Search Results (12)

The rapid advancement of artificial intelligence (AI) has spurred innovation across various domains—information technology, medicine, education, and the social sciences—and is likewise creating new opportunities in architecture for understanding human–environment interactions. This study aims to develop a fine-tuned AI model that leverages electroencephalography (EEG) data to analyse users’ emotional states in real time and apply these insights to architectural spaces. Specifically, the SEED dataset—an EEG-based emotion recognition resource provided by the BCMI laboratory at Shanghai Jiao Tong University—was employed to fine-tune the ChatGPT model for classifying three emotional states (positive, neutral, and negative). Experimental results demonstrate the model’s effectiveness in differentiating these states based on EEG signals, although the limited number of participants confines our findings to a proof of concept. Furthermore, to assess the feasibility of the proposed approach in real architectural contexts, we integrated the model into a 360° virtual reality (VR) setting, where it showed promise for real-time emotion recognition and adaptive design. By combining AI-driven biometric data analysis with user-centred architectural design, this study aims to foster sustainable built environments that respond dynamically to human emotions. The results underscore the potential of EEG-based emotion recognition for enhancing occupant experiences and provide foundational insights for future investigations into human–space interactions. Full article

Background: Malnutrition is highly prevalent in patients with head and neck cancer, with relevant consequences in the treatment results. Methods: Multicenter observational study including 514 patients diagnosed with HNC. The morphofunctional assessment was carried out during the first 2 weeks of radiotherapy treatment. A correlation analysis between nutritional variables and groups of malnutrition, a multivariate logistic regression analysis, and a random forest analysis to select the most relevant variables to predict malnutrition were performed. Results: In total, 51.6% were undernourished (26.3% moderately and 25.3% severely). There was a negative correlation between morphofunctional variables and a positive correlation between hsCRP and well vs. moderate and well vs. severe malnutrition groups. The increase in different bioelectrical and ultrasound parameters was associated with a lower risk of moderate and severe malnutrition when groups with different degrees of malnutrition were compared. To predict the importance of morphofunctional variables on the risk of undernutrition, a nomogram, a random forest, and decision tree models were conducted. For the well vs. moderate, for the well vs. severe, and for the moderate vs. severe malnutrition groups, FFMI (cut-off < 20 kg/m²), BCMI (cut-off < 7.6 kg/m²), and RF-Y-axis (cut-off < 0.94 cm), respectively, were the most crucial variables, showing a greater probability of mortality in the two last comparisons. Conclusions: Malnutrition is very prevalent in HNC patients. Morphofunctional assessment with simple tools such as electrical impedance and muscle ultrasound allows an early nutritional diagnosis with an impact on survival. Therefore, these techniques should be incorporated into the daily clinical attention of patients with HNC. Full article

Background. Childhood brain tumor survivors (CCSs) are at high risk of developing metabolic syndrome (MetS) and sarcopenia. To date, a tool able to predict any body composition changes or detect them early and increased adiposity (and, therefore, increased likelihood of MetS onset) is still lacking in this population. Objective. The objective was to analyze differences in a bioelectrical impedance analysis (BIA) of body composition between male childhood brain tumor cancer survivors and healthy controls. Methods. In this pilot, prospective, observational study, 14 male CCSs were compared to 14 healthy controls matched for sex and age. Results. CCSs showed statistically significant lower mean values in terms of their body metabolic rate (BMR), body cell mass index (BCMI), fat-free mass (FFM), skeleton muscle mass (SM), skeletal muscle mass index (SMI), and appendicular skeletal muscular mass (ASMM). CCSs also showed a statistically significantly higher mean value of resistance when compared with controls. The BMR, BCM, FFM, and ASMM were significantly correlated with total doses of carboplatin (Tau = −0.601; p = 0.018; Tau = −0.599, p = 0.025; Tau = −0.601, p = 0.018; Tau = −0.509, p = 0.045, respectively). Conclusion. A BIA allows for the detection of changes in body composition in survivors of childhood brain tumors, revealing either the presence of central obesity correlated with the risk of MetS or signs of sarcopenia that deserve early treatment. Full article

