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Real estate market analysis can involve many aspects. One of them is the study of the influence of various factors on prices and property values. For this type of issues, different kinds of measures and statistical models are often used. Many of them do not give unambiguous results. One of the reasons for this is the fact that the real estate market is characterized by the concept of local markets, which may be affected in different ways by economic, social, technical, environmental and other factors. Incorporating the influence of local markets, otherwise known as submarkets, into models often helps improve the precision of mass real estate valuation results. The delineation of submarket boundaries can be done in several different ways. One tool that is helpful in these types of situations are geographically weighted regression (GWR) models. The problem that may arise when using such models is related to the nature of some market factors, which may be of a qualitative nature. Because neighborhoods of individual properties may lack variability in terms of some variables, estimating GWR models is significantly difficult or impossible. The study will present an approach in which the categorical variables are transformed into a single synthetic variable, and only this variable will constitute the explanatory variable in the model. Areas where the slope parameters of the GWR model are similar were considered a submarket. The purpose of this paper is to determine the boundaries of submarkets in the study area and to compare the results of modeling the value of real estate using models that do not take local markets into account, as well as those that take into account local markets determined by experts and using the GWR model.

The outbreak of the COVID-19 pandemic has left a great mark on all of humanity. In addition to the immediate threat to health and life, the virus in a way also infected other spheres of human life. The lockdowns, which lasted for many weeks, had a very big impact on various sectors of the economy. Most of them experienced a severe slowdown or recession. However, there were areas that benefited from the fact that the people in many countries stayed at home and worked remotely. Examples of such areas include the computer and tablets market, online stores, and delivery companies. This proves that even in difficult circumstances like a pandemic, we are not facing a total global recession. In such a context, it is worth looking at the impact of the COVID-19 pandemic on the real estate market. This area of the economy can experience the impact of the virus in different ways. On the one hand, a general increase in global uncertainty can cause certain investment projects to freeze or be abandoned. Lockdowns cause difficulties in accessing workers at construction sites. Populations losing their jobs during a pandemic have difficulty paying rent or mortgage payments. On the other hand, rising inflation and low interest rates on bonds and bank deposits may encourage people to protect their savings by buying property. Remote working increases the demand for larger apartments that need to serve as offices in addition to residential functions. Remote work also means not having to commute to workplaces, which may encourage people to move to cheaper locations without having to give up a well-paying job in a larger but also more expensive city. These two groups of impulses are contradictory and may have a completely different impact on the shape of the real estate market understood as the structure of prices and the number of transactions concluded. The study is part of a broader research effort to assess the impact of the COVID-19 pandemic on various areas of the economy. Previous research conducted in the Szczecin agglomeration proved the existence of the price divergence phenomenon. The main city of the agglomeration showed a tendency to pull in the economic potential from the region, which translated into a faster increase in real estate prices in the capital of the region in comparison with the surrounding cities. The aim of this study is to verify whether the pandemic and the socio-economic processes triggered by it, such as the development of remote working, changed the process of divergence into a process of convergence, but whether the faster growth of residential property prices in the main city of the agglomeration, which started years ago, has not been stopped. For this purpose

Fungal infections are still underappreciated and their prevalence is underestimated, which renders them a serious public health problem. Realistic discussions about their distribution, symptoms, and control can improve management and diagnosis and contribute to refinement of preventive actions using currently available tools. This article represents an overview of dermatophytes and endemic fungi that cause infections in humans and animals. In addition, the impact of climate change on the fungal spread is discussed. The endemic fungal infections characterized in this article include coccidioidomycosis, histoplasmosis, blastomycosis, lobomycosis, emergomycosis, and sporotrichosis. Moreover, the geographic distribution of these fungi, which are known to be climate sensitive and/or limited to endemic tropical and subtropical areas, is highlighted. In turn, dermatophytes cause superficial fungal infections of skin, hairs, and nails, which are the most prevalent mycoses worldwide with a high economic burden. Therefore, the possibility of causing zoonoses and reverse zoonoses by dermatophytes is highly important. In conclusion, the article illustrates the current issues of the epidemiology and distribution of fungal diseases, emphasizing the lack of public programs for prevention and control of these types of infection.

After cardiovascular diseases, infectious diseases are the second most common cause of death worldwide. Although these infections are caused mainly by viruses or bacteria, a systematically growing prevalence of human and animal opportunistic fungal infections is noticeable worldwide. More attention is being paid to this problem, especially due to the growing frequency of recalcitrant and recurrent mycoses. The latter are classically divided into superficial, which are the most common type, subcutaneous, and systemic. This work discusses opportunistic fungal pathogens without proven horizontal transmission between different animal species including humans and microsporidia as spore-forming unicellular parasites related to fungi; however, with a yet undetermined taxonomic position. The review also mentions aetiological agents, risk factors, epidemiology, geographical distribution, and finally symptoms characteristic for individual disease entities. This paper provides insight into fungal infections from a global perspective and simultaneously draws attention to emerging pathogens, whose prevalence is continuously increasing. Finally, this work also takes into consideration the correct nomenclature of fungal disease entities and the importance of secondary metabolites in the pathogenesis of fungal infections.

