Applied Sciences

Skin cancer requires early detection for improved survival rates. Most existing methods rely on deep learning based image classification, which is affected by visual similarity among lesions. Fewer studies use Gene Expression (GE) analysis, which captures molecular characteristics but lacks structural and visual details. To overcome limitations of individual modalities, this paper proposes a multimodal framework integrating dermoscopic images and GE profiles for skin cancer classification. EfficientNet and logistic regression are used for image based analysis and genomic skin lesion profiling, respectively, followed by fuzzy rule based decision systems to reduce uncertainty within individual modalities. Finally, fuzzy fusion combines predictions from both modalities using uncertainty based weighting of classifier outputs. The experimental findings show that both the image based and GE based classification models individually achieved accuracies of nearly 92%. However, the integration of prediction results through the proposed fuzzy fusion strategy further enhanced the classification performance, achieving an overall accuracy of 94.25%. The results obtained outperform contemporary methods, highlighting the effectiveness of combining complementary multimodal information compared with single modality approaches.

Introduction: Early exposure to otolaryngology (ENT) procedural skills in undergraduate medical education is limited by patient safety concerns, restricted clinical opportunities, and the cost of commercial simulators. As a result, essential ENT skills are often underrepresented in structured, hands-on curricula for medical students. Methods: We developed a low-cost, multistation ENT simulation curriculum consisting of five reproducible task trainers: ear examination and otologic procedures, mirror laryngoscopy, rigid and flexible endoscopic navigation, introductory mastoid drilling, and emergency cricothyrotomy. The curriculum was delivered as a 2-hour, faculty-led workshop during a third-year medical student otolaryngology rotation. Learners rotated through stations in small groups. Pre- and post-workshop surveys assessed self-reported anatomical familiarity, procedural confidence, and educational value using a 5-point Likert scale, with additional qualitative feedback collected. Results: All participants completed pre- and post-workshop evaluations. Learners demonstrated increased confidence across all assessed anatomical and procedural domains, including otoscopy, endoscopy, mirror laryngoscopy, mastoid drilling orientation, and cricothyroid membrane identification. Educational value ratings were high across all stations, with mean scores ranging from 4.33 to 5.00. Qualitative feedback emphasized the realism, accessibility, and benefit of hands-on practice in a low-stakes learning environment. Conclusion: This low-cost, multistation ENT simulation curriculum provides a feasible and reproducible approach for introducing foundational otolaryngology skills to medical students. The structured format and affordable models support early procedural exposure and may enhance learner preparedness prior to supervised clinical encounters, particularly in settings with limited simulation resources.

Background: Olfactory dysfunction (OD) in children remains underdiagnosed and poorly characterised. Despite its known impacts on nutrition, quality of life, safety awareness, and psychosocial development, no standardised diagnostic or management pathway currently exists for paediatric OD. This study aimed to characterise global practice patterns and identify diagnostic and therapeutic challenges unique to paediatric care. Methodology/Principal: A 44-item cross-sectional online survey was distributed to a verified international network of paediatric otolaryngologists across 36 countries via a closed professional platform. The survey assessed five domains: diagnostic practices, management protocols, technology and innovation, education and training, and barriers to effective care. Regional grouping was used to facilitate meaningful statistical comparisons. Categorical variables were evaluated using chi-square tests, with odds ratios and 95% confidence intervals reported for significant findings. Results: Of 351 potential participants, 167 responded (47.6% response rate). Most respondents (83%) reported seeing children with OD, yet 95% saw fewer than ten such patients annually. Psychophysical testing was never performed by 54.8% of respondents, while 88.4% routinely ordered cross-sectional imaging. Testing frequency increased significantly with patient age (Cochran's Q p<0.001). The most common barriers to objective testing were insufficient training (44.3%), time constraints (29.9%), and funding limitations (28.1%). Multidisciplinary collaboration was negligible. Significant regional variation was observed across most practice domains. Conclusions: Paediatric OD care is characterised by functional underinvestigation, fragmented multidisciplinary collaboration, and systemic educational gaps. These findings support urgent development of standardised clinical guidelines, age-appropriate validated assessment tools, and formal interdisciplinary care pathways.

