Search Results (914)

Background: Angiosarcomas (ASs) represent a heterogeneous and highly aggressive subset of tumors that respond poorly to systemic treatments and are associated with short progression-free survival (PFS) and overall survival (OS). The aim of this study was to develop and validate an immune-related prognostic model—termed the AS score—using data from two independent sarcoma cohorts. Methods: A prognostic model was developed using a previously characterized cohort of 25 angiosarcoma samples. Candidate genes were identified via the Maxstat algorithm (Maxstat v0.7-25 for R), combined with log-rank testing. The AS score was then computed by weighing normalized gene expression levels according to Cox regression coefficients. For external validation, transcriptomic data from TCGA Sarcoma cohort (n = 253) were analyzed. The Immunoscore—which reflects the tumor immune microenvironment—was inferred using the ESTIMATE package (v1.0.13) in R. All statistical analyses were performed in RStudio (v 4.0.3). Results: Four genes—IGF1R, MAP2K1, SERPINE1, and TCF12—were ultimately selected to construct the prognostic model. The resulting AS score enabled the classification of angiosarcoma cases into two prognostically distinct groups (p = 0.00012). Cases with high AS score values, which included both cutaneous and non-cutaneous forms, exhibited significantly poorer outcomes, whereas cases with low AS scores were predominantly cutaneous. A significant association was observed between the AS score and the Immunoscore (p = 0.025), with higher Immunoscore values found in high-AS score tumors. Validation using TCGA sarcoma cohort confirmed the prognostic value of both the AS score (p = 0.0066) and the Immunoscore (p = 0.0029), with a strong correlation between their continuous values (p = 2.9 × 10⁻⁸). Further survival analysis, integrating categorized scores into four groups, demonstrated robust prognostic significance (p = 0.00021). Notably, in tumors with a low Immunoscore, AS score stratification was not prognostic. In contrast, among cases with a high Immunoscore, the AS score effectively distinguished outcomes (p < 0.0001), identifying a subgroup with poor prognosis but potential sensitivity to immunotherapy. Conclusions: This combined classification using the AS score and Immunoscore has prognostic relevance in sarcoma, suggesting that angiosarcomas with an immunologically active microenvironment (high Immunoscore) and poor prognosis (high AS score) may be prime candidates for immunotherapy and this approach warrants prospective validation. Full article

This study developed a copper mineral prospectivity map for the Koldar massif, Kazakhstan, using an integrated approach combining geophysical and satellite methods. A strong spatialgenetic link was identified between faults and hydrothermal mineralization, with faults acting as key conduits for ore-bearing fluids. Lineament analysis and density mapping confirmed the high permeability of the Koldar massif, indicating its structural prospectivity. Hyperspectral and multispectral data (ASTER, PRISMA, WorldView-3) were applied for detailed mapping of hydrothermal alteration (phyllic, propylitic, argillic zones), which are critical for discovering porphyry copper deposits. In particular, WorldView-3 imagery facilitated the identification of new prospective zones. The transformation of magnetic and gravity data successfully delineated geological features and structural boundaries, confirming the fractured nature of the massif, a key structural factor for mineralization. The resulting map of prospective zones, created by normalizing and integrating four evidential layers (lineament density, PRISMA-derived hydrothermal alteration, magnetic, and gravity anomalies), is thoroughly validated, successfully outlining the known Aktogay, Aidarly, and Kyzylkiya deposits. Furthermore, new, previously underestimated prospective areas were identified. This work fills a significant knowledge gap concerning the Koldar massif, which had not been extensively studied using satellite methods previously. The key advantage of this research lies in its comprehensive approach and the successful application of high-quality hyperspectral imagery for mapping new prospective zones, offering a cost-effective and efficient alternative to traditional ground-based investigations. Full article

