Spinal cord disorders in dogs, such as Intervertebral Disc Degeneration, Degenerative Myelopathy, and Degenerative Lumbosacral Stenosis, significantly impact canine health and quality of life. These conditions, varying in manifestation but common in their progressive deterioration, are influenced by factors such as breed, age, and gender, highlighting the complexity of spinal issues in canines. Advanced imaging technologies play a crucial role in diagnosing and managing these disorders. Conventional radiography is vital for initial assessments, while advancements in computed tomography (CT) have enhanced the resolution and accuracy of images, particularly of the spine's bony structures. Magnetic resonance imaging (MRI) remains the preferred modality for its superior ability to depict both bone and soft tissue details, essential for comprehensive evaluations. CT is invaluable for detailed visualization of bone abnormalities, fractures, and degenerative changes, aiding in accurate disease diagnosis and intervention planning. However, due to its limitations in soft tissue assessment, the selection of imaging modalities must be tailored to specific clinical needs. This concise overview emphasizes the importance of a comprehensive diagnostic approach in managing canine spinal disorders and suggests the potential for translational research to benefit both veterinary and human medicine.

VHL disease is an inherited and autosomal dominant disorder affecting 1 in 36,0000 individuals worldwide. It is caused by von Hippel-Lindau (VHL) gene mutations and can affect both genders and all ethnic backgrounds (Nordstrom-O'Brien et al., 2009; Maher, 2004). Here, we generated and characterised two iPSC lines derived from patients with histopathologically confirmed clear cell renal cell carcinoma (ccRCC) and VHL Type 1 enrolled in the TRACERx Renal (TRAcking Renal Cell Carcinoma Evolution Through Therapy (Rx)). PBMCs were reprogrammed to pluripotency using a genome non-integrating Sendai virus (SeV) vectors protocol. Both human iPSC lines displayed normal morphology, expressed markers associated with stemness and differentiated into the three germ layers. The iPSC lines could be used as a disease-specific cellular model to understand furtherthe inherited disorder of Type 1 von Hippel-Lindau (VHL) disease.

BACKGROUND There is limited and conflicting data on the reduction of circulatory inflammatory mediators in patients with apical periodontitis (AP) following endodontic treatment. OBJECTIVE To answer the following research question: in adult healthy patients with AP [Population (P)], is there a difference before [Comparator (C)] and after various endodontic treatments (nonsurgical, surgical or retreatment) [Intervention (I)] on systemic levels of inflammatory biomarkers [Outcome (O)] in the follow-up period [Time (T)]? METHODS An electronic literature search was conducted in the databases Scopus, PubMed, Clarivate Analytics' Web of Science, Cochrane Database of Systematic Reviews and Grey literature from inception to July 2024 with no language restrictions. Observational studies examining changes in serum levels of inflammatory mediators were included. Two independent reviewers selected studies, extracted data and critically appraised the included studies. Qualitative and quantitative (meta-analysis) data synthesis methods were employed. The Newcastle-Ottawa Scale was used to assess the quality of the included studies. RESULTS Sixteen studies met the inclusion criteria, of which six were included in the meta-analysis. These studies were published between 1992 and 2024, involving a total of 596 patients (54% females) aged between 16 and 75 years. The meta-analysis of pooled data showed a significant decrease in high-sensitive C-reactive protein (hs-CRP) levels in the serum of patients with AP 6 months after treatment [2.26 ± 1.76 versus 1.28 ± 1.06 mg/L, (Z = 2.03, p = .04)] and a decrease in interleukin-1β (IL-1β) levels 12 months after treatment [13.01 ± 5.95 versus 10.86 ± 3.52 pg/mL, (Z = 3.72, p < .01)]. One study was assessed as poor quality, while all others were considered high quality. DISCUSSION Despite the differences in methodologies across the included studies, it has been established that effective endodontic treatment leads to a reduction in systemic inflammatory biomarkers in the body. CONCLUSION Following effective endodontic treatment in patients with AP, the systemic levels of hs-CRP and IL-1β exhibit a significant reduction at 6 and 12 months, respectively. Further clinical studies should investigate whether effective endodontic treatment and reduced levels of investigated biomarkers may change the clinical presentation of systemic diseases. REGISTRATION PROSPERO database (CRD42024559271).