Spinal fractures are an important contributor to disability worldwide, particularly in aging populations. However, comprehensive long-term comparisons between China and other major economies remain limited. Using data from the Global Burden of Disease (GBD) 2021 study, we analyzed temporal trends in the incidence, prevalence, and years lived with disability (YLDs) of spinal fractures in China and the overall G20 from 1990 to 2021. Age-standardized rates were assessed using Joinpoint regression and age-period-cohort analysis. Future burden through 2050 was projected using autoregressive integrated moving average modeling, and decomposition analysis was performed to quantify the contributions of demographic and epidemiological factors. Between 1990 and 2021, China experienced substantial increases in absolute burden. Incident cases increased by 52.27%, prevalent cases by 113.66%, and YLDs by 107.21%. The age-standardized prevalence rate (ASPR) and age-standardized YLD rate (ASYR) increased significantly, whereas the age-standardized incidence rate (ASIR) showed a non-significant upward trend. In contrast, the overall G20 aggregate showed increasing absolute case numbers but significantly declining age-standardized rates. Age-period-cohort and age-specific analyses indicated that older adults represented the main burden-bearing population. Projections suggested that Chinas ASIR may decline by 2050, whereas prevalence and YLD burden, particularly among males, may remain relatively high compared with the overall G20 level. Decomposition analysis identified population aging as the major driver of burden growth. China experienced a rising burden of spinal fractures over the past three decades, in contrast to declining age-standardized trends in the overall G20 aggregate. These findings highlight the substantial role of population aging in shaping spinal fracture burden and provide epidemiological evidence for prevention planning and aging-related health policy.

3D scanners have revolutionised how podiatrists capture foot morphology in order to design custom orthoses (insoles). While various 3D scanning technologies are used in clinical practice, they vary greatly in cost and ease of use and many of these are not specifically designed for podiatry applications. There is limited literature comparing accuracy between scanners, and many approaches require prolonged scan times during which the patient must remain still. Multicamera photogrammetry offers a promising solution by enabling high-quality, rapid 3D scanning which other devices cannot provide. This study compared the accuracy and clinical utility of four 3D scanners. One was a high accuracy reference scanner (Artec Spider) which was used as a gold standard. Two further scanners which are commonly used in the clinic were also investigated (Apple iPad 6 with Structure Sensor attachment 'iPad', and Envisic VeriScan Podiatric Scanner 'laser') and these were directly compared with a novel prototype multicamera photogrammetry 3D scanner. The left feet of 20 healthy volunteers were scanned using each of the four devices and scans were evaluated for accuracy, completeness, and acquisition and processing times. All scanners produced clinically acceptable scans, with the novel photogrammetry scanner demonstrating superior accuracy. Scan times varied significantly between scanners, with the photogrammetry device capturing scans much faster. All scanners had acceptable levels of completeness, though the iPad and photogrammetry outperformed the laser scanner. These results provide a valuable tool for clinics seeking guidance on scanner selection and highlight the benefits of instantaneous photogrammetry scanning to improve workflow efficiency and accessibility.

