Search Results (40,887)

Background/Objectives: Cancer survivors often experience physical decline, fatigue, and reduced quality of life (QoL) following cancer treatment. Exercise is an important strategy in survivorship care; however, the role of exercise motivation in sustaining exercise behavior and improving QoL remains unclear. This study evaluated the effects of a structured exercise intervention on QoL, fatigue, and exercise motivation among cancer survivors. Methods: This single-arm longitudinal pre–post-intervention study recruited adult cancer survivors (median age: 55 years) with heterogeneous cancer types from E-Da Hospital, Taiwan, between October 2023 and July 2024. Participants completed a 3-month supervised exercise program consisting of weekly 60 min sessions that included aerobic, resistance, balance, and flexibility training. Assessments were conducted at baseline, immediately after the intervention, and at a 3-month follow-up. Outcome measures included physical fitness tests, fatigue scales, and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), and the Relative Autonomy Index for exercise motivation. Results: Thirty-nine participants completed the study. Improvements in several QoL domains were observed at the 3-month follow-up, particularly in physical and emotional functioning. Pain and fatigue symptoms decreased following the intervention, although some fatigue indicators increased again during follow-up. Female participants showed greater improvements in certain physical fitness measures. Intrinsic exercise motivation increased after the intervention, and greater motivation gains were associated with larger improvements in QoL. Conclusions: Participation in a structured exercise program may be associated with improvements in QoL, fatigue symptoms, and exercise motivation among cancer survivors. However, given the single-arm design and small sample size, these findings should be interpreted cautiously. Larger randomized controlled studies are needed to confirm the long-term benefits of exercise interventions in cancer survivorship care. Full article

In nuclear spectroscopy, a physical phenomenon known as the pile-up effect distorts direct measurements by causing temporal overlap of detector pulses. Existing deep learning-based pile-up correction methods rely heavily on supervised training with simulated data, which often generalize poorly to real measurements due to simulation–experiment discrepancies. In this work, we propose a contrastive learning framework to learn robust and transferable representations directly from large-scale unlabeled real nuclear pulse signals. The detector output is segmented into physically complete pulse aggregations using a zero-crossing-based strategy, which serve as semantically coherent instances for representation learning. Physics-inspired data augmentations are designed to realistically model detector noise and bandwidth effects while preserving pulse area. A one-dimensional ResNet encoder is employed for efficient representation learning. The learned representations are transferred to pile-up identification and counting-rate estimation tasks. Experimental results on real nuclear radiation detection systems demonstrate that our method achieves strong performance and robustness under high counting-rate conditions, with particularly pronounced advantages in challenging peak pile-up scenarios. Full article

Glioblastoma multiforme (GBM) is one of the most aggressive and treatment-resistant forms of brain cancer, posing challenges to modern oncology. Current treatments, including surgery, radiation, and chemotherapy (e.g., Temozolomide or TMZ), often fail due to the inevitable development of drug resistance. TMZ resistance remains a major therapeutic challenge for the reasons that it is the first-line treatment. Recent studies indicate a rising GBM tumour burden and a trend towards earlier age of onset. It highlights the urgent need for evidence-based policymaking and intensified research to address this most difficult-to-treat malignancy in clinical settings. Ferroptosis, a newly recognized type of controlled cell death induced by iron-dependent lipid peroxidation, has emerged as a potential approach to overcome apoptosis resistance and restore drug sensitivity in GBM. This mechanism is modulated by key molecules that can be specifically targeted to either enhance oxidative stress or inhibit antioxidant defences, ultimately leading to tumour cell death. This review conducts a meta-analysis of preclinical evidence to better understand the potential of activating ferroptosis as a key target for developing nanoparticles to resensitize TMZ-resistant GBM cells. Current evidence indicates that combining ferroptosis induction with strategically engineered nanocarrier systems can serve as a novel and effective therapeutic approach to overcome TMZ resistance and advance precision-based GBM treatment. Full article

