Search

Matrix metalloproteinases (MMPs) and A disintegrin and metalloproteinases (ADAMs) are enzymes able to degrade a variety of protein components of the extracellular matrix. Due to the diverse role of MMPs and ADAMs, they are involved in the pathogenesis of many diseases, including chronic inflammatory lung diseases. In this review, the objective is to summarize the current knowledge about the role of the two enzymes from the respective families, namely MMP-8 and ADAM-33, in Bronchial asthma in order to explore the possibility for their expression, polymorphisms or serum/BAL (Bronchoalveolar Lavage) concentration to be used as biomarkers or targets for future target therapy. Considering the key functions of MMP-8 and ADAM-33 in many pathologic conditions, development of proper inhibitors of their action might be useful tools in the treatment approaches. However, a lot of knowledge has yet to be gained about these enzymes and their role in bronchial asthma, since some of the mechanisms are unknown or not discovered yet.

The aim of the present research was to study the influence of the calving season in conditions of the upcoming climate changes on the productive traits of dairy cows in Bulgaria. The study was conducted on a cattle farm with a capacity of 500 dairy cows, which were loose-housed in open free-stall barns (shed-type). In the research, 286 lactations of 199 Holstein cattle from the studied farm were included. The cows with the highest average milk yield for lactation—8522.2 kg—calved in the spring, while the cows with the lowest milk yield—8082.7 kg—calved in the summer. Cows that calved in the spring had the highest maximum daily milk yield (lactation peak)—38 kg—whereas cows that calved in the summer had the lowest—35.7 kg. Regarding the composition indicators of milk, fat, and protein content, no significant effect of the calving season was found, but there was a tendency for the lowest values for the percentage of fat in milk to be reported for cows that calved in the summer—3.68%—and the highest for those calved in the spring—3.71%. Regarding the percentage of protein in the milk, the lowest values were observed for cows that calved in autumn—3.19%—and the highest for cows that calved in summer—3.27%.

Noise is defined as unwanted sound, whether chronic or periodic, and can be described in a variety of terms, including its frequency, intensity, frequency spectrum, and sound pressure shape over time. The sources of noise can be technical devices, various hydraulic systems, the engines of various machines, routine work (opening and closing doors, repairing stalls, talking of workers, feeding), mechanical ventilators, animal activities, including climbing barriers, chewing barriers, vocalizations of cows. Good farms in terms of noise level are considered to be those with a noise level up to 70 dB, while farms with a noise level above 70 dB are problematic. Noise levels above 70 dB also have a detrimental effect on cow welfare, and this is associated with a high number of somatic cells in milk. When milking dairy cows, the noise level should not exceed 65–70 dB, or if it exceeds this value, it should be for a short time, as this can lead to health disorders in humans and animals in the medium term.

Background and Objectives: One of the members of the neurotrophin (NT) family is the brain-derived neurotrophic factor (BDNF). In addition to its role in the nerve system, it has been found to play a role in lung health and diseases. Materials and Methods: The serum concentrations of BDNF were assessed in 57 patients with COPD and in 19 control individuals and the possible associations of BDNF with the spirometric indexes and disease stages were explored. Results: We did not find a significant difference between the serum concentrations of BDNF of patients and controls (p = 0.521). A significant negative correlation of the serum BDNF levels with the age of the patients (Rho = −0.279, p = 0.036) was observed. In addition, a borderline negative correlation with the age of disease onset (Rho= −0.244, p = 0.063) was also found. When analyzing these correlations in different genders, we found stronger statistical significance in male patients (Rho = −0.398, p = 0.009; and Rho = −0.419, p = 0.006), while no such significance was found in females (p = 0.574 and p = 0.342). The analyses of the possible relations of serum BDNF concentration with the spirometric parameters in the whole group of patients did not reveal any significance (p = 0.231 for FEV1%pr. and p = 0.271 for FEV1/FVC%). However, when the patients were dichotomized on the basis of smoking habits, we obtained a strong positive correlation between BDNF and FEV1%pr. (Rho = 0.501, p = 0.048) in non-smokers, but strong negative correlations with FEV1%pr. (Rho = −0.468, p = 0.003) and with FEV1/FVC% (Rho = −0.331, p = 0.040) in ex/current smokers. Non-smokers with moderate disease (GOLD II) had higher BDNF serum concentrations than patients with GOLD stage III/IV (p = 0.031). In ex/current smokers, there was an opposite association (p = 0.045). Conclusions: The results of our study suggest that the expression and secretion of BDNF are changed in COPD, but its effects and functions may differ according to the smoking history of the patients.

