Browse Articles
Discover research articles across all indexed journals
Decision tree model to assess consequences and costs associated with therapy administration pathways for patients with HER2+ breast cancer in Italian oncological centers
Background and aims Human Epidermal Growth Factor Receptor 2-positive (HER2+) breast cancer poses significant therapeutic challenges, particularly concerning treatment administration pathways and their associated costs. This study evaluates the managerial and economic impacts of different therapeutic administration scenarios for HER2-positive breast cancer patients, focusing on optimizing hospital workflows, resource utilization, and patient outcomes in Italian oncological centers. Methods A decision tree model was developed to simulate and compare five treatment administration pathways: Standard, Drug-Change, Drug Day, Dedicated Ambulatory, and Optimal Pathway scenarios. The model integrates patient and healthcare professional (HCP) activity and waiting times, infusion chair occupation, and direct and indirect costs. Sensitivity analyses assessed variability in model outcomes. Results Switching from endovenous (EV) to subcutaneous (SC) administration substantially reduced patient throughput times and HCP workloads. The Optimal Pathway scenario yielded the highest resource optimisation, reducing HCP activity time by up to 48 hours, infusional chair occupational time by up to 150 hours, and patients’ total time by up to 753 hours per 100 patients monthly. Cost analyses indicated significant savings in both direct and indirect cost for all the proposed scenarios in comparison to the Standard one. Conclusion The adoption of SC formulations and innovative pathway optimizations enhances treatment organizational efficiency and reduces both direct and indirect costs. These findings underscore the value of tailored approaches to administration based on the structural and organizational characteristics of individual oncology centers, aligning with current Italian healthcare reforms.
Mining irregular patterns in environmental data using density and neighborhood analysis
EPAS1 knockdown is associated with cell cycle and DNA replication programs and MYC/E2F-related signatures in hemangioma endothelial cells
Infantile hemangioma (IH) is the most common benign tumor of infancy. Hypoxia and activation of hypoxia-inducible factor (HIF) signaling have been proposed to contribute to IH pathogenesis, yet the role of endothelial PAS domain-containing protein 1 ( EPAS1 ), which encodes hypoxia-inducible factor-2α (HIF-2α), in hemangioma endothelial cells (HemECs) remains less well characterized. Here, we investigated HIF-2α in primary HemECs using a pharmacological inhibitor (PT-2399) and shRNA-mediated EPAS1 knockdown under normoxic and hypoxic conditions. In hypoxic cultures, PT-2399 treatment was associated with reduced migration and invasion and with a reduction in junction number in tube formation assays; at the selected dose, PT-2399 did not significantly reduce cell viability. By contrast, EPAS1 knockdown was associated with reduced proliferative capacity and altered cell cycle distribution, together with enrichment of DNA replication/cell cycle-related transcriptional programs, negative enrichment of MYC- and E2F-related gene sets, and directionally consistent protein level changes in selected regulators. EPAS1 knockdown-associated phenotypic trends were broadly similar under normoxia and hypoxia, with no clear evidence that hypoxic stimulation enhanced the magnitude of these changes. In IH tissue transcriptomic data, Egl-9 family hypoxia-inducible factor 3 ( EGLN3 ) showed reduced expression, consistent with a testable hypothesis that hypoxia-independent mechanisms may contribute to maintenance of HIF-2α activity in this context. This study is limited by the use of HemECs derived from a single IH specimen and by the absence of on-target validation; accordingly, the findings should be interpreted as exploratory and hypothesis-generating.
