The main subject of the research is the assessment of the knowledge, attitudes and behaviors of veterinarians regarding the use of antibiotics (AMU) and antimicrobial resistance (AMR) through a questionnaire conducted among veterinarians in the northern region of Serbia. A total of 62 respondents completed the questionnaire, which represents a response rate of 44.3%. Male veterinarians are less likely to be in the group of veterinarians with insufficient knowledge (p < 0.05). Veterinarians engaged in mixed practice (small and large animals) (p < 0.001) and veterinarians who have over 100 patients per month (p < 0.005) are also less likely to be in the group with insufficient knowledge of antimicrobial resistance. The proportion of those with insufficient knowledge is growing among veterinarians whose source is the Internet (p < 0.01), while the proportion of those with insufficient knowledge about antimicrobial resistance is declining among veterinarians whose source of information is continuous education (p < 0.05). The majority of the respondents (n = 59, 95.2%) completely agreed that AMR is a very big issue in the global health sector right now. Unfortunately, there are crucial gaps in the knowledge and attitudes of the surveyed participants. They do not appear to be aware of the importance of AMU in veterinary medicine and its influence on overall AMR, or the crucial part that non-prescribed antibiotics have in all of it. Positively, many veterinarians use good practice AMU guidelines in their everyday practice and in line with the global trend of AMU reduction, respondents have also decreased their AMU compared to the previous year.

A violência contra o idoso ocorre de forma frequente, principalmente por membros da família, se tornado uma grande problemática da área da saúde e necessitando de uma atenção especial. O presente estudo tem como objetivo identificar os cuidados em conjunto realizados pelos profissionais da saúde em situações de violência contra o idoso. Trata-se de uma revisão integrativa da literatura com uma abordagem qualitativa. O período de busca ocorreu no mês de maio de 2022. Onde foi realizada uma busca de artigos nas bases de dados Scientific Electronic Library Online (SCIELO), google acadêmico e o que está presente no estatuto do idoso. Utilizando os Descritores em Ciências da Saúde (DeCS) e Operadores Boleanos na respectiva sequência “Idoso AND Violência AND Equipes de saúde “. Foram utilizados critérios de elegibilidade para melhor se obter os artigos que abordassem a temática de interesse. Após isso realizou-se uma leitura do título e objetivo dos estudos. Após aplicação dos critérios de inclusão e exclusão, restaram 76 artigos que foram analisados. Sendo destes, 62 excluídos por não se encaixarem no foco da pesquisa, restando 10 artigos. Os estudos apontaram que os profissionais que compõem as equipes multiprofissionais de saúde são essenciais na identificação de casos de violência, pois tem proximidade com os pacientes e apesar das dificuldades encontradas podem intervir no combate a esses casos contribuindo na devolução da qualidade de vida dessas pessoas.

Background and objectives: The risk of low energy availability is related to various health problems in sports. This cross-sectional study aimed to identify a possible association between various dance factors, anthropometrics/body build, and energy availability with injury occurrence in contemporary dancers. Materials and Methods: The participants were 50 female competitive dancers (19.8 ± 4.1 years of age). The independent variables included age, dance factors (amount of training and competitions per week–exposure time, experience in dance), anthropometrics/body composition (body height, mass, BMI, body fat percentage (BF%), and fat-free mass (FFM)), and energy availability score (EAS; evaluated by accelerometer-based measurement of energy expenditure and Dance Energy Availability Questionnaires). The dependent variables were the occurrence of (i) soft-tissue injuries and (ii) bone injuries. The measurements were obtained by experienced technicians during the pre-competition period for each specific dance discipline. Univariate and multivariate logistic regressions were calculated to identify the associations between independent variables and injury prevalence. Results: The results showed that EAS (OR = 0.81, 95% CI:0.65–0.91), age (OR = 1.65, 95% CI: 1.1–2.46), higher BF% (OR = 1.23, 95% CI: 1.04–1.46) and BMI (OR = 1.61, 95% CI: 1.05–2.47) were correlated with soft-tissue injuries. Dancers who suffered from bone injuries reported higher exposure time (OR = 1.21, 95% CI: 1.05–1.37) and had lower values of FFM (OR = 0.73, 95% CI: 0.56–0.98). Multivariate regression analyses evidenced a higher likelihood of soft-tissue injuries in older dancers (OR = 1.75, 95% CI: 1.21–2.95) and the ones who had lower EAS (OR = 0.84, 95% CI: 0.71–0.95) while the exposure time was associated with a higher likelihood of bone injuries (OR = 1.21, 95% CI: 1.05–1.39). Conclusions: In order to decrease the injury prevalence among dancers, special attention should be paid to maintaining adequate nutrition that will provide optimal available energy for the demands of training and performing. Additionally, the control of training volume should be considered in order to reduce traumatic bone injuries.