Nutritional therapy (NT) based on a controlled protein intake represents a cornerstone in managing chronic kidney disease (CKD). However, if a CKD patient is at the same time affected by cancer, oncologists and nutritionists tend to suggest a dietary regimen based on high protein intake to avoid catabolism and malnutrition. International guidelines are not clear when we consider onco-nephrological patients and, as a consequence, no clinical shared strategy is currently applied in clinical practice. In particular, no precise nutritional management is established in nephrectomized patients for renal cell carcinoma (RCC), a specific oncological cohort of patients whose sudden kidney removal forces the remnant one to start a compensatory mechanism of adaptive hyperfiltration. Our study aimed to investigate the efficacy of a low–normal-protein high-calorie (LNPHC) diet based on a Mediterranean model in a consecutive cohort of nephrectomized RCC patients using an integrated nephrologist and nutritionist approach. A consecutive cohort of 40 nephrectomized RCC adult (age > 18) patients who were screened for malnutrition (malnutrition screening tool, MST < 2) were enrolled in a tertiary institution between 2020 and 2022 after signing a specific informed consent form. Each patient underwent an initial nephrological and nutritional evaluation and was subsequently subjected to a conventional CKD LNPHC diet integrated with aproteic foods (0.8 g/Kg/die: calories: 30–35 kcal per kg body weight/die) for a period of 6 months (±2 months). The diet was structured after considering eGFR (CKD-EPI 2021 creatinine formula), comorbidities, and nutritional status. MST, body mass index (BMI), phase angle (PA), fat mass percentage (FM%), fat-free mass index (FFMI), body cell mass index (BCMI), extracellular/intracellular water ratio (ECW/ICW), extracellular matrix/body cell mass ratio (ECM/BCM), waist/hip circumference ratio (WHC), lab test exams, and clinical variables were examined at baseline and after the study period. Our results clearly highlighted that the LNPHC diet was able to significantly improve several nutritional parameters, avoiding malnutrition and catabolism. In particular, the LNPHC diet preserved the BCM index (delta on median, ΔM + 0.3 kg/m²) and reduced the ECM/BCM ratio (ΔM − 0.03 *), with a significant reduction in the ECW/ICW ratio (ΔM − 0.02 *), all while increasing TBW (ΔM + 2.3% *). The LNPHC diet was able to preserve FFM while simultaneously depleting FM and, moreover, it led to a significant reduction in urea (ΔM − 11 mg/dL **). In conclusion, the LNPHC diet represents a new important therapeutic strategy that should be considered when treating onco-nephrological patients with solitary kidney due to renal cancer. Full article