The main aim of the article was to present impact of categorical variables encoding on property mass valuation. Categorical variables are often used for describing important properties’ characteristics. In some countries, i.e., Poland, description of properties is mainly conducted with categorical variables, both nominal and ordinal. When property mass valuation is carried out it is important to introduce this kind of variables in best way to achieve most accurate results. There are many techniques of categorical variables encoding. In this study some of them were used in data pre-processing to determine whether the choice of encoding technique affects valuation results obtained with several regression algorithms. Three types of regression models were used in the research: a ridge regression model, k nearest neighbours regression and random forest regression algorithm. Each algorithm used explanatory variables coded using five techniques: one hot encoding, catboost encoding, Helmert encoding, target encoding and ordinal encoding. The results show that mass valuation results vary depending on how the encoding of categorical variables occurs. The regression algorithms used in the study respond differentially to the variable encoding techniques. Nevertheless, the one-hot encoding technique proved to be the best choice. The practical implications of the study are related to the reform of property taxation in Poland. Under this reform, values would become the basis for property taxation. This will be a complex undertaking, requiring the testing of various types of computational techniques to accurately determine the value of an enormous number of properties. The machine learning techniques presented in the study could be a part of a decision support system for introducing a new way of property taxation.

The article explores the economic aspects of area and value-based taxation of Polish real estate. It begins with the presentation of information on the conditions of property taxation in Poland. Next, a review of the research on the cadastral tax is provided, as well as the assumptions of the econometric model used for mass valuation of the analysed real estate. The main part of the article contains the results of the simulation of replacing the property tax with an ad valorem one. Particular attention is given to the impact of the cadastral tax rate on the revenues of municipalities and changes in the tax burden on individual properties. The main aim of this study was to show the importance of the proper setting of the ad valorem tax rate in the process of reforming the property taxation system.

The introduction of the property value tax in Poland may lead to an increase in the tax burden on real estate. Pilot studies may be carried out on samples and the results should feature a high degree of certainty as to the extrapolation of the results on populations (e.g. entire municipalities). Each study may, for various reasons, include outliers in the analyzed data sets. If their presence results from measurement errors or other reasons that cause such observations not to be the result of naturally occurring processes, they should be omitted in the calculations, because they interfere with the study of the occurring regularities. The study presents the results of statistical modelling carried out to determine whether individual objects (land properties), due to their attributes, are at risk of increasing the tax burden as a result of the introduction of ad valorem tax. First, logistic regression model estimation was carried out for the entire set of analyzed properties. Next, several methods of outlier detection were applied, and model estimation was repeated without the observations, i.e. real estates, pointed out as abnormal. The objective of the study is to verify the usefulness of outlier detecting methods in the context of improving the classification results of the analyzed properties.

Research background: Mass valuation is a process in which many properties are valued simultaneously with a uniform approach. An example of a procedure used for mass real estate valuation is the Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA), which can be developed into a multiple regression model. The algorithm is based on a set of drawn representative properties. This set determines, inter alia, the quality of obtained valuations. Purpose: The objective of the study is to verify the hypothesis whether changing the method of sampling representative properties from the originally used simple random sampling to stratified sampling improves the results of the SAREMA econometric variant. Research methodology: The article presents a study that uses two methods of representative properties sampling – simple random sampling and stratified sampling. Errors of the models of valuation created taking into account both methods of sampling and different number of representative properties are compared. A key aspect of the survey is the choice of a better sampling method. Results: The study has shown that stratified sampling improves valuation results and, more specifically, allows for lower root mean square errors. Stratified sampling yielded better results in the initial phase of the study with more observations, but reducing the percentage of strata participating in the draws, despite the increase in RMSE, guaranteed lower errors than the corresponding results based on simple sampling in all variants of the study. Novelty: The article confirms the possibility of improving the results of mass property valuation by changing the scheme of representative properties sampling. The results allowed for the conclusion that stratified sampling is a better way of creating a set of representative properties.