Evaluation and New Technologies in the Context of the Marco Polo - Turandot Project. The Marco Polo - Turandot Project of the University of Modena e Reggio Emilia provides Italian as a Second Language courses for young-adult Chinese students. The educational path is supplemented by a course on Italian Culture and Civilization which aims to introduce Chinese students to the fundamental elements of Italian culture in the form of lessons in L2 following the CLIL methodology. In the 2020/21 Project, due to the Covid-19 pandemic, lessons and testing activities were conducted online from the beginning of the course in November 2020 to April 2021; after that date the teaching activity was carried out in a mixed mode. Distance learning had a significant impact on evaluation and testing activities in both language and culture courses. In this work we will describe the different testing methods adopted during these months, the digital tools and the new technologies chosen to implement them. We will compare the different evaluation methods using data from surveys presented to students. We will also focus on the problems that emerged and on the impact of distance learning on the learning path of the students.

The role of matrix metalloproteinases (MMPs) in pathogenesis and severity of coronavirus disease 2019 (COVID-19) is under extensive exploration. MMPs are a family of extracellular proteases involved in a variety of physiological and pathological processes and conditions. The role of MMPs in COVID-19 stems from the pathogenesis resulting in the release of chemokines and pro-inflammatory markers which cause pulmonary oedema. In addition, the approaches to treatment of COVID-19 often are associated with some complications like acute lung injury due to extracellular matrix remodelling. In this respect, the aim of this review is to summarize, interpret and evaluate the significance of matrix metalloproteinases in SARS-CoV-2 infection in terms of the severity of the condition and delve into potential treatment from this perspective as well as highlighting the physiological and protective role of some MMPs.

The Aral Sea, once the fourth largest freshwater lake on Earth, has lost circa 90% of its original water surface in 1960. Maps of different land cover categories provide a suitable baseline to plan and implement effective measures to combat ongoing desertification, such as reforestation of dried out Aral Sea soils. In this study, we used satellite-based remote sensing data and applied a machine learning method (Random Forest) to map land cover in the Aralkum in 2020. We tested different satellite data from optical (Landsat-8, Sentinel-2) and Radar instruments (Sentinel-1) and trained a random forest model for classifying different combinations of these data sets into ten distinct land cover classes. We further calculated per-pixel uncertainty based on posterior classification probability scores. An accuracy assessment, based on in-situ data, revealed that the average overall accuracy of land cover maps was 86.8%. Fusing optical and radar instruments achieved the highest overall accuracy (88.8%, with lower/higher 95% confidence interval values of 87.6%/89.9%, and a Kappa value of 0.865. Classification uncertainty was lower in more homogeneous landscapes (i.e. large expanses of a single land cover class like water or shrubland). Only around 9% of the study area was still water in 2020, while 32% was covered by saline soils with high erosion risk. Several potential applications of this land cover map in the Aralkum exist – spanning many areas of environmental impact assessment, policy, and planning and management or afforestation. This methodological framework can similarly provide a useful template for more broadly assessing large-scale, land dynamics at high-resolution in the entire Aralkum and surrounding areas.

The aim of the current study is to explore the possible role of L55M, (rs 854560, 163T > A) SNP as a predisposing factor for acute coronary syndrome (ACS) and to assess its potency as a prognostic biomarker for short (1 year) survival and for median (5 years) and 9-year long patients’ outcome. Methods: The current work is a prospective case-control study with 77 patients with acute coronary syndrome (53 with ST-elevation myocardial infarction, STEMI, 14 with non-ST-elevation myocardial infarction, NSTEMI and 10 with unstable angina, UA) and 122 control individuals. Patients were followed-up for 9 years. The genotyping for PON1 L55M SNP was carried on by PCR-RFLP method. Results: The results of the genotyping for PON1 L55M SNP showed a statistically significant difference (p = 0.023) between the controls and the whole group of patients with acute coronary syndrome, as the individuals with genotype with at least one variant M allele had about 2.5-fold higher risk for developing ACS than those which are homozygous of the wild-type L allele (LL genotype). In patients with variant M allele genotypes (LM + MM) which suffer from non-ST-segment elevation ACS (NSTEACS, i.e., UA or NSTEMI), the serum levels of total cholesterol (TC) and triacylglycerols (TAG) are significantly higher than in NSTEACS patients with LL genotype (p = 0.022 for TC and p = 0.015 for TAG). There was no significant difference in the survival rate at the 1st, 5th and 9th year of follow-up between ACS patients with different genotypes, although it is worth to note that in the subgroup of NSTEACS, all patients (n = 13) with variant M allele genotypes (LM + MM) were alive at the end of the first year, while 2 of the patients with LL genotype (18.2%) were dead. Conclusions: The results of our current study suggest that the variant M allele and the M allele genotypes (LM + MM) of the PON1 L55M polymorphism are risk factors for acute coronary syndrome, especially for patients with STEMI, but do not support the possible effect of this polymorphism on the clinical progression and outcome of the patients with ACS either in short or long follow-up periods.

Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation and oxidative stress both in the airways and blood and other organs. Elevated oxidative stress and inflammation have been reported to affect leucocyte telomere length (LTL). Glutathione S-transferase (GST) enzymes are a large family of xenobiotic-metabolizing enzymes that utilize different ROS products. We aimed to explore the link between GSTM1 and GSTT1 gene polymorphisms, LTL and COPD risk. For GSTM1, we genotyped 152 COPD patients and 131 non-affected controls; for GSTT1, we genotyped 149 COPD patients and 130 controls. We were able to assess TL for 91 patients and 88 controls. There was a significant difference in the GSTM1 null genotype frequency between the patients and controls (0.59 vs. 0.38, p ≤ 0.000), but such was not found for GSTT1 (p = 0.192). When combining both polymorphisms, we obtained a significantly greater presence of at least one null genotype among patients (0.12 vs. 0.05, p = 0.027). An association between GSTT1 and LTL was not found. COPD patients carrying the GSTM1 null genotype had shorter telomeres compared to those carrying the non-null genotype (15,720 bp vs. 22,442 bp, p = 0.008); as for the controls, it was the opposite (31,354 bp vs. 17,800 bp, p = 0.020). The significance in both groups remained when combining GSTM1 and GSTT1 (COPD (at least one null) 16,409 bp vs. COPD (non-null) 22,092 bp, p = 0.029; control (at least one null) 29,666 bp vs. control (non-null) 16,370 bp, p = 0.027). The total glutathione level in GSTM1 non-null controls was higher compared to the null genotype (15.39 ng/mL vs. 5.53 ng/mL, p = 0.002). In COPD patients, we found no association (p = 0.301). In conclusion, according to our results, GSTM1, but not GSTT1, null genotypes might play a role in leucocyte telomere shortening, and thus be involved in the pathogenesis of COPD.

The paper proposes an approach for estimating the rectal temperature of dairy cows based on the non-invasive real-time monitoring of their respiration rates and the temperature-humidity index (THI) of the environment, combined with the analysis of infrared images. We use multimodal machine learning for the joint processing (fusion) of these different types of data. The implementation is performed using a new open source AutoML Python module named AutoGluon. After training and optimizing three different regression models (a neural network and two powerful boosting algorithms), it reduces the variance of the result using level 2 stacking. The evaluation metrics we work with are the mean absolute error, MAE, and the coefficient of determination, R2. For a sample of 295 studied animals, a weighted ensemble provides quite decent results: R2=0.73 and MAE ≈0.1 °C. For another sample of 118 cows, we additionally use the pulse rate as a predictor and we achieve R2=0.65, MAE ≈0.2 °C. The maximal error is almost 1 °C due to outliers, but the median absolute error in both cases is significantly lower: MedAE <0.1 °C, with the standard deviations respectively being 0.118° and 0.137°. These encouraging results give us confidence that tabular and visual data fusion in ML models has great potential for the advancement of non-invasive real-time monitoring and early diagnostics methods.

The study was carried out in the milking parlor of a dairy cattle farm consisting 500 animals from Holstein-Friesian breed in Bulgaria. The animals were housed in a freestall dairy barn and milked in double-8 milking parlor “herringbone” type. The level of noise was measured three times in every milking (at the beginning, in the middle and at the finishing of the milking) in the morning, midday and evening milking every month for one year. The noise level in the working environment was recorded by noise meter„ Lutron SL-4023SD. The highest noise levels were reported in summer and winter, with maximum values up to 78.3 dB. It was found that regardless of the season during the morning milking the lowest noise levels in the milking parlor were reported (from 70.37 to 70.46 dB). The average values for noise level for an 8-hour working day by seasons varied from 69.87 dB to 74.36 dB, with the highest reported value for the winter season.

