Search Results (1,535)

Ongoing changes in the distribution and abundance of several tick species of medical relevance in Canada have prompted the development of the eTick platform—an image-based crowd-sourcing public surveillance tool for Canada enabling rapid tick species identification by trained personnel, and public health guidance based on tick species and province of residence of the submitter. Considering that more than 100,000 images from over 73,500 identified records representing 25 tick species have been submitted to eTick since the public launch in 2018, a partial automation of the image processing workflow could save substantial human resources, especially as submission numbers have been steadily increasing since 2021. In this study, we evaluate an end-to-end artificial intelligence (AI) pipeline to support tick identification from eTick user-submitted images, characterized by heterogeneous quality and uncontrolled acquisition conditions. Our framework integrates (i) tick localization using a fine-tuned YOLOv7 object detection model, (ii) resolution enhancement of cropped images via super-resolution Generative Adversarial Networks (RealESRGAN and SwinIR), and (iii) image classification using deep convolutional (ResNet-50) and transformer-based (ViT) architectures across three datasets (12, 6, and 3 classes) of decreasing granularities in terms of taxonomic resolution, tick life stage, and specimen viewing angle. ViT consistently outperformed ResNet-50, especially in complex classification settings. The configuration yielding the best performance—relying on object detection without incorporating super-resolution—achieved a macro-averaged F1-score exceeding 86% in the 3-class model (Dermacentor sp., other species, bad images), with minimal critical misclassifications (0.7% of “other species” misclassified as Dermacentor). Given that Dermacentor ticks represent more than 60% of tick volume submitted on the eTick platform, the integration of a low granularity model in the processing workflow could save significant time while maintaining very high standards of identification accuracy. Our findings highlight the potential of combining modern AI methods to facilitate efficient and accurate tick image processing in community science platforms, while emphasizing the need to adapt model complexity and class resolution to task-specific constraints. Full article

The periodic vehicle routing problem (PVRP) is a well-known challenge in real-life logistics, requiring the planning of vehicle routes over multiple days while enforcing visitation frequency constraints. Although numerous metaheuristic and exact methods have tackled various PVRP extensions, real-world settings call for additional features such as depot configurations, tight visitation frequency constraints, and heterogeneous fleets. In this paper, we present a two-phase biased–randomized algorithm that addresses these complexities. In the first phase, a round-robin assignment quickly generates feasible and promising solutions, ensuring each customer’s frequency requirement is met across the multi-day horizon. The second phase refines these assignments via an iterative search procedure, improving route efficiency and reducing total operational costs. Extensive experimentation on standard PVRP benchmarks shows that our approach is able to generate solutions of comparable quality to established state-of-the-art algorithms in relatively low computational times and stands out in many instances, making it a practical choice for real life multi-day vehicle routing applications. Full article

Background and Objectives: There is a global rise of public interest in integrative medicine. The principles of integrative medicine combining conventional medicine with evidence-based complementary therapies have been implemented in many medical areas, including plastic surgery, to improve patient’s outcome. The aim of the present study was to systematically analyze the application and use of additional non-pharmacological interventions (NPIs) of patients of a German department of plastic surgery. Materials and Methods: The present real-world data study utilized data from the Network Oncology registry between 2016 and 2021. Patients included in this study were at the age of 18 or above, stayed at the department of plastic surgery and received at least one plastic surgical procedure. Adjusted multivariable logistic regression analyses were performed to detect associations between the acceptance of NPIs and predicting factors such as age, gender, year of admission, or length of hospital stay. Results: In total, 265 patients were enrolled in the study between January 2016 and December 2021 with a median age of 65 years (IQR: 52–80) and a male/female ratio of 0.77. Most of the patients received reconstructive surgery (90.19%), followed by hand surgery (5.68%) and aesthetic surgery (2.64%). In total, 42.5% of the enrolled patients accepted and applied NPIs. Physiotherapy, rhythmical embrocations, and compresses were the most often administered NPIs. Conclusions: This exploratory analysis provides a descriptive overview of the application and acceptance of NPIs in plastic surgery patients within a German integrative care setting. While NPIs appear to be well accepted by a subset of patients, further prospective studies are needed to evaluate their impact on clinical outcomes such as postoperative recovery, pain management, patient-reported quality of life, and overall satisfaction with care. Full article