Three-dimensional geological modeling combined with the information value method offers a powerful approach for predicting mineralization in complex geological settings. This study applies these techniques to the Bainiuchang Ag polymetallic deposit in Southwest China. We constructed a detailed 3D geological model to identify key geological factors influencing mineralization, such as the F₃ fault, secondary faults, and the middle Cambrian Tianpeng Formation. Using the information value method, we evaluated the mineralization potential of each unit in the study area. Receiver operating characteristic (ROC) curves and fractal analysis were employed to determine an optimal threshold (information value > 2.6) for delineating high-potential exploration targets. Our results identified three priority targets (A1, A2, and A3), demonstrating the effectiveness of integrating 3D modeling with probabilistic mineral prospectivity mapping. This approach provides a robust framework for deep and peripheral exploration in structurally complex deposits, offering valuable insights for future mineral exploration efforts. Full article

Simultaneous Localization and Mapping (SLAM) has long been a fundamental and challenging task in robotics literature, where safety and reliability are the critical issues for successfully autonomous applications of robots. Classically, the SLAM problem is tackled via probabilistic or optimization methods (such as EKF-SLAM, Fast-SLAM, and Graph-SLAM). Despite their strong performance in real-world scenarios, these methods may exhibit inconsistency, which is caused by the inherent characteristic of model linearization or Gaussian noise assumption. In this paper, we propose an alternative monocular SLAM algorithm which theoretically relies on interval analysis (iMonoSLAM), to pursue guaranteed rather than probabilistically defined solutions. We consistently modeled and initialized the SLAM problem with a bounded-error parametric model. The state estimation process is then cast into an Interval Constraint Satisfaction Problem (ICSP) and resolved through interval constraint propagation techniques without any linearization or Gaussian noise assumption. Furthermore, we theoretically prove the obtained consistency and propose a versatile method for numerical validation. To the best of our knowledge, this is the first time such a proof has been proposed. A plethora of numerical experiments are carried to validate the consistency, and a preliminary comparison with classical EKF-SLAM in different noisy situations is also presented. Our proposed iMonoSLAM shows outstanding performance in obtaining reliable solutions, highlighting the potential application prospect in safety-critical scenarios of mobile robots. Full article

Background: Annual influenza vaccine updates target viral drift, but immune responses may be biased by original antigenic sin (OAS). Few studies have explored this across closely related strains. This study examines how OAS shapes responses to sequential influenza variants in the context of seasonal vaccination. Methods: We conducted a prospective, longitudinal study to assess the humoral immune response to the 2023–2024 seasonal influenza vaccine containing the A/Victoria/4897/2022 (H1N1) strain. Bioinformatic analyses compared the hemagglutinin (HA) sequences of A/Victoria/4897/2022 and the antigenically related A/Victoria/2570/2019 strain. B-cell epitopes were mapped with BepiPred-3.0 and BepiBlast, and their physicochemical properties analyzed via accessibility, β-turns, flexibility, and hydrophilicity. Antibody responses were measured pre- and 28 days post-Vaxigrip Tetra vaccination in young (18–35) and older (>65) adults, stratified by cytomegalovirus (CMV) serostatus. HA sequences showed >97% identity, with variations mainly in the globular head. Predicted B-cell epitopes overlapped variable sites, suggesting possible immune escape. Despite having been vaccinated against the 2022 strain, serology showed higher antibody titers against the 2019 HA strain in all participants. This pattern suggests a potential antigen imprinting effect, though confirmation awaits further analysis. Age groups differed: older adults showed greater variability, while younger CMV+ individuals tended toward stronger 2019 HA responses. Conclusions: These findings suggest a complex interplay of factors shaping immune responses, though the imprinting effect and the potential role of CMV warrant further exploration in larger, more focused studies. Full article

