Search Results (522)

This article examines the evolution and potential cross-cultural adaptations of the “Goddess of the Flaming Mouth”, Jvālāmukhī (Skt.) or Kha ‘bar ma (Tib.), in Indic and Tibetan traditions. A minor figure in medieval Hindu Tantras, Jvālāmukhī is today best known through her tangible manifestation as natural flames in a West Himalayan temple complex in the valley of Kangra, Himachal Pradesh, India. The gap between her sparse portrayal in Tantric texts and her enduring presence at this local “seat of power” (śakti pīṭha) raises questions regarding her historical development and sectarian affiliations. To address these questions, we examine mentions of Jvālāmukhī’s Tibetan counterpart, Kha ‘bar ma, across a wide range of textual sources: canonical Buddhist texts, original Tibetan works of the Bön and Buddhist traditions, and texts on sacred geography. Regarded as a queen of ghost spirits (pretas) and field protector (kṣetrapāla) in Buddhist sources, her portrayal in Bön texts contain archaic motifs that hint at autochthonous and/or non-Buddhist origins. The assessment of Indic material in conjunction with Tibetan texts point to possible transformations of the goddess across these culturally proximate Himalayan settings. In presenting and contextualizing these transitions, this article contributes critical data to ongoing efforts to map the development, adaptation, and localization of Tantric deities along the Indo-Tibetan interface. Full article

Background and Objectives: Malnutrition is one of the most common complications in patients undergoing hemodialysis (HD) and is closely linked to increased morbidity and mortality. This study aimed to investigate the nutritional status of HD patients and the clinical relevance of bioelectrical impedance analysis (BIA) parameters such as the percent body fat (PBF), skeletal muscle mass index (SMI), extracellular water-to-total body water ratio (ECW/TBW), and phase angle (PhA) in assessing malnutrition in Vietnamese HD patients. Materials and Methods: This cross-sectional study was conducted among 184 patients undergoing hemodialysis in Hanoi, Vietnam. The BIA parameters were measured by the InBody S10 body composition analyzer, while malnutrition was assessed by the geriatric nutritional risk index (GNRI), with a GNRI <92 classified as a high risk of malnutrition. The independent BIA variables for predicting malnutrition and its cut-off values were explored using logistic regression models and a receiver operating characteristic (ROC) curve analysis, respectively. Results: Among the study population, 42.9% (79/184) of patients were identified as being at a high risk of malnutrition. The multivariate logistic regression analysis revealed that a higher ECW/TBW was independently associated with an increased risk of malnutrition, while the PBF, SMI, and PhA expressed significant and inverse associations with the malnutrition risk after adjusting for multiple confounders. The cut-off values for predicting the high risk of malnutrition in overall HD patients were determined to be 20.45%, 7.75 kg/m², 5.45°, and 38.03% for the PBF, the SMI, the PhA, and the ECW/TBW ratio, respectively. Conclusions: BIA parameters, including the PBF, SMI, PhA, and ECW/TBW ratio, could serve as indicators of malnutrition in general Vietnamese patients with HD. Full article

The utilisation of edible insects for human nutrition is a long-standing practice in many parts of the globe, and is being gradually introduced into countries without an entomophagic tradition as well. These unconventional sources of protein of animal origin have arisen as a sustainable alternative to other animal protein sources, such as meat. This review intends to present the compilation of data in the scientific literature on the chemical composition and nutritional value of the bee brood of A. mellifera species and subspecies as edible foods. For this, a comprehensive search of the scientific literature was carried out using the databases ScienceDirect, Scopus, Pub-Med, BOn, and SciELO. Appropriate keywords were used for the search to reach the research works that addressed the topics of the review. The results showed that bee brood has considerable quantities of protein, fat and carbohydrates. The most abundant amino acids are leucine and lysine (these two being essential amino acids) and aspartic acid, glutamic acid, and proline (these three being non-essential amino acids). As for the fatty acids, bee broods contain approximately equal fractions of saturated and monounsaturated fatty acids, while the polyunsaturated fatty acids are negligible. The dietary minerals present in higher quantities are potassium, phosphorus, and magnesium, and the most abundant vitamins are vitamin C and niacin; choline is also present, although it is not a true vitamin. Although bee brood from A. mellifera has potential for human consumption as a nutrient-rich food, there are still many aspects that need to be further studied in the future, such as safety and hazards linked to possible regular consumption. Full article