A prospective comparative study of outcomes between zero-profile 3D-printed interbody cages and plate-augmented cages in anterior cervical discectomy and fusion
Multi-view graph-regularized deep metric subspace clustering network
Multi-view subspace clustering has progressed significantly by using deep neural networks to handle nonlinear data representations. A recent advancement, the Multi-view Self-Expressive Subspace Clustering (MSESC) network, achieves markedly higher computational efficiency by substituting the traditional self-expression layer with a deep metric learning approach. Nevertheless, MSESC still suffers from two notable limitations: it fails to adequately capture the high-order geometric structures inherent in multi-view data, and it lacks effective guidance from the underlying clustering distribution. To overcome these shortcomings, we propose a novel framework termed Multi-View Graph Regularized Deep Metric Subspace Clustering (MVGR-DMSC). The proposed method introduces two key components into MSESC to enhance the discriminability of representations. First, a dual-order graph regularization module is devised to maintain both first-order and second-order manifold structures, thereby allowing the model to capture more complex local geometric relationships. Second, an adaptive view-weighted deep clustering module is incorporated, which employs the Kullback–Leibler divergence to guide representation learning while dynamically adjusting the contributions of different views. Through evaluations on five benchmark datasets, we show that MVGR-DMSC consistently yields better results than several state-of-the-art approaches, including the direct baseline MSESC, in both accuracy and robustness.
Weakly supervised attention-based learning supports breast cancer detection on deep ultraviolet-excitation fluorescence images
Abstract Microscopy with ultraviolet surface excitation (MUSE) enables rapid fluorescence imaging of fresh tissue surfaces without conventional sectioning, but its appearance differs from that of haematoxylin and eosin-stained slides. Pixel- or patch-level annotation for deep learning is laborious, particularly for emerging imaging modalities. Here, we evaluated weakly supervised learning (WSL) for breast cancer detection on MUSE images using attention-based multiple instance learning trained with microscopic image-level labels alone. Fresh breast tissues from 35 mastectomy patients were stained with Hoechst 33,342 and terbium and imaged by MUSE. We analysed 700 images, comprising 10 cancerous and 10 non-cancerous images per case. Data were split at the case level into an independent test set of 140 images and a training/validation set of 560 images with fixed four-fold cross-validation. To assess the effect of patch size, we trained models using 224 × 224- or 64 × 64-pixel patches. The models achieved high test performance, with receiver operating characteristic area under the curve values of 0.983 and 0.979 for the 224 × 224- and 64 × 64-pixel models, respectively. Attention maps highlighted tumour-rich regions and cancer-associated stroma. These findings support the feasibility of WSL for MUSE-based breast cancer detection while reducing the need for exhaustive annotation.
Dynamic proprioceptive training improves functional recovery in sprinters with patellofemoral pain: A randomized trial
Background Patellofemoral pain syndrome (PFPS) is a common musculoskeletal condition among physically active individuals, particularly sprinters, and is frequently associated with pain, impaired balance, and reduced functional performance. This study compared the effects of dynamic proprioceptive training and conventional strengthening on multidomain functional recovery in recreational sprinters with PFPS. Methods A two-arm, assessor-blinded randomized controlled trial was conducted among 60 recreational sprinters with unilateral PFPS. Participants were randomly allocated to either a Dynamic Proprioceptive Training (DPT) group or a Strengthening Program (SP) group (n = 30 each). Both groups received supervised rehabilitation three times weekly for 12 weeks. Primary outcomes included pain intensity (Numeric Pain Rating Scale [NPRS]), dynamic balance (Y-Balance Test [YBT]), and single-hop distance. Secondary outcomes included limb symmetry index (LSI), recovery rates, and a composite Recovery Efficiency Index (REI). Assessments were performed at baseline, 6 weeks, and 12 weeks. Repeated-measures ANOVA and regression-based analyses were performed. This trial was registered with the Clinical Trials Registry of India (CTRI/2025/07/090253). Results Both groups improved significantly over time (p < 0.001). However, the DPT group demonstrated greater clinically meaningful improvements than the SP group. At 12 weeks, between-group differences favored DPT for pain reduction (MD = 1.01 NPRS points, 95% CI: 0.61–1.41), dynamic balance (MD = 5.73 cm, 95% CI: 4.31–7.15), and hop performance (MD = 35.84 mm, 95% CI: 16.84–54.85). Conclusion Dynamic proprioceptive training produced greater multidomain functional recovery than conventional strengthening in recreational sprinters with PFPS. Incorporating sensorimotor and perturbation-based exercises into rehabilitation programmes may improve functional recovery, limb symmetry, and sport-specific performance in athletic populations.