Background/Objectives: The SENTIREC-endo study identified a safe sentinel lymph node mapping algorithm combined with PET-positive node dissection, matching radical pelvic and paraaortic lymphadenectomy in high-risk endometrial cancer. The present study evaluated the diagnostic accuracy of FDG-PET/CT for lymph node metastases in the same population based on location, size, and Standardised Uptake Value (SUV), in addition to assessing interrater agreement across three Danish centres. Methods: This prospective multicentre study included women with high-risk endometrial cancer from the Danish SENTIREC study database (2017–2023). All patients underwent preoperative FDG-PET/CT. Diagnostic accuracy was evaluated against a pathology-confirmed reference standard. Interrater agreement was evaluated between trained specialists in Nuclear Medicine. Results: Among 227 patients, 52 patients (23%) had lymph node metastases. FDG-PET/CT identified lymph node metastases with 56% sensitivity (95% CI: 42–68) and 91% specificity (95% CI: 86–94). Positive and negative predictive values were 64% and 87%, respectively. Specificity for paraaortic nodes was high (97%), though sensitivity remained limited (56%). Lymph node size and SUVmax had moderate diagnostic value (AUC-ROC ~0.7). Interrater proportion of agreement was 95% and Cohen’s Kappa κ = 0.84 (95% CI: 0.73–0.94), the latter of which was ‘almost perfect’. Conclusions: FDG-PET/CT had limited sensitivity in lymph node staging in high-risk EC, and the diagnostic accuracy of FDG-PET/CT remains complementary to the sentinel node procedure. Due to its high specificity and strong interrater reliability, FDG-PET/CT is recommended for clinical implementation in combination with the sensitive sentinel node biopsy for the targeted dissection of PET-positive lymph nodes, particularly in paraaortic regions. Full article

The significant burden of polypharmacy in clinical settings contrasts sharply with the narrow research focus on drug–drug interactions (DDIs), revealing an important gap in understanding the complexity of real-world multi-drug regimens. The present study addresses this gap by conducting a high-resolution, multidimensional bibliometric and network analysis of 19,151 DDI publications indexed in the Web of Science Core Collection (1975–2025). Using advanced tools, including VOSviewer version 1.6.20, Bibliometrix 5.0.0, and AI-enhanced terminology normalization, global research trajectories, knowledge clusters, and collaborative dynamics were systematically mapped. The analysis revealed an exponential growth in publication volume (from 55 in 1990 to 1194 in 2024), with output led by the United States and a marked acceleration in Chinese contributions after 2015. Key pharmacological agents frequently implicated in DDI research included CYP450-dependent drugs such as statins, antiretrovirals, and central nervous system drugs. Thematic clusters evolved from mechanistic toxicity assessments to complex frameworks involving clinical risk management, oncology co-therapies, and pharmacokinetic modeling. The citation impact peaked at 3.93 per year in 2019, reflecting the increasing integration of DDI research into mainstream areas of pharmaceutical science. The findings highlight a shift toward addressing polypharmacy risks in aging populations, supported by novel computational methodologies. This comprehensive assessment offers insights for researchers and academics aiming to navigate the evolving scientific landscape of DDIs and underlines the need for more nuanced system-level approaches to interaction risk assessment. Future studies should aim to incorporate patient-level real-world data, expand bibliometric coverage to underrepresented regions and non-English literature, and integrate pharmacogenomic and time-dependent variables to enhance predictive models of interaction risk. Cross-validation of AI-based approaches against clinical outcomes and prospective cohort data are also needed to bridge the translational gap and support precision dosing in complex therapeutic regimens. Full article

This technical report presents a compelling case for the use of very-high-power, very-short-duration (VHPSD) radiofrequency ablation as a promising and efficient strategy for treating symptomatic premature ventricular contractions (PVCs) originating from the right ventricular outflow tract (RVOT). The patient with frequent, symptomatic PVCs and a 24% burden underwent successful ablation using a 90 W/4 s recipe via the QDOT MICRO™ catheter. The procedure resulted in immediate and sustained elimination of PVCs, with only 4 s of ablation time, near-zero fluoroscopy, no complications, and no PVC recurrence at 6 months. VHPSD ablation, though originally developed for atrial fibrillation, demonstrated remarkable procedural efficiency, precision, and lesion efficacy in this case. Compared to standard power, long-duration (SPLD) ablation, VHPSD offers the potential to significantly reduce procedural time, minimize tissue edema, and lower complication risk, particularly advantageous in anatomically challenging areas or in situations where maintaining stable catheter contact for extended periods is difficult or unfeasible. This technical report suggests the transformative potential of VHPSD as a first-line ablation strategy for RVOT-PVCs, provided careful mapping and appropriate technique are used. It underscores the need for further prospective studies to validate its broader safety, efficacy, and role in PVC management, particularly in cases involving intramural origins. Full article