The increasing reliance on Medical Internet of Things (MIoT) devices introduces critical cybersecurity vulnerabilities, necessitating advanced, adaptive defense mechanisms. Recent cyber incidents—such as compromised critical care systems, modified therapeutic device outputs, and fraudulent clinical data inputs—demonstrate that these threats now directly impact life-critical aspects of patient security. In this paper, we introduce a machine learning-enabled Cognitive Cyber-Physical System (ML-CCPS), which is designed to identify and respond to cyber threats in MIoT environments through a layered cognitive architecture. The system is constructed on a feedback-looped architecture integrating hybrid feature modeling, physical behavioral analysis, and Extreme Learning Machine (ELM)-based classification to provide adaptive access control, continuous monitoring, and reliable intrusion detection. ML-CCPS is capable of outperforming benchmark classifiers with an acceptable computational cost, as evidenced by its macro F1-score of 97.8% and an AUC of 99.1% when evaluated with the ToN-IoT dataset. Alongside classification accuracy, the framework has demonstrated reliable behaviour under noisy telemetry, maintained strong efficiency in resource-constrained settings, and scaled effectively with larger numbers of connected devices. Comparative evaluations, radar-style synthesis, and ablation studies further validate its effectiveness in real-time MIoT environments and its ability to detect novel attack types with high reliability. Full article

Irritable bowel syndrome (IBS) is a gut–brain axis chronic disorder, characterized by recurrent abdominal pain and altered bowel habits in the absence of organic pathology. Nutrition plays a central role in symptom management, yet no single dietary strategy has demonstrated universal effectiveness. This narrative review critically evaluates current nutritional approaches to IBS. The low-Fermentable Oligo-, Di-, Mono-saccharides and Polyols (FODMAP) diet is the most extensively studied and provides short-term symptom relief, but its long-term effects on microbiota diversity remain concerning. The Mediterranean diet, due to its anti-inflammatory and prebiotic properties, offers a sustainable, microbiota-friendly option; however, it has specific limitations in the context of IBS, particularly due to the adverse effects of certain FODMAP-rich foods. A gluten-free diet may benefit individuals with suspected non-celiac gluten sensitivity, although improvements are often attributed to fructan restriction and placebo and nocebo effects. Lactose-free diets are effective in patients with documented lactose intolerance, while a high-soluble-fiber diet is beneficial for constipation-predominant IBS. IgG-based elimination diets are emerging but remain controversial and require further validation. In this review, we present the 10 dietary commandments for IBS, pragmatic and easily retained recommendations. It advocates a personalized, flexible, and multidisciplinary management approach, avoiding rigidity and standardized protocols, with the aim of optimizing adherence, symptom mitigation, and health-related quality of life. Future research should aim to evaluate, in real-world clinical settings, the impact and applicability of the 10 dietary commandments for IBS in terms of symptom improvement and quality of life Full article