Purpose: The objective of the article is to identify machine learning methods that provide the best real estate appraisals for small-sized samples, particularly on poorly developed markets. A hypothesis is verified according to which machine learning methods result in more accurate appraisals than multiple regression models do, taking into account sample sizes. Design/Methodology/Approach: Four types of regression were employed in the study: a multiple regression model, a ridge regression model, random forest regression and k nearest neighbours regression. A sampling scheme was proposed which enables defining the impact of a sample size in training datasets on the accuracy of appraisals in test datasets. Findings: The research enabled drawing several conclusions. First of all, the greater the training set was, the more precise the appraisals in a test set were. The conclusion drawn is that a reduction of a training set causes the deterioration of modelling results, but such deterioration is not substantial. Secondly, ridge regression model appeared to be the best model, and thereby the one most resistant to a low number of data. This model, apart from demonstrating the greatest resistance, additionally has the advantage of being a parametric, hence allowing inference. Practical Implications: Presented considerations are important, for instance in the case of valuations conducted for fiscal purposes, when it becomes necessary to determine the value of every type of real properties, even the ones featuring sporadically occurring states of properties. Originality/Value: The study contains modelling of the values defined by property appraisers, and not prices, as in the majority of studies. This decision enabled increasing the diversity of states of real estate properties, thereby including in the modelling process not just those real properties which are most typically traded., peer-reviewed

Background The impact of Malassezia yeasts on skin mycobiome and health has received considerable attention recently. Pityriasis versicolor (PV), a common dermatosis caused by Malassezia genus worldwide, is a manifestation of dysbiosis. PV can be associated with hyper- and/or hypopigmented skin lesions. This disease entity is characterized by high percentage of relapses, which demands a proper antifungal therapy that is based on unambiguous species identification and drug susceptibility testing. Case presentation Comprehensive analysis of PV case in man presenting simultaneously hyper- and hypopigmented skin lesions was performed. Conventional and molecular diagnostic procedures revealed Malassezia furfur and Malassezia sympodialis, respectively as etiological agents of skin lesions observed. Susceptibility tests showed significantly lowered sensitivity of M. furfur cells to fluconazole. Based on susceptibility profiles local antifungal therapy with drugs characterized by entirely different mechanism of action was included. Conclusions Our study indicates that cases of PV represented by two types of skin lesions in one patient may be associated with distinct Malassezia species. Moreover, as observed in this case, each of the isolated etiological agents of PV may differ significantly in susceptibility to antifungals. This can significantly complicate the treatment of dermatosis, which by definition is associated with a significant percentage of relapses. In the presented case localized topical treatment was sufficient and successful while allowing maintaining the physiological mycobiome.

Background Dermatomycoses are the most common fungal infections in the world affecting a significant part of the human and animal population. The majority of zoophilic infections in humans are caused by Trichophyton mentagrophytes. Currently, the first-line drug for both oral and topical therapy is terbinafine. However, an increasing number of cases that are difficult to be cured with this drug have been noted in Europe and Asia. Resistance to terbinafine and other allylamines is very rare and usually correlated with point mutations in the squalene epoxidase gene resulting in single amino acid substitutions in the enzyme, which is crucial in the ergosterol synthesis pathway. Purpose Here, we report terbinafine-resistant T. mentagrophytes isolates among which one was an etiological factor of tinea capitis in a man and three were obtained from asymptomatic foxes in Poland. Methods We used the CLSI protocol to determine antifungal susceptibility profiles of naftifine, amphotericin B, griseofulvin, ketoconazole, miconazole, itraconazole, voriconazole, and ciclopirox. Moreover, the squalene epoxidase gene of the terbinafine-resistant strains was sequenced and analysed. Results In the genomes of all four resistant strains exhibiting elevated MICs to terbinafine (16 to 32 µg/ml), single-point mutations leading to Leu393Phe substitution in the squalene epoxidase enzyme were revealed. Among the other tested substances, a MIC50 value of 1 µg/ml was shown only for griseofulvin. Conclusion Finally, our study revealed that the terbinafine resistance phenomenon might not be acquired by exposure to the drug but can be intrinsic. This is evidenced by the description of the terbinafine-resistant strains isolated from the asymptomatic animals.

The major problems in determining the causative factors of the high prevalence of dermatophytoses include the lack of a well-standardized antifungal susceptibility testing method, the low consistency of in vitro and clinical minimal inhibitory concentration values, the high genomic diversity of the population, and the unclear mechanism of pathogenicity. These factors are of particular importance when the disease is recalcitrant and relapses. Herein, we identified and characterizedTrichophyton mentagrophytesisolates obtained from therapy-resistant cases in humans and animals. We used genomic diversity analysis of 17 human and 27 animal clinical isolates with the MP-PCR technique, determined their phenotypic enzymatic activity and host range, and performed antifungal susceptibility testing to currently available antifungal drugs from various chemical groups. Genomic diversity values of 35.3% and 33.3% were obtained for clinical isolates from humans and animals, respectively, yet without any relationship to the host species or antifungal drug to which resistance in therapy was revealed. The highest activity of keratinase enzymes was recorded for fox, guinea pig, and human hairs. These hosts can be considered as the main species in the host range of these isolates. A phenyl morpholine derivative, i.e. amorolfine, exhibited superior activity against strains obtained from both humans and animals with the lowest MIC50. Interestingly, high compliance of terbinafine in vitro resistance with clinical problems in the treatment with this substance was shown as well. The high resistance of dermatophytes to drugs is the main cause of the recalcitrance of the infection, whereas the other features of the fungus are less important.

