Search Results (2,010)

Due to the effect of room acoustics on musical interpretation, a musician’s rehearsal may be greatly enhanced by leveraging virtual and augmented reality technology. This paper presents a preliminary study on a rehearsal tool designed for musicians, enabling practice in a virtual acoustic environment with audience-positioned playback. Fourteen participants, both professional and non-professional musicians, were recruited to practice with the rehearsal tool prior to performing in an unfamiliar venue. Throughout the rehearsal, the subjects either played in a virtual environment that matched the acoustics of the performance venue or one that was acoustically different. A control group rehearsed in an acoustically dry room with no virtual acoustic environment. The tool’s effectiveness was evaluated with two 16-item questionnaires that assessed quality, usefulness, satisfaction with the rehearsal, and aspects of the performance. Findings indicate that rehearsing in a virtual acoustic environment that matches the performance venue improves acoustic awareness during the performance and enhances ease and comfort on stage compared to practising in a different environment. These results support the integration of virtual acoustics in rehearsal tools to help musicians better adapt their performance to concert settings. Full article

Membrane transporters play a crucial role in any cell. Identifying the substrates they translocate across membranes is important for many fields of research, such as metabolomics, pharmacology, and biotechnology. In this study, we leverage recent advances in deep learning, such as amino acid sequence embeddings with protein language models (pLMs), highly accurate 3D structure predictions with AlphaFold 2, and structure-encoding 3Di sequences from FoldSeek, for predicting substrates of membrane transporters. We test new deep learning features derived from both sequence and structure, and compare them to the previously best-performing protein encodings, which were made up of amino acid k-mer frequencies and evolutionary information from PSSMs. Furthermore, we compare the performance of these features either using a previously developed SVM model, or with a regularized feedforward neural network (FNN). When evaluating these models on sugar and amino acid carriers in A. thaliana, as well as on three types of ion channels in human, we found that both the DL-based features and the FNN model led to a better and more consistent classification performance compared to previous methods. Direct encodings of 3D structures with Foldseek, as well as structural embeddings with ProstT5, matched the performance of state-of-the-art amino acid sequence embeddings calculated with the ProtT5-XL model when used as input for the FNN classifier. Full article

Fibromyalgia is a complex disorder characterized by chronic widespread pain and a variety of related symptoms. Growing evidence suggests that the central and peripheral nervous systems are involved, with small fiber neuropathy playing a key role in its development. We retrospectively reviewed the medical records of 100 patients diagnosed with primary fibromyalgia. Those showing symptoms indicative of small fiber dysfunction who were treated with L-Acetyl Carnitine (LAC) and Palmitoylethanolamide (PEA) alongside standard care (SOC) were compared to matched controls who received only SOC. To ensure comparable groups, propensity score matching was used. Changes in Fibromyalgia Impact Questionnaire Revised (FIQR) scores over 12 weeks were analyzed using non-parametric tests due to the data’s non-normal distribution. After matching, 86 patients (43 in each group) were included. The group receiving LAC and PEA as add-on therapy experienced a significant median reduction in FIQR scores (−19.0 points, p < 0.001), while the SOC-only group showed no significant change. Comparisons between groups confirmed that the improvement was significantly greater in the LAC+PEA group (p < 0.001). These results suggest that adding LAC and PEA to standard care may provide meaningful symptom relief for fibromyalgia patients with suspected small fiber involvement. This supports the hypothesis that peripheral nervous system dysfunction contributes to the disease burden in this subgroup. However, further prospective controlled studies are needed to confirm these promising findings. Full article

Estrogen receptor alpha (ERα) plays a vital role in the development and progression of breast cancer by regulating the expression of genes associated with cell proliferation in breast tissue. ERα inhibition is a key strategy in the prevention and treatment of breast cancer. Previous research modified chalcone compounds into pyrazoline benzenesulfonamide derivatives (Modifina) which show activity as an ERα inhibitor. This study aimed to design novel pyrazoline benzenesulfonamide derivatives (PBDs) as ERα antagonists using in silico approaches. Structure-based and ligand-based drug design approaches were used to create drug target molecules. A total of forty-five target molecules were initially designed and screened for drug likeness (Lipinski’s rule of five), cytotoxicity, pharmacokinetics and toxicity using a web-based prediction tools. Promising candidates were subjected to molecular docking using AutoDock 4.2.6 to evaluate their binding interaction with ERα, followed by molecular dynamics simulations using AMBER20 to assess complex stability. A pharmacophore model was also generated using LigandScout 4.4.3 Advanced. The molecular docking results identified PBD-17 and PBD-20 as the most promising compounds, with binding free energies (ΔG) of −11.21 kcal/mol and −11.15 kcal/mol, respectively. Both formed hydrogen bonds with key ERα residues ARG394, GLU353, and LEU387. MM-PBSA further supported these findings, with binding energies of −58.23 kJ/mol for PDB-17 and −139.46 kJ/mol for PDB-20, compared to −145.31 kJ/mol, for the reference compound, 4-OHT. Although slightly less favorable than 4-OHT, PBD-20 demonstrated a more stable interaction with ERα than PBD-17. Furthermore, pharmacophore screening showed that both PBD-17 and PBD-20 aligned well with the generated model, each achieving a match score of 45.20. These findings suggest that PBD-17 and PBD-20 are promising lead compounds for the development of a potent ERα inhibitor in breast cancer therapy. Full article