MicroRNAs (miRNAs) are short non-coding RNAs that function in post-transcriptional gene silencing and mRNA regulation. Although the number of nucleotides of miRNAs ranges from 17 to 27, they are mostly made up of 22 nucleotides. The expression of miRNAs changes significantly in cancer, causing protein alterations in cancer cells by preventing some genes from being translated into proteins. In this research, a structural analysis of 587 miRNAs that are differentially expressed in myeloid cancer was carried out. Length distribution studies revealed a mean and median of 22 nucleotides, with an average of 21.69 and a variance of 1.65. We performed nucleotide analysis for each position where Uracil was the most observed nucleotide and Adenine the least observed one with 27.8% and 22.6%, respectively. There was a higher frequency of Adenine at the beginning of the sequences when compared to Uracil, which was more frequent at the end of miRNA sequences. The purine content of each implicated miRNA was also assessed. A novel motif analysis script was written to detect the most frequent 3–7 nucleotide (3–7n) long motifs in the miRNA dataset. We detected CUG (42%) as the most frequent 3n motif, CUGC (15%) as a 4n motif, AGUGC (6%) as a 5n motif, AAGUGC (4%) as a 6n motif, and UUUAGAG (4%) as a 7n motif. Thus, in the second part of our study, we further characterized the motifs by analyzing whether these motifs align at certain consensus sequences in our miRNA dataset, whether certain motifs target the same genes, and whether these motifs are conserved within other species. This thorough structural study of miRNA sequences provides a novel strategy to study the implications of miRNAs in health and disease. A better understanding of miRNA structure is crucial to developing therapeutic settings.

The paper proposes a Hybrid Electric Vehicle (HEV) design based on the installation of a fuel cell (FC) module in the existing Daewoo Tico electric vehicle to increase its range in urban areas. Installing an FC module supplied by a 2 kg hydrogen tank would not significantly increase the mass of the electric vehicle, and the charging time of the hydrogen tank is lower than the battery charging time. For design analysis, a model was created in the MATLAB/Simulink software package. The model simulates vehicle range at different HEV speeds for Absorbent Glass Mat (AGM) and Proton Exchange Membrane Fuel Cell (PEMFC) power sources. The greatest anticipated benefit derived from the model analysis relates to velocities ranging from 20 km/h to 30 km/h, although the optimal HEV velocity in an urban area is in the range of 30 km/h to 40 km/h. The results indicate that this conversion of Electric Vehicle (EV) to HEV would bring a benefit of 87.4% in terms of vehicle range in urban areas. Therefore, the result of the conversion in this case is a vehicle with sub-optimal characteristics, which are nevertheless very close to optimal.

Sweet cherry (Prunus avium L.) stems in the form of infusions and decoctions are traditionally consumed for diuretic and anti-inflammatory purposes. This study aimed to evaluate antimicrobial and antibiofilm activity of ethanolic and methanolic extract made from sweet cherry stems. Extracts are obtained by the Soxhlet extraction and maceration procedures. For the determination of the minimum inhibitory concentration, the broth microdilution method is employed, and the assessment of the microbiocidal activity of the extracts is conducted. The antibiofilm activity was tested through the tissue culture plate method, which also allowed the determination of the biofilm-forming categories of investigated strains. The final step involved the calculation of the biofilm inhibition percentage. Examined extracts with the balanced activity inhibited the growth of all microorganisms, with Gram-negative bacteria being more sensitive in comparison to Gram-positive. The values of the minimum inhibitory concentration were 125 µg/ml, and 250 µg/ml, respectfully. Candida albicans was the most susceptible and the minimum inhibitory concentration of both extracts was 62.50 µg/ml. The microbiocidal activity of the extracts was not recorded. Extracts exhibited different impacts on the biofilm-forming capacity of the investigated microbes, and both inhibition and stimulation effects are noted. The percentage of the biofilm inhibition was from 14.27% to 84.78%, with the highest inhibition recorded for the multidrug-resistant Escherichia coli, treated with the ethanolic extract. Sweet cherry stems are a valuable source of natural bioactive compounds, but their usage in the treatment of microbial infections should be correctly and carefully implemented.

