Search Results (155)

Periprosthetic joint infection (PJI) is a complex complication of total joint arthroplasty, with microbiological profiles varying across centers worldwide. However, most studies are limited to single-center or intra-country multicenter analyses, often including mixed cohorts of primary and revision PJI cases, with limited data regarding global antibiotic resistance patterns. This study compared the microbiological characteristics, polymicrobial culture rates, prevalence of culture-negative infections, and antibiotic resistance patterns in PJI cases across five referral centers from five continents. A total of 717 patients with primary hip and knee PJI were included from centers in Argentina, Canada, Turkey, England, and New Zealand. Staphylococcus aureus and Staphylococcus epidermidis were the most common pathogens (48.5%, p < 0.01). Culture-negative infection rates varied significantly, ranging from 4.2% (England) to 24.6% (Turkey) (p < 0.01). Polymicrobial infections were the most frequent in Canada (8.9%) and the least frequent in England (1.1%) (p < 0.01). Gram-negative bacteria comprised 13.1% of culture-positive cases, with no significant intercountry difference. Multidrug resistance was observed in all centers, ranging from 23.7% (Argentina) to 43.1% (Turkey), with no statistical significance. Vancomycin resistance was detected in England (2.3%) and Canada (1.2%) but absent in Turkey, New Zealand, and Argentina. These findings underscore significant intercontinental variability, emphasizing the need for regional considerations in regards to empiric antibiotic selection and PJI management. Full article

The use of recurrent neural networks has proven effective in time series prediction tasks such as weather. However, their use in resource-limited systems such as MCUs presents difficulties in terms of both size and stability with longer prediction windows. In this context, we propose a variant of the LSTM model, which we call SE-LSTM (Single Embedding LSTM), which uses embedding techniques to vectorially represent seasonality and latent patterns through variables such as temperature and humidity. The proposal is systematically compared in two parts: The first compares it against other reference architectures such as CNN-LSTM, TCN, LMU, and TPA-LSTM. The second stage, which includes implementation, compares it against the CNN-LSTM, LSTM, and TCN networks. Metrics such as the MAE and MSE are used along with the network weight, a crucial aspect for MCUs such as an ESP32 or Raspberry Pi Pico. An analysis of the memory usage, energy consumption, and generalization across different regions is also included. The results show that the use of embedding optimizes the network space without sacrificing the performance, which is crucial for edge computing. This research is part of a larger project, which focuses on improving agricultural monitoring systems. Full article

Background: In volleyball, upper limb dimensions, handgrip strength (HGS), and baropodometric parameters are critical for executing offensive and defensive actions during the match. These movements demand not only physical precision but also carry a significant risk of injury, varying by playing position. Objectives: This study aimed to determine the differences in specific upper limb anthropometric characteristics, HGS, and selected baropodometric variables among U-23 male volleyball players concerning playing position. Methods: The sample consisted of 92 U-23 male players who prepared for the U-23 Men’s Volleyball National Championship 2022 (20.39 (1.74) years, 184 (8.46) cm, 75.52 (10.20) kg). Playing positions analyzed were setters (n = 12), outside (n = 18), opposites (n = 19), middle blockers (n = 16), and liberos (n = 12). Results: player position differences in HGS and several anthropometric upper limb variables were observed. Middle blockers, outsides, and opposites exhibited superior anthropometric traits in most of the measurements compared to liberos and setters (p < 0.05). Differences in baropodometric parameters were only found between feet and their zones when the entire sample was evaluated. Finally, regression analysis identified dominant hand breadth (β = 3.42, 95%CI [0.43, 6.40], upper arm muscle area (β = 0.157, 95%CI [0.02, 0.29]), and wrist diameter (β = 3.59, IC 95% [0.49, 6.68]) as associated variables of HGS. Conclusions: The study underscores the importance of positional profiling in volleyball, revealing key physical traits linked to performance. The observed differences are likely attributable to the specific role and physical demands inherent to each playing position. These findings can guide targeted training and injury prevention strategies to enhance performance. Full article