Background: In clinical practice, visual outcomes with anti-VEGF therapy may be worse than those observed in clinical trials. In this study, we aim to investigate the long-term outcomes of neovascularization treated with intravitreal aflibercept injections (IAI) in a teaching hospital setting. Methods: This is a retrospective, single-center study including 81 nAMD patients (116 eyes), those both newly diagnosed and switched from ranibizumab. All patients had a follow-up duration of at least seven years. Treatment involved three monthly injections followed by either a pro re nata (PRN) or treat and extend regimen. Follow-up care was primarily conducted by training physicians. The primary endpoint was the change in best-corrected visual acuity (BCVA) over seven years. Secondary endpoints included central retinal thickness changes, qualitative OCT parameters, macular atrophy progression, injection frequency, and treatment adherence. Results: Among the 116 eyes, 52 (44.8%) completed the seven-year follow-up. Visual acuity improved by +2.1 letters in the overall population (+6.3 letters in treatment-naive eyes) after the loading phase but gradually declined, resulting in a loss of −12.3 letters at seven years. BCVA remained stable (a loss of fewer than 15 letters) in 57.7% of eyes. Central retinal thickness (CRT) decreased significantly during follow-up in both naive and switcher eyes. Macular atrophy occurred in 94.2% of eyes, progressing from 1.42 mm² to 8.55 mm² over seven years (p < 0.001). The mean number of injections was 4.1 ± 1.8 during the first year and 3.7 per year thereafter. Advanced age at diagnosis was a risk factor for loss to follow-up, with bilaterality being a protective factor against loss to follow-up (p < 0.05). Conclusions: This study highlights the challenges faced by a retina clinic in a teaching hospital. Suboptimal functional and anatomical outcomes in real life may derive from insufficient patient information and inconsistent monitoring, which contributes to undertreatment and affects long-term visual outcomes. It also raises concerns about supervision in a teaching hospital which needs to be improved. Full article

Hydrogen produced from renewable sources has the potential to tackle various energy challenges, from allowing cost-effective transportation of renewable energy from production to consumption regions to decarbonizing intensive energy consumption industries. Due to its application versatility and non-greenhouse gaseous emissions characteristics, it is expected that hydrogen will play an important role in the decarbonization strategies set out for 2050. Currently, there are some barriers and challenges that need to be addressed to fully take advantage of the opportunities associated with hydrogen. The present work aims to characterize the state of the art of different hydrogen production, storage, transport, and distribution technologies, which compose the hydrogen value chain. Based on the information collected it was possible to conclude the following: (i) Electrolysis is the frontrunner to produce green hydrogen at a large scale (efficiency up to 80%) since some of the production technologies under this category have already achieved a commercially available state; (ii) in the storage phase, various technologies may be suitable based on specific conditions and purposes. Technologies of the physical-based type are the ones mostly used in real applications; (iii) transportation and distribution options should be viewed as complementary rather than competitive, as the most suitable option varies based on transportation distance and hydrogen quantity; and (iv) a single value chain configuration cannot be universally applied. Therefore, each case requires a comprehensive analysis of the entire value chain. Methodologies, like life cycle assessment, should be utilized to support the decision-making process. Full article

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a chronic upper airway disease that may involve different inflammatory endotypes, although in Western populations it is most commonly associated with type 2 inflammation. CRSwNP has a significant impact on the patient’s quality of life. The recommended appropriate medical therapy is effective in controlling CRSwNP symptoms in many patients; however, a subset continues to exhibit persistent type 2 inflammation, evidenced by recurrent nasal polyps, elevated eosinophil counts, or the need for systemic corticosteroids or surgery. Monoclonal antibodies have recently become a novel and personalized treatment that can help refractory patients restore disease control. Objective: The present study aims to evaluate the effectiveness of mepolizumab in real-world settings in a diverse patient population, focusing on assessing the impact of this therapy on patient-reported outcomes after six months of treatment. Methods: This is a multicenter, observational study of CRSwNP patients treated with mepolizumab carried out in five hospitals located in Spain. Adult patients with a diagnosis of uncontrolled CRSwNP were included in the study. The change in the nasal polyp score (NPS) was the main clinical endpoint. Changes in the Sinonasal Outcome Test (SNOT-22), nasal congestion and smell impairment visual analogue scale scores, and blood and nasal polyp tissue eosinophil counts were among other endpoints included. Results: In total, 47 patients were included, and 91% were asthmatic. The nasal polyp score (0–8) was reduced significantly in the cohort (mean change: −2.56, p < 0.0001). The mean SNOT-22 score improved 25.29 points. Nasal congestion (−3.57, p < 0.0001) and smell impairment (−4.0, p < 0.0001) visual analog scale scores (0–10) showed a significant improvement. Blood and tissue eosinophil median counts showed significant reductions versus baseline of 86% and 26%, respectively. Among those patients with asthma, the asthma control test score achieved a median value of 24 points. Conclusions: This study provides real-world evidence supporting the effectiveness of mepolizumab in managing CRSwNP in patients with features suggestive of type 2 inflammation. The observed improvements in patient-reported outcomes, nasal polyp burden, and asthma control suggest that mepolizumab may be a valuable therapeutic option for this patient population. Full article