More and more investments are being made in energy conversion projects from renewable energy sources (RESs), and a large number of investors are entering this sector. The focus of this study is the decision-making by the investor BD Green Energy in the Brčko District of Bosnia and Herzegovina. In order to choose the RES system that would realize this investment in the most efficient way, expert decision-making based on the fuzzy–rough approach and the Bonferroni mean operator was used. Determining the importance of the criteria was conducted using the fuzzy–rough SiWeC (simple weight calculation) method. The results of this method showed that all used criteria have similar importance for the investor. RES system selection was conducted using the fuzzy–rough CoCoSo (combined compromise solution) method. The results of this method showed that investing in photovoltaic (PV) energy is the best for the investor. This research provided guidance on how investors should make investment decisions in RES systems with incomplete information and uncertainty in the decision-making process.

Sclerosing mucoepidermoid carcinoma (SMEC) of the salivary glands is a rare variant of low-grade mucoepidermoid carcinoma with scanty cellular atypia characterized by marked fibrosis/sclerosis and a rich inflammatory infiltrate. Herein, we report 25 unpublished cases of SMEC, two of them with prominent eosinophilia (2/25; 8%) and three with abundant IgG4-positive plasma cells (3/25; 12%). In our series of salivary SMEC, molecular analysis using fluorescence in situ hybridization (FISH) and/or next-generation sequencing (NGS) provided evidence of MAML2 gene rearrangement in 18 cases of the 21 analyzable cases tested (86%), while this gene locus was intact in 3 cases (14%). This study focuses on the diagnostic criteria of salivary SMEC given its challenge of abundant collagenous stroma, minimal residual neoplastic areas, and inconspicuous mucous cells. Follow-up data of our cases indicate that salivary SMECs have favorable outcomes. Molecular analysis for MAML2 gene rearrangement suggests that SMECs of salivary glands represent a rare variant of conventional low-grade MECs of salivary glands. In contrast, SMECs of the thyroid gland are genetically distinct from salivary-type thyroid MECs.

The usage of natural materials is widely recognized, from the extensive resource potential, and low energy production to the possibilities of recycling in the building construction. This article aims to provide a systematic review of the correlation between the sustainable characteristics of the building material and its influence on the aesthetic experience, or the rather overlooked character of the material that significantly determines the spatial atmosphere and sensory perception of the architectural building. Precisely, to determine an interaction of criteria and indicators of materiality, wellbeing, and aesthetics. Natural building materials, besides providing a sustainable eco-friendly solution through a highly aesthetic appearance and material properties contribute to a multisensory experience, wellbeing, restorativeness, and human comfort. The application of natural materials in building construction recalls traditional principles enriched with contemporary demands, and resembles a conceptually expanded built natural environment that heightens the proven potential of this unlimited resource, from energy consumption to architectural experience. The integration of nature, environment, and overall natural resources into a symbiotic link with the architectural building is crucial, providing in that way a blurring between nature and architectural structure as an enhancement and richness of the sensory perception.

This paper examines the status quo of an urban void located among three key museums in Sarajevo: The National Museum, the Historical Museum, and the under-construction Contemporary Art Museum. This in-between space is controversial due to its designation in urban plans as the site for a major transversal road, intended to connect the northern and southern avenues via a four-lane road and bridge crossing the Miljacka River, which would disrupt the existing continuity of a prominent longitudinal green space. In the interim period before the road is developed, this void offers numerous possibilities for alternative uses and temporary public projects through tactical urbanism. One potential option is to develop the area into a museum quartier. Academic activities, workshops, and architecture studios have been organized to critically examine the key aspects of the urban plans within the context of political and economic transitions, and to juxtapose them with the goals of sustainable development and the actual priorities of Sarajevo's inhabitants. This paper aims to spark a discussion about the future of this urban threshold: whether it should be transformed into a transversal traffic link, or instead developed into a socio-cultural hub that fosters public activity. Through observation, projection, and experimentation with various activities and interventions, this study challenges the notions of "permanent temporality" and "temporary permanence" in this in-between space during the interim period awaiting future development.