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality globally. While multi-modal artificial intelligence (AI) models offer significant predictive potential, their translation into routine clinical practice is delayed by the “black box” nature of complex algorithms and the fragmentation of heterogeneous data. We present LANTERN-XGB, a hierarchical machine learning workflow designed to bridge this gap by generating interpretable “digital human avatars” for precision oncology. The methodology employs a multi-stage scalable tree boosting system (XGBoost) architecture utilizing shapley additive explanations (SHAP) for rigorous hierarchical feature selection, missing value management, and patient-specific decision support. The workflow was developed and benchmarked using a retrospective cohort of 437 patients with clinical N0 NSCLC, followed by validation on a prospective dataset (n = 100) and an independent external dataset (n = 100). The pipeline integrates diverse data modalities to predict occult lymph node metastasis (OLM). LANTERN-XGB identified a robust consensus signature driven by non-linear interactions among CT textural fragmentation, PET metabolic heterogeneity, tumor density distribution, and systemic clinical modulators. Exploratory transcriptomic pathway analysis (GSVA) revealed that high-risk predictions strongly correlate with systemic molecular dysregulation, such as the enrichment of immune-inflammatory signaling and metabolic stress pathways. The model achieved robust discrimination in external validation (AUC ≈ 0.77), performing comparably to state-of-the-art nomogram benchmarks. Crucially, the LANTERN-XGB framework demonstrated superior utility in handling diagnostic ambiguity; local force plots allowed for the correct reclassification of “borderline” prediction by visualizing feature interactions that standard linear models fail to capture. LANTERN-XGB provides a validated, open-source framework that successfully balances predictive power with clinical transparency. By empowering clinicians to visualize and verify the logic behind AI predictions, this workflow offers a pragmatic path for integrating reliable multi-modal avatars into daily medical decision-making. Full article

In this work, we present a study of newly developed two-layered composite scintillators based on epitaxial structures of garnet compounds for the simultaneous registration of different components of mixed radiation fluxes, and we evaluate their α/β/γ discrimination performance. The composite scintillators under study were doubly layered structures composed of TbAG:Ce or TbAG:Ce,Mg single-crystalline film grown onto Czochralski-grown GAGG:Ce single-crystal substrates using the liquid-phase epitaxy (LPE) method. The spectrometry measurements were performed with four different radioactive sources: ¹³⁷Cs (emitting 661.6-keV γ rays), ²⁴¹Am (5.5-MeV α particles and 59.5-keV γ rays), ⁹⁰Sr (β particles with energies up to 2 MeV), and ¹⁴C (β particles with energies up to 156 keV). The pulse-height spectra (PHS) were recorded with a shaping time of 10 μs in an amplifier due to the presence of long scintillation components in the tested samples. Scintillation time profiles were measured under excitation of 661.6-keV γ rays, 5.5-MeV α particles, and β particles from ⁹⁰Sr/⁹⁰Y and ¹⁴C. Both types of TbAG:Ce film/GAGG:Ce substrate and TbAG:Ce,Mg film/GAGG:Ce substrate composites show good ability for the simultaneous registration of the mentioned components in the mixed radiation field with very reasonable Figure-of-Merit values: FoM(τ) greater than 0.2 and FoM(PSD) greater than 1.0. Full article

Radiation-induced bone injury, characterized by oxidative stress damage and impaired osteogenesis, lacks effective treatments. Exosome-based therapies have recently emerged as a safe and effective modality for radiation damage, and their functional capacity can be further potentiated through tailored preconditioning strategies—such as nanoparticle induction or physical stimulation. This study developed a novel exosome-based therapy by preconditioning bone marrow mesenchymal stem cells (BMSCs) with Iron oxide (Fe₃O₄) magnetic nanoparticles (MNPs, 50 µg/mL) and a static magnetic field (SMF, 100 mT). Exosomes derived from these preconditioned cells (BMSC-Fe₃O₄-SMF-Exos) exhibited enhanced yield and dual functionality. In irradiated BMSCs, BMSC-Fe₃O₄-SMF-Exos significantly promoted osteogenic differentiation, restoring alkaline phosphatase activity, mineralization, and expression of RUNX2, OCN, and COL1A1. They concurrently alleviated oxidative stress by scavenging reactive oxygen species, reducing malondialdehyde, and boosting superoxide dismutase activity. Mechanistically, miR-429 was found to be highly enriched in BMSC-Fe₃O₄-SMF-Exos, which directly targeted Noggin (NOG). Our functional validation experiments also confirmed that overexpression of miR-429 could inhibit NOG, alleviate oxidative stress and rescue the osteogenic differentiation of irradiated BMSCs. In conclusion, exosomes derived from preconditioning BMSCs with Fe₃O₄ MNPs and SMF mitigate radiation-induced damage via the miR-429/NOG pathway, presenting a promising cell-free strategy for bone regeneration. Full article