Background/Objectives: Aging is often accompanied by physical and cognitive decline, affecting older adults’ mobility. Virtual reality (VR) offers innovative opportunities to safely practice everyday tasks, such as street crossing. This study was designed as a feasibility and pilot study to explore acceptance, usability, and preliminary effects of a VR-based road-crossing intervention for older adults. It investigates the use of virtual reality (VR) as an innovative training tool to support senior citizens in safely navigating everyday challenges such as crossing roads. By providing an immersive environment with realistic traffic scenarios, VR enables participants to practice in a safe and controlled setting, minimizing the risks associated with real-world road traffic. Methods: A VR training application called “Wegfest” was developed to facilitate targeted road-crossing practice. The application simulates various scenarios commonly encountered by older adults, such as crossing busy streets or waiting at traffic lights. The study applied a single-group pre-post design. Outcomes included the Timed Up and Go test (TUG), Falls Efficacy Scale-International (FES-I), and Montreal Cognitive Assessment (MoCA). Results: The development process of “Wegfest” demonstrates how a highly realistic street environment can be created for VR-based road-crossing training. Significant improvements were found in the Timed Up and Go test (p = 0.002, d = 0.784) and fall-related self-efficacy (FES-I, p = 0.005). No change was observed in cognitive function (MoCA, p = 0.56). Participants reported increased subjective safety (p < 0.001). Discussion: The development of the VR training application “Wegfest” highlights the feasibility of creating realistic virtual environments for skill development. By leveraging immersive technology, both physical and cognitive skills required for road-crossing can be effectively trained. The findings suggest that “Wegfest” has the potential to enhance the mobility and safety of older adults in road traffic through immersive experiences and targeted training interventions. Conclusions: As an innovative training tool, the VR application not only provides an engaging and enjoyable learning environment but also fosters self-confidence and independence among older adults in traffic settings. Regular training within the virtual world enables senior citizens to continuously refine their skills, ultimately improving their quality of life. Full article

Background and Objectives: The aim of our study was to evaluate in an ex vivo setting the impact of the holmium laser lithotripsy over the temperature of the irrigation fluid. Materials and Methods: We recorded temperature changes in an ex vivo porcine model during laser activation using dusting (18 Hz, 0.6 J, 10.8 W) and fragmenting settings (8 Hz, 2 J, 16 W). The temperature was recorded for each of these modes in three settings: without irrigation or access sheath, with irrigation but no access sheath, and with irrigation and a 10/12 F access sheath in place. Results: Using dusting settings, the maximum recorded temperatures were 42.3 degrees Celsius (no irrigation, no sheath), 37.3 degrees Celsius (with irrigation but no access sheath) and 36.2 degrees Celsius (with irrigation and access sheath). In fragmenting mode, the maximum recorded temperatures were 52 degrees Celsius (no irrigation, no sheath), 43.1 degrees Celsius (with irrigation but no access sheath), and 42.9 degrees Celsius (with irrigation and access sheath). Conclusions: In certain conditions (no irrigation, more watts) the temperature may rise to dangerous levels. However, in closer to real-life settings (with irrigation and especially when ureteral access sheaths are employed) the magnitude of this effect is limited, making flexible intrarenal laser lithotripsy a reasonably safe procedure. Full article