Building height information plays an important role in many urban-related applications, such as urban planning, disaster management, and environmental studies. With the rapid development of real scene maps, street view images are becoming a new data source for building height estimation, considering their easy collection and low cost. However, existing studies on building height estimation primarily utilize remote sensing images, with little exploration of height estimation from street-view images. In this study, we proposed a deep learning-based method for estimating the height of a single building in Baidu panoramic street view imagery. Firstly, the Segment Anything Model was used to extract the region of interest image and location features of individual buildings from the panorama. Subsequently, a cross-view matching algorithm was proposed by combining Baidu panorama and building footprint data with height information to generate building height samples. Finally, a Two-Branch feature fusion model (TBFF) was constructed to combine building location features and visual features, enabling accurate height estimation for individual buildings. The experimental results showed that the TBFF model had the best performance, with an RMSE of 5.69 m, MAE of 3.97 m, and MAPE of 0.11. Compared with two state-of-the-art methods, the TBFF model exhibited robustness and higher accuracy. The Random Forest model had an RMSE of 11.83 m, MAE of 4.76 m, and MAPE of 0.32, and the Pano2Geo model had an RMSE of 10.51 m, MAE of 6.52 m, and MAPE of 0.22. The ablation analysis demonstrated that fusing building location and visual features can improve the accuracy of height estimation by 14.98% to 69.99%. Moreover, the accuracy of the proposed method meets the LOD1 level 3D modeling requirements defined by the OGC (height error ≤ 5 m), which can provide data support for urban research. Full article

The development of Global Positioning System (GPS) technology has contributed in various ways to improving the physical condition of modern football players by enabling the quantification of physical load. Previous studies have reported that the running demands of matches vary depending on playing position and formation. Over the past decade, despite the widespread use of GPS technology, studies that have investigated the running performance of young football players within the 1-4-3-3 formation are particularly limited. Therefore, the aim of the present study was to create the match running profile of playing positions in the 1-4-3-3 formation among high-level youth football players. An additional objective of the study was to compare the running performance of players between the two halves of a match. This study involved 25 football players (Under-19, U19) from the academy of a professional football club. Data were collected from 18 league matches in which the team used the 1-4-3-3 formation. Positions were categorized as Central Defenders (CDs), Side Defenders (SDs), Central Midfielders (CMs), Side Midfielders (SMs), and Forwards (Fs). The players’ movement patterns were monitored using GPS devices and categorized into six speed zones: Zone 1 (0.1–6 km/h), Zone 2 (6.1–12 km/h), Zone 3 (12.1–18 km/h), Zone 4 (18.1–21 km/h), Zone 5 (21.1–24 km/h), and Zone 6 (above 24.1 km/h). The results showed that midfielders covered the greatest total distance (p = 0.001), while SDs covered the most meters at high and maximal speeds (Zones 5 and 6) (p = 0.001). In contrast, CDs covered the least distance at high speeds (p = 0.001), which is attributed to the specific tactical role of their position. A comparison of the two halves revealed a progressive decrease in the distance covered by the players at high speed: distance in Zone 3 decreased from 1139 m to 944 m (p = 0.001), Zone 4 from 251 m to 193 m (p = 0.001), Zone 5 from 144 m to 110 m (p = 0.001), and maximal sprinting (Zone 6) dropped from 104 m to 78 m (p = 0.01). Despite this reduction, the total distance remained relatively stable (first half: 5237 m; second half: 5046 m, p = 0.16), indicating a consistent overall workload but a reduced number of high-speed efforts in the latter stages. The results clearly show that the tactical role of each playing position in the 1-4-3-3 formation, as well as the area of the pitch in which each position operates, significantly affects the running performance profile. This information should be utilized by fitness coaches to tailor physical loads based on playing position. More specifically, players who cover greater distances at high speeds during matches should be prepared for this scenario within the microcycle by performing similar distances during training. It can also be used for better preparing younger players (U17) before transitioning to the U19 level. Knowing the running profile of the next age category, the fitness coach can prepare the players so that by the end of the season, they are approaching the running performance levels of the next group, with the goal of ensuring a smoother transition. Finally, regarding the two halves of the game, it is evident that fitness coaches should train players during the microcycle to maintain high movement intensities even under fatigue. Full article