In this study, the impact of glucocorticoid, betamethasone dipropionate on enzyme activity in vitro and its effects on hematological parameters in vivo was investigated. The immobilized catalase, crucial for cell oxidative stress response via hydrogen peroxide reduction, exhibited a robust electrocatalytic response, maintaining its biological activity. The in vitro inhibition kinetics of catalase, as determined by electrocatalytic methods and expressed using Lineweaver-Burke diagrams, revealed an uncompetitive type of inhibition with altered Imax and Km in the presence of a range of betamethasone dipropionate concentrations. The in vivo experiments conducted on Rattus norvegicus demonstrated significant alterations in hematological parameters following betamethasone dipropionate administration. These changes included a decrease in erythrocyte count, an increase in hemoglobin, a reduction in mean corpuscular volume (MCV), and an elevation in mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC). Notably, the leukocyte counts substantially increased. The observed hematological shifts suggest an impact of betamethasone dipropionate on the hematopoietic system, reinforcing the need for cautious corticosteroid administration. The findings underline the necessity for judicious corticosteroid treatment, acknowledging both enzymatic and systemic repercussions.

Introduction: Children of school age are in a slow phase of growth and development in which the skeleton grows slowly, and due to the still unfinished process of ossification, the skeleton of the children is still subject to various deviations. Nowadays, the practical application of new possibilities of objective qualitative as well as quantitative determination of foot deformation in children and youth is becoming more and more widespread. Pedobarography is a special technical discipline that developed within podiatry, an orthopedic subspecialty that deals with the foot. Research objective: To determine the effect of swimming on the transverse arch of junior sports swimmers compared to the control groups. Methods: The research was carried out in the private practice of the physiatrist "Sporticus" - dr. Edin Buljugić and the “Otoka Olympic pool” in Sarajevo. The research method is retrospective-prospective, and the type of research is cross-sectional-observational. Results: The analysis revealed that the average age of the total sample was 10.85±2.50 years. Our results showed that swimming does not significantly change the longitudinal and transverse arch of the foot. Research findings show that swimmers had a better transmission of forces and pressure, especially on the lateral part of the foot, while subjects who did not swim had more pressure on the medial part. The research also showed that the status of the feet is significantly better in children who started swimming in early childhood, compared to the feet of children who started swimming after the age of 10. Conclusion: Swimming does not change the transversal arch of the foot.

Red mud is a by-product of alumina production, which is largely stored in landfills that can endanger the environment. Red mud, or bauxite residue, is a mixture of inorganic compounds of iron, aluminum, sodium, titanium, calcium and silicon mostly, as well as a large number of rare earth elements in small quantities. Although certain methods of using red mud already exist, none of them have been widely implemented on a large scale. This paper proposes a combination of two methods for the utilization of red mud, first by carbothermic reduction and then, by leaching under high pressure in an autoclave in order to extract useful components from it with a focus on titanium. In the first part of the work, the red mud was reduced with carbon at 1600 °C in an electric arc furnace, with the aim of removing as much iron as possible using magnetic separation. After separation, the slag is leached in an autoclave at different parameters in order to obtain the highest possible yield of titanium, aiming for the formation of titanium oxysulfate and avoiding silica gel formation. A maximal leaching efficiency of titanium of 95% was reached at 150 °C using 5 mol/L sulfuric acid with 9 bar oxygen in 2 h. We found that high-pressure conditions enabled avoiding the formation of silica gel during leaching of the slag using 5 mol/L sulfuric acid, which is a big problem at atmospheric pressure. Previously silica gel formation was prevented using the dry digestion process with 12 mol/L sulfuric acid under atmospheric pressure.

This study investigates the potential of speech-reception-threshold (SRT) estimation through electroencephalography (EEG) based envelope reconstruction techniques with continuous speech. Additionally, we investigate the influence of the stimuli’s signal-to-noise ratio (SNR) on the temporal response function (TRF). Twenty young normal-hearing participants listened to audiobook excerpts with varying background noise levels while EEG was recorded. A linear decoder was trained to reconstruct the speech envelope from the EEG data. The reconstruction accuracy was calculated as the Pearson’s correlation between the reconstructed and actual speech envelopes. An EEG SRT estimate (SRTneuro) was obtained as the midpoint of a sigmoid function fitted to the reconstruction accuracy versus SNR data points. Additionally, the TRF was estimated at each SNR level, followed by a statistical analysis to reveal significant effects of SNR levels on the latencies and amplitudes of the most prominent components. The SRTneuro was within 3 dB of the behavioral SRT for all participants. The TRF analysis showed a significant latency decrease for N1 and P2 and a significant amplitude magnitude increase for N1 and P2 with increasing SNR. The results suggest that both envelope reconstruction accuracy and the TRF components are influenced by changes in SNR, indicating they may be linked to the same underlying neural process.