Spatial interrelationships between flood risk and ecosystem services in the Beijing–Tianjin–Hebei region at multiple scales
Associations between health-related social capital and oral frailty risk among older adults: A stratified analysis by socioeconomic status in the JAGES longitudinal study
Background Although socioeconomic inequalities in oral health persist despite universal dental care, the role of social determinants remains unclear. Social capital may influence oral frailty, but evidence is limited, particularly regarding individual- and community-level social capital and differences by socioeconomic status (SES). This study examined these associations among community-dwelling older adults. Methods We analyzed longitudinal data from the Japan Gerontological Evaluation Study (JAGES) collected at baseline (2019) and follow-up (2022), including 31,378 older adults. Social capital was assessed across three domains: civic participation, social cohesion, and reciprocity at individual and community levels. Oral frailty was estimated using a validated predictive model incorporating age, remaining teeth, chewing ability, and swallowing function. Multivariable logistic regression analyses examined associations between individual- and community-level social capital and oral frailty risk, as well as the interaction effects of social capital, stratified by SES, on oral frailty risk across SES groups. All models were adjusted for potential confounders, including sex, age, education, household composition, and chronic conditions. Results Over three years, 21.6% of participants developed oral frailty risk, with a higher incidence among low-SES participants (24.6%) than among high-SES participants (19.9%). At the higher individual level, higher health-related social capital and social cohesion were significantly associated with lower odds of oral frailty risk across SES groups. Higher civic participation was also associated with lower oral frailty risk across SES groups, with a stronger association observed among low-SES participants. At the community level, higher civic participation was associated with lower oral frailty risk in the overall sample and among low-SES participants. A significant interaction between SES and individual-level civic participation was observed, while no significant interactions were found for other social capital measures. Conclusions Individual-level health-related social capital was associated with a lower risk of oral frailty among older adults. Furthermore, the inverse association between civic participation and oral frailty was stronger among individuals with low socioeconomic status, suggesting that promoting social participation may be a promising strategy for reducing socioeconomic inequalities in oral frailty.
Effect of wheat straw content on mechanical, moisture, and formability performance of hot-pressed PLA biocomposite boards
Kilowatt-class planar four-way gysel combiner with power-aware impedance optimization for L-band pulsed radar
This work presents a compact planar four-way Gysel power divider/combiner designed for kilowatt-class coherent power combining in L-band pulsed radar transmitters. Unlike previously reported waveguide and coaxial Gysel architectures, the proposed planar implementation achieves a 3 kW peak output on an RO4003C substrate while maintaining low-loss, highly manufacturable microstrip construction. A power-aware full-wave electromagnetic optimization framework is introduced to refine characteristic impedances and electrical lengths, explicitly accounting for current distribution, thermal dissipation, and fabrication tolerance sensitivity, resulting in improved mid-band isolation and stable high-power performance. The fabricated prototype achieves an input return loss better than 15 dB, inter-port isolation exceeding 25 dB, amplitude imbalance within ± 0.3 d B , and phase deviation within ± 1 ∘ across 1.2–1.4 GHz. Grounded isolation branches equipped with flange-mounted high-power resistors, together with thermally optimized via arrays, ensure efficient dissipation of odd-mode energy under mismatch conditions. Experimental validation shows close agreement with simulation results, demonstrating that the proposed design represents a rare example of a planar microstrip Gysel combiner experimentally validated for reliable kilowatt-class operation in L-band solid-state radar systems, achieving a practical balance between power handling, compactness, and manufacturability.
MSE-YOLOv8n: a cotton leaf disease detection model for complex backgrounds and small targets
Analysis of swimming teaching programs, aquatic competencies and specific skills in school settings from early childhood to secondary education: A systematic review
The teaching of swimming in school contexts has become increasingly important due to the benefits in the integral development of students and the prevention of aquatic accidents.This study analyses, by means of a systematic review, the aquatic teaching programmes and Competencies implemented in school settings over the last 25 years, from infant to secondary education. The Methodological approach was based on the PRISMA guidelines, with searches in scientific databases (PubMed, Scopus, Sport Discus and Web of Science) and secondary sources. Sixteen studies were selected according to the PICOS model, assessed with the STROBE and TREND tools. The results show a predominance of technical-utilitarian approaches focused on specific swimming skills, with little curricular integration and limited involvement of PE teachers. Most of the studies focused on infant and primary school, being scarce in secondary school. A high variability in duration, frequency, Contents and Assessment instruments was evidenced. The studies highlight the need for greater inclusion of swimming in school curricula, with more comprehensive pedagogical approaches adapted to each stage. It is concluded that although progress has been made, systematic implementation is still limited, requiring greater institutional support, teacher training and methodological coherence.
