Focused Ultrasound, an Emerging Tool for Atherosclerosis Treatment: A Comprehensive Review

Cytotoxic and Cellular Response of Doped Nb-NTO Nanoparticles Functionalized with Mentha arvensis and Mucuna pruriens Extracts on MDA-MB-231 Breast Cancer Cells

Triple-negative breast cancer (TNBC) poses significant challenges as it lacks specific treatment approaches. In this study, we synthesized niobium-nitrogen-doped titanium dioxide (Nb-NTO) nanoparticles (NPs) functionalized with Mentha arvensis ethanolic and Mucuna pruriens methanolic extracts and evaluated their anti-cancer potential against MDA-MB-231 TNBC cells. The functionalization of doped Nb-NTO NPs with Mentha arvensis and Mucuna pruriens extract exhibited significant synergistic effects, reducing cell viability in a dose-dependent manner with enhanced cytotoxicity at lower concentrations compared to individual treatments. Microscopic analysis revealed morphological changes indicative of apoptosis and necrosis, while flow cytometry demonstrated increased apoptotic and necrotic cell populations in the combination-treated groups. These treatments also significantly reduced the secretion of pro-inflammatory cytokines IL-6 and IL-8, suggesting modulation of the inflammatory tumor microenvironment. Furthermore, the functionalized Nb-NTO NPs effectively targeted cancer stem cell (CSC) properties, inhibiting mammosphere formation and clonogenic survival and downregulating critical CSC markers, including c-Myc, OCT4, and NANOG. This study highlights the potential of Nb-NTO NPs functionalized with Mentha arvensis and Mucuna pruriens as a novel therapeutic strategy for TNBC, addressing key hallmarks of cancer, including apoptosis, inflammation, and CSC targeting. While these findings demonstrate promising in vitro anti-cancer efficacy, further in vivo validation and mechanistic studies are necessary to advance these treatments toward clinical anti-cancer applications.

Eco-friendly synthesis of bioactive silver nanoparticles from black roasted gram (Cicer arietinum) for biomedical applications

Green synthesis leverages biological resources such as plant extracts to produce cost-effectively and environmentally friendly NPs. In our study, silver nanoparticles (AgNPs) are biosynthesized using blank roasted grams (Cicer arietinum) as reducing agents. CA-AgNPs were characterized by a characteristic surface plasmon resonance (SPR) peak at 224 nm in the UV-Vis spectrum. FTIR analysis revealed functional groups with O-H stretching at 3410 cm-1, C-H stretching at 2922 cm-1, and C=O stretching at 1635 cm-1. XRD patterns exhibited sharp peaks at 33.2°, 38.4°, 55.7°, and 66.6°, confirming high crystallinity. Morphological analysis through FESEM indicated spherical CA-AgNPs averaging 500 nm in size, with EDS revealing Ag at 97.51% by weight. Antimicrobial assays showed zones of inhibition of 14 mm against Candida albicans, 18 mm against Escherichia coli., and 12 mm against Propionibacterium acnes. The total phenolic content of CA-AgNPs was 26.17 ± 13.54 mg GAE/g, significantly higher than the 11.85 ± 9.57 mg GAE/g in CA extract. The ABTS assay confirmed the antioxidant potential with a lower IC50 value of 1.73 ± 0.41 µg/mL, indicating enhanced radical scavenging activity. Anti-melanogenesis was validated through tyrosinase, showing inhibition rates of 97.97% at the highest concentrations. The anti-inflammatory was evaluated by western blot, which showed decreased expression of iNOS and COX-2. This study demonstrates the green synthesis of CA-AgNPs and its potential biomedical applications. The results of this study demonstrate that biosynthesized CA-AgNPs have key biological applications.

Employing machine learning for enhanced abdominal fat prediction in cavitation post-treatment

This study investigates the application of cavitation in non-invasive abdominal fat reduction and body contouring, a topic of considerable interest in the medical and aesthetic fields. We explore the potential of cavitation to alter abdominal fat composition and delve into the optimization of fat prediction models using advanced hyperparameter optimization techniques, Hyperopt and Optuna. Our objective is to enhance the predictive accuracy of abdominal fat dynamics post-cavitation treatment. Employing a robust dataset with abdominal fat measurements and cavitation treatment parameters, we evaluate the efficacy of our approach through regression analysis. The performance of Hyperopt and Optuna regression models is assessed using metrics such as mean squared error, mean absolute error, and R-squared score. Our results reveal that both models exhibit strong predictive capabilities, with R-squared scores reaching 94.12% and 94.11% for post-treatment visceral fat, and 71.15% and 70.48% for post-treatment subcutaneous fat predictions, respectively. Additionally, we investigate feature selection techniques to pinpoint critical predictors within the fat prediction models. Techniques including F-value selection, mutual information, recursive feature elimination with logistic regression and random forests, variance thresholding, and feature importance evaluation are utilized. The analysis identifies key features such as BMI, waist circumference, and pretreatment fat levels as significant predictors of post-treatment fat outcomes. Our findings underscore the effectiveness of hyperparameter optimization in refining fat prediction models and offer valuable insights for the advancement of non-invasive fat reduction methods. This research holds important implications for both the scientific community and clinical practitioners, paving the way for improved treatment strategies in the realm of body contouring.

Healing Process after High-Intensity Focused Ultrasound Treatment of Benign Skin Lesions: Dermoscopic Analysis and Treatment Guidelines

Background: High-Intensity Focused Ultrasound (HIFU) has emerged as a precise and non-invasive modality for tissue ablation and healing. This study presents a detailed dermoscopic analysis of skin healing post-High-Intensity Focused Ultrasound (HIFU) treatment, focusing on common benign skin lesions, such as seborrheic keratosis, sebaceous hyperplasia, vascular lesions, and sebaceous nevi. Methods: Prior to HIFU treatment, a comprehensive assessment was conducted, integrating ultrasound scanning and clinical evaluations. The TOOsonix System ONE-M was employed for HIFU treatments, with parameters tailored to each lesion type. Results: A common pattern observed across all lesions includes initial whitening post treatment, followed by scab formation and the development of a pink area with reparative vessels. This study, however, highlights distinct differences in fibrosis patterns and healing timelines across different lesion types. Each lesion type exhibited unique fibrosis patterns post treatment. Flatter variants of seborrheic keratosis healed within a month, displaying hypopigmentation and reparative vessels, alongside a distinct lattice fibrosis pattern in more verrucous forms, which took about two months to heal. Sebaceous hyperplasia, characterized by rapid healing within three weeks, demonstrated fibrosis with pink areas and perpendicular white lines, concluding with a slight depression. Vascular lesions varied in healing time based on depth, with superficial ones showing whitening and crust formation, while deeper lesions had vessel occlusion and size reduction accompanied by concentric fibrotic bands. Sebaceous nevi presented the longest healing duration of three months, characterized by amorphous white-gray structures, scab formation, and the emergence of pink areas with branching vessels, leading to clear skin with reduced white lines. Conclusions: in conclusion, this meticulous clinical evaluation highlights the unique healing characteristics and timelines for each skin lesion type treated with HIFU. These insights are invaluable for optimizing follow-up assessments, identifying potential complications, and refining treatment protocols. By providing detailed insights into the healing timelines and patterns for different types of lesions, patients can be better informed about their post-treatment journey.