This investigation is to address the aerodynamic noise generated from laminar flow over a D-shaped cylinder at a low Reynolds number (Re). Proposed is a novel assembly of arc-shaped splitter plates to effectively reduce the aeolian tone for the D-shaped cylinder. The two-dimensional flow field is simulated at an Re of 160 to investigate the mechanism of reducing the sound of the arc-shaped plates. The radiated sound has been predicted by Ffowcs Williams and Hawkings (FW-H) acoustic analogy. To verify calculations, the predicted results of a circular cylinder have been compared with the data in the literature. The results reveal that the introduction of the arc plates decreases the lift and drag fluctuations as well as the vortex shedding frequency in comparison with the no-arc plate case. The pressure and velocity fluctuations in the wake zone are reduced by the arc plates due to vortex shedding suppression. The application of the arc plates shows an effective control of sound, leading to a maximum reduction in sound pressure level (SPL) by almost 34 dB. Full article

Objective: Inadequate radiation delivery to recurrent pelvic and abdominal tumors is frequently attributable to the dose limitations of surrounding normal structures, particularly the intestines. Radiotherapy guided by magnetic resonance imaging (MRI) significantly enhances the accuracy of soft-tissue delineation. The purposes of this study were to demonstrate the feasibility and effectiveness of MR-Linac Adaptive stereotactic body radiotherapy in patients with pelvic–abdominal recurrent or metastatic gynecological malignancies with or without systemic therapies. Methods: Patients with pelvic–abdominal recurrent or metastatic gynecological malignancies are eligible for MR-Linac Adaptive stereotactic body radiotherapy. Systemic therapies, including chemotherapy, immunotherapy, and targeted therapy, are considered acceptable treatment options. The safety, tolerability, and efficacy of MR-Linac Adaptive stereotactic body radiotherapy were assessed. Results: Between October 2019 and May 2025, 15 patients were subjected to MR-Linac Adaptive stereotactic body radiotherapy. With a median follow-up period of 4.67 months (range, 0.73–20.10 months), the 6-month overall survival (OS), progression-free survival (PFS), and local control (LC) rates were 93.3%, 66.0%, and 92.3%, respectively. The 12-month OS, PFS, and LC rates were 83.8%, 37.7%, and 70.5%, respectively. The best objective response rate (ORR = CR + PR) for the irradiated lesions was 73.3% (11/15 patients). MR-Linac Adaptive stereotactic body radiotherapy led to objective responses in 73.3% (11/15) of the patients. As of the data cutoff (28 May 2025), one patient experienced dose-limiting toxicity (an enteric fistula). Another patient developed grade 4 thrombocytopenia during treatment; it was considered chemotherapy-induced. Conclusions: These findings suggest that MR-Linac Adaptive stereotactic body radiotherapy is relatively effective and safe and can be an important treatment option for patients with pelvic–abdominal recurrent or metastatic gynecological malignancies. MR-Linac Adaptive stereotactic body radiotherapy exhibited acceptable tolerability, promising efficacy, and a favorable local control rate with regard to heavily pretreated advanced solid tumors. Full article

Radiative sky cooling can be effectively integrated with pipe-embedded wall systems to reduce building cooling loads. However, the energy-saving and carbon reduction potential of this technology varies according to climatic conditions and the method of integration, requiring quantification. To address this gap, a revised degree-hour method of evaluating energy efficiency for an integrated system is proposed and validated, and a global potential map is developed. The proposed method can be used to predict the energy-saving and carbon reduction potential of radiative sky coolers under different climatic conditions. Compared to physical model prediction methods, the revised degree-hour method is faster and more accurate, with an evaluation error of approximately 5%. The results indicate that the integrated system performs well in most regions with cooling demand. The system’s energy-saving potential is highest in cities in tropical savanna and desert climate zones, achieving energy savings of approximately 53.96 kWh/m² and reducing carbon emissions by approximately 22.99 kgCO₂/m² during the cooling season. Its performance is reduced in subtropical monsoon zones, with savings of 8.36 kWh/m² and 3.56 kgCO₂/m². Furthermore, the system’s energy-saving potential generally declines as the cold-water temperature of the radiative sky cooler increases, especially in tropical regions. This work provides a rapid assessment tool and global reference data to support low-energy building design. Full article