Research background: Mass appraisal is a process in which multiple properties are appraised simultaneously, with a uniform approach. One of the tools that can be used in this area are multiple regression models. In the valuation of real estate features are often described on an ordinal or nominal scale. Replacing them with dummy variables with an insufficient number of observations leads to multicollinearity. On the other hand, there is a risk of overfitting the model. One of the ways to eliminate or weaken these phenomena is to introduce regularization based on a model’s penalization for the high values of its weights. Purpose: The aim of the study is to verify the hypothesis whether regularized regression reduces the errors of property valuation and which of the analyzed methods is the most effective in this context. Research methodology: The article will present a study in which two ways of regularization will be applied – ridge and lasso regression, in the context of their impact on the errors of property valuation. The analyzed data set includes over 300 land properties valued by property appraisers. The key aspects of the study are the selection of optimal values of the regularization parameter and its influence on model’s errors with a different number of observations in the training sets. Results: The study showed that regularization improves valuation results and, more specifically, allows for lower average absolute percentage errors. The improvement of model effectiveness was more pronounced in the case of ridge regression. An important result is also that regularization has provided a higher accuracy of valuation compared to multiple regression models for smaller training sets. Novelty: The article confirms the effectiveness of regularization as a way to eliminate the problem of multicollinearity or overfitting of the model. The results showed that ridge regression can be an effective way of modelling the value of real estate. Especially in the case of a small amount of market data, which is an important conclusion in the context of the real estate market.

Background Fungal infections of the skin, hair, and nails are the largest and most widespread group of all mycoses. Nannizzia nana is a relatively rare etiological factor of dermatomycosis in humans, as it usually affects animals, e.g. pigs and boars. In addition to the zoophilic nature, there are also reports of the geophilic reservoir of this dermatophyte species. Objective In this study, we present symptomatic infections with N. nana aetiology in humans reported recently in Poland. Interestingly, these cases had a non-specific clinical picture and occurred as skin lesions on the neck and foot as well as onychomycosis of the toenails. From the medical history, the patients had no contact with pigs. Methods Diagnostics of these infections was performed with a combination of classical phenotypic and molecular genomic methods. The genomic diversity of the isolates was determined using the MP-PCR method. In vitro antifungal susceptibility tests against itraconazole, ketoconazole, terbinafine and naftifine hydrochloride were also performed. Results Nannizzia nana has been identified as an etiological factor of dermatomycosis. Moreover, heterogeneity of the genomes was revealed for the obtained strains. In vitro activities of antifungal agents showed that isolates were susceptible to all tested drugs. The patients were treated with oral terbinafine and topical ketoconazole cream, which led to a complete recovery. Conclusions In conclusion, the cases studied by us may indicate that the infrequency of N. nana infections may not necessarily be related to the low infectivity of this fungal agent, but they are rather associated with misdiagnosis. Furthermore, N. nana reservoirs should also be sought in soil.

The MALDI-TOF MS method is a new technique, which is being increasingly used in clinical laboratories for identification of microorganisms. The wide interest in this method has been aroused by its high accuracy, instantaneous identification results, and relatively low cost of analyses. However, the application of this technique for identification of dermatophytes poses difficulties. They are caused by the natural biological complexity of filamentous fungi, very slow growth of cultures, and frequent production of pigments. Furthermore, identification of dermatophytes with this technique is a challenge due to the lack of a clear species definition for some taxa or within certain species complexes. A review of scientific literature indicates that the reliability of identification of dermatophytes based on MALDI-TOF MS is in the range between 13.5 and 100%. This variability is determined by many critical factors associated with routine laboratory procedures, i.e. the type of culture medium, incubation time, protein extraction technique, type of device, or version of the reference spectrum library. Despite these numerous limitations, the MALDI-TOF MS method is part of the significant technical progress in mycological diagnostics and an alternative to the time-consuming and labor-intensive identification of dermatophytes based on morphological traits and DNA sequencing. Nevertheless, before the technique can be implemented into routine diagnostic tests, it is necessary to expand the reference spectra library and develop procedures for direct analysis of dermatological samples. 1. Introduction. 2. Identification of microorganisms using the MALDI-TOF MS method. 3. MALDI TOF MS in mycological identification. 4. Critical factors in identification of dermatophytes with the MALDI-TOF method. 4.1. Impact of the microbiological medium. 4.2. Impact of the incubation time. 4.3. Impact of the protein extraction procedure and preparation of the matrix. 4.4. Impact of the mass spectrometry apparatus. 4.5. Impact of the reference spectrum library. 4.6. Impact of the spectrum comparison algorithm. 4.7. Impact of taxonomic changes. 5. Prospects for the development of MALDI-TOF MS in mycological diagnostics. 6. Summary