Accurate analysis of medical videos remains a major challenge in deep learning (DL) due to the need for effective spatiotemporal feature mapping that captures both spatial detail and temporal dynamics. Despite advances in DL, most existing models in medical AI focus on static images, overlooking critical temporal cues present in video data. To bridge this gap, a novel DL-based framework is proposed for spatiotemporal feature extraction from medical video sequences. As a feasibility use case, this study focuses on gastrointestinal (GI) endoscopic video classification. A 3D convolutional neural network (CNN) is developed to classify upper and lower GI endoscopic videos using the hyperKvasir dataset, which contains 314 lower and 60 upper GI videos. To address data imbalance, 60 matched pairs of videos are randomly selected across 20 experimental runs. Videos are resized to 224 × 224, and the 3D CNN captures spatiotemporal information. A 3D version of the parallel spatial and channel squeeze-and-excitation (P-scSE) is implemented, and a new block called the residual with parallel attention (RPA) block is proposed by combining P-scSE3D with a residual block. To reduce computational complexity, a (2 + 1)D convolution is used in place of full 3D convolution. The model achieves an average accuracy of 0.933, precision of 0.932, recall of 0.944, F1-score of 0.935, and AUC of 0.933. It is also observed that the integration of P-scSE3D increased the F1-score by 7%. This preliminary work opens avenues for exploring various GI endoscopic video-based prospective studies. Full article

Background: Hypotension following epidural labor analgesia (ELA) is its most common complication, affecting approximately 20% of patients and posing risks to both maternal and fetal health. As digital tools and predictive analytics increasingly shape perioperative and obstetric anesthesia practices, real-world implementation data are needed to guide their integration into clinical care. Current monitoring practices rely on intermittent non-invasive blood pressure (NIBP) measurements, which may delay recognition and treatment of hypotension. The Hypotension Prediction Index (HPI) algorithm uses continuous arterial waveform monitoring to predict hypotension for potentially earlier intervention. This clinical trial evaluated the feasibility, acceptability, and efficacy of continuous HPI-guided treatment in reducing time-to-treatment for ELA-associated hypotension and improving maternal hemodynamics. Methods: This was a prospective randomized controlled trial design involving healthy pregnant individuals receiving ELA. Participants were randomized into two groups: Group CM (conventional monitoring with NIBP) and Group HPI (continuous noninvasive blood pressure monitoring). In Group HPI, hypotension treatment was guided by HPI output; in Group CM, treatment was based on NIBP readings. Feasibility, appropriateness, and acceptability outcomes were assessed among subjects and their bedside nurse using the Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of Intervention Measure (FIM) instruments. The primary efficacy outcome was time-to-treatment of hypotension, defined as the duration between onset of hypotension and administration of a vasopressor or fluid therapy. This outcome was chosen to evaluate the clinical responsiveness enabled by HPI monitoring. Hypotension is defined as a mean arterial pressure (MAP) < 65 mmHg for more than 1 min in Group CM and an HPI threshold < 75 for more than 1 min in Group HPI. Secondary outcomes included total time in hypotension, vasopressor doses, and hemodynamic parameters. Results: There were 30 patients (Group HPI, n = 16; Group CM, n = 14) included in the final analysis. Subjects and clinicians alike rated the acceptability, appropriateness, and feasibility of the continuous monitoring device highly, with median scores ≥ 4 across all domains, indicating favorable perceptions of the intervention. The cumulative probability of time-to-treatment of hypotension was lower by 75 min after ELA initiation in Group HPI (65%) than Group CM (71%), although this difference was not statistically significant (log-rank p = 0.66). Mixed models indicated trends that Group HPI had higher cardiac output (β = 0.58, 95% confidence interval −0.18 to 1.34, p = 0.13) and lower systemic vascular resistance (β = −97.22, 95% confidence interval −200.84 to 6.40, p = 0.07) throughout the monitoring period. No differences were found in total vasopressor use or intravenous fluid administration. Conclusions: Continuous monitoring and precision hypotension treatment is feasible, appropriate, and acceptable to both patients and clinicians in a labor and delivery setting. These hypothesis-generating results support that HPI-guided treatment may be associated with hemodynamic trends that warrant further investigation to determine definitive efficacy in labor analgesia contexts. Full article