Discriminating between original paintings and replicas is a challenging task. In recent years, the fractal dimension (FD) has been used as a quantitative measure of self-similarity to analyze differences between paintings. However, while the FD parameter has proven effective, previous studies often did not utilize all available image information, typically requiring binarization or grayscale analysis and the manual selection of painting regions. This study introduces a novel, color-FD-based method for differentiating original paintings from replicas. Our approach employs a sliding window approach combined with recent color-FD computation techniques. To assess the effectiveness of our FD methodology, we used two public datasets where originals and replicas were produced by the same artist under identical conditions, ensuring maximum similarity. Statistical comparisons were performed using the nonparametric Wilcoxon rank-sum test. Our method identified significant differences between original and replica paintings for 18 out of 19 pairs across both datasets, outperforming previous studies using the same datasets. As expected, our method discriminates more effectively between paintings by different artists (hit rate of 96.6%) than between originals and replicas by the same artist (hit rate of 91.7%). These findings indicate that combining the FD of color images with a sliding window approach is a promising tool for forgery detection. Full article

Multiple sclerosis is a prevalent neurodegenerative disease that significantly affects gait and exercise capacity. The core system is involved in providing sufficient spinal stability for dealing with stability demands. People with multiple sclerosis exhibit reduced trunk stability, which may affect stability during tasks such as reaching, stepping, and unexpected perturbations. This systematic review aimed to evaluate the effects of core training on gait and exercise capacity in people with multiple sclerosis. A systematic review was conducted in the databases PubMed/Medline, Web of Science (WOS), ScienceDirect, CINAHL, Scopus, and Physiotherapy Evidence Database (PEDro). Randomized controlled trials up to January 2025 included the following PICO inclusion criteria: (Participants) adults with a multiple sclerosis diagnosis; (Intervention) a core stability training program (alone or combined with another intervention); (Comparison) compared to no intervention, placebo or any other intervention; (Outcomes) and including at least one outcome related to gait and/or exercise capacity. The search identified 781 records, and finally 12 studies were included in this review. Methodological quality and risk of bias were assessed using the PEDro scale (with 8 as the median score) and the Cochrane risk assessment tool (ROB2), showing in most cases some concerns, particularly regarding outcome selection. Most of the studies included reported significant improvements in gait assessed with the timed up and go, timed 25-foot walk, and six spot step tests. Also, the results of exercise capacity assessed with the 6 min and 2-min walk test significantly increased in most of the studies. The reviewed articles suggest that a core-based exercise program may be effective in improving gait and exercise capacity in people with multiple sclerosis. However, considering the heterogeneity of the interventions, results, population, and the high risk of bias of some trials, more research is needed to validate these preliminary results. Full article

Bone defects caused by various traumas and diseases such as osteoporosis, which affects bone density, and osteosarcoma, which affects the integrity of bone structure, are now well known. Given this situation, several innovative research projects have been reported to improve orthopedic methods and technologies that positively contribute to the regeneration of affected bone tissue, representing a significant advance in regenerative medicine. This review article comprehensively analyzes the transition from existing methods and technologies for implants and bone tissue regeneration to innovative biomaterials. These biomaterials have been of great interest in the last decade due to their physicochemical characteristics, which allow them to overcome the most common limitations of traditional grafting methods, such as the availability of biomaterials and the risk of rejection after their application in regenerative medicine. This could be achieved through an exhaustive study of the applications and properties of various materials with potential applications in regenerative medicine, such as using magnetic nanoparticles and hydrogels sensitive to external stimuli, including pH and temperature. In this regard, this review article describes the most relevant compounds used in bone tissue regeneration, promoting the integration of these biomaterials with the affected area’s bone structure, thereby allowing for regeneration and preventing amputation. Additionally, the types of interactions between biomaterials and mesenchymal stem cells and their effects on bone tissue are discussed, which is critical for developing biomaterials with optimal regenerative properties. Furthermore, the mechanisms of action of the various biomaterials that enhance osteoconduction and osteoinduction, ensuring the success of orthopedic therapies, are analyzed. This enables the treatment of bone defects tailored to each patient’s condition, thereby avoiding limb amputation. Consequently, a promising future for regenerative medicine is emerging, with various therapies that could revolutionize the management of bone defects, offering more efficient and safer solutions. Full article