Bioactive glass materials have been used for decades in orthopedic surgery, traumatology, and oral and maxillofacial surgery to repair bone defects. This study aimed to evaluate in vitro the survival and proliferation of MG63 human osteosarcoma-derived cells on S53P4 bioactive glass (BonAlive^® granules). Microscopic visualization was performed to directly observe the interactions between the cells and the material. Osteoblast-like cells were examined on non-adherent test plates, on tissue culture (TC)-treated plates and on the surface of the bioglass to assess the differences. Cell survival and proliferation were monitored using a CCK-8 optical density assay. Comparing the mean OD of MG63 cells in MEM on TC-treated plates with cells on BG, we detected a significant difference (p < 0.05), over each time of observation. The sustained cell proliferation confirmed the non-cytotoxic property of the bioglass, as the cell number increased continuously at 48, 72, 96, and 168 h and even did not plateau after 168 h. Since the properties of bioglasses can vary significantly depending on their composition and environment, a thorough characterization of their biocompatibility is crucial to ensure their effective and appropriate application—for example, during hip and knee prosthesis insertion. Full article

Background/Objectives: Sarcopenia is an age-related disease resulting in muscle mass deterioration and declining strength and functional ability. Muscle protein degradation pathways are activated through the ubiquitin–proteasome system, which is integral to the pathogenesis of sarcopenia. This study examined the capability of Lactobacillus plantarum beLP1 as a postbiotic ingredient of kimchi that prevents sarcopenia. Methods: We evaluated cell viability and measured diameters in a C2C12 myotube damage model and muscle volume, muscle weight, muscle strength, and the expression of muscle degradation proteins MuRF1 and Atrogin-1 in dexamethasone-induced sarcopenic model rats using a heat-killed beLP1 strain. Results: beLP1 had no cytotoxic effects on C2C12 and prevented dexamethasone-induced cellular damage, suggesting its role in muscle protein degradation pathways. beLP1 treatment significantly prevented the dexamethasone-induced reduction in myotube diameter. In a dexamethasone-induced sarcopenic rat model, oral beLP1 significantly mitigated muscle mass decline and prevented grip strength reduction. Microcomputed tomography demonstrated that beLP1 reduced dexamethasone-induced muscle volume loss. beLP1 treatment reduced Atrogin-1 and Muscle RING-finger protein-1 (MuRF1) and the transcription factor Forkhead box O3 alpha (FoxO3α), which triggers muscle protein breakdown. beLP1 exerts protective effects by inhibiting the ubiquitin-proteasome system and regulating FoxO3α signaling. It increased AKT (Ser473) phosphorylation, which affected muscle protein synthesis, degradation, and cell survival, suggesting its potential to prevent sarcopenia. Conclusions: Heat-killed Lactobacillus plantarum beLP1 alleviates muscle mass wasting and weakness in a dexamethasone-induced sarcopenia model by regulating muscle protein degradation pathways and signaling molecules. Thus, postbiotics may be functional ingredients in sarcopenia prevention. Full article