Polyphenols are compounds synthesized by plants as part of their chemical defense system to counteract biotic and abiotic stressors. These compounds share two key chemical characteristics: their aromatic groups make them insoluble in water, while hydroxy groups provide redox properties. These characteristics may explain how polyphenols interact with mitochondrial membranes (which are lipophilic) and participate in redox (electron scavenging) reactions of the electron transport chain, ultimately affecting ATP synthesis via oxidative phosphorylation. This interaction accounts for both the beneficial and adverse effects of polyphenols. However, no research has examined how hydroxyl groups or a lipophilic environment influence the biological activity of polyphenols. Therefore, this study aimed to explore the impact of hydroxy groups and a lipophilic environment on the biological activity of polyphenols. We tested four polyphenols (quercetin, naringenin, resveratrol, and gallic acid) with varying numbers of hydroxyl and other functional groups to determine how hydroxyl groups affect their biological activity (toxicity) in Saccharomyces cerevisiae. Additionally, we evaluated different fatty acids to understand how a lipophilic environment influences polyphenol biological activity. The results of this study support the two main ideas of our hypothesis: 1) a lipid solvent increases the toxicity of polyphenols, and 2) the molecule with the most hydroxyl groups is the most toxic (as seen with quercetin, which has five hydroxyl groups). Consequently, the increased toxicity of polyphenols in lipid solvents, along with their association with oxidizable groups, opens the door to the development of new technologies based on polyphenols.

Background: Childhood and adolescent hearing loss affects not only communication and cognitive development but also motor skills and school participation. Consequently, it generates inequalities in learning and educational inclusion. Nevertheless, no systematic review has yet analyzed these differences from an inclusive education perspective. Methods: A systematic review with meta-analysis was conducted following PRISMA guidelines and registered in PROSPERO. Observational studies comparing physical fitness between children and adolescents with hearing loss and their hearing peers were included. Methodological quality was assessed using the Newcastle--Ottawa Scale, and standardized effect sizes were calculated with a random-effects model. Results: Five studies (n=404) were analyzed. Findings revealed significant differences in strength, agility, speed, and balance. Moreover, the meta-analysis showed a large standardized effect favoring hearing children (ES=-2.35; 95% CI: -3.34 to -1.37). Conclusions: Children and adolescents with hearing loss present significantly lower physical fitness, which may affect the planning of physical education activities if their capacities are misinterpreted. Implementing inclusive and adapted strategies within the school curriculum is essential to ensure equal opportunities, improve physical fitness, and promote educational equity.

Cellobiose is an important disaccharide used in food, health, and biorefinery applications, but its efficient enzymatic production from crystalline cellulose remains challenging. In this study, crystalline cellulose was dissolved in ionic liquids and regenerated by dilution, and subsequently hydrolyzed at 80{degrees}C using a highly thermostable cellobiohydrolase, HmCel6A-3SNP. The enzyme retained activity in the presence of low concentrations of ionic liquids. Among the pretreatment conditions tested, cellulose treated with 1-butyl-3-methylimidazolium chloride ([Bmim]Cl) showed the highest enzymatic digestibility. After washing to remove residual ionic liquid, the reaction produced reducing sugars at levels 1.5-fold higher than those obtained in the presence of 10% [Bmim]Cl, with cellobiose accounting for approximately 96% of the products. Under the optimized conditions, the hydrolysis yield reached [~]36% after 48 hr. Structural analyses using birefringence imaging, electron microscopy, and Fourier transform infrared spectroscopy indicated that higher-order structural changes in regenerated cellulose strongly influence enzymatic accessibility. These results demonstrate the potential of combining ionic-liquid pretreatment with thermostable enzymes for selective cellobiose production from cellulose.

This study aimed to clarify aerosol exposure risks throughout the workflow of a Biosafety Level 2 (BSL-2) polymerase chain reaction (PCR) laboratory, validate the suitability of the {Phi}X174 bacteriophage as an indicator virus, and provide evidence for biosafety control measures. The {Phi}X174 bacteriophage was used to simulate viral samples, and a concentration-bacteriophage plaque standard curve was constructed (R2=0.998). Five operational steps in a simulated PCR laboratory were quantitatively monitored for aerosol concentration using double-layer agar plates, with blank controls used to eliminate interference. Statistical analysis was employed to identify risk differences. Sample homogenization ((5.67 {+/-} 1.23) x 104 plaque-forming units (PFU)/m3) and nucleic acid extraction ((3.45 {+/-} 0.89) x 104 PFU/m3) were identified as high-/very high-risk steps. The viral load in the samples was strongly positively correlated with the aerosol concentration (r = 0.926, P <0.001), with aerosol levels linearly decreasing with increasing distance in high-risk steps. The {Phi}X174 bacteriophage demonstrated high detection sensitivity (101 PFU/ml) and demonstrated safety compatibility with BSL-2 laboratories. Aerosol risks in PCR laboratories exhibit step-specific differentiation, and {Phi}X174 serves as an ideal indicator virus. Proposed strategies such as equipment upgrades and personal protective equipment (PPE) grading can reduce exposure risks.

