By leveraging AI techniques such as ANN, this study demonstrates the potential for improved cyanide remediation. The integration of environmental factors and predictive models can contribute to more effective strategies for addressing cyanide pollution in soil.

Molecular detection and phylogenetic analysis of Borrelia spp. from sheep and goats blood samples in West Azerbaijan province, Iran.

Borrelia species are spirochetes transmitted by ticks that are important in human and animals. In most countries, there is still no molecular epidemiology of borreliosis in ruminants. This study was aimed to evaluate the existence of Borrelia spp. DNA in the blood samples of small ruminants using polymerase chain reaction (PCR) method in West Azerbaijan Province, Iran. To detect Borrelia spp. DNA, about 1,018 ruminants (456 goats and 562 sheep) blood samples were examined from different bioclimatic regions in West Azerbaijan province, Iran. The DNA extracting and PCR were conducted. In sheep, the following prevalence rates were respectively obtained for the 16S rRNA, 5S - 23S rRNA and ospA genes: 3.55% (20/562), 2.13% (12/562) and 0.88% (5/562). And so, the prevalence rates of the genes in goats were 0.87% (4/456) for 5S - 23S rRNA gene, 1.75% (8/456) for 16S rRNA gene and 0.65% (3/456) for ospA gene. The prevalence of Borrelia spp. was significantly different in small ruminants based on the farms and localities. The sheep and goats in humid areas (north of West Azerbaijan) were infected statistically more than those in sub-humid areas (south of West Azerbaijan). It is demonstrated that host species like sheep and goats may have a key role in natural Lyme disease cycles and other borreliosis diseases in Iran.

Designing an Agile Marketing Model for Small and Medium-sized Enterprises in Iran (Case Study: SMEs in the Northwest Regions of Iran)

Objective: The aim of this research was to design and propose an agile marketing model for small and medium-sized enterprises (SMEs) in Iran using a grounded theory approach. The study investigated the factors influencing the implementation of agile marketing, its enablers, barriers, and outcomes in SMEs located in the northwest regions of Iran. Methodology: This study employed a mixed-method approach (qualitative and quantitative). In the qualitative phase, theoretical sampling was conducted until theoretical saturation was reached through 21 semi-structured interviews, and the data were analyzed using the grounded theory method. In the quantitative phase, field data were collected via questionnaires from 406 SMEs in the provinces of East Azerbaijan, West Azerbaijan, Ardabil, and Zanjan, and the data were analyzed using statistical methods. Findings: The findings revealed that agile marketing improves the skills of specialized employees, enhances customer-centricity, and increases the competitiveness of SMEs. Furthermore, the role of digital technologies and data analytics as facilitators in the successful implementation of this approach was confirmed. Barriers such as organizational resistance and the complexity of the business environment were also identified as factors hindering agile marketing implementation. Conclusion: The study demonstrated that agile marketing can significantly enhance the performance and competitiveness of SMEs in turbulent markets. However, successful implementation requires appropriate infrastructure, digital technologies, and cultural changes within the organization. Agile marketing is proposed as an effective strategy for improving marketing and market management capabilities in SMEs.

Designing a Model for National Banks’ Support to Foster Entrepreneurial Behavior in Small and Medium-Sized Enterprises

Small and medium-sized enterprises (SMEs) are considered the main drivers of economic development, and financial and technical support for them can have significant impacts on overall economic flows. Banks, as the primary arm for financing and credit provision to businesses, play an indispensable role in this regard. Thus, the primary objective of this study is twofold: first, to propose a model for national banks’ support aimed at fostering entrepreneurial behavior in SMEs, and second, to examine the significance and prioritization of key factors influencing banks' supportive role in developing entrepreneurial behavior in SMEs. To achieve this, the study utilized expert opinions from a panel of seven specialists in economics and banking from West Azerbaijan province for the qualitative section, and 464 managers from banks (specifically Sepah Bank) and SMEs in the province for the quantitative section. Data collection tools included semi-structured interviews for the qualitative phase and a researcher-made questionnaire for the quantitative phase. For data analysis and identifying influencing factors regarding banks' support for the development of entrepreneurial behavior in SMEs, thematic analysis and MAXQDA software were employed. Additionally, quantitative data analysis was conducted using structural equation modeling and AMOS software. The qualitative findings revealed that a total of 82 primary themes, organized into 14 organizing themes, can be identified in the context of banks' role in supporting the development of entrepreneurial behavior in SMEs. In the quantitative section, the significance and prioritization of causal, intervening, and contextual factors were examined. The results also demonstrated how the entrepreneurial behaviors of SMEs can either advance or stagnate based on banks' behaviors.