Accurate agricultural yield prediction is a fundamental tool for sustainable agricultural planning and to ensure food security in regions critically affected by climate change and extreme weather events. Existing regression-based crop yield estimation approaches typically rely on a specific set of predictor variables, but have not been compared systematically. This paper demonstrates and compares the utilization and the combinatorial use of three different sets of object-based predictors for sugarcane yield estimation through the agricultural monitoring platform ag|knowledge which utilizes earth observation data of the Sentinel-2 satellites, captured between 2018 and 2019 for a study area of about 10,000 hectares in Ethopia. We compare several regression models using a range of different predictor variables, such as (i) multi-temporal variables (i.e., parcel-based vegetation index time series), (ii) time series descriptors (i.e., phenological metrics) and (iii) spatio-temporal variables. We achieve R² scores of up to 0.84 for the estimation of sugarcane yield and up to 0.82 for the estimation of sugar quantity through Random Forest regression, based on the combinatorial use of all predictor variables. Our experiments demonstrate that dimensionality-independent phenological metrics achieve good yield estimation results which could be a very useful variable set for model transfer and domain adaptation.

In this paper, we demonstrate the capabilities of Pleiades-1a imagery for very high resolution (VHR) crop yield estimation by utilizing the predictor variables from the horizontal-spectral information, through Normalized Difference Vegetation Indices (NDVI), and the vertical-volumetric crop characteristics, through the derivation of Crop Canopy Models (CCMs), from the stereo imaging capacity of the satellite. CCMs captured by Unmanned Aerial Vehicles are widely used in precision farming applications, but they are not suitable for the mapping of large or inaccessible areas. We further explore the spatiotemporal relationship of the CCMs and the NDVI for five observation dates during the growing season for eight selected crop fields in Germany with harvester-measured ground truth crop yield. Moreover, we explore different CCM normalization methods, as well as linear and non-linear regression algorithms, for the crop yield estimation. Overall, using the Extremely Randomized Trees regression, the combination of CCMs and NDVI achieves an R2 coefficient of determination of 0.92.

The survey was conducted in workers in dairy farming in Bulgaria. In the survey were not reported Thermal Work Limit (TWL) index values, which require cessation of employment and constitute a danger to human health. The lowest values of TWL were registered during the summer and spring months, respectively 229.3 and 258.4 W/m2. The highest are normally registered in the autumn and winter months - 318.3 and 312.2 W/m2. Outdoor the lowest average TWL values were reported in the summer and spring months 236 and 287.9 W/m2, respectively, and the highest in the autumn and winter months - 316.4 and 317.2 W/m2. An inverse dependency was found between the calculated values of Temperature-humidity index (THI) and the TWL.

The subject of the study are the most commonly used bedding materials in freestall housing system in dairy cattle farming and the factors determining their choice. In recent years, in many countries as well as in Bulgaria there has been a tendency to change from small dairy cattle farms to larger ones by applying intensive farming systems. Many factors must be taken into account when developing appropriate interior design of dairy freestall barns. Among these factors is the providing of comfortable resting places with minimal risk of body injuries and bacterial infections. The bedding must meet many conditions: to be inexpensive, dry, not to support bacterial growth, not to contain pathogens, to be comfortable for cows to rest, and to be compatible with the manure cleaning system. Increased amounts of bedding have been shown to increase cow comfort by increasing the lying time, however controlling bacterial counts and udder health requires frequent removal of bedding material. The most widely used bedding materials in dairy cattle farming worldwide can be grouped into two main groups: organic - straw, hay (dried grass), sawdust, wood shavings, crop residues, composted manure and paper, and inorganic: sand, limestone, gypsum, rubber mats and mattresses, cement. When choosing bedding, first the comfort that it will provide to the animals must be considered, then whether the bedding will properly match the manure cleaning system and last but not least the price it will cost.