Background: Vascular Ehlers–Danlos syndrome (vEDS) is a rare connective tissue disorder characterized by collagen type III deficiency, predisposing to spontaneous arterial, uterine, and intestinal ruptures. While intestinal complications are recognized in vEDS, intestinal failure (IF) secondary to these complications is a rare and potentially life-threatening occurrence. This study aimed to describe the clinical presentation, surgical management, and outcomes of pediatric patients with IF secondary to vEDS and to provide a comprehensive review of the limited existing literature on this challenging clinical scenario. Methods: This study comprises a case series of pediatric patients with IF due to vEDS complications and a comprehensive literature review. Clinical data were collected from medical records, including age at diagnosis, surgical history, complications, nutritional status, and long-term outcomes. A literature review was performed to identify studies reporting gastrointestinal complications, surgical outcomes in pediatric vEDS patients, and cases of intestinal failure. Results: Two pediatric patients with vEDS and IF were included. Both patients experienced intestinal perforations and surgical complications and required long-term parenteral nutrition (PN). One patient required PN for 18 months before achieving enteral autonomy, while the other remains dependent. The literature review included four articles and revealed a high risk of complications, including anastomotic leaks, fistulae, and recurrent perforations, in patients with vEDS undergoing intestinal surgery. Delayed diagnosis of vEDS was common. Conclusions: Intestinal complications in pediatric patients with vEDS can lead to severe short bowel syndrome and long-term PN dependence. Early diagnosis and a multidisciplinary approach are crucial for optimizing patient care and minimizing complications. Full article

Background/Objectives: Chronic plantar fasciopathy is a degenerative pathology that elicits persistent heel pain, significantly impacting quality of life. When conservative treatments fail to yield satisfactory outcomes, radiofrequency microtenotomy utilizing the Topaz technique presents a minimally invasive alternative with regenerative potential. This study aims to evaluate its efficacy in pain reduction, functional improvement, and complication rate compared to other treatments. Methods: A systematic review was conducted in accordance with the PRISMA guidelines and registered in PROSPERO (CRD4202525648314). PubMed, EBSCOhost, Web of Science, and Scopus (2014–2024) were comprehensively searched to identify studies on the Topaz technique for refractory chronic plantar fasciopathy. Clinical trials, cohort studies, and case series were included, and a meta-analysis was performed using a random-effects model to assess pain, the Visual Analog Scale (VAS), American Orthopaedic Foot & Ankle Society function(AOFAS), and complications. Results: Fifteen studies encompassing 1576 patients were analyzed. The meta-analysis demonstrated a significant reduction in pain of 5.90 points on the VAS scale (95% CI: 5.03 to 6.77, p < 0.001) and a functional improvement of 0.28 points on the AOFAS scale (95% CI: 0.27 to 0.28, p < 0.001). The complication rate was low (3.00%), with high patient satisfaction (90%) and rapid recovery. Conclusions: The findings suggest that the Topaz technique is a safe and effective option for chronic plantar fasciopathy, demonstrating significant improvements and minimal complications. Full article