Introduction: Physical activity during pregnancy can be tracked directly by accelerometer measurements and indirectly by validated questionnaires. Considering the advancement of the Internet of Things (IOT), managing and/or monitoring physical activities can be better explored to analyze individuals, as well as indirectly compare the intensity and domains of physical activities carried out by pregnant women. The project, called 'EVA'(Expert Virtual Assistant), suggests combining several fields of knowledge to obtain better information about physical activity during pregnancy, surpassing the claim made in previous research that studying and measuring the duration of daily physical activities in pregnant women is a challenge. Objective: In the present study, we present the results of the first stage of the EVA project, which aims to develop a Virtual Assistant (VA) in Portuguese, providing examples of health management features for monitoring Physical Activity measurements for pregnant women assisted in the Unified Health System (SUS) and the adaptation of the Pregnancy Physical Activity Questionnaire (PPAQ). Methods and Analysis: The methods used were developed in two stages: adapting the physical activity questionnaire and building the Virtual Assistent to monitor physical activities. Thirty pregnant women who used the Unified Health System (SUS) in the city of Ribeir&atildeo Preto, Brazil participated in the study. The pregnant women wore sensor wristbands (accelerometers) and answered the sociodemographic, lifestyle and physical activity questionnaires via an application developed for this study. Results: The questionnaire used was the PPAQ adapted for Brazilian pregnant women. The most important changes were in the occupational domain for the house cleaning and in sedentary behavior activities. In the pilot study, it was observed that pregnant women spend more energy at home and in light and moderate intensity activities. textbfConclusion:This study made important contributions to evaluating PA in pregnant women. The proposal and studies for the construction of the AV-EVA, the inclusion of a specific occupational domain for pregnant women with domestic occupations and the new cutoff points for PA intensity measurements obtained via accelerometers.

(1) Background: Brain cancer is the ninth leading cause of cancer death in the US, with approximately 76,000 newly diagnosed cases annually. Studies show that at time of diagnosis, up to six-months post-treatment, 50%-80% of brain cancer survivors (BCS) report cognitive dysfunction. Mild cognitive impairment (MCI) has gained increasing attention as a persistent disability experienced by up to 75% of all BCS, which affects memory, concentration, executive function, etc. Studies show cognitive training with computerized gaming as improving cognitive function for patients with stroke, dementia, and Parkinsons. It is of significant clinical interest to develop innovative interventions that reduce MCI. Aim: To improve cognitive performance of BCS suffering with MCI by evaluating the feasibility, acceptability and effect of a Virtual Reality Cognitive Rehabilitation Training (VR-CRT) platform during four weeks of cognitive training. (2) Methods: We employed a quasi-experimental pretest/posttest non-randomized/non-blinded single-arm design for 4 weeks, with an experimental group (n=6, after attrition) using VR-CRT. Participants were selected based on convenience sampling using the electronic medical record to identify qualified patients, guided by inclusion/exclusion criteria. Feasibility was defined by retention as >80%, with usability testing using the System Usability Scale (SUS) and NASA-TLX surveys. The Hopkins Verbal Learning Test (HVLT), Controlled Oral Word Association (COWA) test, and Trail Making A-B (TM-A/B) test were used to measure cognitive performance, comparing baseline to post week-four. (3) Results: The feasibility criteria of >80% was met. All SUS and NASA scores were in the higher index, suggesting a high degree of usability, with low workload demand. For effect, the COWA findings showed a significant improvement (41.38%), with a paired sample T-Test confirming that the participants COWA scores improved significantly from pre- to post-intervention (p = 0.03), indicating enhanced verbal fluency and executive functioning after intervention. HVLT (combined) showed improvements of 18.75% for Form A and 11.32% for Form B, which also showed a significant improvement (p = .04) in the retention discrimination index from pre- to post-test. The TM-A/B test showed an improvement (25.97%), suggesting that the participants spent less time completing both parts A and B, but was not statistically significant. (4) Conclusion: This study fulfilled our aim to demonstrate modest to significant cognitive improvement using VR-CRT with brain cancer patients with MCI. Despite the small sample size, we believe the use of virtual reality will lead to important advances for patients with MCI, particularly the frontal lobe brain region, expressed in executive function.

