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Background The aim of this study was to construct an electronic bowel sound recording system and determine its usefulness for the diagnosis of appendicitis, mechanical ileus and diffuse peritonitis. Materials and methods A group of 67 subjects aged 17 to 88 years including 15 controls was examined. Bowel sounds were recorded using an electret microphone placed on the right side of the hypogastrium and connected to a laptop computer. The method of adjustable grids (converted into binary matrices) was used for bowel sounds analysis. Results Significantly, fewer (p ≤ 0.05) sounds were found in the mechanical ileus (1004.4) and diffuse peritonitis (466.3) groups than in the controls (2179.3). After superimposing adjustable binary matrices on combined sounds (interval between sounds

In this study, the detection of dairy cows with difficult calvings using artificial neural networks (ANN) and classification functions (CF) is presented. The set of 15 classification variables was used. The dependent variable was the class of calving difficulty: difficult or easy. Perceptrons with one (MLP1) and two (MLP2) hidden layers as well as radial basis function (RBF) networks were analyzed. The prepared classifiers were characterized by good quality. The accuracy amounted to 75–92 %. Only the RBF network had somewhat worse quality. The level of correct detection by ANN was also high. The sensitivity on a test set was 67–80 % at specificity of 61- 81 %. In the case of CF, a considerable disproportion between sensitivity (6 %) and specificity (99 %) was found. The variables with the greatest contribution to the determination of calving difficulty class were calving season, CYP19-PvuII genotype, pregnancy length and, to a lesser degree, other variables. The performed analyses proved the usefulness of ANN for the detection of cows with difficult calvings, whereas the detection by CF was inaccurate.

Objective The aim of this study was to verify the usefulness of artificial neural networks (ANN), multivariate adaptive regression splines (MARS), naïve Bayes classifier (NBC), general discriminant analysis (GDA), and logistic regression (LR) for dystocia detection in Polish Holstein-Friesian Black-and-White heifers and cows and to indicate the most influential predictors of calving difficulty. Methods A total of 1,342 and 1,699 calving records including six categorical and four continuous predictors were used. Calving category (difficult vs easy or difficult, moderate and easy) was the dependent variable. Results The maximum sensitivity, specificity and accuracy achieved for heifers on the independent test set were 0.855 (for ANN), 0.969 (for NBC), and 0.813 (for GDA), respectively, whereas the values for cows were 0.600 (for ANN), 1.000 and 0.965 (for NBC, GDA, and LR), respectively. With the three categories of calving difficulty, the maximum overall accuracy for heifers and cows was 0.589 (for MARS) and 0.649 (for ANN), respectively. The most influential predictors for heifers were an average calving difficulty score for the dam’s sire, calving age and the mean yield of the farm, where the heifer was kept, whereas for cows, these additionally included: calf sex, the difficulty of the preceding calving, and the mean daily milk yield for the preceding lactation. Conclusion The potential application of the investigated models in dairy cattle farming requires, however, their further improvement in order to reduce the rate of dystocia misdiagnosis and to increase detection reliability.

The aim of this study was to check the effectiveness of classification and regression trees (CART), support vector machines (SVM) and generalized linear model (GLZ) in the detection of difficult calvings in the Polish Holstein-Friesian Black-and-White heifers and to identify the most influential predictors of such calvings with special regard to oestrogen receptor alpha (ERα) and cytochrome P450 (CYP19) aromatase genotypes. A total of 529 calving records containing four continuous and four categorical predictors were analysed. Calving category (difficult vs. easy) was a dependent variable. The most significant predictors were as follows: gestation length, body condition score index and calving age (for CART), as well as ERα genotype (for GLZ). Sensitivity (percentage of correctly diagnosed difficult calvings) and specificity (percentage of correctly diagnosed easy calvings) on a test set were 70.0% and 94.7% (for CART) as well as 50.0% and 99.0% (for SVM and GLZ), respectively. The studied models were cha...