Motivated by the article [Getz and Mills. Host–parasitoid coexistence and egg-limited encounter rates. Am Nat. 1996;148:301–315], in this paper, we explore a discrete model involving a host and a parasitoid with search and egg limitations and arbitrary host-escape function. We added proportional refuge for the hosts to the model. We focus on the system's behavior at the equilibrium points and the nearby regions. In addition to the topological classification of these points, we examined local behavior. In the case of the extinction equilibrium, we obtain the global result. We describe the dynamical behavior scenarios in the neighborhood of the non-isolated exclusion equilibrium point (1:1 resonant). For the unique coexisting equilibrium, we prove the emergence of the Neimark–Sacker bifurcation and calculate the first Lyapunov exponent. This bifurcation can be either super or sub-critical. We have also established the occurrence of the Chenciner bifurcation. Our findings indicate that proportional refuge may or may not stabilize the system, and the choice of host-escape function plays a crucial role in shaping the system's dynamics. We also provide numerical examples to support our theoretical results.

INTRODUCTION: AI-based EKG has shown good accuracy for diagnosing heart failure. However, due to the heterogeneity of studies regarding cutoff points, its precision for specifically detecting heart failure with reduced ejection fraction (LVEF <40%) is not yet well established. Research question: What it is the sensitivity and specificity of artificial-based electrocardiogram to diagnose heart failure with low ejection fraction(cut-off of 40%) Aims: We conducted a meta-analysis and systematic review to evaluate the accuracy of artificial intelligence electrocardiograms in predicting an ejection fraction below 40%. METHODS: We searched PubMed, Embase and Cochrane Library for studies evaluating the performance of AI EKGs in diagnosing HFrEF. We computed true positives, true negatives, false positives and false negatives events to estimate pooled sensitivity, specificity and area under the curve, using R software version 4.3.1, under a random-effects model. RESULTS: We identified 8 studies,including 136151 patients with a paired artificial intelligence enabled electrocardiogram with an echocardiography. 9349(6.8%) patients had an ejection fraction below 40% according to the echocardiogram. The AI-ECG data yielded areas under the receiver operator of, sensitivity of 0.861(0.815-0.897), and specificity of 0.874(0.834-0.905) , and area under the curve of 0.929(0.876-0.949). Mean/median age ranged from 60±9 to 67.8±14.4 years. CONCLUSIONS: In this systematic review and meta-analysis, the use of electrocardiogram-based artificial intelligence models demonstrated high sensitivity and specificity for the diagnosis of heart failure with an ejection fraction below 40%

Introduction/Background: Cardiovascular symptoms appear in a high proportion of patients in the few months following a severe SARS-CoV-2 infection. Non-invasive methods to predict disease severity could help personalizing healthcare and reducing the occurrence of these symptoms. Research Questions/Hypothesis: We hypothesized that blood long noncoding RNAs (lncRNAs) and machine learning (ML) could help predict COVID-19 severity. Goals/Aims: To develop a model based on lncRNAs and ML for predicting COVID-19 severity. Methods/Approach: Expression data of 2906 lncRNAs were obtained by targeted sequencing in plasma samples collected at baseline from four independent cohorts, totaling 564 COVID-19 patients. Patients were aged 18+ and were recruited from 2020 to 2023 in the PrediCOVID cohort (n=162; Luxembourg), the COVID19_OMICS-COVIRNA cohort (n=100, Italy), the TOCOVID cohort (n=233, Spain), and the MiRCOVID cohort (n=69, Germany). The study complied with the Declaration of Helsinki. Cohorts were approved by ethics committees and patients signed an informed consent. Results/Data: After data curation and pre-processing, 463 complete datasets were included in further analysis, representing 101 severe patients (in-hospital death or ICU admission) and 362 stable patients (no hospital admission or hospital admission but not ICU). Feature selection with Boruta, a random forest-based method, identified age and five lncRNAs (LINC01088-201, FGDP-AS1, LINC01088-209, AKAP13, and a novel lncRNA) associated with disease severity, which were used to build predictive models using six ML algorithms. A naïve Bayes model based on age and five lncRNAs predicted disease severity with an AUC of 0.875 [0.868-0.881] and an accuracy of 0.783 [0.775-0.791]. Conclusion: We developed a ML model including age and five lncRNAs predicting COVID-19 severity. This model could help improve patients’ management and cardiovascular outcomes.