Background: Chronic rhinosinusitis (CRS) is a heterogeneous inflammatory airway disease associated with impaired mucociliary clearance and persistent inflammation. While prior work has focused on inflammatory and molecular pathways, the physicochemical properties of mucus itself remain poorly characterized. This study aimed to define compositional and biophysical features of CRS mucus that may contribute to dysfunction. Methods: A prospective cross-sectional study was conducted in 15 adults undergoing endoscopic sinus surgery (11 CRS, 4 controls). Mucus was collected from the middle meatus. Hydration was measured by lyophilization. Ionic composition was quantified using mass spectrometry. Viscoelasticity was assessed via oscillatory shear rheology. Total protein, total carbohydrate, sialic acid (Sia) and fucose (Fuc) content were quantified using enzymatic and chemical assays. Statistical comparisons were performed using nonparametric tests. Results: CRS mucus exhibited significantly higher Ca2+; and Mg2+; concentrations (approximately two-fold; p<0.05) and increased variability in hydration and ion content compared to controls. Rheology showed greater heterogeneity and a non-significant trend toward increased viscoelasticity in CRS. Total protein and carbohydrate content were not significantly different; however, the carbohydrate-to-protein ratio was significantly reduced in CRS (p=0.04). Sia content and Sia-to-carbohydrate ratio were significantly elevated in CRS (p=0.04 and p=0.002), particularly in CRS with nasal polyps. Fuc content did not differ between groups. Conclusions: CRS mucus demonstrates coordinated alterations in ionic composition and glycosylation, characterized by increased cation content, hypersialylation, and reduced carbohydrate-to-protein ratios. These changes may contribute to altered mucus properties and impaired mucociliary clearance, highlighting mucus composition as a potential therapeutic target in CRS.

Mental health challenges among university students have increased due to academic pressure, lifestyle changes, and continuous digital engagement. Existing approaches for mental health assessment often rely either on self-reported psychological scales or isolated behavioral indicators, limiting their ability to capture complex temporal and contextual patterns. This study proposes an interpretable multimodal framework for student mental health risk assessment using behavioral sensing, academic information, ecological momentary assessments (EMA), and psychometric survey data. A bidirectional Long Short-Term Memory autoencoder is employed to learn latent temporal representations from day-level behavioral sequences, while graph embeddings capture structural relationships among students using similarity-based neighborhood graphs. These representations are fused with academic and survey-derived features and reduced using Principal Component Analysis and Uniform Manifold Approximation and Projection. K-means clustering is then applied to identify behaviorally distinct student groups. Experimental analysis on the StudentLife dataset demonstrates meaningful clustering performance with a Silhouette Score of 0.4209 and Adjusted Rand Index stability of 0.6869. The identified clusters correspond to low-risk, moderate-risk, and high-risk behavioral profiles. To improve interpretability and practical usability, a fuzzy inference system is introduced to compute mental risk, academic risk, and wellbeing indices using psychometric indicators including PHQ-9, PSS, PANAS, VR-12, and Big Five personality traits. The results demonstrate the potential of combining multimodal behavioral modeling with interpretable fuzzy reasoning to support early mental health risk assessment in educational settings.