Background/Objectives: Transthoracic echocardiography (TTE) is a non-invasive tool for real-time assessment of cardiac motion and blood flow. It is widely used in emergency and bedside settings as a Focus Cardiac Ultrasound (FoCUS) device. However, standardized training methods and adequate educational environments are limited. Methods: A TTE image assessment artificial intelligence (AI) system was developed in this study, focusing on probe positioning and image quality for non-supervised TTE practice. Results: The view classification model achieved a high F1-score of 0.956. The position evaluation model achieved F1-scores of 0.678, 0.864, and 0.831 for the parasternal long-axis, parasternal short-axis, and apical four-chamber views, respectively. The quality evaluation model achieved F1-scores of 0.674, 0.845, and 0.746. Combining the position and quality models improved the F1-score for the parasternal long-axis view to 0.714, showing the benefit of integrating views with lower baseline performance. Conclusions: This study presents a novel AI-based educational system that assesses probe position and image quality in TTE. The model was developed using a custom dataset of healthy young adults that reflects beginner-level training scenarios, including many suboptimal images similar to those commonly acquired by novices. The proposed framework, which integrates position and quality models, lays the groundwork for future AI-assisted ultrasound training, particularly in unsupervised or resource-limited settings. Full article

This paper presents an indoor self-localization framework for mobile robots, an essential component for automation in Industry 4.0 and smart environments. We evaluate a Received Signal Strength Indicator (RSSI) fingerprinting technique utilizing Long-Range (LoRa) technology to overcome the challenges of congested indoor settings. To optimize communication parameters, the Structural Similarity Index Measure (SSIM) was employed to select the most effective spreading factor, while the entropy of the RSSI database was calculated to verify fingerprint stability. For positional prediction, a Multi-layer Perceptron (MLP) neural network was developed to classify the location of the target within a grid-based experimental setup, featuring cells spaced 60 cm apart. The MLP achieved a validation accuracy of 91.8 percent during training and demonstrated high precision in classifying grid regions within a signal-dense environment. For scenarios where slow-moving robots (5 cm/s) are required, like radiation mapping, this method provide highly accurate high-level localization data.These results suggest that the proposed LoRa-MLP integration provides a robust, low-power solution for high-accuracy indoor positioning systems (IPSs) in modern industrial infrastructure. Full article

Background: Patients with estrogen receptor (ER)-positive ductal carcinoma in situ (DCIS) derive a greater benefit from endocrine therapy than patients with ER-negative disease. The relevance of ER status and progesterone receptor (PR) status in DCIS to radiation therapy has not been well explored. Methods: Patients undergoing breast-conserving surgery with or without radiation were grouped by ER and PR status and matched using rank-based Mahalanobis optimal matching with respect to lesion size and grade and patient age and race. Cumulative incidences were estimated and competing risk regressions with subdistribution hazard ratios (sHRs) were calculated. Results: Among patients who underwent breast-conserving surgery only, 369 patients with ER-PR- disease were matched to 738 patients with ER+PR+ disease (1:2 matching). In multivariate models, patients with ER-PR- disease were at increased risk of any invasive events (sHR = 2.47, p = 0.007) and early ipsilateral invasive events (sHR = 2.64, p = 0.02 in the 0-to-4-year period) relative to patients with ER+PR+ disease. Among patients who underwent breast-conserving surgery with adjuvant radiation, 1498 patients with ER+PR+ disease were matched to 1498 patients with ER-PR- disease. No significant differences were noted with respect to cumulative incidence of any invasive event (5.6% vs. 5.6%) or ipsilateral invasive events (1.9% vs. 2.9%). In multivariate models, no significant differences were noted. Patients with ER-PR+ lesions had similar cumulative incidences of ipsilateral invasive events to patients with ER-PR- disease in the absence of radiation (5.9% vs. 5.9%) and similar cumulative incidences of contralateral invasive events to patients with ER+PR+ disease when radiation was administered (3.2% vs. 4.2%). Conclusion: The statuses of ER and PR carry independent prognostic and therapeutic implications beyond those of traditional clinicopathologic risk factors. Given that ER and PR statuses are routinely collected for patients with DCIS, incorporation of these variables into clinicopathologic risk classification systems is warranted. Full article