This paper presents a fully-integrated optical sensor with SPAD and mixed quenching/resetting circuit with sensing stage based on a tunable-threshold inverter optimized for the standard 0.35-µm CMOS technology. The presented quencher features a controllable detection threshold voltage and an adjustable total dead time. The quenching circuit 5QC achieves 16.5 V excess bias voltage (five times the supply voltage). The dead time ranges from 7.5 ns to 51.5 ns, which corresponds to a saturation count rate range from 19.4 Mcps to 133.3 Mcps. The quencher is optimized for SPADs with a capacitance ranging from 50 fF up to 400 fF. Using our published measured photon detection probability (PDP) results and extrapolating them, a peak PDP of 75.6% at 652 nm and a PDP of 39.2% at 854 nm is estimated for VEX = 16.5 V. To the authors' best knowledge, the presented PDP result has never been reached before for a fully-integrated SPAD sensor in standard CMOS technology.

Lentigo maligna (LM) based on biopsy material might be lentigo maligna melanoma (LMM) after excision.

The aim of this study is to present a fully automatic deep learning algorithm to segment liver Colorectal cancer metastases (lmCRC) on CT images, based on a U-Net structure, comparing nets with and without the transfer learning approach. This is a bi-centric study, enrolling patients who underwent CT exam before (baseline) and after first-line therapy (TP1). Patients were divided into training (using a portion of baseline sequences from both centers) to train the DL model, and two validation sets: one with baseline (valB), and one with TP1 (valTP1) sequences. The reference standard for the automatic segmentations was defined by the manual segmentations performed by an experienced radiologist on the portal phase of the baseline and TP1 CT exam. The best performing model obtained Dice Similarity Coefficient (DSC) of $0.68\pm 0.24$, Precision (Pr) of $0.74\pm 0.27$, Recall (Re) of $0.73\pm 0.26$, Detection Rate (DR) of 93% on the valB, and DSC of $0.61\pm 0.28$, Pr of $0.68\pm 0.31$, Re of $0.65\pm 0.29$ and DR of 88% on the valTP1. These encouraging results, if confirmed on larger dataset, might provide a reliable and robust tool that can be used as first step of future radiomics analyses aimed at predicting response to therapy, improving the management of lmCRC patients.

The use of Deep Learning (DL) algorithms in the medical imaging field is increasing in recent years. However, they require the selection of a set of parameters to properly perform. In this study we evaluated the impact of three factors (the construction of the training set, the number of network layers and the loss function) on the performance of a U-Net system in the segmentation of Locally Advanced Rectal Cancer (LARC) on Magnetic Resonance Imaging (MRI). Images from 3 different institutions and 4 different scanners were used to this scope, for a total of 100 patients. All images underwent a pre-processing step to normalize and to highlight the tumoral area. The sequences of two scanners were used to construct the networks while the remaining sequences were employed for validating the best performing systems. From our results, it emerged that Dice Similarity Coefficient is not affected by any of the evaluated factors. Conversely, the choice of loss function could bias the results towards either precision or recall and, thus, it should be properly performed according to the scope of the network. Moreover, a slightly improvement of the performances was observed using a training set based on clustering, maybe due to a better representation of the heterogeneity characterizing medical images.

An analysis of students’ difficulties for a curricular topic may help the educator to gain better insight into students’ reasoning about that topic which is a prerequisite for high-quality teaching. The purpose of this study was to demonstrate how distractor analysis may be used for identifying students’ difficulties in a certain topic. In order to be in position to perform invariant measurement and to easily relate students’ difficulties to their achievement levels, we decided to take a Rasch modeling approach. Our study included 14 wave optics items and 286 students from five universities in Slovenia, Croatia, and Bosnia and Herzegovina. Rasch modeling was used to estimate item and student measures, as well as to create option probability curves which allowed us to relate students’ achievement levels to the choice of individual distractors. It has been found that all 14 included items function in line with the Rasch model. In 10 out of 14 items there were distractors chosen by at least 25% of students. For several out of these 10 items, the option probability curves indicated that attractiveness of individual distractors depended on students’ ability levels. We could conclude that the Rasch-based distractor analysis may provide very useful information for differentiation of physics instruction.