Paradoxically, despite the progress in medicine, the prevalence of fungal infections is increasing from year to year. At the beginning of the third millennium, practical therapeutic options are still very limited. Currently, only eight classes of antifungal compounds are in clinical use, only four of which are used in the treatment of dermatomycoses. The intense search for the “Holy Grail” of antifungal therapy that has been going on since the second half of the 20th century faces serious obstacles arising from the eukaryotic model of fungal cell structure. In this paper, new groups of chemical compounds of mainly natural origin have been synthetically described, which due to their interesting antifungal activity, including pathogenic species of dermatophytes, may constitute new therapeutic options. Among compounds currently arousing great interest, compounds from the group of terpenoids, alkaloids, saponins, flavonoids and essential oils deserve attention. Many of these compounds are in clinical trials as potential antifungal agents, while others are in preclinical studies. Future research should focus on attempting to determine the applicability of the given substances in implementation for routine use and their effectiveness, toxicity and side effects. 1. Introduction. 2. General characteristics of dermatophytes in the therapeutic aspect. 3. New synthetic preparations with antifungal activity. 4. Natural antifungal preparations. 4.1. Terpenoids and essential oils. 4.2. Alkaloids. 4.3. Flavonoids. 4.4. Saponins. 4.5. Other chemical compounds 5. Summary

In nature, there are many species of fungi known to produce various mycotoxins, allergens and volatile organic compounds (VOCs), as well as the commonly known etiological agents of various types of mycoses. So far, none of them have provoked so much emotion among homeowners, builders, conservators, mycologists and clinicians as

Research background: The article discusses the issue of the identification and measurement of market characteristics of real estate for valuation purposes. This problem is the most difficult stage of the whole valuation process in terms of both a substantive, methodological and analytical basis. Goal: The aim of the research is to outline and explore on the basis of literature studies as well as developed problems to be solved in the process of mass valuation together with the presentation of an exemplary solution. Methodology: In the theoretical part a hypothetical-deductive method which consists of developing a certain hypothesis and deducing its consequences was applied. The empirical section uses the method of scientific discussion among scientists and practicing valuers and, for the presentation of the results; some graphical methods were used for a statistical analysis. Results: As a result of the conducted research, criteria to be used in identifying and classifying market characteristics for the purposes of valuation were identified and a set of market characteristics of properties was developed along with a method of identifying their states for the purposes of mass valuation. Novelty: The article proves that the problem of the identification and classification of market characteristics of real estate for valuation purposes is extremely important from the point of view of the valuation process and the results obtained as a result of it as well. In addition, for some features, it is proposed to develop special measures such as the plot shape attractiveness ratio. This meets the problem of the objective measurement of market features of real estate. In relation to other features, the legitimacy of the expert approach was pointed out.

Property valuation in the comparative approach requires the determination of the impact of market characteristics on the formation of prices on the local real estate market. Valuers have a variety of methods for determining weights. Some of them require the collection of a sufficiently large database of information on transactions. However, this is not always possible. In the absence of sufficient data, alternative approaches, including an expert approach, may be used. The goal of the article is the proposal of an expert approach at the stage of assessing the influence of attributes on the value of the real estate. The AHP (Analytical Hierarchy Process) method will be used. On its basis, pairwise comparisons of the importance of attributes will be done by experts (valuers). By means of the AHP method, the weights of each attribute will be obtained and, subsequently, the influence of each attribute on the real estate value will be assessed. Research will be done on the basis of 318 real estates in Szczecin.

Dermatophytes are a group of filamentous fungi infecting skin, hair, and nails that raise great diagnostic difficulties. qRT-PCR is a reliable technique for quantifying gene expression with increasingly frequent use in mycological diagnostics. Knowledge of genes and molecular markers with potential to be used in the identification of dermatophytes is of great importance for the development of this branch of diagnostics. In this article, the suitability of six candidate reference genes (TUBB, ACTB, ADPRF, RPL2, SDHA, and EEF1A1) was investigated for gene expression analysis in the dermatophyte Trichophyton verrucosum, which was cultured in various mycological media that are commonly used in a diagnostic laboratory, i.e., Sabouraud, potato dextrose, and keratin-supplemented MM-Cove. The different culture conditions are extremely important factors for the growth and physiology of dermatophytes. Gene expression stability was evaluated using geNorm, NormFinder, BestKeeper, and RefFinder algorithms. Regarding the stability of expression, SDHA was the most stable housekeeping gene, hence, this gene is recommended for future qRT-PCR studies on T. verrucosum strains. These results allow us to conclude that the SDHA gene can be an additional good candidate as an identification target in the qRT-PCR technique.