Sport injury recognition is rapidly evolving with the integration of new emerging technologies. This systematic review aims to identify and evaluate technologies capable of detecting injuries during sports participation. A comprehensive search of PUBMED, Sport Discus, Web of Science, and ScienceDirect was conducted following the PRISMA 2020 guidelines. The review was registered on PROSPERO (CRD42024608964). Inclusion criteria focused on prospective studies involving athletes of all ages, evaluating tools which are utilised to identify injuries in sports settings. The review included research between 2014 and 2024; retrospective, conceptual, and fatigue-focused studies were excluded. Risk of bias was assessed using the Critical Appraisal Skills Program (CASP) tool. Of 4283 records screened, 70 full-text articles were assessed, with 21 studies meeting the final inclusion criteria. The technologies were grouped into advanced imaging (Magnetic Resonance Imaging (MRI), Diffusion Tensor Imaging (DFI), and Quantitative Susceptibility Mapping (QSM), with biomarkers (i.e., Neurofilament Light (NfL), Tau protein, Glial Fibrillary Acidic Protein (GFAP), Salivary MicroRNAs, and Immunoglobulin A (IgA), and sideline assessments (i.e., the King–Devick test, KD-Eye Tracking, modified Balance Error Scoring System (mBESS), DETECT, ImPACT structured video analysis, and Instrumented Mouth Guards (iMGs)), which demonstrated feasibility for immediate sideline identification of injury. Future research should improve methodological rigour through larger, diverse samples and controlled designs, with real-world testing environments. Following this guidance, the application of emerging technologies may assist medical staff, coaches, and national governing bodies in identifying injuries in a sports setting, providing real-time assessment. Full article

Mathematical modeling and computer visualization of hazardous zones of toxic substance cloud spread that occur during different accidents at industrial enterprises located near residential areas are in high demand to support the operational planning of evacuation measures and accident response. The possible chain-like nature of fires and explosions of containers with toxic substances inside increases the importance of predicting changes in hazardous zone parameters in real time. The objective of this study is to develop algorithms for the development of a mathematical model of a hazardous zone during an explosion and fire at an enterprise. The subject of this study is a software tool created for the visualization of hazardous substance emission zones in real time, superimposed onto a development map to determine potential damage to human health and for the operational planning of evacuation measures. The proposed model takes into account variables such as the air temperature, wind speed and direction, the mass of the substance at each explosion and fire site, etc. C# and Visual Studio 2022 languages and an SQL database were used to create a software tool for visualizing the hazardous area. The testing of the calculation model and software used for the visualization of the hazardous zones of toxic substance cloud spread are presented on the basis of explosion cases involving a railway tank containing ammonia and the combustion of polyvinyl chloride at a chemical industry enterprise. The results confirmed the operability of the software and the prospects of its use in regard to the mitigation of the consequences of human-made accidents. Full article