Background: Early prediction of ICU death in acute hypoxemic respiratory failure (AHRF) could inform clinicians for targeting therapies to reduce harm and increase survival. We sought to determine clinical modifiable and non-modifiable features during the first 24 h of AHRF associated with ICU death. Methods: This is a development, testing, and validation study using data from a prospective, multicenter, nation-based, observational cohort of 1241 patients with AHRF (defined as PaO₂/FiO₂ ≤ 300 mmHg on mechanical ventilation [MV] with positive end-expiratory pressure [PEEP] ≥ 5 cmH₂O and FiO₂ ≥ 0.3) from any etiology. Using relevant features captured at AHRF diagnosis and within 24 h, we developed a logistic regression model following variable selection by genetic algorithm and machine learning (ML) approaches. Results: We analyzed 1193 patients, after excluding 48 patients with no data at 24 h after AHRF diagnosis. Using repeated random sampling, we selected 75% (n = 900) for model development and testing, and 25% (n = 293) for final validation. Risk modeling identified six major predictors of ICU death, including patient’s age, and values at 24 h of PEEP, FiO₂, plateau pressure, tidal volume, and number of extrapulmonary organ failures. Performance with ML methods was similar to logistic regression and achieved a high area under the receiver operating characteristic curve (AUROC) of 0.88, 95%CI 0.86–0.90. Validation confirmed adequate model performance (AUROC 0.83, 95%CI 0.78–0.88). Conclusions: ML and traditional methods led to an encouraging model to predict ICU death in ventilated AHRF as early as 24 h after diagnosis. More research is needed to identify modifiable factors to prevent ICU deaths. Full article

The rise of social media is transforming education by replacing traditional materials and promoting digital competence, a key area of focus in current training. Platforms like Instagram facilitate collaboration, access to learning, and content creation, becoming essential tools for the development of students and future educators in digital environments. This study aimed to enhance the digital competence of pre-service teachers, particularly in communication and collaboration, through Instagram as an educational tool. A quasi-experimental study with pretest and post-test measures was conducted, involving 391 students from the University of Granada. The results indicated an intermediate level of digital competence with improvements in both groups, though no significant differences were found between them. However, significant effects were observed in the intragroup analysis. The experimental group, which used Instagram as an educational tool for 11 weeks, showed improvements in communication and collaboration, digital content creation, and security. The control group also demonstrated progress, mainly in information search and problem-solving. These improvements align with previous studies, though the progress in the control group may be attributed to factors such as content focused on educational technology, student motivation, and engagement. This study confirms that social media can enhance digital competence as a learning tool. Full article

Background: Ukrainian refugees fleeing the conflict between Russia and Ukraine may face significant challenges to their physical, psycho-emotional, social, and spiritual wellbeing. Aim: To identify the health needs of Ukrainian refugees seen in primary care facilities in Tenerife, Canary Islands, Spain. Methods: A mixed-methods design was employed. Quantitative data were obtained through a descriptive analysis of health records, while qualitative data were collected via focus group interviews and thematic analysis of testimonies. Results: The sample comprised 59 individuals (45.4% of all patients seen). Eight participants from five family groups took part in the focus group. The typical profile of a Ukrainian refugee in the Canary Islands is female (79.7%), relatively young, with a high socio-cultural background, generally in good health, travelling alone or with her minor children. The main reasons for consultation were routine health check-ups and control blood tests. The NANDA-I nursing diagnoses indicated a need for psycho-emotional care, with the most prevalent being Risk for Relocation Stress Syndrome (27.1%); Interrupted Family Processes, Disturbed sleep pattern, Risk for Impaired Resilience (13.6% each); and Anxiety (11.9%). Participants rated the healthcare system positively, but language barriers and long waiting times for access to specific services were noted as limitations. The primary social demands include seeking employment, learning the language, and increasing support groups among Ukrainians themselves. Conclusions: This study underscores the need for a tailored approach to refugee care, considering their unique circumstances and needs. Early provision of information about available healthcare services and protocols can facilitate access, manage expectations, and aid decision-making. Full article

