Search Results (7,459)

Background: In recent years, there has been increasing interest in the application of repetitive Transcranial Magnetic Stimulation (rTMS) and transcranial Direct-Current Stimulation (tDCS) to enhance and rehabilitate the language abilities in individuals with neurodegenerative diseases. Objective: The aim of this narrative literature review is to investigate the usefulness of rTMS and tDCS to improve language abilities in people with Primary Progressive Aphasia (PPA). Methods: This narrative literature review was conducted through a search of the PubMed online database to identify studies investigating the effects of multiple sessions of rTMS or tDCS on language abilities in PPA patients, applied either as stand-alone interventions or in combination with language treatment. Results: Thirty-three studies fulfilled the inclusion criteria; five studies employed rTMS without language treatment; two studies applied tDCS as stand-alone intervention; twenty-two studies combined tDCS with language treatment; and four studies assessed the effects of tDCS during verbal task without language treatment. Conclusions: rTMS and tDCS applied with or without concomitant language treatment appear to be promising interventions for enhancing language abilities in PPA, with sustained effects reported over time. Further research is necessary to optimise stimulation protocols and to improve our understanding of their long-term effects. Moreover, randomised controlled trials (RCTs) with larger sample sizes are critically needed to clarify the true impact of brain stimulation in PPA, with a focus on changes in cognitive and functional performance, neural activity, and potential molecular correlates. Full article

Breast cancer is the leading cause of cancer-related mortality among women world-wide, and early screening is critical for improving patient survival. Medical imaging plays a central role in breast cancer screening, diagnosis, and treatment monitoring. However, conventional imaging modalities—including mammography, ultrasound, and magnetic resonance imaging—face limitations such as low diagnostic specificity, relatively slow imaging speed, ionizing radiation exposure, and dependence on exogenous contrast agents. Photoacoustic imaging (PAI), a novel hybrid imaging technique that combines optical contrast with ultrasonic spatial resolution, has shown great promise in addressing these challenges. By revealing anatomical, functional, and molecular features of the breast tumor microenvironment, PAI offers high spatial resolution, rapid imaging, and minimal operator dependence. This review outlines the fundamental principles of PAI and systematically examines recent advances in its application to breast cancer screening, diagnosis, and therapeutic evaluation. Furthermore, we discuss the translational potential of PAI as an emerging breast imaging modality, complementing existing clinical techniques. Full article

Herein, the energy dispersion relationship and the density of states of triangular and rectangular moiré patterns are investigated using a tight binding model. Their characteristics of Hofstadter butterflies under different magnetic fields are also examined. The results indicate that, by analyzing different moiré superlattices, Hofstadter butterflies arising from different moiré pattern structures are obtained, exhibiting considerable fractal characteristics and self-similarities. Moreover, it is also observed that under an alternating magnetic field, the redistribution of electronic states leads to a significant change in the density of states curve, and the Van Hove peak changes with the increase in magnetic field intensity. This study enriches the understanding of the electronic behavior of moiré systems, but it also provides multiple potential application directions for future technological development. Full article

Obesity is a chronic disorder associated with serious comorbidities such as diabetes, cardiovascular disease, and cancer. Conventional pharmacological treatments often suffer from limited efficacy, poor selectivity, and undesirable side effects, highlighting the need for more effective alternatives. Nanomedicine offers a promising approach by overcoming these limitations through targeted drug delivery and enhanced therapeutic precision. This review examines key nanotechnological strategies in obesity management, including targeting white adipose tissue (WAT) and the vascular marker prohibitin, promoting WAT browning, and utilizing photothermal therapy and magnetic hyperthermia as nanotheranostic tools. We discuss major nanomedicine platforms—such as liposomes, nanoemulsions, and polymeric nanoparticles—alongside emerging applications in gene nanotherapy and herbal formulations. Potential toxicity concerns are also addressed. In summary, nanomedicine holds substantial potential to revolutionize obesity treatment through targeted, effective, and multifunctional therapeutic strategies. Full article

Accurate detection of Alzheimer’s disease (AD) is critical yet challenging for early medical intervention. Deep learning methods, especially convolutional neural networks (CNNs), have shown promising potential for improving diagnostic accuracy using magnetic resonance imaging (MRI). This study aims to identify the most informative combination of MRI slice orientation and anatomical location for AD classification. We propose an automated framework that first selects the most relevant slices using a feature entropy-based method applied to activation maps from a pretrained CNN model. For classification, we employ a lightweight CNN architecture based on depthwise separable convolutions to efficiently analyze the selected 2D MRI slices extracted from preprocessed 3D brain scans. To further interpret model behavior, an attention mechanism is integrated to analyze which feature level contributes the most to the classification process. The model is evaluated on three binary tasks: AD vs. mild cognitive impairment (MCI), AD vs. cognitively normal (CN), and MCI vs. CN. The experimental results show the highest accuracy (97.4%) in distinguishing AD from CN when utilizing the selected slices from the ninth axial segment, followed by the tenth segment of coronal and sagittal orientations. These findings demonstrate the significance of slice location and orientation in MRI-based AD diagnosis and highlight the potential of lightweight CNNs for clinical use. Full article