Cancer metabolism is a hallmark of cancer. However, the impact of systemic metabolism and diet on tumour evolution is less understood. This study delves into the role of glucagon, as a component of the pancreatic microenvironment, in regulating features of pancreatic neuroendocrine tumour (pNET) cells and the metabolic remodelling occurring in the presence and absence of glucose. pNET cell lines (BON-1 and QGP-1) and the non-malignant pancreatic α-TC1 cell line were used as models. Results showed that pNET cells responded differently to glucose deprivation than α-TC1 cells. Specifically, pNET cells upregulated the GCGR in the absence of glucose, while α-TC1 cells did so in high-glucose conditions, allowing the glucagon-related pERK1/2 activation under these conditions in pNET cells. Glucagon enhanced cancerous features in pNET BON-1 cells under glucose-deprived and hyperglucagonemia-compatible concentrations. In the α-TC1 cell line, glucagon modulated cell features under high-glucose and physiological glucagon levels. NMR exometabolome analysis revealed differences in metabolic processes based on glucose availability and glucagon stimulation across cell lines, highlighting amino acid metabolism, glycolysis, and gluconeogenesis. The expression of metabolic genes was consistent with these findings. Interestingly, QGP-1 and α-TC1 cells produced glucose in no-glucose conditions, and glucagon upregulated glucose production in α-TC1 cells. This suggests that gluconeogenesis may be beneficial for some pNET subsets, pointing out novel metabolism-based strategies to manage pNETs, as well as a step forward in endocrinology and systemic metabolism. The association between GCGR expression and malignancy and a negative correlation between glucagon receptor (GCGR) and glucagon-like peptide-1 receptor (GLP-1R) expression was observed, indicating a biological role of glucagon in pNETs that deserves to be explored. Full article

Objective: This study aimed to compare the efficacy of Sticky Tooth (ST) derived from ground teeth and Sticky Bone (SB) based on equine bone and human allograft in maxillary bone defect regeneration through histological examination. Materials and Methods: Forty patients underwent maxillary alveolar ridge regeneration using four different biomaterials: Sticky Tooth processed with the BonMaker device (n = 10), Sticky Tooth prepared with the Smart Dentin Grinder (n = 10) Sticky Bone derived from an equine xenograft (n = 10), and Sticky Bone derived from human allografts (n = 10). CBCT imaging was performed preoperatively, post-regeneration, and during follow-up. Histological and quantitative statistical evaluation was conducted on biopsy samples obtained four months post-regeneration at the time of implant placement. Results: Successful alveolar ridge regeneration was achieved in all 40 patients. Histological analyses confirmed good integration between the biomaterials and bone tissue without signs of inflammation. Conclusion: Histological comparisons demonstrated that both ST and SB are effective biomaterials for bone regeneration. However, ST exhibited a faster bone healing process compared to xenograft and allograft SB. Full article

Tetrastigma erubescens, a native medicinal plant of Vietnam, has long been used in folk medicine to manage various diseases, including skin-related issues. However, limited research has been conducted on this herb’s bioactivities and chemical composition. This study aims to investigate the chemical constituents and evaluate the anti-tyrosinase activity and UV-A/UV-B absorption capacity of T. erubescens extracts, highlighting their potential as natural sources for skin-whitening and sun protection agents. In vitro assays demonstrated that the ethyl acetate (EA) extract of T. erubescens exhibited a significant UV-A and UV-B absorption capacity. Notably, this extract showed a strong anti-tyrosinase activity for the first time, with a maximum inhibition rate of 99.2% and an IC₅₀ value of 70.3 µg/mL. Based on the UHPLC and GCMS analysis, phenolic compounds (1–9) and ten volatile constituents (10–19) were identified in the EA extract of T. erubescens. Of these, almost all volatiles and some phenolics were reported for the first time in this genus. The molecular docking analysis revealed that all identified phytochemicals showed a comparable or greater binding affinity to both mushroom tyrosinase (docking scores: from −7.5 to −14.1 kcal/mol) and human tyrosinase (from −6.7 to −14.8 kcal/mol) than kojic acid (−8.7 and −8.6 kcal/mol, respectively). In addition, these identified compounds showed favorable drug-like properties and low toxicity risks via ADMET prediction and Lipinski’s Rule of Five analyses. The results obtained in this work suggest that the EA extract of T. erubescens is a promising natural source of bioactive compounds for cosmetic applications, particularly in whitening and sun protection formulations. Full article