The aim of the study was to isolate and identify species belonging to the Aeromonas genus and evaluate the antimicrobial resistance and virulence patterns of isolates colonizing European pond turtles (Emys orbicularis) from natural environment of Eastern Poland. In total, 74 turtles and 15 samples of water from their natural environment were examined. More than 40 strains were isolated and identified: A. bestiarum (n = 1), A. hydrophila (n = 13), A. allosaccharophila (n = 2), A. salmonicida (n = 3), and A. veronii (n = 23). The highest incidence of resistance was noted for ampicillin (100%) and sulfamethoxazole (62.0%), followed by erythromycin and colistin (both 40.5%). Moreover, eight strains were intermediately resistant to meropenem (19%). Most Aeromonas isolates were found to possess more than one virulence gene among fla, aer, hlyA, act, ela, alt, and ast. We showed that the population of free-living European pond turtles was highly colonized by Aeromonas spp. Such strains may be an infectious agent not only for the population of turtles but also for other species of animals inhabiting their natural environment. Moreover, the undesirable properties of water quality caused by the presence of drug-resistant aeromonads could have a negative impact on human health.

Simple Summary Fungal infections of the skin, hair, and nails in humans and animals are the most prevalent mycoses worldwide, with a high economic burden. The high degree of transmissibility poses an epidemiological threat and gives these infections a significant importance as zoonoses. Hence, the control of the presence of dermatophytes in herds of cattle and other species of farm animals should be routinely performed. The ongoing improvements in the field of fungal detection techniques give new scope for clinical implementations in specialized laboratories and hospitals or veterinary clinics, including the monitoring of disease and the detection of side effects of drugs and environmental risks. This study aimed to evaluate the analytical specificity and clinical application of direct sample real-time PCR by comparison with direct microscopy and culture methods. The pan-dermatophyte primers in the qPCR technique facilitated detection of the presence of the genetic material of dermatophytes with greater specificity than the microscopic examination. Moreover, this article describes an interesting case of the isolation of two different species of dermatophytes from the same clinical lesion, i.e., Trichophyton verrucosum and T. benhamiae. Abstract Dermatophytes are filamentous fungi with the ability to digest and grow on keratinized substrates. The ongoing improvements in fungal detection techniques give new scope for clinical implementations in laboratories and veterinary clinics, including the monitoring of the disease and carrier status. The technologically advanced methods for dermatophyte detection include molecular methods based on PCR. In this context, the aim of this study was to carry out tests on the occurrence of dermatophytes in cattle herds using qPCR methods and a comparative analysis with conventional methods. Each sample collected from ringworm cases and from asymptomatic cattle was divided into three parts and subjected to the real-time PCR technique, direct light microscopy analysis, and culture-based methods. The use of the real-time PCR technique with pan-dermatophyte primers detected the presence of dermatophytes in the sample with a 10.84% (45% vs. 34.17%) higher efficiency than direct analysis with light microscopy. Moreover, a dermatophyte culture was obtained from all samples with a positive qPCR result. In conclusion, it seems that this method can be used with success to detect dermatophytes and monitor cowsheds in ringworm cases and carriers in cattle.

Purpose Anthropophilic dermatophytes as etiological factors of onychomycoses are more common than zoophilic fungi. In the case of the latter, reverse zoonoses are possible, which poses a threat to the persistence of dermatophytes in the environment. Nevertheless, without treatment, both types of tinea unguium may lead to complete nail plate destruction and secondary mixed infections with fungi and bacteria. One of the zoophilic dermatophytes that cause onychomycosis is Trichophyton verrucosum, whose prevalence has been increasing in recent years. Such infections are usually treated with allylamines and/or azoles, but such a conventional treatment of infections caused by T. verrucosum often fails or is discontinued by patients. Methods Herein, we reveal the results of our in vitro studies related to direct application of cold atmospheric pressure plasma (CAPP) on Trichophyton verrucosum growth, germination and adherence to nail as a new alternative treatment method of such types of dermatomycoses. Results Our in vitro studies showed that, while exposure to CAPP for 10 min delays germination of conidia and clearly impairs the fitness of the fungal structures, 15 min is enough to kill all fungal elements exposed to plasma. Moreover, the SEM images revealed that T. verrucosum cultures exposed to CAPP for 10 and 15 min were not able to invade the nail fragments. Conclusion The results revealed that single exposure to CAPP was able to inhibit T. verrucosum growth and infection capacity. Hence, cold atmospheric pressure plasma should be considered as a promising alternative treatment of onychomycoses.

The possibility of using multiple regression models in real estate valuation is the subject of disputes, both in theory and in practice. Econometric modelling is a difficult process, since a number of issues of substantive and numerical nature occur during that process. Modern technologies enable quick and easy model estimation with the use of virtually any quality of data. Naturally, it provokes property appraisers to use such models in the practice of real property valuation, particularly in mass appraisal, frequently without taking those issues into account. Consequently, the models obtained and applied in practice turn out to be of poor quality and, objectively speaking, should not serve as the basis for determining real estate value. The specificity of the real estate market and of the real properties themselves as objects traded in that market additionally exert a negative impact on the quality of the obtained models. In this article, the authors present the results of research which involved a simulation of various types of disturbances of a model artificially developed database of real estate prices and attributes as well as their impact on the quality of estimated models. The research will make it possible to answer the question of the degree and type of disturbances that are permissible in the functioning of a real estate market if the estimated models are to still satisfy the qualitative requirements defined for them, and thereby produce accurate valuation results. A model database will be disturbed by the deviation of prices from model prices and by reducing its size. Radom generators were used to obtain database disturbances.