BACKGROUND The aim of this study was to assess the distribution and dynamics of temperature changes on the surface of selected body parts after systemic cryostimulation. The changes that occurred as a reaction to the 1st, 5th, and 10th session of a series of 10 sessions were also analyzed. METHODS The study group consisted of 24 students (12 women and 12 men, ∼21 yr of age) from the University School of Physical Education in Krakow. They were treated in a cryogenic chamber at the Rehabilitation Center in Krakow once daily for 10 d. The mean temperature in the chamber was -130°C ± 10°C and the session duration was 3 min. Thermovisual examination of temperature distribution in the selected parts of the upper and lower extremities was conducted before and immediately after a session on the 1(st) (S1), 5(th) (S2), and 10(th) (S3) day of treatment. All thermograms were digitally recorded using a Flir Therma CAM TM Sc500 camera. RESULTS On the 5th day of treatment, the examined group demonstrated the smallest mean temperature changes (4.57°C-17.31°C for the anterior part of the upper extremities in men and the posterior part of the lower extremities in women, respectively) before and after cryostimulation. The most significant temperature changes were observed in the group of women (6.80°C-20.08°C for the posterior parts of the upper extremities on S2 and the lower extremities on S3, respectively). CONCLUSION There is an important difference in response to cryogenic temperature between men and women in a series.

The aim of this study was to analyze age-related effects influencing retrobulbar blood flow parameters.The study enrolled healthy volunteers (162 eyes) with a mean age of 49.64 years (SD ± 17.50). Participants were divided into 5 groups (G1-G5) based on 12-year age spans (means from 25.41 to 73.87 years). Peak systolic velocity (PSV), end diastolic velocity (EDV), mean velocity (MV), pulsatility index (PI) and resistive index (RI) of the ophthalmic (OA), central retinal (CRA) and posterior ciliary arteries (PCAs) were measured by color Doppler ultrasonography (CDU). In addition, systemic blood pressure (BP), ocular perfusion pressure (OPP) and intraocular pressure (IOP) were evaluated. Statistical analysis was performed using the Shapiro-Wilk, Levene's, Spjotvoll-Stoline and analysis of variance tests (p ≤ 0.05 was considered statistically significant).In the oldest group, significantly lower PSV, EDV in the CRA and PCAs as well as MV in the CRA were confirmed. Significantly increased RI in the OA, CRA and PCAs in regard to age was recorded.CDU has considerable potential for evaluating hemodynamic changes in the retrobulbar circulation in relation to age. Age laboratory standards for a specific CDU device should be established for further analyses of blood flow in ocular diseases of vascular origin.

BACKGROUND This study verifies selected opinions on breast cosmetic surgery in the population of Polish women. MATERIALS AND METHODS A total of 78 women aged 20 to 48 years were surveyed between 2008 and 2010 before and after breast augmentation surgery using a questionnaire. The χ and Wilcoxon signed rank tests were used for statistical analysis. Most were married and single women aged approximately 30 years and residents of large cities. RESULTS The significance of professional success in the hierarchy of values and the level of self-assessment increased after surgery (P = 0.0000 and 0.0213, respectively). The distribution of responses concerning the expectations of surgery and the evaluation of their fulfillment changed significantly (P = 0.0031). In general, the satisfaction with one's life after surgery also increased (P = 0.0000). CONCLUSIONS A well-thought-out decision on breast cosmetic surgery positively affects at least several spheres of psychosocial functioning and fulfills most women's expectations.

Daily body weight gains are an important indicator for the evaluation of beef production. The objective of this study was to verify the quality and detection abilities of selected data mining methods (artificial neural networks and decision trees) applied to the analysis of daily body weight gains in beef heifers. A total of 261 individuals (Charolais, Charolais A— Simmental and Charolais A— Hereford) were genotyped and their daily body weight gains were recorded. The genetic analysis included polymorphic variants of leptin, myostatin, and prion protein genes. The animals were divided into two categories: those with daily body weight gains equal to or lower than the mean for the analyzed population (99 heifers) and those with daily body weight gains higher than the mean (112 heifers). Heifer birth weight, breed, birth season, dam body weight at calving, calving interval, and genotypes were used as predictors. From among the analyzed models, the neural network with 8 neurons in a single hidden layer (root mean squared error equal to 0.4471) and the tree with an error coefficient of 0.4076 were selected. These classifiers correctly detected 20 out of 27 heifers with daily body weight gains below the mean. In the case of heifers with daily body weight gains above the mean, neural networks correctly classified 17 out of 23 individuals, whereas decision tree only 14. Breed, leptin genotype and combined genotype turned out to be the most important variables contributing to the determination of body weight gains class for both types of classifiers.