Genome instability is a hallmark of cancer, often driven by mutations and altered expression of genome maintenance factors involved in DNA replication and repair. Rap1 Interacting Factor 1 (RIF1) plays a crucial role in genome stability and is implicated in cancer pathogenesis. Cells express two RIF1 splice variants, RIF1-Long and RIF1-Short, which differ in their ability to protect cells from DNA replication stress. Here, we investigate differential expression and splicing of RIF1 in cancer cell lines following replication stress and in patients using matched normal and tumour data from The Cancer Genome Atlas (TCGA). Overall RIF1 expression is altered in several cancer types, with increased transcript levels in colon and lung cancers. RIF1 also exhibits distinct splicing patterns, particularly in specific breast cancer subtypes. In Luminal A (LumA), Luminal B (LumB), and HER2-enriched breast cancers (HER2E), RIF1 Exon 31 tends to be excluded, favouring RIF1-Short expression and correlating with poorer clinical outcomes. These breast cancer subtypes also tend to exclude other short exons, suggesting length-dependent splicing dysregulation. Basal breast cancer also shows exon exclusion, but unlike other subtypes, it shows no short-exon bias. Surprisingly, however, in basal breast cancer, RIF1 Exon 31 is not consistently excluded, which may impact prognosis since RIF1-Long protects against replication stress. Full article

Veterinarians are not just animal health professionals; they are also considered animal welfare experts. Animal-directed empathy, the ability to understand and match an animal’s emotional state, is essential for recognizing animal welfare issues. It is therefore a vital competency for veterinarians. The factors that play a role in shaping this empathy are animal, personal, and cultural influences, as well as the categorization of animals based on their benefit or harm to people: pet, pest or profit (used for economic purposes). We conducted a survey among veterinary students in the Netherlands to assess their levels of animal-directed empathy by scoring their attitude toward animals with the “Pet, Pest, Profit Scale”. Analysis of 321 completed surveys revealed that students showed the highest empathy for pets, the second-highest levels for pest animals, and the lowest levels for profit animals. Empathy levels also differed depending on career choice, background, and diet. These findings indicate that categorizing animals influences veterinary students’ empathy levels, which can lead to unrecognized welfare issues, especially for pest and profit animals. It is important to enhance empathy for these categories through targeted educational interventions to help prepare veterinary students for their responsibility as veterinarians, ensuring the welfare of all animals, whether pet, pest or profit. Full article

The report examines food availability and demand in the Anthropocene era, exploring the connections between global population growth and carrying capacity through an extended version of Cohen’s Condorcet concept. It recalls the super-Malthus and Verhulst-type scalings, matched with the recently introduced analytic relative growth rate. It focuses particularly on the ongoing Fifth Industrial Revolution (IR) and its interaction with the concept of a sustainable civilization. In this context, the significance of innovative food preservation technologies that can yield high-quality foods with health-promoting features, while simultaneously increasing food quantities and reducing adverse environmental impacts, is discussed. To achieve this, high-pressure preservation and processing (HPP) can play a dominant role. High-pressure ‘cold pasteurization’, related to room-temperature processing, has already achieved a global scale. Its superior features are notable and are fairly correlated with social expectations of a sustainable society and the technological tasks of the Fifth Industrial Revolution. The discussion is based on the authors’ experiences in HPP-related research and applications. The next breakthrough could be HPP-related sterilization. The innovative HPP path, supported by the colossal barocaloric effect, is presented. The mass implementation of pressure-related sterilization could lead to milestone societal, pro-health, environmental, and economic benefits. Full article