Male infertility is a multifactorial condition often associated with disruptions in sperm metabolism and mitochondrial function, yet traditional semen analysis provides limited insight into these molecular mechanisms. Understanding sperm bioenergetics and metabolic dysfunctions is crucial for improving the diagnosis and treatment of conditions such as asthenozoospermia and azoospermia. This systematic review synthesizes recent literature, focusing on advanced tools and techniques—including omics technologies, advanced imaging, spectroscopy, and functional assays—that enable comprehensive molecular assessment of sperm metabolism and development. The reviewed studies highlight the effectiveness of metabolomics, proteomics, and transcriptomics in identifying metabolic biomarkers linked to male infertility. Non-invasive imaging modalities such as Raman and magnetic resonance spectroscopy offer real-time metabolic profiling, while the seminal microbiome is increasingly recognized for its role in modulating sperm metabolic health. Despite these advances, challenges remain in clinical validation and implementation of these techniques in routine infertility diagnostics. Integrating molecular metabolic assessments with conventional semen analysis promises enhanced diagnostic precision and personalized therapeutic approaches, ultimately improving reproductive outcomes. Continued research is needed to standardize biomarkers and validate clinical utility. Furthermore, these metabolic tools hold significant potential to elucidate the underlying causes of previously misunderstood and unexplained infertility cases, offering new avenues for diagnosis and treatment. Full article

Broth cooking is a traditional pretreatment and ripening strategy for high-commercial-value dehydrated marine food, effectively enhancing its texture and rehydration properties. In this work, we characterized the structural information of Maillard reaction products (MRPs) derived from beef scrap stock and investigated their effects on the texture and rehydration performance of dehydrated abalone. The optical and structural properties of the MRPs were analyzed using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), transmission electron microscopy (TEM), and fluorescence spectroscopy. These MRPs showed osmosis in abalone processing including pretreatment and drying. Low-field nuclear magnetic resonance (LF-NMR) results revealed that MRP pretreatment improved the moisture migration and physicochemical properties of dehydrated abalone. These findings suggest that MRPs, owing to their high osmotic efficiency and nanoscale size, could serve as promising food additives and potential alternatives to traditional penetrating agents in the food industry, enhancing the rehydration performance of dried seafood and reducing quality deterioration. Full article

The high incidence of melanoma leading to a poor prognosis rate endorses the development of alternative and innovative approaches in the treatment of melanoma. Therefore, the present study aims to develop and characterize, in terms of physicochemical features and biological impact, an aqueous suspension of magnetite (Fe₃O₄) coated with β-cyclodextrin (Fe₃O₄@β-CD) as a potential innovative alternative nanosystem for melanoma therapy. The nanosystem exhibited physicochemical characteristics suitable for biological applications, revealing a successful complexation of Fe₃O₄ NPs with β-CD and an average size of 18.1 ± 2.1 nm. In addition, the in vitro evaluations revealed that the newly developed nanosystem presented high biocompatibility on a human keratinocyte (HaCaT) monolayer and selective antiproliferative activity on amelanotic human melanoma (A375) cells, inducing early apoptosis features when concentrations of 10, 15, and 20 μg/mL were employed for 48 h and 72 h. Collectively, the Fe₃O₄@β-CD nanosystem reveals promising features for an adjuvant approach in melanoma treatment, mainly due to its β-cyclodextrin coating, thus endorsing a potential co-loading of therapeutic drugs. Furthermore, the intrinsic magnetic core of Fe₃O₄ NPs supports the magnetically based cancer treatment strategies. Full article

This work presents a semi-classical, quantum-corrected model of gravitational collapse for a charged, spherically symmetric dust cloud, extending the classical Oppenheimer–Snyder (OS) framework through loop quantum gravity effects. Our goal is to study phenomenological quantum modifications to geometry, without necessarily embedding them within full loop quantum gravity (LQG). Building upon the quantum Oppenheimer–Snyder (qOS) model, which replaces the classical singularity with a nonsingular bounce via a modified Friedmann equation, we introduce electric and magnetic charges concentrated on a massive thin shell at the boundary of the dust ball. The resulting exterior spacetime generalizes the Schwarzschild solution to a charged, regular black hole geometry akin to a quantum-corrected Reissner–Nordström metric. The Israel junction conditions are applied to match the interior APS (Ashtekar–Pawlowski–Singh) cosmological solution to the charged exterior, yielding constraints on the shell’s mass, pressure, and energy. Stability conditions are derived, including a minimum radius preventing full collapse and ensuring positivity of energy density. This study also examines the geodesic structure around the black hole, focusing on null circular orbits and effective potentials, with implications for the observational signatures of such quantum-corrected compact objects. Full article