One of the key determinants of the quality of real estate mass appraisal is the algorithm used for conducting such an appraisal. Other determinants include detailed methodological and substantive solutions within the scope of a selected, applied algorithm. This article is dedicated to one of the major stages of the process of land real estate mass appraisal with the use of the Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA), namely defining and determining the so-called elementary terrains. The paper aims to present the methods for designating the boundaries of elementary terrains, the manner of defining their number and size and, consequently, the number of real properties that will be covered by an automated process of mass appraisal in a given area. Ways of defining the boundaries of elementary terrains were proposed in the paper based on the existing surveying districts, zoning plans, background maps, thematic map layers, real estate market analyses as well as statistical methods. Elementary terrain boundaries thus designated were verified with the use of actual real estate resources of the city of Szczecin.

Today a growing number of studies are focusing on antibiotic resistance in wildlife. This is due to the potential role of wild animals as reservoirs and spreaders of pathogenic and resistant bacteria. This study focused on isolating and identifying Escherichia coli from the feces of wild animals living in the Apuan Alps Regional Park (Tuscany, Italy) and evaluating some of their antibiotic resistance and pathogenicity traits. Eighty-five fecal samples from different species were studied. Seventy-one E. coli were identified by matrix assisted laser desorption ionization-time of flight mass spectrometry analysis, subjected to antibiograms and polymerase chain reaction for the detection of antibiotic resistance genes and pathogenicity factors. The highest resistance rates were found against cephalothin (39.4%) and ampicillin (33.8%), followed by amoxicillin/clavulanic acid (15.5%), streptomycin (12.7%), and tetracycline (5.6%). Regarding resistance genes, 39.4% of the isolates were negative for all tested genes. The remaining isolates were positive for blaCMY-2, sul2, strA-strB and aadA1, tet(B), and tet(A), encoding resistance to beta-lactams, trimethoprim/sulfamethoxazole, streptomycin, and tetracycline, respectively. With regard to virulence factors, 63.4% of the isolates were negative for all genes; 21.1% carried astA alone, which is associated with different pathotypes, 9.9% carried both escV and eaeA (aEPEC); single isolates (1.4%) harbored escV (aEPEC), escV associated with astA and eaeA (aEPEC), astA with stx2 and hlyA (EHEC) or astA and stx1, stx2, and hlyA (EHEC). These results show that wildlife from nonanthropized environments can be a reservoir for antibiotic-resistant microorganisms and suggest the need for a deeper knowledge on their origin and diffusion mechanisms through different ecological niches.

The introduction of an ad valorem tax can lead to an increase in the tax burden on real estate. There are concerns that this increase will be large and widespread. Before undertaking any actual actions related to the real estate tax reform, pilot studies and statistical analyses need to be conducted in order to verify the validity of those concerns and other aspects regarding the replacement of a real estate tax, agricultural tax and forest tax with an ad valorem tax. The article presents results of research on the effectiveness of the classification of real estate into a group at risk of an increase of tax burden with the use of the k-nearest neighbors method. The main focus was to determine the size of a real estate set (training data set) on the basis of which classification is conducted, as well as on the efficiency of that classification, depending on the size of such data set.

Aim/purpose – General real estate taxation is a process regulated, inter alia, by the Real Estate Management Act. It is intended to establish a tax base for real estate in the event of a change in real estate tax base. General taxation is one of several applications of mass valuation of real estate, which enables valuation of many properties at the same time and with a uniform approach. One of the methods of mass valuation of real estate already applied in practice is the Szczecin Algorithm of Real Estate of Mass Appraisal (SAREMA). One of the immanent features of general taxation and the algorithm itself is the division of a selected area into possibly homogeneous areas called taxing zones within the general taxation terminology and, more broadly, elementary areas, according to the nomenclature used in the SAREMA. The paper presents the results of the studies on the measurement of elementary areas homogeneity on the example of land plots located in Szczecin. It is important to assess whether the designated sub-areas ofvaluation cover properties similar to each other in terms of their specific characteristics. If so, it will help to obtain more accurate mass valuation results. Design/methodology/approach – The paper proposes to use a modified entropy measure to establish whether the designated areas are homogeneous in terms of the specified properties of real estate. The database of real estate includes more than 1.5 thousand urbanised land plots located in Szczecin. The measurement of entropy will be preceded by the specification of elementary areas. The available methods include the application of an expert approach, under which land boundaries will be indicated by property valuers. Findings – The main conclusion of the study is that a modified measure of entropy ensures a better indication of the degree of indefiniteness of valued sub-areas and thus it offers a better way of supporting the delimitation of these sub-areas in comparison to the classical measure of entropy. Research implications/limitations – The delimitation of valuation sub-areas constitutes an important element of mass valuation. Proper execution of this process enables obtaining much more precise valuations. An objective measure of homogeneity gives a chance to compare different approaches to the creation of the above-mentioned sub-areas and to choose the best of them. Originality/value/contribution – The main achievement of the study is a proposal to modify the classical entropy measure, thanks to which it better reflects the specificity of the assessment of homogeneity of the areas valued in terms of property market analysis.