Designing a Capacity-Building Organizational Model with a Grounded Theory Approach (Case Study: Municipalities of West Azerbaijan Province)

Objective: The purpose of this research is to design a capacity-building organizational model in the municipalities of West Azerbaijan Province. Methodology: This study was conducted using a qualitative research strategy, employing grounded theory and the Strauss and Corbin paradigm model, aiming to provide a comprehensive model for capacity building in municipal organizations. In this regard, semi-structured interviews were conducted using theoretical sampling until theoretical saturation was achieved. In this study, data reached theoretical saturation after conducting 11 interviews. However, to ensure sufficiency, five additional interviews were conducted. Participants in the study were selected from university professors and individuals with management experience in municipal organizations. Data were collected during April to July 2022, with the permission of the participants recorded. The data were then transcribed and, after several readings, analyzed using MAXQDA10 software. After performing the three stages of open, axial, and selective coding, the final model was obtained by the researcher. Findings: The findings include the capacity-building organization as the central category, causal conditions (capacity-building manager and structure), contextual factors (capacity-building employees), intervening conditions (capacity-building culture), strategies (capacity-building policy), and consequences (outcomes for the organization, individual, and group) within the framework of the paradigm model. Conclusion: Each of these conditions and factors are composed of variables and categories that contribute to achieving the ultimate goal of the capacity-building organization in the municipalities.

Screening of vancomycin resistance-associated genes in methicillin-resistant Staphylococcus aureus isolates from cattle, sheep and goats in northwestern Iran.

Staphylococcus aureus is an important pathogen causing a wide range of diseases in both humans and animals. The aim of this research was to screen the vancomycin resistance-associated genes in methicillin-resistant Staphylococcus aureus (MRSA) isolates from animals. A total of 400 nasal swab samples were collected from cattle, goats and sheep between February and August 2022 from both industrial and traditional livestock farms in West Azerbaijan province, Iran. Then, nasal swabs were cultured on mannitol salt agar and molecular analysis was performed after bacteriological examination to confirm the presence of S. aureus. The MecA gene was used to detect MRSA isolates, and two important vancomycin resistance-associated genes, namely vanA and vanB, were searched in the isolates. Out of 400 nasal swabs, 69 samples had S. aureus; of which seven isolates were resistant against methicillin. No vancomycin resistance-associated genes were detected in the MRSA isolates. Based on these findings, vancomycin could be used to treat infections caused by this bacterium.

Do trade barriers have the same effect on SMEs in a country under sanctions? The case study of Iran

PurposeThis paper aims to investigate the difference between the impacts of indicators of trade barriers (TBs) on bankrupt enterprises (BEs), new enterprises (NEs) and other enterprises (OEs).Design/methodology/approachThe paper has used a multiple-step approach. At the first stage, the initial data has been collected from interviews with 164 top managers of SMEs in West Azerbaijan in Iran during two periods of 2013–2015 and 2017–2019. At the second step, multiple correspondence analysis has been used to summarize the relationships between variables and construct indices for different groups of TBs. Finally, the generalized structural equation model method was used to examine the impact of export barriers.FindingsThe results showed that the political legal index is the main TBs for BEs and NEs, but it had a more significant impact on BEs; the financial index was the second major TBs factor for BEs, while OEs did not have a problem in performance index, and the financial index was classified as a minor obstacle for them. All indicators of marketing barriers (except production index) had a negative and significant effect on all enterprises; the most important TBs for NEs was the information index.Originality/valueThe results indicated that if enterprises have a strong financial system and function, they can lessen the impact of sanctions and keep themselves in the market.