A wide range of strategies have been developed to modulate dysfunctional brain activities. This narrative review provides a comparative analysis of biophysical, genetic, and biological neuromodulation approaches with an emphasis on their known or unknown molecular targets and translational potential. The review incorporates data from both preclinical and clinical studies covering deep brain stimulation, transcranial electrical and magnetic stimulation, focused ultrasound, chemogenetics, optogenetics, magnetogenetics, and toxin-based neuromodulation. Each method was assessed based on specificity, safety, reversibility, and mechanistic clarity. Biophysical methods are widely used in clinical practice but often rely on empirical outcomes due to undefined molecular targets. Genetic tools offer cell-type precision in experimental systems but face translational barriers related to delivery and safety. Biological agents, such as botulinum neurotoxins, provide long-lasting yet reversible inhibition via well-characterized molecular pathways. However, they require stereotaxic injections and remain invasive. To overcome individual limitations and improve targeting, delivery, and efficacy, there is a growing interest in the synthesis of multiple approaches. This review highlights a critical gap in the mechanistic understanding of commonly used methods. Addressing this gap by identifying molecular targets may help to improve therapeutic precision. This concise review could be valuable for researchers looking to enter the evolving field of the neuromodulation of brain function. Full article

Interior-mounted permanent magnet (IPM) machines have been widely used in recent years due to their high efficiency, high torque/power densities, and so on. These machines can produce reluctance torque whereas their surface-mounted (SPM) counterparts cannot. Hence, IPMs are attractive in industrial applications that require high torque density. ${\mathrm{I}}_{\mathrm{d}}=0$ control is commonly adopted to drive permanent magnet (PM) machines, and the strategy is attractive due to its simplicity. However, although it is suitable for SPMs, adopting it in IPMs sacrifices the reluctance torque that can be obtained from the machine. Hence, it is vital to control IPMs using the maximum torque per ampere (MTPA) strategy. This paper adopts the MTPA strategy for a 4.1 kW prototype IPM machine. Test system configuration is discussed step by step by paying particular attention to potential practical issues and inspirational discussions on their solutions. The issues associated with misaligned rotor positions or whistling problems pertinent to inappropriate power conversion strategies are addressed to overcome such issues in practical IPM drives. Comprehensive discussions and extensive comparisons of well-matched simulation and experimental results of both ${\mathrm{I}}_{\mathrm{d}}=0$- and MTPA-controlled drives at different evaluation metrics will be quite insightful to achieve efficiency-optimized IPM drives. Full article

One of the promising research areas involving carborane derivatives is boron neutron capture therapy (BNCT). Due to the high boron atom content in carborane molecules, these compounds are considered potential candidates for BNCT-based cancer treatment. Despite ongoing studies on various biologically active carboranyl-containing compounds, the search continues for substances that meet the stringent requirements of effective BNCT agents. In this study, the synthesis of carboranyl-containing derivatives of β-arylaliphatic acids is described, along with the investigation of their reactivity with primary and secondary amines, as well as with metals and their hydroxides. The molecular structures of the synthesized compounds were confirmed using Fourier-transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, elemental analysis, and mass spectrometry (LC-MS). Cytotoxicity of the water-soluble compound potassium 3-(2-isopropyl-1,2-dicarba-closo-dodecaboran-1-yl)-3-phenylpropanoate was evaluated using several cell lines, including HdFn and MCF-7. Full article

Recovering oil by fracturing fluid imbibition has demonstrated significant potential for enhanced oil recovery (EOR) in tight oil reservoirs. White mineral oil (WMO), kerosene, or saturated alkanes with matched apparent viscosity have been widely used as “crude oil” to investigate imbibition mechanisms in light shale oil or tight oil. However, the representativeness of these simulated oils for low-maturity crude oils with higher viscosity and greater content of resins and asphaltenes requires further research. In this study, imbibition experiments were conducted and T₂ and T₁–T₂ nuclear magnetic resonance (NMR) spectra were adopted to investigate the oil recovery characteristics among resin–asphaltene-rich Jimusar shale oil and two WMOs. The overall imbibition recovery rates, pore scale recovery characteristics, mobility variations among oils with different occurrence states, as well as key factors influencing imbibition efficiency were analyzed. The results show the following: (1) WMO, kerosene, or alkanes with matched apparent viscosity may not comprehensively replicate the imbibition behavior of resin–asphaltene-rich crude oils. These simplified systems fail to capture the pore-scale occurrence characteristics of resins/asphaltenes, their influence on pore wettability alteration, and may consequently overestimate the intrinsic imbibition displacement efficiency in reservoir formations. (2) Surfactant optimization must holistically address the intrinsic coupling between interfacial tension reduction, wettability modification, and pore-scale crude oil mobilization mechanisms. The alteration of overall wettability exhibits higher priority over interfacial tension in governing displacement dynamics. (3) Imbibition displacement exhibits selective mobilization characteristics for oil phases in pores. Specifically, when the oil phase contains complex hydrocarbon components, lighter fractions in larger pores are preferentially mobilized; when the oil composition is homogeneous, oil in smaller pores is mobilized first. Full article