Background and Objectives: Non-invasive imaging biomarkers for the early detection of chronic kidney allograft injury are needed to improve long-term transplant outcomes. T1 mapping by magnetic resonance imaging (MRI) has emerged as a promising method to assess renal structure and function. This study aimed to determine the potential of MRI as a diagnostic tool for evaluating graft function and structural changes in kidney grafts 1 year after transplantation. Materials and Methods: Thirty-four kidney transplant recipients were prospectively recruited, with 27 completing the follow-up at one year. Renal MRI at 3T was performed to acquire T1, T2, and apparent diffusion coefficient (ADC) maps. Clinical parameters, including estimated glomerular filtration rate (eGFR), albumin-to-creatinine ratio (ACR), protein-to-creatinine ratio (PCR), and histological IF/TA scores, were collected. MRI parameters were compared across the groups stratified by clinical and histological markers. Diagnostic accuracy was assessed using receiver operating characteristic (ROC) analysis. Results: At 1 year, T1 corticomedullary differentiation (CMD) values were significantly higher in patients with elevated ACR (≥3 mg/mmol), PCR (≥15 mg/mmol), and mild to moderate or severe IF/TA, reflecting a reduction in the corticomedullary gradient. T1 CMD demonstrated moderate-to-good diagnostic performance in detecting ACR (AUC 0.791), PCR (AUC 0.730), and IF/TA (AUC 0.839). No significant differences were observed in T2 or ADC values across these groups. T1 CMD also showed a significant positive correlation with ACR but not with eGFR, suggesting a closer association with structural rather than functional deterioration. Conclusions: T1 mapping, particularly T1 CMD, shows promise as a non-invasive imaging biomarker for detecting chronic allograft injury and monitoring renal function 1 year after kidney transplantation. Full article

Background: Since the 1980s, numerous case reports have explored the use of intramuscular botulinum toxin (BoNT) for Complex Regional Pain Syndrome (CRPS), with significant variation in rationale, dosing, guidance techniques, and outcome measures. This narrative review aims to summarize published evidence on the use of intramuscular BoNT in patients with CRPS, including studies using earlier terminology such as reflex sympathetic dystrophy (RSD). Given the heterogeneous and largely anecdotal nature of the literature, this review is intended to map the existing landscape rather than conduct a formal analysis. Methods: The PubMed and EMBASE databases were searched in August 2024 using terms related to CRPS and botulinum toxin. Following abstract and full-text screening, 25 publications were included. Results: The included studies span single case reports, case series, and small cohorts, encompassing at least 96 individual CRPS patients treated with intramuscular BoNT. Reported outcomes were heterogeneous, and key treatment parameters—such as toxin type, target muscles, guidance technique, and dosing—were inconsistently reported. Conclusion: The evidence for intramuscular BoNT in CRPS remains limited and heterogeneous, preventing firm conclusions on its efficacy or safety. Its use may be considered in select cases, particularly those with disabling or painful focal dystonia or myofascial pain, but standardized prospective studies are needed to clarify its clinical role. Full article

The Xixia Imperial Tombs (XITs) represent a crucial, yet still largely mysterious, component of the Tangut civilization’s legacy. Located in northwestern China, this extensive necropolis offers invaluable insights into the Tangut state, culture, and burial practices. This study employs an integrated approach utilizing multi-resolution and multi-temporal satellite remote sensing data, including Gaofen-2 (GF-2), Landsat-8 OLI, declassified GAMBIT imagery, and Google Earth, combined with deep learning techniques, to conduct a comprehensive archaeological investigation of the XITs’ burial landscape. We performed geomorphological analysis of the surrounding environment and automated identification and mapping of burial mounds and mausoleum features using YOLOv5, complemented by manual interpretation of very-high-resolution (VHR) satellite imagery. Spectral indices and image fusion techniques were applied to enhance the detection of archaeological features. Our findings demonstrated the efficacy of this combined methodology for archaeology prospect, providing valuable insights into the spatial layout, geomantic considerations, and preservation status of the XITs. Notably, the analysis of declassified GAMBIT imagery facilitated the identification of a suspected true location for the ninth imperial tomb (M9), a significant contribution to understanding Xixia history through remote sensing archaeology. This research provides a replicable framework for the detection and preservation of archaeological sites using readily available satellite data, underscoring the power of advanced remote sensing and machine learning in heritage studies. Full article