Rugby Union is a high-impact sport with considerable injury risk, especially in emerging rugby settings where structured physical preparation may be limited. This study aimed to assess the epidemiological profile and injury incidence among Rugby Union players in Brazil, providing insights to inform strength and conditioning strategies. A cross-sectional observational study was conducted between October 2023 and February 2024 using a digital questionnaire that captured demographic data, sports participation history, and detailed information about injuries sustained in 2022 and 2023. A total of 236 players participated (58.9% male; mean age = 29.4 ± 7.5 years), with males averaging 29.6 ± 7.7 years and females 29.1 ± 7.5 years. Overall, 183 injuries were reported. Most injuries occurred during matches (73.3%) and were contact-related (82.1%), with the shoulder/clavicle and knee being the most affected regions. Ligament injuries (27.3%), dislocations (15.3%), and fractures (16.4%) were the most prevalent types. Female players had a distinct injury pattern, with a greater proportion of non-contact mechanisms. Significant associations were found between injury occurrence and sex (p = 0.012), playing modality (p < 0.001), injury type (p = 0.013), and recovery time (p = 0.006). These findings highlight the urgent need for tailored strength and conditioning interventions focused on injury prevention and athletic preparedness. Such programs should address sport-specific demands, promote neuromuscular resilience, and be accessible across competitive levels to improve performance and minimize injury-related setbacks. Full article

Stainless steel dust (SSD) is a by-product generated during the smelting process of stainless steel, which is rich in valuable metals such as Fe, Cr, Ni, and Mn. To optimize the carbothermic reduction process of SSD, this study first conducted the thermodynamic analysis of the carbothermic reduction of SSD and then employed walnut shell biochar as a reductant with non-isothermal thermogravimetric analysis with linear heating rates of 5 °C/min, 10 °C/min, 15 °C/min, and 20 °C/min. The activation energies of the carbothermic reduction reactions were calculated using the FWO method, KAS method, and Friedman method, respectively. Subsequently, the corresponding kinetic models were fitted and matched using the Málek method. The results indicate that before 600 °C, the direct reduction of SSD by carbon plays a dominant role. As the temperature increases, the indirect reduction becomes the main reduction reaction for SSD due to the generation of CO. The activation energies calculated by the Flynn–Wall–Ozawa (FWO) method, Kissinger–Akahira–Sunose (KAS) method, and Friedman method are 412.120 kJ/mol, 416.930 kJ/mol, and 411.778 kJ/mol, respectively, showing close values and a general trend of increasing activation energy as the conversion rate increased from 10% to 90%. Moreover, the reduction reaction is staged. In the conversion range of 10% to 50%, the carbothermic reduction reaction conforms to the shrinking core model within phase boundary reactions, coded as R1/4. In the conversion range of 50% to 60%, it conforms to the shrinking core model within phase boundary reactions, coded as R1/2; in the conversion range of 60% to 90%, the carbothermic reduction reaction follows the second-order chemical reaction model, coded as F2. Full article

Background and Aims: Primary biliary cholangitis (PBC) is a chronic autoimmune liver disease frequently associated with fatigue and mild cognitive impairment. Brain-derived neurotrophic factor (BDNF) plays key roles in neuroplasticity, immune regulation, and metabolism. This study aimed to evaluate plasma BDNF levels in early-stage PBC and examine their clinical and biochemical associations. Methods: In this observational study, plasma BDNF, IL-6, and IL-18 concentrations were measured by ELISA in 45 patients with early-stage PBC and 31 age- and sex-matched healthy controls (mean age 60.5 years; 96% women). All participants underwent liver elastography using point shear wave elastography (ElastPQ), Doppler ultrasound, laboratory testing, and assessment of cognitive function (PHES) and fatigue severity (MFIS). Non-invasive fibrosis scores (APRI, FIB-4) were calculated. Results: Median plasma BDNF concentrations were significantly higher in PBC patients than in controls [median: 21.04 ng/mL (IQR: 10.68–38.07) vs. 5.80 ng/mL (IQR: 4.58–7.54); p < 0.0001]. In PBC patients, higher BDNF levels correlated inversely with liver stiffness measured by ElastPQ (R = −0.39, p = 0.0258), spleen dimensions, splenic vein flow volume (R = −0.49, p = 0.0018), suggesting an association with milder liver fibrosis and early hemodynamic alterations. A trend toward association between BDNF and IL-6 levels was observed in multivariate analysis. No significant associations were found between BDNF concentrations and markers of hepatocellular injury, cognitive performance, or fatigue severity. Conclusions: Plasma BDNF concentrations are elevated in early-stage PBC and inversely correlate with liver fibrosis severity. No significant associations were found with hepatocellular injury, cognitive function, or fatigue. These findings suggest that BDNF may play a protective role against hepatic fibrogenesis, or alternatively, that BDNF concentrations may decline with advancing liver disease. Further studies are needed to clarify its significance in PBC. Full article