The storage enclosures are vital for stabilizing the micro-environment within, facilitating preventive conservation efforts, and enabling energy savings by reducing the need for extensive macro-environmental control within the room. However, real-time conformity monitoring of the micro-environment to ensure compliance with preventive conservation specifications poses a practical challenge due to a limitation in implementing physical sensors for each enclosure. This study aims to address this challenge by using an ANN (Artificial Neural Network)-based prediction for temperature and RH (Relative Humidity) changes in response to macro-environmental fluctuations. A numerical model was developed to simulate transient heat and mass transfer between macro- and micro-environments and then employed to determine an acceptable macro-environmental range for sustainable preventive conservation and to generate a dataset to train a sequence-to-sequence ANN model. This model was specially designed for 24 h real-time prediction of heat and mass transfer and to simulate the micro-environmental conditions under varying levels of control accuracy over the macro-environment. The effectiveness of the prediction model was tested through a real trial application in the laboratory, which revealed a robust prediction of micro-environments inside different enclosures under various macro-environmental conditions. This modeling approach offers a promising solution for monitoring the micro-environmental conformity and further implementing the relaxing control strategy in the macro-environment without compromising the integrity of the collections stored inside the enclosures. Full article

Objectives: to assess the ability of high-performing open-weight large language models (LLMs) in extracting key radiological features from prostate MRI reports. Methods: Five LLMs (Llama3.3, DeepSeek-R1-Llama3.3, Phi4, Gemma-2, and Qwen2.5-14B) were used to analyze free-text MRI reports retrieved from clinical practice. Each LLM processed reports three times using specialized prompts to extract (1) dimensions, (2) volume and PSA density, and (3) lesion characteristics. An experienced radiologist manually annotated the dataset, defining entities (Exam) and sub-entities (Lesion, Dimension). Feature- and physician-level performance were then assessed. Results: 250 MRI exams reported by 7 radiologists were analyzed by the LLMs. Feature-level performances showed that DeepSeek-R1-Llama3.3 exhibited the highest average score (98.6% ± 2.1%), followed by Phi4 (98.1% ± 2.2%), Llama3.3 (98.0% ± 3.0%), Qwen2.5 (97.5% ± 3.9%), and Gemma2 (96.0% ± 3.4%). All models excelled in extracting PSA density (100%) and volume (≥98.4%), while lesions’ extraction showed greater variability (88.4–94.0%). LLMs’ performance varied among radiologists: Physician B’s reports yielded the highest mean score (99.9% ± 0.2%), while Physician C’s resulted in the lowest (94.4% ± 2.3%). Conclusions: LLMs showed promising results in automated feature-extraction from radiology reports, with DeepSeek-R1-Llama3.3 achieving the highest overall score. These models can improve clinical workflows by structuring unstructured medical text. However, a preliminary analysis of reporting styles is necessary to identify potential challenges and optimize prompt design to better align with individual physician reporting styles. This approach can further enhance the robustness and adaptability of LLM-driven clinical data extraction. Full article

Background/Objectives: The objective of this review is to map nurses’ responsibilities in addressing individuals who are victims of violence, specifically in the preservation of forensic evidence in both intra- and extra-hospital contexts. The research question is as follows: What are a nurse’s responsibilities regarding the care of victims of violence for the preservation of forensic evidence in in-hospital and out-of-hospital emergencies? Methods: The mnemonic PCC (P-Population, C-Concept, and C-Context) method was followed according to the recommendations of the Joanna Brigs Institute (2024). The population is defined as “individuals who are victims of violence”, the concept (phenomenon of interest) as “nursing interventions determining responsibilities in forensic evidence preservation”, and the context as “intra- and extra-hospital emergencies”. A search was conducted in the following databases: CINAHL Complete via EBSCO Host, Medline Complete via EBSCO Host, PubMed, Web of Science, and RCAAP via B-ON. From the total articles retrieved, 18 were selected for analysis. Results: The 18 articles emphasized the critical role of nurses in preserving forensic evidence in both intra- and extra-hospital contexts. These findings were grouped into six domains to clarify the topic: (1) knowledge and training of nurses on forensic evidence preservation and the implementation of standardized protocols; (2) collection of biological and non-biological samples to preserve evidence on the victim’s body; (3) collection of biological and non-biological samples to preserve evidence on the victim’s objects and belongings; (4) documentation of forensic traces and evidence; (5) maintenance of the chain of custody; and (6) ongoing interprofessional collaboration between nurses, law enforcement, and judicial authorities. Conclusions: Intra- and extra-hospital emergencies, teams must be proficient in recognizing victims of violence and in conducting appropriate evidence preservation to ensure their legal admissibility. Full article