The aim of the present study was to evaluate the level of gonad masculinization in PIS individuals of different age and the expression profile of genes potentially involved in this process. The study involved a total of eight White Improved goats, 1–12 months of age, with different proportion of Saanen and Alpine genes. A control group of three horned and three polled male kids at an analogous age was included in the study. Molecular analysis showed that all individuals with developmental changes in the reproductive tract were the SRY(−) females, which has already been described in PIS goats. Moreover, the PIS deletion was found in the experimental group individuals. Histological analysis confirmed in seven cases the presence of testes and in one case the presence of ovotestis. The expression pattern of the SOX9 and PISRT1 genes in the gonads obtained from the 1- and 3-month-old individuals with sex reversal as well as from horned and polled male kids at an analogous age was similar, whereas in the hermaphrodite's gonads, transcriptional activity of the SOX9 and PISRT1 genes was not observed. A high mRNA level of PISRT1 was found in the testes of the horned male. So what is the role of the latter in male gonads? Although the molecular cause of the discussed syndrome in goats is known, it seems possible that the effect of this long deletion on the development of reverse phenotype may be more complex.

Polledness intersex syndrome (PIS) is a phenomenon associated with 2 distinct conditions occurring in goats, namely polledness and intersexuality. The first is a trait exhibiting complete dominance, whereas the latter is recessive. The extreme case of intersexualism is complete sex reversal, which is observed only in females (60,XX). The trait PIS is inherited in a recessive manner and caused by deletion of 11.7 kbp DNA on chromosome 1q43. Female goats with PIS exhibit a broad range of developmental abnormalities of the sexual system, from only subtle changes to complete sex reversal. The phenotypic diversity in goats with PIS is most likely an effect of complexity of the sexual differentiation process, in which the gene-dosage effect may potentially play a crucial role, in addition to the numerous molecular factors regulating the developmental pathway. The occurrence may explain different degrees of masculinization. Nevertheless, the sex reversal phenomenon appearing in female goats (60,XX) with PIS is not considered a serious problem in breeding programs because properly planned selection of individuals for reproduction can allow for complete exclusion of risk of occurrence of this syndrome in offspring. On the other hand, female goats with PIS are still one of the most suitable animal models for studying complex processes of determination and differentiation of sex in mammals.

Summary Background The aim of this study was to determine the relationships between lens opacity, vascular and lipid factors and retrobulbar blood flow parameters in type-1 diabetic (DM) adolescents. Material/Methods Glycated haemoglobin (HbA1c), total cholesterol (TCH), high- and low-density cholesterol, triglycerides (TG) and apolipoprotein B (ApoB) were determined in 28 patients with (DM-1) and without (DM-0) lens opacity and 18 controls. In the ophthalmic, central retinal (CRA) and temporal posterior ciliary (TPCA) arteries, the systolic (PSV), end-diastolic and mean blood flow velocities as well as pulsatility and resistance (RI) indices were measured. Results Ten (35.71%) diabetic patients exhibited lens opacification. Higher TG and TCH levels in the DM-1 group and HbA1c level in the DM-0 and DM-1 groups were observed (P≤0.05). Diabetic patients had lower PSV and higher RI within CRA and TPCA (P≤0.05). Significant correlations between biochemical and blood flow parameters were found. Conclusions Glycaemic and lipid factors may play a vasoconstrictive role in retrobulbar endotheliopathy.

