239700 research outputs found
Sort by
Regression and machine learning approaches identify potential risk factors for glioblastoma multiforme
No full textGlioblastoma multiforme is a lethal disease, with a 5-year survival rate of <10%. The identification of risk factors for glioblastoma multiforme is essential for the understanding of this disease and could facilitate more effective stratification of high-risk individuals. However, our current knowledge of glioblastoma multiforme risk factors is limited. Given the complexity and heterogeneity of the disease, traditional epidemiological approaches may be insufficient to study risk factors for glioblastoma multiforme. The combination of traditional approaches with machine learning models could prove effective in identifying relevant factors for glioblastoma multiforme risk. In this study, we developed glioblastoma multiformerisk models in the UK Biobank cohort using 576 glioblastoma multiforme cases and 302 602 controls. First, 369 exposures were tested with traditional regression models in a case–control study and significant associations were identified. Subsequently, significant features were filtered based on their completion rate and correlation. The selected exposures were then used to develop two machine learning models: a support vector machine and a Multi-Layer Perceptron. To address the imbalance within the subpopulation, two controls per case with full data were selected, resulting in 442 glioblastoma multiforme cases and 884 controls being analysed with the machine learning models. Relevant factors for glioblastoma multiforme risk were identified by explaining the results of the two models with Shapley Additive explanations. Traditional regression methods identified 38 significant associations between environmental exposures and glioblastoma multiforme risk under the Bonferroni threshold (P < 1.35 × 10−4). Subsequent filtration results in the selection of 12 exposures, which were then analysed with age, sex and a polygenic score using the two machine learning models. Support vector machine and the multi-layer perceptron demonstrated a good sensitivity (0.91 and 0.82, respectively). In addition to age and genetics, Shapley Additive explanations demonstrated significant contributions of insulin-like growth factor 1 blood levels and the right-hand grip strength on the predictions made by the models, with the latter effect potentially being confounded by endogenous testosterone levels. The integration of machine learning with traditional models has the potential to enhance the identification of risk factors for glioblastoma multiforme
KE-MHISTO: Towards a Multilingual Historical Knowledge Extraction Benchmark for Addressing the Long-Tail Problem
No full textLarge Language Models (LLMs) face significant challenges when queried about long-tail knowledge, i.e., information that is rarely encountered during their training process. These difficulties arise due to the inherent sparsity of such data. Furthermore, LLMs often lack the ability to verify or ground their responses in authoritative sources, which can lead to plausible yet inaccurate outputs when addressing infrequent subject matter. Our work aims to investigate these phenomena by introducing KE-MHISTO, a multilingual benchmark for Entity Linking and Question Answering in the domain of historical music knowledge, available in both Italian and English. We demonstrate that KE-MHISTO provides significantly broader coverage of long-tail knowledge compared to existing alternatives. Moreover, it poses substantial challenges for state-of-the-art models. Our experiments reveal that smaller, multilingual models can achieve performance comparable to significantly larger counterparts, highlighting the potential of efficient, language-aware approaches for long-tail knowledge extraction. KE-MHISTO is available at: https://github.com/polifonia-project/KE-MHISTO
Global and local minima of -Brjuno functions
No full textThe main goal of this article is to analyze some peculiar features of the global (and local) minima of α-Brjuno functions Bα where α∈(0,1]. Our starting point is the result by Balazard–Martin (Fund Math 218(3): 193–224, 2012). https://doi.org/10.4064/fm218-3-1, who showed that the minimum of B1 is attained at g:=5-12; analyzing the scaling properties of B1 near g we shall deduce that all preimages of g under the Gauss map are also local minima for B1. Next we consider the problem of characterizing global and local minima of Bα for other values of α: we show that for α∈(g,1) the global minimum is again attained at g, while for α in a neighbourhood of 1/2 the function Bα attains its minimum at γ:=2-1. The fact that the minimum of Bα is attained when α ranges over a whole interval of parameters is non trivial. Indeed, we prove that Bα is lower semicontinuous for all rational α, but we also exhibit an irrational α for which Bα is not lower semicontinuous
A Flexible Frequency-Coded Electromagnetic Sensing Array for Contactless Biological Tissues Health Monitoring