Today’s exoskeletons face challenges with low fluency (a quantifiable alternative to “seamlessness”), hypothesized to be caused by a lag in active control innate in many leader–follower paradigms seen in contemporary systems, leading to inefficiencies and discomfort. Furthermore, tandem fluency, a variation of fluency specific for tandem robots systems as exoskeletons, is yet to be rigorously tested in practice. This study aims to utilize metrics of tandem fluency in order to demonstrate improved human–robot interaction (HRI) in exoskeletons through human subject testing of a prototype 1 degree of freedom (DoF) exoskeleton using a motion prediction bidirectional long short-term memory (bi-LSTM) deep learning network. Subjects were recruited to conduct various upper body exercises about the elbow joint, and the collected sEMG, goniometer, and gas exchange data was used to design, test, optimize, and assess the performance of the 1 DoF exoskeleton using tandem fluency metrics. We found that the correlation between I-ACT, a metric of tandem fluency, the subjective survey responses, and metabolic data suggest that the use of a predictive bi-LSTM network to control a 1 DoF exoskeleton about the elbow results in an overall positive trend, which may correlate to high tandem fluency. Full article

This study examined the effectiveness of professional development for inclusive education and best practices through a short-term technical assistance (TA) model across 15 schools. The professional development was structured to enhance school professionals’ knowledge about inclusion as a concept, as well as best practices in inclusive education. Topics included the use of accommodations and modifications, differentiation and Universal Design for Learning (UDL), building an inclusive school culture, and co-teaching. Pre- and post-test measures were utilized to measure participants’ growth in the knowledge of these topics. Descriptive statistics and dependent t-tests were utilized to analyze data across all topic areas. The findings indicate that short-term TA models of professional development prove beneficial for improving attitudes and beliefs in inclusive education for content knowledge and building an inclusive school culture. Short-term TA did not yield statistically significant increases for classroom strategies or implementation, suggesting that more intensive professional development models need to be incorporated as a wider professional development plan for using best practices in inclusive education by school professionals. Full article

This paper proposes a novel approach to the virtual 3D modeling of articulated mechanisms. It follows the widespread use of XML (eXtensible Markup Language) for various applications and defines a version of XML that is specially designed for the description of 3D geometric models of articulated bodies. In addition, it shows how the 3D geometric model of a mechanism can be gradually developed through the use of suitably defined elements and stored in a corresponding XML file. The developed XML model is processed, and using a powerful VTK (Visualization Toolkit) library, the corresponding virtual model is built and shown on the computer screen. To drive the virtual model, the dynamic model of the mechanism is developed using Bond Graph modeling techniques. Virtual 3D geometric and dynamic models are created using the corresponding software packages: BonSim3D 2023 Visual and BondSim 2023. The models are interconnected by a two-way named pipe. During the simulation of the dynamic model, the parameters necessary to drive the virtual model (e.g., the joint displacements) are collected and sent to the virtual model over the pipe. When the virtual model receives a package, the computer screen is updated by showing the new state of the mechanism. The approach is demonstrated using the example of a holonomic omnidirectional mobile robot. Full article

A series of catalysts were synthesized via a combination of evaporation-induced self-assembly and spray pyrolysis; they were then applied to the direct decomposition of methane. Among them, Ni-Cu/MgO catalysts exhibited the smallest Ni particle size (~9 nm), attributed to the Cu-induced suppression of Ni crystal growth during synthesis. These catalysts achieved the highest carbon yield, primarily due to the enhanced dispersion and nanoscale size of Ni particles. The interaction between methane and the catalysts, as well as the structural and electrical properties of the resulting carbon nanotubes, such as crystallinity and conductivity, were investigated with respect to the support material (MgO vs. Al₂O₃) and metal composition (Ni vs. Ni-Cu). The findings provide valuable insights for designing advanced catalyst systems for the efficient conversion of methane into high-value carbon-based materials. Full article