Monitoring activities of daily living (ADLs) in the home is a promising approach for tracking dementia progression in older adults. While ambient sensor-based ADL systems are well-studied, most existing ADL recognition systems rely on globally trained models that ignore the spatial organization of in-home activities. In real deployments, where training data are sparse and highly home-specific, global transformer models may fail to capture room-dependent behavioral structure. We propose a deterministic Mixture of Experts (MoE) architecture for in-home ADL recognition, in which each expert is a compact transformer specialized to one room of the home (bedroom, kitchen, bathroom, living area). Input segments are routed using a deterministic gating strategy based on room-level motion activity and time-of-day priors for sleep-related behaviors. Unlike learned routing networks, the proposed gate encodes domain knowledge about where ADLs are likely to occur, reducing model complexity under limited per-home training data. By decomposing ADL recognition into room-specific activity spaces, the proposed architecture reduces competition between dominant and low-frequency activities under highly imbalanced residential data. We evaluated the system on data collected via low-cost ambient sensors (motion, light, temperature, humidity) and Raspberry Pi edge devices across five homes, with ground-truth ADL labels provided by participants and caregivers. Across the five homes, the proposed MoE consistently outperformed global transformer, 1D CNN, and Random Forest baselines, achieving macro-F1 scores ranging from 0.60 to 0.88, highlighting the importance of home-specific modeling in real-world deployments. These findings suggest that room-aware expert specialization may provide a practical and interpretable strategy for low-data ADL recognition in real-world residential environments.

ObjectiveAnterior cruciate ligament (ACL) tears increase the risk for developing posttraumatic osteoarthritis (PTOA). Females have greater risk for both. However, studies defining sex-specific protein responses in human cartilage after ACL injury are lacking. We hypothesize that articular cartilages response to an injurious environment differs depending on sex. DesignWe compared the proteomic profiles of normal cartilage with injured cartilage harvested from the intercondylar area during ACL surgery. Sex-specific injury effects were estimated through contrasts between Injured Male and Normal Male and between Injured Female and Normal Female. Pathway enrichment analysis was done using gene ontology (GO) and compared against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Extracellular matrix (ECM) proteins were further analyzed using the Matrisome AnalyzeR. ResultsFrom the 2,188 proteins identified, males and females shared 1,121 upregulated and 23 downregulated proteins in injured compared to normal cartilage. Analysis of ECM proteins and enriched pathways revealed mostly similar male and female responses to an injurious environment, with evidence of early cartilage remodeling in both sexes. Nevertheless, more than 240 proteins were affected specifically by sex, and significant sex differences were found in inflammation, ECM-related, and metabolic pathways. Males were enriched mostly in "ECM-receptor interaction", while females were enriched in "Citrate cycle (TCA cycle)", "Fatty acid degradation", and "Fatty acid metabolism" pathways. ConclusionArticular cartilage shows signs of remodeling soon after ACL injury, even when only exposed to an injurious environment rather than being physically impacted. Sex differences were observed in inflammation, metabolic pathways, and ECM synthesis.