This paper presents a methodology for detecting the pest Aleurothrixus floccosus in citrus crops in Pedregal de Arequipa, Peru. The study employs simple random sampling during image collection to minimize bias, alternating and extracting leaves from different citrus trees. Image processing techniques, including noise reduction, edge smoothing, and segmentation, are applied for pest detection. Machine learning algorithms are used to classify the images, culminating in a robust detection methodology. A dataset of 1200 images was analyzed during the study. Full article

Background/Objectives: Lung cancer is the primary cause of cancer-related deaths. Most patients are typically diagnosed at advanced stages. Low-dose computed tomography (LDCT) has been proven to reduce lung cancer mortality, but screening programs using LDCT are associated with a high number of false positives and unnecessary thoracotomies. It is therefore imperative that a certain diagnosis is refined, especially in cases of solitary pulmonary nodules that are difficult to technically access for an accurate preoperative diagnosis. Extracellular vesicles (EVs) involved in intercellular communication may be an innovative biomarker for diagnosis and therapeutic strategies in lung cancer, regarding their ability to carry tumor-specific cargo. The aim of the LUCEx study is to determine if extracellular vesicle cargoes from both lung tissue and blood could provide complementary information to screen lung cancer patients and enable personalized follow-up after the surgery. Methods: The LUCEx study is a prospective study aiming to recruit 600 patients with lung cancer and 50 control subjects (false positives) undergoing surgery after diagnostic imaging for suspected pulmonary nodules using computed tomography (CT) scans. These patients will undergo curative surgery at the Department of Thoracic Surgery of the Miguel Servet Hospital in Zaragoza, Spain, and will be followed-up for at least 5 years. At baseline, samples from both tumor distal lung tissue and preoperative peripheral blood will be collected and processed to compare the quantity and content of EVs, particularly their micro-RNA (miRNA) cargo. At the third and fifth years of follow-up, CT scans, functional respiratory tests, and blood extractions will be performed. Discussion: Extracellular vesicles and their miRNA have emerged as promising tools for the diagnosis and prognosis of several diseases, including cancer. The LUCEx study, based on an observational clinical cohort, aims to understand the role of these vesicles and their translational potential as complementary tools for imaging diagnosis and prognosis. Full article

Cardiovascular diseases (CVD) pose a significant global health challenge, requiring innovative therapeutic strategies. Vasodilators, which are central to vasodilation and blood pressure reduction, play a crucial role in cardiovascular treatment. This study integrates quantitative structure– (QSAR) modeling and molecular dynamics (MD) simulations to predict the biological activity and interactions of vasodilatory compounds with the aim to repurpose drugs already known and estimateing their potential use as vasodilators. By exploring molecular descriptors, such as electronegativity, softness, and highest occupied molecular orbital (HOMO) energy, this study identifies key structural features influencing vasodilatory effects, as it seems molecules with the same mechanism of actions present similar frontier orbitals pattern. The QSAR model was built using fifty-four Food Drugs Administration-approved (FDA-approved) compounds used in cardiovascular treatment and their activities in rat thoracic aortic rings; several molecular descriptors, such as electronic, thermodynamics, and topographic were used. The best QSAR model was validated through robust training and test dataset split, demonstrating high predictive accuracy in drug design. The validated model was applied on the FDA dataset and molecules in the application domain with high predicted activity were retrieved and filtered. Thirty molecules with the best-predicted pKI50 were further analyzed employing molecular orbital frontiers and classified as angiotensin-I or β1-adrenergic inhibitors; then, the best scoring values obtained from molecular docking were used to perform a molecular dynamics simulation, providing insight into the dynamic interactions between vasodilatory compounds and their targets, elucidating the strength and stability of these interactions over time. According to the binding energies results, this study identifies novel vasodilatory candidates where Dasabuvir and Sertindole seem to have potent and selective activity, offering promising avenues for the development of next-generation cardiovascular therapies. Finally, this research bridges computational modelling with experimental validation, providing valuable insight for the design of optimized vasodilatory agents to address critical unmet needs in cardiovascular medicine. Full article