The aim of the study was to carry out a comparative analysis of the occurrence of sequence types, genotypes, and virulence genes of multidrug-resistant Enterococcus faecium isolated from humans, domestic animals, and wildlife from eastern Poland. The genetic correlation of strains was determined using multilocus sequence typing, and the method of Amplification of DNA fragments Surrounding Rare Restriction Sites. The presence of 49 different STs (including 12 not reported previously) was shown. All human isolates, 56% of E. faecium isolated from poultry and 40% isolated from wildlife, belonged to the hospital-adapted CC17. E. faecium CC17 were characterized by statistically higher resistance to aminoglycosides and penicillin, the presence of the aac(6')-Ie-aph(2″)-Ia and hyl gene and mutations in gyrA and parC, compared to other strains (p 0.05). E. faecium were classified into 73 genotypes grouped into clusters including isolates from the same host species. The present study showed that the virulence, resistance, and genotype profiles of E. faecium were correlated with the individual host but not with the sequence type. The occurrence of E. faecium CC17 in both humans and animals proves the large circulation of the complex among various hosts.

European Apis mellifera and Asian Apis cerana honeybees, are essential crop pollinators. Microbiome studies can provide complex information on health and fitness of these insects in relation to environmental changes, and plant availability. Amplicon sequencing of variable regions of 16S rRNA and internally transcribed spacers (ITSs) allow identification of the metabiome. These methods provide a tool for monitoring otherwise uncultured microbes isolated from the gut of the honeybees. They also help monitor the composition of the gut fungi and, intriguingly, pollens collected by the insect. Here, we present data from amplicon sequencing of the 16S rRNA and ITS2 regions from honeybees collected at various time points from anthropogenic landforms as urban areas in Poland, UK, Spain, Greece, and Thailand. We have analysed microbial composition of honeybee intestine as well as fungi and pollens. We conclude that differences between samples were mainly influenced by the bacteria, plant pollens and fungi, respectively. Moreover, honeybees feeding on a honeydew diet, mainly based on sugars, were more prone to fungal pathogens (Nosema ceranae) and neogregarines. Finally, the period when honeybees switch to the winter generation (longer-lived forager honeybees) is the most sensitive to diet perturbations and hence pathogens attack, for the whole beekeeping season. It is possible that evolutionary adaptation of bees fails to benefit them in the modern anthropomorphised environment.

European Apis mellifera and Asian Apis cerana honeybees are essential crop pollinators. Microbiome studies can provide complex information on health and fitness of these insects in relation to environmental changes, and plant availability. Amplicon sequencing of variable regions of the 16S rRNA from bacteria and the internally transcribed spacer (ITS) regions from fungi and plants allow identification of the metabiome. These methods provide a tool for monitoring otherwise uncultured microbes isolated from the gut of the honeybees. They also help monitor the composition of the gut fungi and, intriguingly, pollen collected by the insect. Here, we present data from amplicon sequencing of the 16S rRNA from bacteria and ITS2 regions from fungi and plants derived from honeybees collected at various time points from anthropogenic landscapes such as urban areas in Poland, UK, Spain, Greece, and Thailand. We have analysed microbial content of honeybee intestine as well as fungi and pollens. Furthermore, isolated DNA was used as the template for screening pathogens: Nosema apis, N. ceranae, N. bombi, tracheal mite (Acarapis woodi), any organism in the parasitic order Trypanosomatida, including Crithidia spp. (i.e., Crithidia mellificae), neogregarines including Mattesia and Apicystis spp. (i.e., Apicistis bombi). We conclude that differences between samples were mainly influenced by the bacteria, plant pollen and fungi, respectively. Moreover, honeybees feeding on a sugar based diet were more prone to fungal pathogens (Nosema ceranae) and neogregarines. In most samples Nosema sp. and neogregarines parasitized the host bee at the same time. A higher load of fungi, and bacteria groups such as Firmicutes (Lactobacillus), γ-proteobacteria, Neisseriaceae, and other unidentified bacteria was observed for Nosema ceranae and neogregarine infected honeybees. Healthy honeybees had a higher load of plant pollen, and bacteria groups such as: γ-proteobacteria, Orbales, Gilliamella, Snodgrassella, γ-proteobacteria and Enterobacteriaceae. Finally, the period when honeybees switch to the winter generation (longer-lived forager honeybees) is the most sensitive to diet perturbations, and hence pathogen attack, for the whole beekeeping season. It is possible that evolutionary adaptation of bees fails to benefit them in the modern anthropomorphised environment.