Background/Objectives: Contralateral breast cancer (CBC) is a significant concern among breast cancer survivors, particularly in those with moderator-high penetrance germline mutations such as BRCA1, BRCA2, CHEK2, and ATM. While radiotherapy (RT) is a crucial component of breast cancer (BC) treatment, its potential role in increasing CBC risk remains unclear. This systematic review and meta-analysis aim to evaluate the incidence of radiation-induced CBC in germline mutation carriers. Methods: Following PRISMA guidelines, we conducted a comprehensive search in six electronic databases (PubMed, Scopus, Cochrane Library, ProQuest, EBSCO, and Epistemonikos) for studies published fifteen years prior, up to August 2025. We included cohort and case–control studies assessing the association between RT and CBC incidence in germline mutation carriers. A meta-analysis was performed using a random-effects model to estimate cumulative risk (CR) and rate ratios (RR). Results: Seven studies were included. The 5-year cumulative risk (CR) of contralateral breast cancer (CBC) was 0.55 for BRCA1/2, 0.89 for ATM, and 0.80 for CHEK2 carriers. At 10 years, overall CR increased to 0.65, with ATM and CHEK2 remaining high. Rate ratio (RR) analysis showed a significant risk for ATM (2.98), while overall RR indicated more than a two-fold increased CBC risk with radiotherapy (RR = 2.70 common-effect; 2.53 random-effects). Conclusions: Radiotherapy significantly increases contralateral breast cancer risk, particularly in ATM and CHEK2 carriers, emphasizing the importance of personalized genetic risk stratification in treatment decisions. Full article

Ultrasound imaging is a crucial tool for guiding radiation therapy, particularly for cancers such as pancreatic cancer, where tumors exhibit respiration-induced motion. While flexible ultrasound transducers offer improved anatomical conformity and reduced compression-induced distortion compared to rigid probes, their variable geometry presents significant challenges for conventional beamforming. In this study, we investigate a deep learning-based beamforming framework that directly predicts delayed RF data from raw RF input, bypassing explicit transducer shape estimation and traditional delay-and-sum computations. Building upon an artificial curvature simulation strategy, we systematically analyze the impact of curvature-induced variation and inherent RF noise on model performance and generalizability. We further introduce frequency-domain analysis to quantify RF-level signal variation that may not be apparent in spatial-domain image comparisons. Our results demonstrate that although noise-augmented training improves prediction consistency, reconstruction performance remains limited under the current prototype noise conditions. These findings highlight the importance of RF data diversity and noise characterization in developing clinically robust deep learning beamformers for flexible transducer-based ultrasound-guided radiation therapy. Full article

Chronic diabetic wound remain difficult to heal because persistent inflammation, oxidative stress, and impaired regeneration delay repair, while effective noninvasive options are limited. In this study, graphene-based far-infrared radiation (FIR) therapy was evaluated in a streptozotocin (STZ)-induced diabetic rat full-thickness wound model, and mechanisms were examined in vivo and in vitro. Wound closure was quantified by serial imaging, whereas tissue remodeling and angiogenesis were assessed by H&E and Masson’s trichrome staining and CD34-based analyses. Transcriptomic responses were profiled by RNA sequencing with qRT-PCR validation, immune phenotypes were characterized by immunofluorescence, and high-glucose cell assays were performed. Re-epithelialization, collagen deposition, and neovascularization were quantified histologically. These datasets enabled integrated evaluation of inflammation, oxidative stress, and repair programs over time. Graphene FIR accelerated closure, reaching 83.9% healing by day 14 vs. 66.8% in untreated controls. Treatment was associated with downregulation of Cxcl2/Cxcl3, suppression of M1 polarization with enhanced M2 polarization, and reduced ROS accumulation. Consistently, NF-κB signaling was inhibited, supporting restoration of a pro-regenerative microenvironment. Collectively, graphene FIR represents a promising noninvasive strategy for diabetic wound repair via coordinated immunomodulatory and antioxidant actions. Full article