So far the studies on the prion protein (PRNP) gene have mainly been focused on the search for an association between detected polymorphisms in this gene and the susceptibility of cattle to bovine spongiform encephalopathy. The PRNP gene location on chromosome 13 suggests that the polymorphisms within this gene can be potential quantitative trait locus (QTL) markers for milk production traits. The aim of this study was the analysis of the potential effect of the insertion/deletion polymorphisms within the promoter region (23 bp) and intron 1 (12 bp) of the PRNP gene on milk production traits in Jersey cattle. The study material consisted of 171 Jersey cows. The following milk production traits were analysed: milk yield, milk fat and protein yield, milk fat and protein content. Statistically significant differences were found in milk fat content in the second lactation between animal groups representing the ins/del and del/del genotypes for the 23 bp polymorphism (P≤0.05). The ins/del 12 bp polymorphism wa...

Revisions and redescriptions of species and higher taxa have been known in parasitology since the first description of a parasite. Usually, they are based on standard morphometric methods or more modern genetic analysis. The former are not always sufficiently reliable, while the latter often require expensive equipment, pre-defined genetic markers, and appropriately prepared research material. They may be replaced by multivariate statistical methods, in particular discriminant analysis and cluster analysis, and Kohonen artificial neural networks included in data mining. This paper presents the examples of specific applications of these methods for the verification of the affinity of nematodes. The discriminant analysis showed that it was possible to statistically significantly discriminate individual nematode species, both for males and females, based on morphometric variables. This confirmed the previously assumed division of the species complex Amidostomum acutum into three distinct species. Similarly, hierarchical cluster analysis, used for the determination of coherent groups of nematode parasites, allowed the identification of relatively homogeneous clusters of nematode species depending on their circle of hosts, and groups of hosts.

The aim of this study was to relate polymorphic variants of CYP19, CYP21 and ER1 genes to reproductive traits in 472 Polish Holstein-Friesian cows. High frequencies of one of the homozygous genotypes were found. The ER1/SnaBIAA homozygotes were not identified. In the first and third lactation, an average calving-to-conception interval (CLVC) in cows of ER1/SnaBIGG genotype was significantly shorter (P ≤ 0.05) than in heterozygous cows. In the cows of ER1/BglIGG genotype, significantly shorter CLVC (P ≤ 0.05) was observed compared to heterozygotes in the first lactation, whereas in the third lactation, CLVC in homozygous cows was significantly longer (P ≤ 0.05) than in heterozygous ones. It was also found that homozygous cows were characterized by significantly longer calving interval (CLVI; P ≤ 0.05) compared to heterozygotes in the third lactation. Longer CLVCs in CYP19AA cows were found, compared to heterozygotes, and this difference was significant in the first and third lactation (P ≤ 0.05). Similarly, the average CLVIs were longer in CYP19AA homozygotes than in heterozygous cows; however, significance was proven only in the third lactation (P ≤ 0.05). Description of the molecular mechanisms regulating reproduction, and thus identification of the individuals of genotypes with optimal potential may facilitate the employment of selected reproductive model by a breeder.

In the present study, the detection of cows with artificial insemination (AI) difficulties using selected statistical and machine learning methods is presented. Cows were divided into two classes: those that conceived after one or two services (''GOOD'') and those that required more than two services per conception (''POOR''). The best performance was exhibited by one of the artificial neural networks (ANN) and the multivariate adaptive regression spline (MARS) method (AIC, BIC, RMS and accuracy); whereas logistic regression (LR) and classification functions (CF) were of somewhat lower quality. The detection of cows with AI difficulties, performed on the basis of the test set comprising new instances, showed that the ANN and MARS were more precise in comparison with the statistical methods. Sensitivity and specificity were over 85% for the perceptron with two hidden layers (MLP2) and MARS and approximately 80% or lower for LR and CF. From among variables determining the AI category, the average calving interval and cow body condition index were the most important. Other significant variables were lactation number, pregnancy length, sex of calf from previous calving and cow age. The prognoses obtained using ANN and MARS can be used for the appropriate preparation of cows for AI.

The quality of life (QoL) in patients with advanced venous insufficiency (including venous stasis ulcers, skin discoloration, stasis eczema, and lipodermatosclerosis) assessed using the Clinical Etiological Anatomical Pathophysiological (CEAP) and Venous Clinical Severity Score (VCSS) classifications is presented. Also, disease features such as: intensity of pain, edema and inflammatory response that exerted the most profound effect on different domains of QoL are reported. The global QoL in patients with lower leg venous ulcerations was relatively similar to that observed in other patients with chronic venous insufficiency. The presence of venous ulcerations was associated with lower QoL in a Physical domain. Significant correlations were found between pain intensity and the values of Physical, Physiological, Level of Independence and Environmental domains, between edema intensity and Social domain as well as between the intensity of inflammatory response and Physical and Spiritual domains.