First molecular detection of Francisella tularensis in turtle (Testudo graeca) and ticks (Hyalomma aegyptium) in Northwest of Iran

Francisella tularensis, causative agent of tularemia, is a contagious zoonotic ailment. This study was aimed to molecularly detect F. tularensis in tortoise blood (n = 100) and ticks (n = 100) collected in the West Azerbaijan province, Iran suing a 16SrRNA gene of the Francisella genus through employment of the Nested-PCR technique. The identified ticks were s Hyalomma aegyptium by morphological analysis. Seven percent (with a 95% CI: 3.5%–13.75%) of animal blood samples yielded positive results for the presence of the Francisella. Meanwhile, the Francisella was identified in tick samples at a rate of fifteen percent (15%) (with a 95% CI: 9%–23%). The samples containing positive results were specifically classified as F. tularensis subsp. holarctica. The samples were taken from ticks belonging to the H. aegyptium species that were gathered in Oshnavieh, southern part of West Azerbaijan province, Iran. This research was aimed to validate the existence of F. tularensis in ticks found within the West Azerbaijan province. Consequently, it is vital to acknowledge the potential of these ticks to transmit the bacteria to both livestock and humans through tick bites in this specific area.

Typhoid and Non-Typhoid Salmonellosis Related Mortality in Iran, National Data from the Ministry of Health.

Despite the declining trend, salmonellosis is still an important preventable cause of death in Iran and the world, especially in certain age and occupational subgroups, and the need for preventive measures, especially raising awareness of at-risk groups, is necessary. Data were obtained from the Ministry of Health covering the years 2013 to 2019. The data were then stratified by year, season, month, and province of death as well as sex, age group, belonging to rural vs. urban communities and cause of death and were then analyzed using SPSS to report differences in age, sex, seasonal patterns, and spatial distribution. Non-typhoid salmonellosis (NTS) and typhoid were recorded as the cause of 800 and 32 deaths, respectively, with the highest number in 2015 and 2013. Septicemia was the cause of 87.3% of deaths due to NTS, whereas typhoid was the cause of 62.5% of its respective cases. The highest percentage of death related to both occurred in spring (P<0.001). NTS mortality rates were higher in the 70-80 and 80-90 age groups, while typhoid mortality was greatest in the under 10 yr age group. NTS mortality was higher in urban while typhoid mortality was higher in rural areas (P<0.001). Most deaths occurred in Ardabil, Sistan and Baluchistan and Khorasan Razavi provinces and Sistan and Baluchistan, West Azerbaijan and Khorasan Razavi related to NTS and typhoid, respectively. Salmonella remains a preventable cause of death, especially among the elderly and children, the data gathered in this study provides important information for priority setting in specific subpopulations and food safety policy.

Integration of fruit fly and firefly optimization algorithm with support vector regression in estimating daily pan evaporation.

The purpose of the present study was to predict the pan evaporation values at four stations including Urmia, Makou, Mahabad, and Khoy, located in West Azerbaijan, Iran, using support vector regression (SVR), SVR coupled by fruit fly algorithm (SVR-FOA), and SVR coupled with firefly algorithm (SVR-FFA). Therefore, for the first time, this research has used the combined SVR-FOA to predict pan evaporation. For this purpose, meteorological parameters in the period of 1990-2020 were gathered and then using the Pearson's correlation coefficient, significant inputs for pan evaporation estimation were determined. The correlation evaluation of the parameters showed that the two parameters of wind speed and sunshine hours had the highest correlation with the pan evaporation values, and in addition, these parameters, as input to the models, improved the results and increased the accuracy of the models. The obtained results indicated that at Urmia station, SVR-FFA with the lowest error was the best model. The SVR-FOA also had better performance than the SVR model. Additionally, the result showed that SVR-FOA with the lowest errors had the best capability in pan evaporation estimation at other studied stations. Therefore, it was concluded that FOA with advantages such as simplicity, fewer parameters, easy adjustment, and less calculation can significantly increase the capability of independent SVR models. Hence, based on the overall results, SVR-FOA may be recommended as the most accurate method for pan evaporation estimation.