The catalytic rate constant (kcat) for product formation is considered a turnover number. Therefore, it is often mistakenly believed that kcat equals the turnover number and the number of substrate molecules changed per unit of time. Therefore, the aim of this study is to show that the rate constant for product synthesis and release is not always the same as the rate constant [Formula] for substrate utilization. To determine the precise substrate concentration at which these two rate constants are identical, it is appropriate to derive equations that allow the computation of [Formula]. In the end, the study will provide the most likely concentration of enzymes that can guarantee minimal or no recycling. An analysis of the literature on invertase (EC 3.2.1.26) and the Bernfeld method of generating Michaelian kinetic parameters for human salivary alpha-amylase (HSAA, EC 3.2.1.1) revealed that all kinetic parameters except [Formula] increased with substrate concentration. Meanwhile, the values for invertase decreased from 0.0697 to 0.0361/min, and the values for HSAA decreased from 5,802.4687 to 3,213.0124/min. The magnitude of [Formula] for each substrate concentration ([ST]) is not always equal, except when [ST] is determined post-assay by computation or extrapolation. The lower [ST] at which [Formula] and kcat for [HSAA] are equal is 3.667540128 g/L (5.682584642 M), which is similar to the molarity of HSAA (5.6101967709 M). The kcat for HSAA was 11,930.9885/min. Future assays should aim to generate large amounts of data for a robust statistical analysis. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=164 SRC="FIGDIR/small/728646v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@c49b65org.highwire.dtl.DTLVardef@1b60655org.highwire.dtl.DTLVardef@159ba67org.highwire.dtl.DTLVardef@1dce0af_HPS_FORMAT_FIGEXP M_FIG C_FIG

Rheumatic heart disease (RHD) remains a major public health concern across low- and middle-income countries in the Global South. Early detection through community-based screening of asymptomatic individuals has been identified as a critical strategy for reducing the disease burden. Despite this, the absence of accessible, automated population screening tools continues to impede implementation at scale. This study investigates the screening potential of integrating electrocardiography (ECG) and phonocardiography (PCG) for the early detection of RHD in asymptomatic schoolchildren. The dataset was obtained as part of an ambulatory screening initiative conducted across multiple school sites in rural areas of Ethiopia. It comprised ECG and PCG recordings from 611 asymptomatic schoolchildren aged 10 to 20 years. A comprehensive set of time-frequency, visibility graph and non-linear features were extracted from both signal modalities. These features were subsequently evaluated using machine learning models to assess their utility in the automated screening of early RHD. The best model achieved an average 10-folds cross-validation scores on sensitivity, positive-predictive-value and F1-score of 59.6%, 63.6% and 60.8%, respectively for multimodal ECG and PCG signals. Whereas separate evaluation of ECG showed an F1-score of 61.1% and PCG achieved 23.5%. Key features included the T-wave, the area under the QRS complex, and entropy measures derived from beat visibility graphs in the ECG. In addition, visibility graph features from multi-band S1 and S2 heart sound segments, along with MFCC coefficients from the PCG, were also relevant. However, PCG alone performed poorly and did not show improved results over the ECG features. Although auscultation is key clinical diagnosis tool in symptomatic RHD, combined PCG with ECG features does not enhance asymptomatic RHD detection using the ECG modality alone.

Purpose: Modified Barium Swallow (MBS) studies utilize videofluoroscopy, a dynamic X-ray technique for evaluating swallowing anatomy and physiology. Each MBS exam typically includes multiple bolus trials, often involving different bolus consistencies. Accurate classification of bolus types is essential, as swallowing dynamics, aspiration risks, and residue levels vary with bolus consistency. In this preliminary study, we propose a deep learning-based approach for automated bolus type classification in MBS, aiming to provide a standardized and efficient framework for automated processing of swallowing assessments. Methods: A total of 206 patients (Mean +/- SD age: 60.24 +/- 9.02 years; 89.32% men) underwent MBS examinations, comprising 277 individual MBS studies. The dataset included 2,752 bolus-level video segments, categorized by bolus type as follows: 1,711 liquid (IDDSI 0-3, 62.17%), 521 pudding (IDDSI 4, 18.93%), and 520 solid boluses (IDDSI 7, cookie or cracker, 18.89%). To standardize variable video lengths for the data pipeline, each MBS video was temporally segmented into a fixed-length frame sequence, with shorter videos padded using static frames and longer videos randomly cropped to the target length. We employed an Inflated 3D convolutional neural network to develop the deep learning model. Results: Each video segment contained an average of 273.03 +/- 195.81 frames. On the independent test set, the deep learning model achieved an overall accuracy of 96.13%, and the macro F1-score was 95.05% in classifying food bolus types within MBS videos. Conclusions: The developed AI-based system demonstrated effective automated classification of food bolus types in MBS videos, representing an important step toward fully automated MBS analysis for swallowing efficiency assessment. The AI model reduces the reliance on manual labels, thereby promising to streamline clinical and research workflows.