Data mining techniques involve mainly searching for various relationships in large data sets. However, they can also be used in a much narrower range, sometimes as an alternative to classical statistics. The characteristic feature of these models is the use of a specific strategy, usually requiring the division of data into training set, sometimes also verification set, which enable the evaluation of the model quality as well as a test set for checking its prognostic or classification abilities. Among many different methods belonging to data mining, the following can be distinguished: the general models of classification and regression trees (G_Trees), general CHAID (Chi-square Automatic Interaction Detection) models, interactive classification and regression trees (also with boosting – Boosted Trees), random forest, MARS (Multivariate Adaptive Regression Splines), artificial neural networks (ANN), other machine learning methods such as: naive Bayes classifier (NBC), support vector machines (SVM), k-nearest neighbors (k-NN) and other regarded (or not) by different authors as data mining techniques. These methods are more and more frequently applied to various issues associated with animal breeding and husbandry.

PURPOSE To obtain ultrasonographic measurements of ocular axial length (AL) in preterm infants without retinopathy of prematurity (ROP) but with different refractive power in regard to birth weight (BW) and gestational age (GA). METHODS Refraction was measured after cycloplegia (at 6 months of life) in 350 eyes of 180 preterm (non-astigmatic) infants without ROP. Subjects were grouped according to the refractive error: A [above -6.0 dioptres (D)]; B (-3.1 to -6.0 D); C (0 to -3.0 D); D (0.1 to +3.0 D); E (+3.1 to +6.0 D); F (above +6.0 D). The AL measurement was performed by ocular A-scan ultrasound biometry (10 MHz probe). RESULTS The longest AL was found in group B (20.62 mm) compared to group D and E (19.35, 19.28 mm; P< or =0.01) and group F and A (19.63, 19.39 mm; P< or =0.05). Only regressive correction for BW was statistically significant. Correlations between AL and BW (Rs=0.23) or GA (Rs=0.17) were found only in group E. CONCLUSIONS AL of myopic eyes was significantly longer. In general, hyperopia was positively correlated with BW, whereas correlation between myopia and BW or GA was not found.