Chronic obstructive pulmonary disease (COPD) is characterized by irreversible airflow obstruction and is associated with chronic local and systemic inflammation and oxidative stress. The enhanced oxidative stress and inflammation have been reported to affect telomere length (TL). Furthermore, a number of SNPs at loci encoding the main components of the telomerase genes, TERT and TERC have been shown to correlate with TL. We aimed to explore the leukocyte TL and genotypes for single nucleotide polymorphisms, rs12696304 (C > G) and rs10936599 (C > T) near TERC in COPD cases and matched healthy controls using q-PCR technologies. Successful assessment of TL was performed for 91 patients and 88 controls. The patients had shorter TL (17919.36 ± 1203.01 bp) compared to controls (21 271.48 ± 1891.36 bp) although not significant (p = 0.137). The TL did not associate with the gender, age, spirometric indexes, smoking habits but tended to correlate negatively with BMI (Rho = − 0.215, p = 0.076) in the controls, but not in COPD patients. The genotype frequencies of the SNPs rs12696304 and rs10936599 were compared between patients and controls and the odds ratios (OR) for developing COPD were calculated. The carriers of the common homozygous (CC) genotypes of the SNPs had higher risk for COPD, compared to carriers of the variants alleles (rs12696304 CG+GG vs. CC; OR: 0.615, 95% CI [0.424–0.894], p = 0.011 and for rs10936599 CT+TT vs. CC OR = 0.668, 95% CI [0.457–0.976], p = 0.044). Analysis on the combined effects of the TERC rs12696304 (C > G) and rs10936599 (C > T) genotypes, CC/CC genotype combination was associated with higher risk for COPD (p

In recent years the dairy farming massively went from tied to free housing of dairy cows, and more widely in conditions of Bulgaria the semi open free‑stall barns housing system is applied. One of the main factors associated with cow comfort in this housing system are the dimensions and design of the individual stalls. Indicators for stall comfort can be postures of cows when using the – standing with four or two legs in the stall, standing or lying diagonally, lying back in the stall, and more, these postures can also greatly guide us on the specific design problems that make stalls uncomfortable for the animals. In uncomfortable stalls cows spend less time resting and more time standing on the concrete floor of the technological alleys. Comfort indices are quickly and easily applicable to assessing comfort when used in general practice. For their correct application, careful consideration should be given to factors that affect their values ‑ farm activity schedule, time of reporting during the day, season of reporting, etc.

The aim of the study was to investigate the risk factors for formation of hock lesions in dairy cattle farms with different housing system. The study included 508 Black‑and‑white Holstein‑type cows from 14 dairy farms in different regions of Bulgaria. On cows a hock lesion assessment (scale 1 to 3) and body condition scoring (scale 1 to 5) were made. From the total number of cows, 231 cows (45.5 %) with score of 2 and 3 were reported, which clinical manifestation was from loss of hairs on the hock joint surface to swellings and wounds. A statistically significant effect of lactation period, body condition scores (BCS) and housing system on the hock assessment score was found. The least square means (LSM) for hock assessment score increased with the advancing of lactation period from 1.22 in cows to 60 days in milk (DIM) to 1.52 in cows after 120 DIM. The percentage of cows with BCS 3 and 3.5 was lower 1.5 to 2 times compared to cows with BCS 1.5. With the lowest mean hock assessment score (1.14), were the cows housed free group on a thick bedding. Tie‑stall housing system occupied an intermediate position with respect to hock assessment, only 1.4 % of cows were with a score of 3. The highest percentage of cows with varying degrees of hock lesions were reported in free‑stall housing system with using of rubber mats for stall floors, 75.5 % of the cows were with hock lesion assessment score 2 and 3. This percentage was slightly lower when small amounts of straw were placed on the rubber mats.

Design science (DS) approaches have been emerging in engineering, management and other disciplines operating at the interface between design research and the natural or social sciences. Research informed by DS is challenging because it involves “mixing oil with water”, using a famous phrase of Herbert Simon. A key challenge here is the dual role of theory: one can develop a “theory of” any empirical phenomenon to explain its characteristics and outcomes, or alternatively, develop a “theory for” generating this phenomenon, focused on solving problems and enlarging possibilities. To clearly distinguish these two perspectives, we talk about theorizing in relation to theory-of and framing related to theory-for. A state-of-the-art review of how DS is applied by management researchers results in two main findings. First, explicit (re)framing efforts appear to be highly instrumental in challenging a given theoretical paradigm and thereby reduce the risk of being constrained to it; these findings confirm the generative nature of design activity. Moreover, many studies reviewed draw on knowledge formats that synthesize descriptive-explanatory and prescriptive-normative knowledge. Our main findings are subsequently integrated into a DS methodology, which may especially be of interest to design-oriented disciplines that tend to adopt a rather intuitive (undefined) notion of theory.