Alzheimer’s disease (AD) involves the accumulation of amyloid-β (Aβ) plaques, whose quantification plays a central role in understanding disease progression. Automated segmentation of Aβ deposits in histopathological micrographs enables large-scale analyses but is hindered by the high cost of detailed pixel-level annotations. Weakly supervised learning offers a promising alternative by leveraging coarse or indirect labels to reduce the annotation burden. We evaluated a weakly supervised approach to segment and analyze thioflavin-S-positive parenchymal amyloid pathology in AD and age-matched brains. Our pipeline integrates three key components, each designed to operate under weak supervision. First, robust preprocessing (including retrospective multi-image illumination correction and gradient-based background estimation) was applied to enhance image fidelity and support training, as models rely more on image features. Second, class activation maps (CAMs), generated by a compact deep classifier SqueezeNet, were used to identify, and coarsely localize amyloid-rich parenchymal regions from patch-wise image labels, serving as spatial priors for subsequent refinement without requiring dense pixel-level annotations. Third, a patch-based convolutional neural network, U-Net, was trained on synthetic data generated from micrographs based on CAM-derived pseudo-labels via an extensive object-level augmentation strategy, enabling refined whole-image semantic segmentation and generalization across diverse spatial configurations. To ensure robustness and unbiased evaluation, we assessed the segmentation performance of the entire framework using patient-wise group k-fold cross-validation, explicitly modeling generalization across unseen individuals, critical in clinical scenarios. Despite relying on weak labels, the integrated pipeline achieved strong segmentation performance with an average Dice similarity coefficient (≈0.763) and Jaccard index (≈0.639), widely accepted metrics for assessing segmentation quality in medical image analysis. The resulting segmentations were also visually coherent, demonstrating that weakly supervised segmentation is a viable alternative in histopathology, where acquiring dense annotations is prohibitively labor-intensive and time-consuming. Subsequent morphometric analyses on automatically segmented Aβ deposits revealed size-, structural complexity-, and global geometry-related differences across brain regions and cognitive status. These findings confirm that deposit architecture exhibits region-specific patterns and reflects underlying neurodegenerative processes, thereby highlighting the biological relevance and practical applicability of the proposed image-processing pipeline for morphometric analysis. Full article

This study analyses the physical performance variables involved in different training tasks aimed at replicating the worst-case scenarios (WCSs) observed during official matches in professional football, with a focus on playing positions and occurrences within a 1 min period. Data were collected from 188 training sessions and 42 matches of a Spanish Second Division team during the 2021/2022 season. All data were reported on a per-player basis. GPS tracking devices were used to record physical variables such as total distance, high-speed running (HSR), sprints, accelerations, decelerations, and high metabolic load distance (HMLD). Players were grouped according to their match positions: central defenders, wide players, midfielders and forwards. The results showed that none of the training tasks fully replicated the physical demands of match play. However, task TYPEs 11 (Large-Sided Games) and 9 (small-sided games with orientation and transition) were the closest to match demands, particularly in terms of accelerations and decelerations. Although differences were observed across all variables, the most pronounced discrepancies were observed in sprint and HSR variables, where training tasksfailed to reach 60% of match demands. These findings highlight the need to design more specific drills that simulate the intensity of WCS, allowing for more accurate weekly training load planning. This study offers valuable contributions for optimising performance and reducing injury risk in professional footballers during the competitive period. Full article

Basketball referees play a crucial role in game management, yet the physical and physiological demands placed on them during a game remain understudied. This study analyzed the workload of 35 group 1 referees during a U-18 Spanish championship, examining the effects of refereeing technique (two referees vs. three referees) and competition sex (male vs. female) across game quarters. Physical and physiological demands were measured using inertial devices and heart rate monitors during 37 matches (18 men’s and 19 women’s). The results revealed that 2-referee teams experienced significantly greater physical demands, covering approximately 25% more total distance and demonstrating higher values in high-intensity running compared to 3-referee teams. Female competition elicited higher demands in specific variables, particularly in the distance covered above 16 km/h and average speed. Analysis across quarters showed distinct temporal patterns, with the first and third quarters presenting the highest demands, especially for 2-referee teams. These findings suggest that basketball referees’ physical preparation should be tailored to the officiating technique and competition sex, with a particular emphasis on developing specific conditioning programs for the 2-referee technique and implementing targeted recovery strategies between quarters to maintain optimal performance throughout the game. Full article