Saljuq Architecture in Iran: The Friday Mosque of Urmiya

Abstract This study details the Masjid-i Jami‘ of Urmiya, the earliest surviving mosque in the West Azerbaijan province in Iran. The building suggests the expansion of constructing Saljuq-domed mosques outside central Iran in the mid-sixth/twelfth century, embellished with a stunning Ilkhanid mihrāb (prayer niche) in the seventh/thirteenth century. This study provides as much information as possible for recognizing the structure's main features. While the mosque is comprised of various parts, this paper mainly focuses on its dome chamber as the earliest surviving structure. Several new inscriptions and drawings in the mosque's decoration are published for the first time in this article.

Environmental pollution status and health risk assessment of selective heavy metal(oid)s in Iran's agricultural soils: A review

The assessment of heavy metal(oid) concentrations in agricultural soil holds significant importance due to its impact on crop safety and quality, as well as the potential risks it poses to human health. This review utilized secondary online published data to evaluate the contamination levels of seven HMs (As, Cd, Cu, Cr, Ni, Pb, and Zn) in Iranian farmland soils. As a result, 31 research papers were collected to compile a dataset offering a comprehensive analysis of HM concentrations, distribution, sources, ecological risks, and potential health risks. The findings indicated that mean concentrations of Ni and Cd exceeded their corresponding permissible levels in farmland soils, while other HMs remained below this threshold. The mean Igeo (geoaccumulation index) values followed the sequence Ni > As > Cu > Cr > Zn > Pb > Cd, with Igeo values suggesting low to slight enrichment for the studied HMs. Pollution index (PI) results revealed notable contamination of As in various provinces, including Kurdistan, Hamedan, Tehran, Mazandaran, West Azerbaijan, Kermanshah, Hormozgan, Golestan, and the Kamfiruz region of Fars. Elevated contamination of Pb and Cd was observed in Fars (Shiraz region), and Cr and Ni in the Sabzevar area farmland soils. As, Cd, and Cu exhibited higher ecological risks (EI) compared to Zn, Cr, Ni, and Pb. The potential ecological risks (PER) ranged from 9.9 to 244.6, indicating low to moderate risk levels. Non-carcinogenic assessments indicated that ingestion was the primary exposure pathway to HMs in Iranian farmland soils, followed by inhalation and dermal contact. Total hazard index (HI) values for studied HMs did not exceed 1, indicating no significant non-carcinogenic risk for both population age groups. This study highlights the current lack of well-documented scientific reports on the status of HMs in agricultural farmland soils across 12 other provinces in Iran, emphasizing the need for further investigation. Moreover, the bioavailability of HMs in agricultural soils significantly influences HM content in crops, underscoring the need for future research to ascertain HM concentrations in different soil fractions.

A new approach to simulate watershed sediment graphs

Soil loss management requires reliable data for assessing the conditions prevailing in a watershed. Suspended sediment concentration (SSC) is one of the indicators of soil loss, and its data and associated properties are essential for integrated watershed management. However, until now, practical methods for estimating the temporal variation of SSC at the watershed scale, i.e., a sediment graph (SG), using measured data have been given less attention. Therefore, the current study was planned to simulate the SG through conceptual modeling of the soil erosion process and sediment yield. The Galazchai Watershed in West Azerbaijan Province, Iran, was selected as a case study. In this regard, the isochrone histograms were initially prepared using two methods of the longitudinal channel profile and spatially distributed travel time. Soil erosion was calculated in each isochrone segment using the Revised Universal Soil Loss Equation (RUSLE), applying the lumped and cellular automata approach. The soil erosion between isochrones was subsequently routed using the Hadley, WaTEM/SEDEM, and newly modified U.S. Forest Service methods. The last method was developed based on seven standardized variables for the current research. Synthetic SGs were ultimately derived from 12 different combinations of the study methods. The modeling performance was assessed using 38 storm events collected over several years. The base time, time to peak, peak value, and total sediment load of the simulated and observed SGs were evaluated using relative error. Comparison based on the evaluation indicators indicated better performance of the combination of the spatially distributed travel time method, cellular automata, and modified U.S. Forest Service method with the coefficient of efficiency and the normalized coefficient of efficiency varying from −1.16 to 0.99 and from 0.32 to 0.99 for the calibration and validation stages, respectively. However, none of the models were simulating satisfactorily the entire sediment graphs.