This study extends our prior blockchain-based traceability framework, WEave, for application to a furniture supply chain scenario, while using the original multi-tier apparel supply chain as an anchoring use case. We integrate circular economy principles such as product reuse, recycling traceability, and full lifecycle transparency to bolster sustainability and resilience in supply chains by enabling data-driven accountability and tracking for closed-loop resource flows. The enhanced approach can track post-consumer returns, use of recycled materials, and second-life goods, all represented using a closed-loop supply chain topology. We describe the extended network architecture and smart contract logic needed to capture circular lifecycle events, while proposing new metrics for evaluating lifecycle traceability and reuse auditability. To validate the extended framework, we outline simulation experiments that incorporate circular flows and cross-industry scenarios. Results from these simulations indicate improved transparency on recycled content, audit trails for returned products, and acceptable performance overhead when scaling to different product domains. Finally, we offer conclusions and recommendations for implementing WEave functionality into real-world settings consistent with the goals of digital, resilient, and sustainable supply chains. Full article

The accurate estimation and prediction of internal states in lithium-ion (Li-Ion) batteries, such as State of Charge (SoC) and Remaining Useful Life (RUL), are vital for optimizing battery performance, safety, and longevity in electric vehicles and other applications. This paper presents a unified, modular, and extensible machine learning (ML) framework designed to address the heterogeneity and complexity of battery state prediction tasks. The proposed framework supports flexible configurations across multiple dimensions, including feature engineering, model selection, and training/testing strategies. It integrates standardized data processing pipelines with a diverse set of ML models, such as a long short-term memory neural network (LSTM), a convolutional neural network (CNN), a feedforward neural network (FFNN), automated machine learning (AutoML), and classical regressors, while accommodating heterogeneous datasets. The framework’s applicability is demonstrated through five distinct use cases involving SoC estimation and RUL prediction using real-world and benchmark datasets. Experimental results highlight the framework’s adaptability, methodological transparency, and robust predictive performance across various battery chemistries, usage profiles, and degradation conditions. This work contributes to a standardized approach that facilitates the reproducibility, comparability, and practical deployment of ML-based battery analytics. Full article

Background/Objectives: Acute myeloid leukemia (AML) with FLT3 internal tandem duplication (FLT3-ITD) mutations carries a poor prognosis. While FLT3 inhibitors like midostaurin show benefits in combination with chemotherapy, the role of allelic ratio (AR), NPM1 mutation status, and hematopoietic stem cell transplantation (HSCT) remains uncertain. Real-world data can help refine prognostic classification and treatment strategies. Methods: We retrospectively analyzed 37 fit patients with FLT3-ITD AML treated with standard “7+3” chemotherapy, with and without midostaurin, between 2013 and 2022. Patients were stratified by FLT3-ITD AR, NPM1 status, and treatment approach. Outcomes assessed included complete remission (CR), disease-free survival (DFS), and overall survival (OS). Results: Overall, 67.6% achieved CR/CRi. Response rates did not differ significantly by AR (low vs. high: 66.7% vs. 69.2%) or midostaurin use (72.6% vs. 60%; p = 0.49). NPM1 mutations were associated with improved DFS (10.3 vs. 3 months, p = 0.036) but not OS. HSCT, performed in 54.1% of patients, mainly in first remission (CR1), significantly prolonged DFS (not reached vs. 5.3 months, p = 0.005) and remained an independent predictor in multivariate analysis (HR: 0.160, p = 0.039). OS (median 15.1 months) did not vary significantly across subgroups. Among patients achieving CR1, OS was significantly longer in those who underwent HSCT after midostaurin-based induction compared to those not transplanted (median OS not reached vs. 12.8 months; 95% CI, 6.9–18.7; p = 0.045), whereas no significant benefit was observed after standard induction. In a landmark analysis restricted to patients transplanted in CR1, those who had received midostaurin-based induction showed a trend toward improved OS compared to those treated with standard induction (median OS not reached vs. 11.5 months; 95% CI, 0.5–25.0; p = 0.086). Conclusions: This real-life study supports the importance of NPM1 mutations and HSCT in CR1, especially in the midostaurin era, for improving DFS in FLT3-ITD AML. These findings support updated guidelines for reducing the prognostic weight of AR and highlight the need for improved post-remission strategies in this setting. Full article