Amyotrophic lateral sclerosis (ALS) is a progressive disease with a high prevalence of malnutrition that can influence prognosis. The main objective of this study is to compare the validity of muscle ultrasonography in the diagnosis of malnutrition and the prognosis of patients with ALS. Methods: This is a prospective observational study that analyzes the nutritional status of patients at the beginning of nutritional monitoring. The morphofunctional assessment included the examination of anthropometric variables such as weight, height, body mass index (BMI), arm circumference, and calf circumference. Additionally, electrical bioimpedanciometry (BIA) was used to measure electrical parameters and estimate other relevant metrics. Muscle ultrasonography^® (quadriceps rectus femoris (QRF)) assessed muscle mass parameters, including muscle area index (MARAI), anteroposterior diameter of the QRF (Y-axis) (cm), transverse diameter of the QRF (X-axis) (cm), and the sum of the quadriceps thickness (RF+VI) (cm), as well as muscle quality parameters such as echogenicity and the Y–X index. Results: A total of 37 patients diagnosed with amyotrophic lateral sclerosis (ALS) were included in this study. Of these patients, 51.4% were men. The mean age was 64.27 (12.59) years. A total of 54.1% of the patients had a bulbar onset of amyotrophic lateral sclerosis, and 45.9% had spinal onset. The percentage of subjects with malnutrition diagnosed by the Global Leadership Initiative on Malnutrition (GLIM) criteria was 45.9% of patients. There was a direct correlation between muscle mass parameters assessed by muscle ultrasonography (RF+VI) and active mass markers measured by bioimpedanciometry (body cellular mass index (BCMI) (r = 0.62; p < 0.01), fat-free mass index (FFMI) (r = 0.75; p < 0.01), and appendicular skeletal mass index (ASMI) (r = 0.69; p < 0.01)). There was a direct correlation between echogenicity and resistance (r = 0.44; p = 0.02), as well as between the fat-free mass index and the Y–X index (r = 0.36; p = 0.14). Additionally, there was a negative correlation between echogenicity and BCMI (r = −0.46; p < 0.01) and ASMI (r = 0.34; p = 0.06). Patients with low quadriceps thickness (male < 2.49 cm; female < 1.84 cm) showed an increased risk of hospital admission adjusted by age, sex, and presence of dysphagia (OR: 7.84 (CI 95%: 1.09–56.07); p-value = 0.04), and patients with low-quality mass (Y–X index < 0.35) had a higher risk of hospital admission adjusted by age, sex, and presence of dysphagia (OR: 19.83 (CI 95%: 1.77–222.46); p-value = 0.02). Conclusions: In patients with ALS, ultrasonography echogenicity was inversely related to BCMI, FFMI, and ASMI, and the Y–X index was directly related to FFMI. The lowest quartiles of quadriceps thickness and Y–X index are risk factors for hospital admission. Full article

Background: Sarcopenia has recently been recognized as a complication of diabetes. However, there are few results about the prevalence of sarcopenia and dynapenia and the related clinical outcomes in type 1 diabetes mellitus (T1DM). Our objectives were to evaluate the prevalence of sarcopenia and dynapenia and to determine whether there are any associations with disease-related factors in people with T1DM. Methods: A cross-sectional study was conducted in people with T1DM. We assessed appendicular skeletal mass index (ASMI) using bioimpedance 50 Hz (Nutrilab Akern). Muscle function was assessed through handgrip strength (HGS) using a Jamar dynamometer. Sarcopenia was defined as a low HGS with low ASMI, whereas dynapenia was defined as low HGS with a normal ASMI. We used HGS data from the Spanish population percentile table and a cut-off point at p5 as dynapenia. The association of clinical, metabolic, and lifestyle variables with sarcopenia and dynapenia was studied. Results: This study included 62 T1DM patients (66% females, mean age of 38 ± 14 years, body mass index (BMI) of 24.9 ± 4.7 kg/m²). The prevalence of sarcopenia and dynapenia was 8% and 23%, respectively. In our sample, there were more men in the sarcopenic and dynapenic groups. The sarcopenic group showed a significantly higher mean HbA1c value. Lower diabetes duration, PREDIMED score, BMI, and muscle mass measures (fat-free mass index (FFMI), ASMI, and body cell mass index (BCMI)) were significantly associated with sarcopenia. Decreased diabetes duration, PREDIMED score, phase angle (PhA), and HGS values showed a significant association with dynapenia. Conclusions: The prevalence of sarcopenia and dynapenia was high in people with T1DM in our study. Specifically, the proportion of dynapenia was quite high. HGS and ASMI are practical tools for the assessment of muscle health status in T1DM, and low values are associated with poor glycemic control, underweight, and low adherence to the Mediterranean diet. Thus, dynapenia may predict accelerated muscle aging in T1DM. Full article