No full textIn this study, we present a wearable sensing system for monitoring the physiological status of damaged biological tissues based on a flexible, frequency-coded electromagnetic spiral resonator array. The physiological parameter evaluation is performed in a contactless way, avoiding the placing of electronically active elements directly upon the patient’s skin, thus ensuring safety and comfort. Firstly, we report in detail the physical principles behind the sensing strategy: a passive array is interrogated through an actively fed external single-loop probe that is inductively coupled with the double-layer spiral unit cells. The variation in the physiological parameters influences the array response, thus providing sensing information, due to the different complex dielectric permittivity values related to the tissue status. Moreover, the proposed frequency-coded approach allows for spatial information on the lesion to be retrieved, thus increasing the sensing ability. In order to prove the validity of this general methodology, we created a numerical test case, designing a practical implementation of the wearable sensing system working at a radiofrequency regime (10–100 MHz). In addition, we also fabricated prototypes, exploiting PCB technology, and realized stratified phantoms by incorporating opportune additives to control the dielectric properties. The numerical results and the experimental verification demonstrated the validity of the developed sensing strategy, showing satisfying agreement and, thus, proving the good sensibility and spatial resolution of the frequency-coded array. These results can open the path to a radically novel approach for self-care and monitoring of inflamed status and, more generally, for wearable sensing devices in biomedical applications
Advancing Cardiovascular Risk Stratification and Functional Assessment: A Narrative Review of CPET and ESE Applications
No full textCardiopulmonary exercise testing combined with exercise stress Echocardiography (CPET-ESE) is an advanced diagnostic modality for evaluating cardiovascular disease and tailoring patient-specific treatment strategies. By integrating metabolic, ventilatory, and hemodynamic data with real-time imaging, CPET-ESE offers a comprehensive assessment of cardiovascular function under physiological stress. CPET provides detailed insights into metabolic and ventilatory performance, while ESE allows for the dynamic visualisation of cardiac structure and function during exercise. This review outlines the physiological foundations and core parameters of CPET and ESE, emphasising their complementary roles in cardiovascular diagnostics and prognostication and exploring their clinical value for evaluating unexplained dyspnoea and exercise-induced hemodynamic abnormalities. CPET-ESE plays a pivotal role in detecting subtle hemodynamic abnormalities, assessing functional capacity, and contributing to earlier diagnosis, targeted interventions, and improved clinical outcomes
Premessa. Una serie di 'distinguo'.
No full textIl volume è la prima classificazione storiografico-letteraria delle opere scritte da psichiatri sulla malattia mentale (dai primi dell'Ottocento a oggi)
Corte Costituzionale e diritto privato: la funzione del metodo sistematico e i limiti della drittwirkung
No full textLavandula angustifolia Essential Oil: GC–MS Composition, In Vitro Antimicrobial Activity, Vapor-Phase Efficacy on Fruit and Vegetable Models, and Anti-Escherichia coli Effect in Sous-Vide Potatoes
No full textThis study evaluated the antimicrobial activity of Lavandula angustifolia essential oil (LAEO) in vitro and in the vapor phase (in situ) against selected bacteria and yeasts, and against Escherichia coli in a sous-vide potato model, while characterizing its chemical composition. GC–MS identified 40 compounds covering 99.8% of the oil, dominated by linalyl acetate (37.4%) and linalool (34.3%). By disk diffusion and minimum inhibitory concentration assays on six bacterial and five yeast strains, the best inhibition zone was observed for Bacillus subtilis (17.33 mm) and the lowest for Candida parapsilosis (6.67 mm); the most favorable MIC was for Candida glabrata (MIC50 0.533 mg/mL). In situ, the highest dose (500 μg/L) yielded the strongest effects on fruit models: B. subtilis inhibition 96.55% (strawberry) and Listeria monocytogenes 86.13% (banana). On vegetable models, the lowest dose (62.5 μg/L) was most effective, with 95.93% inhibition of E. coli on potato and 96.55% of Yersinia enterocolitica on radish. Kinetic growth experiments confirmed the potential of LAEO, particularly at elevated temperatures, to suppress E. coli. In the sous vide potato food model, counts were monitored on days 1 and 7; groups treated with LAEO showed the most pronounced inhibitory effects. Across the sous-vide potato model, MALDI-TOF profiling most frequently recovered members of Enterobacteriaceae and Pectobacteriaceae, with E. coli, Pectobacterium carotovora subsp. carotovora, and Bacillus licheniformis among the dominant taxa. Overall, the data support the antimicrobial potential of LAEO, with a matrix- and dose-dependent action in the vapor phase and a modest but measurable benefit in sous-vide potatoes, indicating promise as a natural preservative for plant-based foods and SV potatoes