Biodegradation of petroleum hydrocarbon by Gordonia oleivorans sp. nov. isolated from oil-contaminated soil
Virtual screening of Kocuria oceani AT-1 metabolites as potential maize growth regulators under drought conditions using molecular docking and dynamics simulation
Maize is a vital cereal crop, severely affected by environmental factors and climate change. Among abiotic factors, drought stress is considered one of the most detrimental factors limiting plant growth and biomass production. However, the molecular basis of bacterial metabolite-mediated drought tolerance in cereal crops remains poorly understood. The current in silico study aimed to investigate the molecular interactions between Kocuria oceani AT-1 metabolites and the maize UGT706F8 protein, using molecular docking and dynamics simulation analyses. The molecular interactions between bacterial metabolites and the UGT706F8 protein (glycosyltransferase enzyme, PDB ID 7Q3S) from Zea mays L. were evaluated. The in silico docking findings revealed a favorable binding affinity between bacterial metabolites and the target protein, indicating stable molecular interactions at the protein active site. Specifically, 4-tetradecanoyl-2,6-piperazinedione, and 3-benzylhexahydropyrrolo(1,2-a)pyrazine-1,4-dione displayed binding energies of −7.5 ± 0.33 and −8.5 ± 0.36 kcal/mol against the target protein, respectively. Under identical docking parameters, the known plant growth regulators (indole acetic acid and abscisic acid) yielded binding energies of −6.6 ± 0.34 and −5.8 ± 0.32 kcal/mol, respectively. Re-docking of the native uridine-5-diphosphate (UDP) ligand yielded a Root Mean Square Deviation (RMSD) of 0.9 Å, validating the reliability of the docking procedure. Additionally, molecular dynamics simulation (200 nanoseconds) outcomes supported these predictions, indicating stable molecular interactions and structural integrity of ligand-protein complexes, with ligand RMSD values remaining between 2 and 3 Å. The formation of hydrogen bonding (an average of 2.4 ± 0.6 and 2.1 ± 0.5, respectively), hydrophobic interactions, and stable Solvent-Accessible Surface Area (SASA) profiles (ranging between 19,000–22,000 Å 2 and 19,000–21,000 Å 2 , respectively) suggest the stability of complexes. Moreover, Molecular Mechanics Generalized Born Surface Area (MM-GBSA) outcomes (−102.05 ± 13.96 and −54.86 ± 7.93 kcal/mol, respectively) supported the favorable binding energetics of ligand-protein complexes. These computational outcomes suggest that Kocuria oceani metabolites can establish stable molecular interactions with the UGT706F8 protein, which may influence glycosyltransferase function. Further in vivo experimental validation is required to confirm their predicted maize growth-promoting potential under drought conditions.
Association between helminth infection and impaired SARS-CoV-2 antibody responses following COVID-19 vaccination: a cross-sectional study in Malawi
Abstract Chronic helminth infections can modulate immune responses to infection and vaccination. This study explored the association between current helminth infection, including waterborne and soil-transmitted helminths (STHs), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralising and IgG antibody responses. Samples were collected cross-sectionally from participants across rural (Karonga) and urban (Lilongwe) regions in Malawi. Helminth infections were detected via real-time PCR in stool and urine samples, targeting Schistosoma spp., Ascaris lumbricoides , Ancylostoma duodenale , Necator americanus , and Trichuris trichiura . SARS-CoV-2 nAbs were measured using a human immunodeficiency virus (HIV)-based pseudotyped virus neutralisation assay. A nucleocapsid (N) protein enzyme-linked immunosorbent assay (ELISA) identified prior natural SARS-CoV-2 infection in vaccinated participants. IgG targeting the spike (S) protein was measured using an ELISA. Helminth infection was found to be associated with reduced nAb responses post coronavirus disease 2019 (COVID-19) vaccination, but not after natural SARS-CoV-2 infection. Generalised additive model analysis confirmed this interaction while considering covariates. IgG responses were also impaired among those helminth-infected. It should be investigated whether integrating pre-vaccination deworming improves vaccine responses in helminth-endemic regions.