The gluten-free diet [GFD] has been linked to an increased risk of weight gain and the development of metabolic disorders. Most of the studies have focused on the effect of GFD on the Body Mass Index [BMI]. We aimed to evaluate the nutritional status using specific nutritional parameters in patients with celiac disease [CeD] at diagnosis and on a GFD compared to healthy controls. We recruited subjects at our outpatient clinic at the University of Padua. We collected demographic and clinical data and values obtained with bioelectrical impedance analysis. A total of 24 CeD patients and 28 healthy controls were enrolled. CeD patients at diagnosis had a lower body cell mass index [BCMI, p = 0.006], fat-free mass index [FFMI, p = 0.02], appendicular skeletal muscle index [ASMI, p = 0.02], and phase angle [PA] [p < 0.001] compared to controls. Their percentage of extracellular water [ECW] was also higher [p < 0.001]. Considering CeD patients after GFD, nutritional status significantly improved after 6 months of GFD. We did not observe differences in BMI among groups [p = ns]. CeD patients at diagnosis were found to have a poorer nutritional status than healthy controls, with a positive effect of the GFD on their nutritional status, underlining the inefficacy of evaluating this aspect through only BMI evaluation. Full article

In our life, emotions often have a profound impact on human behavior, especially for drivers, as negative emotions can increase the risk of traffic accidents. As such, it is imperative to accurately discern the emotional states of drivers in order to preemptively address and mitigate any negative emotions that may otherwise manifest and compromise driving behavior. In contrast to many current studies that rely on complex and deep neural network models to achieve high accuracy, this research aims to explore the potential of achieving high recognition accuracy using shallow neural networks through restructuring the structure and dimensions of the data. In this study, we propose an end-to-end convolutional neural network (CNN) model called simply ameliorated CNN (SACNN) to address the issue of low accuracy in cross-subject emotion recognition. We extracted features and converted dimensions of EEG signals from the SEED dataset from the BCMI Laboratory to construct 62-dimensional data, and obtained the optimal model configuration through ablation experiments. To further improve recognition accuracy, we selected the top 10 channels with the highest accuracy by separately training the EEG data of each of the 62 channels. The results showed that the SACNN model achieved an accuracy of 88.16% based on raw cross-subject data, and an accuracy of 91.85% based on EEG channel data from the top 10 channels. In addition, we explored the impact of the position of the BN and dropout layers on the model through experiments, and found that a targeted shallow CNN model performed better than deeper and larger perceptual field CNN models. Furthermore, we discuss herein the future issues and challenges of driver emotion recognition in promising smart city applications. Full article

A Brain-Computer Music Interface (BCMI) system may be designed to harness electroencephalography (EEG) signals for control over musical outputs in the context of emotionally expressive performance. To develop a real-time BCMI system, accurate and computationally efficient emotional biomarkers should first be identified. In the current study, we evaluated the ability of various features to discriminate between emotions expressed during music performance with the aim of developing a BCMI system. EEG data was recorded while subjects performed simple piano music with contrasting emotional cues and rated their success in communicating the intended emotion. Power spectra and connectivity features (Magnitude Square Coherence (MSC) and Granger Causality (GC)) were extracted from the signals. Two different approaches of feature selection were used to assess the contribution of neutral baselines in detection accuracies; 1- utilizing the baselines to normalize the features, 2- not taking them into account (non-normalized features). Finally, the Support Vector Machine (SVM) has been used to evaluate and compare the capability of various features for emotion detection. Best detection accuracies were obtained from the non-normalized MSC-based features equal to 85.57 ± 2.34, 84.93 ± 1.67, and 87.16 ± 0.55 for arousal, valence, and emotional conditions respectively, while the power-based features had the lowest accuracies. Both connectivity features show acceptable accuracy while requiring short processing time and thus are potential candidates for the development of a real-time BCMI system. Full article