In this study, we evaluated the impact of different in vitro 3D culture modelling methods on the activity of doxorubicin (DOX) and 5-fluorouracil (5-FU) in human melanoma spheroids. Human melanoma A375 and IGR39 spheroids were generated using the hanging drop and non-adhesive surface methods. Spheroid growth dynamics were assessed by measuring changes in spheroid diameter. To compare the effects of anticancer drugs in spheroids of different sizes, spheroids of approximately 200 and 400 {micro}m were formed. Drug activity was evaluated based on spheroid growth and cell viability using the MTT assay. A375 spheroids formed using the non-adhesive surface method were more sensitive to DOX than spheroids formed using the hanging drop method. In smaller A375 spheroids, 10 {micro}M 5-FU reduced cell viability more effectively in spheroids formed using the hanging drop method. In contrast, IGR39 spheroids formed by the hanging drop method were more resistant than those formed on a non-adhesive surface. However, in IGR39 spheroids, the effects of DOX and 5-FU on growth and viability did not significantly differ between formation methods. In conclusion, A375 spheroid growth was not significantly influenced by the formation method, whereas IGR39 spheroid growth depended on the method used. A375 spheroids formed on non-adhesive surfaces were more sensitive to DOX, whereas 5-FU activity depended on drug concentration and spheroid size. In IGR39 spheroids, the effects of DOX and 5-FU on growth and viability were largely independent of the spheroid formation method. Based on these results, it can be concluded that the researchers should carefully select the spheroid formation method for their studies, as this may influence the results of the tested compounds effect on their size and viability.

Fungal contamination of food with yeast and moulds is associated with major economic losses due to spoilage and also poses health risks in the form of mycotoxin production. The strain Pantoea agglomerans APC 4211 isolated from leaves of Ilex aquifolium (holly tree) has broad spectrum antifungal activity against a variety of food spoilage fungi. Genomic analysis of the strain confirmed the presence of biosynthetic gene clusters potentially encoding for the enzymatic machinery required for the production of the antifungal lipopeptide herbicolin A. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of the cell-free supernatant (CFS) confirmed the presence of molecular masses corresponding to herbicolin A (1300.8 Da), and herbicolin B (1138 Da). Purified herbicolin A has desirable properties for biotechnological applications, including potent antifungal activity against a range of spoilage fungi, thermal stability and resistance to proteases. Herbicolin A has low cytotoxicity against epithelial cell lines and has minimum inhibitory concentrations (MICs) lower than those of some commercial antifungal drugs (0.2 - 2.5 {micro}g/ml). In a model dairy system (10% skim milk), herbicolin A demonstrated excellent solubility and stability, effectively eliminating Aspergillus niger and Penicillium notatum at a concentration of 5 {micro}g/mL. In conclusion, herbicolin A is a potent, naturally occurring antifungal agent with the potential to be applied as a biopreservative in food systems, providing a safe, clean-label, and efficient compound for synthetic preservatives replacement. HighlightsO_LIHerbicolin A has a strong potential as a natural preservative for food protection C_LIO_LIHerbicolin A shows lower MICs than several antifungal agents C_LIO_LIHerbicolin A is stable under heat and resistant to proteolytic degradation C_LIO_LIHerbicolin A has strong solubility and stability in a model dairy system C_LIO_LIHerbicolin A indicates low cytotoxicity against epithelial cell lines C_LI Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.