Knowledge and awareness of oral cancer among adults in North-Western Italy: A cross-sectional questionnaire-based survey in community pharmacies
Early detection is a key determinant of prognosis in oral squamous cell carcinoma (OSCC); however, delayed diagnosis remains common. Insufficient public awareness and knowledge of OSCC have been identified as important barriers to timely diagnosis. Therefore, the aim of this observational study is to assess knowledge of OSCC and its risk factors, and to identify possible differences in awareness and information sources according to demographic and subject-related factors. A cross-sectional survey was conducted between July 2023 and June 2024 in community pharmacies in North-Western Italy. Adult customers completed a structured questionnaire administered by trained interviewers. Associations were evaluated using chi-square tests and multivariable logistic regression analyses. A total of 914 participants were consecutively included (mean age 54.1 ± 17.0 years). Overall, 70.4% were aware of OSCC, mostly from family/friends (51.8%) and media (43.2%). Smoking was widely recognized as a risk factor (97.9%), while alcohol consumption and sunlight exposure were less known (63.9% and 18.6%, respectively). Awareness was significantly influenced by gender, higher educational level, age and smoking status. Most respondents (92.2%) expressed a need for further information, with community pharmacies identified as the preferred source (67.3%). The present findings highlight the need for OSCC awareness campaigns in North-Western Italy and suggest that community pharmacies may represent a valuable setting for delivering such interventions.
A fine-grained defect-sensitive local–global multiscale vision transformer framework for urban visual pollution prediction
Evaluating the feasibility and effectiveness of a capacity-building model to nurture junior independent clinical research investigators in Uganda
Background Research capacity-building initiatives remain crucial to achieving Sustainable Development Goal 3 on health and well-being, especially in LMICs. We aimed to evaluate the effectiveness of the Infectious Disease Institute’s (IDI) Capacity-Building Model to nurture junior independent clinical research investigators in Uganda. Methods From 13 th July 2021–06 th February 2023, we conducted a cross-sectional study using a mixed-methods approach to assess the extent to which the Capacity-Building Model was effective, feasible, and acceptable. For quantitative research, we conducted an online survey with 80 scholars (Master’s, PhD, and Post-doctoral fellows), comprising 20 alumni and 60 current scholars, to explore their experiences and perceptions as former and current scholars of the Capacity Building Unit (CBU) at IDI. For qualitative research, we purposively selected 20 scholars to participate in the in-depth interviews. Results Participants reported that the capacity-building Model had a beneficial impact on their career progression, with 90% expressing a willingness to recommend it to others. The overall scientific benefit reported was 48.7%; this was significantly higher among continuing scholars than among alumni (56.7% vs 25.0%, respectively; p-value = 0.046). Additionally, 85% achieved their career goals, and 65% said it expanded their employment opportunities. Qualitative findings highlighted its significant positive impact on research training and professional development. Participants praised the Model’s emphasis on mentorship, with both scientific and non-scientific support proving crucial in guiding junior researchers through technical challenges, manuscript writing, and career planning. Soft skills training, dissemination platforms, and networking opportunities further contributed to scholars’ academic growth. Scholars benefited from robust institutional support, including access to research infrastructure, grantsmanship assistance, and administrative systems. However, challenges such as limited research funding, slow procurement processes, and delays in supervision hindered progress. The COVID-19 pandemic also disrupted mentorship and training. Participants recommended improvements in mentorship coordination, procurement efficiency, broader model visibility, and expansion to other universities and disciplines to enhance its effectiveness and sustainability. Conclusion Overall, the Capacity-Building Model was highly acceptable among scholars; however, minor administrative challenges need to be addressed to further enhance learning. We recommend tailored, relevant scholarly programs to meet the evolving needs of emerging scientists and foster scholarly growth and research innovation in academic institutions, enabling them to tackle local public health challenges. Future research is required to assess the cost of capacity building and its sustainability.