Unveiling host-seeking behaviour in entomopathogenic nematodes via lab-on-a-chip technology
No full textEntomopathogenic nematodes (EPNs) can be employed as biological control agents (BCAs) for many insect pests’ sustainable management. Despite their widespread use, our understanding of EPNs biology, particularly interactions with their hosts, remains limited. Advancing knowledge of EPNs ecology and host interactions is crucial for optimising their efficacy in pest management. This study pioneers an interdisciplinary approach, at the interface of engineering and applied entomology, to investigate the behaviour of the EPN Steinernema carpocapsae. A novel method combining microfluidics, machine learning, and optical flow is presented. A lab-on-a-chip platform was designed to enable accurate investigation of EPN response to stimuli. A convolutional neural network (CNN) identified nematodes and distinguished their responses to host-derived cues achieving 0.94 accuracy and 1.00 precision in detecting stimulus presence at video-level, classifying EPN behaviour within a controlled environment that simulates host conditions. Optical flow analysis revealed differences in motor activity of EPN upon exposure to stimuli, providing new insights into their dynamic responses. Steinernema carpocapsae exhibited more intense activity in presence of host-borne cues (p = 0.0055). Support vector machine (SVM) and multilayer perceptron (MLP) classifiers distinguished stimulus contexts from optical flow features, with an area under the receiver operating characteristic (ROC) curve of 0.71. These results highlight that, although S. carpocapsae is typically considered an ambusher, it may actively engage in host-seeking behaviour, suggesting a shift in our understanding of its search strategies. This methodology significantly enhances the detection and understanding of EPN responses to cues, advancing their potential in precision biocontrol programs for sustainable pest management actions. Science4Impact statement (S4IS): This study develops a novel lab-on-a-chip platform integrating artificial intelligence (AI) for the precise investigation of host-seeking behaviours in the entomopathogenic nematode Steinernema carpocapsae, a biological control agent (BCA) with potential for sustainable pest management. By combining microfluidic design with deep learning, the platform accurately assesses nematode responses to host-derived cues, providing new insights into its foraging adaptability beyond conventional techniques. This research can help researchers and agricultural stakeholders by enhancing understanding of BCA behaviour, optimising pest control applications, and informing evidence-based decisions on sustainable crop protection. The findings also support quality assurance in biological control validation by offering a rigorous framework for evaluating nematode effectiveness under realistic conditions, promoting its broader adoption in integrated pest management strategies
Circulating free PSA in breast cancer patients: is it a reliable biomarker?
No full textIntroduction: Prostate-specific antigen (PSA), a serine protease primarily expressed in the prostate, has also been detected in hormonally regulated female tissues, including the breast. Some studies suggest a correlation between increased levels of circulating free PSA (fPSA) and breast cancer, but its role remains debated. This study aimed to evaluate this association while minimizing hormonal confounding factors. Methods: A total of 82 breast cancer patients (aged 35–86 years) and 31 healthy premenopausal women (aged 18–58 years) were enrolled. Patients had a primary breast cancer diagnosis with no other malignancies and had not undergone preoperative chemotherapy or radiotherapy. Participants with hormonal conditions affecting PSA expression were excluded. fPSA levels were measured using an improved VIDAS® fPSA immunoassay with enhanced analytical sensitivity. Results: Despite the increased sensitivity of the modified assay, fPSA was undetectable in all plasma samples. This may be due to the exclusion of participants with hormonal imbalances who might exhibit higher PSA expression. Conclusions: The absence of androgen receptor (AR)-positive triple-negative breast cancer (TNBC) patients in this cohort further supports the role of androgens in PSA regulation. These findings suggest that fPSA may not be a reliable circulating biomarker for breast cancer. However, a key limitation is the lack of fPSA assessment within breast cancer tissue. Future studies should investigate its expression in tumors, particularly in AR-positive TNBC, and evaluate circulating fPSA and testosterone levels as potential biomarkers of tumor androgenic activity