Mass spectrometric (MS) fingerprinting coupled with chemometrics for the detection of plants in plant mixtures is sparsely researched. This paper aims to check its value for herbal adulteration concerning plants with slimming as an indication. Moreover, it is among the first to exploit the full three-dimensional dataset (i.e., time × intensity × mass) obtained with liquid chromatography hyphenated with MS for herbal fingerprinting purposes. The MS parameters were optimized to achieve highly specific fingerprints. Trituration’s (total 55), blanks (total 11) and reference plants were injected in the MS system to generate the dataset. The dataset was complex and humongous, necessitating the application of compression techniques. After compression, Partial Least Squares-Discriminant Analysis (PLS-DA) was performed to generate models validated for accuracy using cross-validation and an external test set. Confusion matrices were constructed to provide insight into the modeling predictions. A complimentary evaluation between data obtained using a previously developed Diode Array Detection (DAD) method and the MS data was performed by data fusion techniques and newly generated models. The fused dataset models were comparable to MS models. For ease of application, MS modeling was deemed to be superior. The future market studies would adopt MS modeling as the preferred choice. A proof of concept was carried out on 10 real-life samples obtained from illegal sources. The results indicated the need for stronger monitoring of (illegal) plant food supplements entering the market, especially via the internet. Full article

Background: Asparaginase (ASPase) plays an important role in the therapy of acute lymphoblastic leukemia (ALL). Serum ASPase activity (SAA) can be modified and even abolished by host immune responses; therefore, current treatment guidelines recommend to monitor SAA during treatment administration. The SAA monitoring schedule needs to be carefully planned to reduce the number of samples without hampering the possibility of measuring pharmacokinetics (PK) parameters in individual patients. Complex modelling approaches, not easily applicable in common practice, have been applied in previous studies to estimate ASPase PK parameters. This study aimed to estimate PK parameters by using a simplified approach suitable for real-world settings with limited sampling. Methods: Our study was based on 434 patients treated in Italy within the AIEOP-BFM ALL 2009 trial. During the induction phase, patients received two doses of pegylated ASPase and were monitored with blood sampling at five time points, including time 0. PK parameters were estimated by using the individually available SAA measurements with simple modifications of the classical non-compartmental PK analysis. We also took the opportunity to develop and validate a series of limited sampling models to predict ASPase exposure. Results: During the induction phase, average ASPase activity at day 7 was 1380 IU/L after the first dose and 1948 IU/L after the second dose; therapeutic SAA levels (>100 IU/L) were maintained until day 33 in 90.1% of patients. The average AUC and clearance were 46,937 IU/L × day and 0.114 L/day/m², respectively. The database was analyzed for possible associations of PK parameters with biological characteristics of the patients, finding only a limited dependence on sex, age and risk score; however, these differences were not sufficient to allow any dose or schedule adjustments. Thereafter the possibility of further sampling reduction by using simple linear models to estimate the AUC was also explored. The most simple model required only two samplings 7 days after each ASPase dose, with the AUC being proportional to the sum of the two measured activities A(7) and A(21), calculated by the formula AUC = 14.1 × [A(7) + A(21)]. This model predicts the AUC with 6% average error and 35% maximum error compared to the AUC estimated with all available measures. Conclusions: Our study demonstrates the feasibility of a direct estimation of PK parameters in a real-life situation with limited and variable blood sampling schedules and also offers a simplified method and formulae easily applicable in clinical practice while maintaining a reliable pharmacokinetic monitoring. Full article