Phylogenetic analysis of Ehrlichia species isolated from horses and dogs in Iran

This study aimed to determine the prevalence and phylogenetic analysis of Ehrlichia spp. in horses and dogs in Iran. Blood samples were collected from 400 animals, including 200 horses and 200 dogs, from five different provinces in Iran. Polymerase chain reaction (PCR) was used to detect Ehrlichia spp. based on amplification of the 16S rRNA gene. The semi-nested PCR method was used to amplify the dsb, TRP36, and gltA genes. The results showed that 4.5 % of the samples (3 % horses and 6 % dogs) were positive for Ehrlichia sp. The highest prevalence was observed in Kerman and Khuzestan, while the lowest was found in West Azerbaijan, Golestan, and Mazandaran. The study suggests that the populations of dogs and horses in the country should be considered important factors in the epidemiology of ehrlichiosis. Phylogenetic analysis based on the dsb and TRP36 genes revealed that the prevalent species were E. canis and E. ruminantium.

The first molecular characterization and phylogenetic analysis of bovine papular stomatitis virus in Iran

Bovine papular stomatitis (BPS) generally is a mild viral disease caused by the Bovine papular stomatitis virus (BPSV) belonging to the genus Parapoxvirus (PPV). This study aimed to perform the first molecular characterization and phylogenetic analysis of BPSV in beef calves in Iran. Clinical examinations were carried out on four beef cattle herds in West Azerbaijan province, which had experienced outbreaks of papular lesions. Fifty swab samples were collected from the papular lesions on the muzzle, lips, and oral cavity of affected calves, and after viral DNA extraction, they were subjected to polymerase chain reaction (PCR). The results of PCR confirmed the presence of BPSV in all calves with clinical symptoms. The partial B2L gene was sequenced based on nucleotides, and phylogenetic analysis was performed using MEGA 11.0.13. The analysis revealed that BPSV isolates from beef calves in Iran formed two clades. Clade 1 exhibited similarities to the isolates from Finland, Japan, and Georgia, while Clade 2 was similar to the Zambian isolates. These findings indicate the presence of genetic diversity and potential variability within the virus population. Further studies with larger sample sizes and diverse geographic regions will increase the resolution of the phylogenetic tree and contribute to a comprehensive understanding of how BPSV circulates in the country.

MITE FAUNA OF SUBFAMILY PHYLLOCOPTINAE (ACARI ERIOPHYIDAE) IN MAKU COUNTY WITH THREE NEW RECORDS FOR ASIA AND THREE NEW RECORDS FOR IRAN

During the survey on eriophyid mites fauna of Maku county in West Azerbaijan Province of Iran in summers 2020 and 2021, a total of three tribes, 10 genera and 20 species belonging to the subfamily Phyllocoptinae Nalepa were identified. Among them, three species including Leipothrix coactus (Nalepa, 1896), Aculus tomentosi Meyer et Ueckermann, 1990 and Aculus chamaespariti Carmona, 1974 were new reports for Asia and three species including Epitrimerus inulae Farkas, 1963, Aculodes capillarisi Skoracka, 2003 and Abacarus cynodonis Abou-Awad et Nasr, 1983 were new for Iran. The tribe Tegonotini Bagdasarian and seven species including Aculodes altamurgiensis de Lillo et Vidović, 2018, Aculus mogeri Farkas, 1960, Aculus thyrsoidi Lotfollahi et Tajaddod, 2018, Aculops rhodensis Keifer, 1957, Aculops seguieranae Lotfollahi, Khanjani, Mogaddam et de Lillo, 2012, Aculops pachyphora Honarmand, Sadeghi &amp; de Lillo, 2020, Shevtchenkella denticulata Lotfollahi, de Lillo et Haddad, 2014 were new reports for West Azerbaijan Province. The most abundant mites belonged to Abacarus hystrix species complex. The supplementary descriptions of L. coactus and A. cynodonis are provided in this study. Key Words: Abacarus, Aculodes, Aculops, Aculus, Leipothrix, Shevtchenkella, Tegonotini