Background: Dystocia in cattle results in adverse consequences (increased calf morbidity and mortality, decreased fertility, and milk production, lower cow survival and reduced welfare) leading to considerable economic losses. Objective: To classify calvings in dairy cattle according to their difficulty using selected data mining methods [classification and regression trees (CART), chi-square automatic interaction detection trees (CHAID) and quick, unbiased, efficient, statistical trees (QUEST)], and to identify the most significant factors affecting calving difficulty. The results of data mining methods were compared with those of a more traditional generalized linear model (GLM). Methods: A total of 1,342 calving records of Polish Holstein-Friesian black-and-white heifers from four farms were used. Calving difficulty was divided into three categories (easy, moderate and difficult). Results: The percentages of calvings correctly classified by CART, CHAID, QUEST, and GLM were as follows: 35.14, 18.92, 19.82, and 43.24% (easy), 68.70, 73.91, 81.74, and 41.74% (moderate), and 77.27, 85.45, 73.64, and 81.82% (difficult), respectively. The most important factors affecting calving difficulty were bull’s rank (based on the mean calving difficulty score of its daughters), calving age, farm category (based on its mean milk yield) and calving season. Conclusion: All classification models were satisfactory and could predict the class of calving difficulty. Keywords: classification , dairy heifers, decision support systems, dystocia, electronic learning. Resumen Antecedentes: La distocia en el ganado resulta en consecuencias adversas (elevadas morbilidad y mortalidad de terneros, reducida fertilidad y produccion de leche, menor supervivencia y bienestar de las vacas) que conllevan a perdidas economicas considerables. Objetivo: Clasificar los partos del ganado lechero en funcion de su grado de dificultad a traves de metodos seleccionados de mineria de datos [arboles de clasificacion y de regresion (CART), deteccion automatica de interaccion chi-cuadrado (CHAID) y arboles estadisticos no sesgados y eficientes (QUEST)] e identificar los factores mas caracteristicos de dificultad al parto. Los resultados de los metodos de mineria de datos se compararon con los del modelo lineal generalizado tradicional (GLM). Metodos: Se utilizaron 1.342 registros de parto de novillas de raza polaca Holstein-Friesian blanca y negra de cuatro explotaciones lecheras. La dificultad de parto del ganado se dividio en tres categorias (facil, moderado y dificil). Resultados: El porcentaje de partos correctamente clasificados por CART, CHAID, QUEST y GLM fue 35,14, 18,92, 19,82 y 43,24% (facil), 68,70, 73,91, 81,74 y 41,74% (moderado), y 77,27, 85,45, 73,64 y 81,82% (dificil), respectivamente. Los factores mas importantes de dificultad de parto fueron el rango de toro (determinado sobre la base de dificultad media de los partos de sus hijas), la edad al parto, la categoria de las fincas (sobre la base del rendimiento medio de leche) y la temporada de parto. Conclusion: Todos los modelos de clasificacion se caracterizaron como satisfactorios y podrian predecir la clase de dificultad al parto. Palabras clave: aprendizaje electronico, clasificacion, distocia, novillas lecheras, sistemas de soporte de decisiones. Resumo Antecedentes: A distocia em bovinos resulta em consequencias adversas (aumento da morbidade e mortalidade dos bezerros, diminuicao da fertilidade e da producao de leite, baixa sobrevivencia da vaca e reducao do bem-estar) levando a consideraveis perdas economicas. Objetivo: Classificar os partos do gado leiteiro segundo o seu grau de dificuldade atraves dos metodos selecionados de data mining [arvores de classificacao e regressao (CART), deteccao automatica de interacao chi-quadrado (CHAID) e ârvores estatisticas eficientes e rapidas e imparciais (QUEST)] e identificar os fatores mais importantes para a dificuldade nos partos. Os resultados dos metodos de data mining foram comparados com os resultados do modelo lineal generalizado (GLM) mais convencional. Metodos: Foram utilizados 1.342 registos de partos de novilhas da raca polaca Holstein-Frisia branca e preta de quatro fazendas. A dificuldade em um parto foi dividida em tres categorias (facil, media, dificil). Resultados: A percentagem de partos corretamente classificados atraves de CART, CHAID, QUEST e GLM foram de 35,14, 18,92, 19,82 e 43,24% (facil), 68,70, 73,91, 81,74 e 41,74% (media) e 77,27, 85,45, 73,64 e 81,82% (dificil), respetivamente. Os fatores mais importantes de dificuldade no parto foram a classifi cacao do touro (determinada com base na dificuldade media nos partos de suas filhas), a idade no momento de parto, a categoria de exploracao leiteira (com base no rendimento medio de leite) e a temporada de parto. Conclusao: Todos os modelos de classificacao destacaram-se por sua qualidade satisfatoria e foram capazes de prever a categoria de dificuldade de um parto. Palavras chave: aprendizagem electronica, classifi cacao, distocia, novilhas leiteiras, sistemas de apoio a decisao.

Associations between two polymorphisms localized in the seventh exon of the butyrophilin gene (BTN/HaeIII and BTN/SchI) and milk production traits of Jersey cattle were analysed. A total of 171 cows were included in the study. PCR-RFLP method was used. In both polymorphisms three genotypes were identified. Statistically significant differences between polymorphic variants and milk production traits of Jersey cows were observed. Those differences concerned the percentage fat content in milk in the case of both polymorphisms and additionally the yield of milk and protein in the case of BTN/HaeIII polymorphism. The influence of the combined genotypes (BTN/HaeIII/SchI) on the examined traits was also analysed. GGHaeIII/AGSchI combined genotype was characterized by a significantly lower percentage fat content in comparison to other combinations. Moreover, incomplete linkage between the studied polymorphic sites was observed, despite relatively small distance between them.