The emergence and rapid evolution of human pathogenic viruses, combined with the difficulties in developing effective vaccines, underline the need to develop innovative broad-spectrum antiviral therapeutic agents. The present study aims to determine the in silico antiviral potential of six bacterial antimicrobial peptides (AMPs), two phytochemicals (silvestrol, andrographolide), and two bacterial secondary metabolites (lyngbyabellin A, hapalindole H) against dengue virus, Zika virus, Ebola virus, the major variants of SARS-CoV-2 and monkeypox virus. The comparison of docking scores obtained with natural biomolecules was performed with specific neutralizing antibodies (positive controls for ClusPro) and antiviral drugs (negative controls for Autodock Vina). Glycocin F was the only natural biomolecule tested to show high binding energies to all viral surface proteins and the corresponding viral cell receptors. Lactococcin G and plantaricin ASM1 also achieved high docking scores with all viral surface proteins and most corresponding cell surface receptors. Silvestrol, andrographolide, hapalindole H, and lyngbyabellin A showed variable docking scores depending on the viral surface proteins and cell receptors tested. Three glycocin F mutants with amino acid modifications showed an increase in their docking energy to the spike proteins of SARS-CoV-2 B.1.617.2 Indian variant, and of the SARS-CoV-2 P.1 Japan/Brazil variant, and the dengue DENV envelope protein. All mutant AMPs indicated a frequent occurrence of valine and proline amino acid rotamers. AMPs and glycocin F in particular are the most promising biomolecules for the development of broad-spectrum antiviral treatments targeting the attachment and entry of viruses into their target cell. Full article

Current advancements in music technology enable the creation of customized Digital Musical Instruments (DMIs). This paper presents a systematic review of Accessible Digital Musical Instruments (ADMIs) in inclusive music practice. History of research concerned with facilitating inclusion in music-making is outlined, and current state of developments and trends in the field are discussed. Although the use of music technology in music therapy contexts has attracted more attention in recent years, the topic has been relatively unexplored in Computer Music literature. This review investigates a total of 113 publications focusing on ADMIs. Based on the 83 instruments in this dataset, ten control interface types were identified: tangible controllers, touchless controllers, Brain–Computer Music Interfaces (BCMIs), adapted instruments, wearable controllers or prosthetic devices, mouth-operated controllers, audio controllers, gaze controllers, touchscreen controllers and mouse-controlled interfaces. The majority of the AMDIs were tangible or physical controllers. Although the haptic modality could potentially play an important role in musical interaction for many user groups, relatively few of the ADMIs (14.5%) incorporated vibrotactile feedback. Aspects judged to be important for successful ADMI design were instrument adaptability and customization, user participation, iterative prototyping, and interdisciplinary development teams. Full article

The aim of this study was to assess the body composition and nutritional status of hospitalized pediatric patients with newly diagnosed type 1 diabetes by using bioelectrical impedance analysis (BIA) with phase angle (PA) calculation. PA is considered to be a useful and very sensitive indicator of the nutritional and functional status, and it has not yet been evaluated in such a population. Sixty-three pediatric patients aged 4 to 18 years, with newly diagnosed type 1 diabetes, were included in the study. The control group consisted of 63 healthy children and adolescents strictly matched by gender and age in a 1:1 case: control manner. In both groups, BIA with PA calculation was performed. Diabetic patients, in comparison to control subjects, had a highly significantly lower PA of 4.85 ± 0.86 vs. 5.62 ± 0.81, p < 0.001. They also demonstrated a lower percentage of body cell mass (BCM%), 46.89 ± 5.67% vs. 51.40 ± 4.19%, p < 0.001; a lower body cell mass index (BCMI), 6.57 ± 1.80% vs. 7.37 ± 1.72%, p = 0.004; and a lower percentage of muscle mass (MM%), 44.61 ± 6.58% vs. 49.40 ± 7.59%, p < 0.001, compared to non-diabetic controls. The significantly lower PA value in diabetic patients indicate their worse nutritional and functional status compared to healthy subjects. To assess the predictive and prognostic value of this finding in this population, further prospective studies involving larger sample of patients are required. Full article