Background: Pancreatic cystic lesions (PCLs), including intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs), pose a diagnostic challenge due to their variable malignant potential. Current guidelines, such as Fukuoka and American Gastroenterological Association (AGA), have moderate predictive accuracy and may lead to overtreatment or missed malignancies. Artificial intelligence (AI), incorporating machine learning (ML) and deep learning (DL), offers the potential to improve risk stratification, diagnosis, and management of PCLs by integrating clinical, radiological, and molecular data. This is the first systematic review to evaluate the application, performance, and clinical utility of AI models in the diagnosis, classification, prognosis, and management of pancreatic cysts. Methods: A systematic review was conducted in accordance with PRISMA guidelines and registered on PROSPERO (CRD420251008593). Databases searched included PubMed, EMBASE, Scopus, and Cochrane Library up to March 2025. The inclusion criteria encompassed original studies employing AI, ML, or DL in human subjects with pancreatic cysts, evaluating diagnostic, classification, or prognostic outcomes. Data were extracted on the study design, imaging modality, model type, sample size, performance metrics (accuracy, sensitivity, specificity, and area under the curve (AUC)), and validation methods. Study quality and bias were assessed using the PROBAST and adherence to TRIPOD reporting guidelines. Results: From 847 records, 31 studies met the inclusion criteria. Most were retrospective observational (n = 27, 87%) and focused on preoperative diagnostic applications (n = 30, 97%), with only one addressing prognosis. Imaging modalities included Computed Tomography (CT) (48%), endoscopic ultrasound (EUS) (26%), and Magnetic Resonance Imaging (MRI) (9.7%). Neural networks, particularly convolutional neural networks (CNNs), were the most common AI models (n = 16), followed by logistic regression (n = 4) and support vector machines (n = 3). The median reported AUC across studies was 0.912, with 55% of models achieving AUC ≥ 0.80. The models outperformed clinicians or existing guidelines in 11 studies. IPMN stratification and subtype classification were common focuses, with CNN-based EUS models achieving accuracies of up to 99.6%. Only 10 studies (32%) performed external validation. The risk of bias was high in 93.5% of studies, and TRIPOD adherence averaged 48%. Conclusions: AI demonstrates strong potential in improving the diagnosis and risk stratification of pancreatic cysts, with several models outperforming current clinical guidelines and human readers. However, widespread clinical adoption is hindered by high risk of bias, lack of external validation, and limited interpretability of complex models. Future work should prioritise multicentre prospective studies, standardised model reporting, and development of interpretable, externally validated tools to support clinical integration. Full article

The cosmetics industry has been seeking to develop products with renewable natural ingredients to reduce the use of or even replace synthetic substances. Biosurfactants can help meet this demand. These natural compounds are renewable, biodegradable, and non-toxic or have low toxicity, offering minimal risk to humans and the environment, which has attracted the interest of an emerging consumer market and, consequently, the cosmetics industry. The aim of the present study was to produce a biosurfactant from the yeast Starmerella bombicola ATCC 22214 cultivated in a mineral medium containing 10% soybean oil and 5% glucose. The biosurfactant reduced the surface tension of water from 72.0 ± 0.1 mN/m to 33.0 ± 0.3 mN/m after eight days of fermentation. The yield was 53.35 ± 0.39 g/L and the critical micelle concentration was 1000 mg/L. The biosurfactant proved to be a good emulsifier of oils used in cosmetic formulations, with emulsification indices ranging from 45.90 ± 1.69% to 68.50 ± 1.10%. The hydrophilic–lipophilic balance index demonstrated the wetting capacity of the biosurfactant and its tendency to form oil-in-water (O/W) emulsions, with 50.0 ± 0.20% foaming capacity. The biosurfactant did not exhibit cytotoxicity in the MTT assay or irritant potential. Additionally, an antioxidant activity of 58.25 ± 0.32% was observed at a concentration of 40 mg/mL. The compound also exhibited antimicrobial activity against various pathogenic microorganisms. The characterisation of the biosurfactant using magnetic nuclear resonance and Fourier transform infrared spectroscopy revealed that the biomolecule is a glycolipid with an anionic nature. The results demonstrate that biosurfactant produced in this work has potential as an active biotechnological ingredient for innovative, eco-friendly cosmetic formulations. Full article