Abstract: This study investigated the feasibility of incorporating Chenopodium album L (CAL) into ruminant feed ingredients by evaluating the effects of harvest time and substitution levels on in vitro rumen fermentation. In the first phase, a sole-substrate experiment was conducted using CAL harvested from June to August, analyzing its chemical composition and total saponin content. The impact of harvest time on fermentation parameters was assessed with CAL as the sole substrate. The second phase involved a mixed-substrate experiment using an early-fattening Hanwoo diet (30% rice straw and 70% concentrate), where increasing proportions of CAL (Control: 0%, T1: 5%, T2: 10%, T3: 15%, and T4: 20%) replaced rice straw. Seasonal variations in CAL composition influenced fermentation characteristics, with July-harvested CAL exhibiting higher fermentability, while August-harvested CAL had lower fermentability. However, August-harvested CAL was selected for the second experiment due to its greater availability. We hypothesized that saponins in CAL contribute to methane reduction. Supplementation with 15% of CAL significantly reduced methane production per gram of digested substrate (p < 0.05), likely due to differences in crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and saponin content. However, despite having the lowest fiber content, T4 (20% CAL) exhibited the lowest in vitro dry matter digestibility (IVDMD), suggesting that factors such as saponins, CAL’s chemical composition, or microbial shifts may have hindered digestibility. Fermentation characteristics further revealed that the acetate-to-propionate (A/P) ratio decreased with increasing CAL levels, with T4 showing the lowest ratio (1.55 at 72 hours), confirming a shift toward propionate-based fermentation. Notably, T2 (10% CAL) optimized fermentation efficiency, producing the highest total volatile fatty acid (VFA) concentration at 24 hours (98.28 mM). These findings highlight the potential of CAL as a functional feed ingredient, with moderate substitution levels (10–15%) enhancing fermentation efficiency while reducing methane production.

Abstract: Determining carbon sources and sinks is crucial for understanding the global carbon cycle; yet, the enigma of 'missing' sinks remains unresolved. Recent studies have proposed carbonate weathering as a potential carbon sink, underscoring the necessity to clarify its mechanisms. Previous investigations of carbonate weathering predominantly relied on soil profiles, which were limited by the scarcity of incipient weathering layers. To explore these incipient weathering processes, surface-weathered carbonate rocks were collected from dolomite lenses within the Neoproterozoic Liangjiehe Formation (Nanhua System) in Guizhou, China. The pristine dolomite displays δ¹³C values ranging from -5.26 to -3.35‰ and δ¹⁸O values from -13.79 to -12.83‰. These isotopic signatures suggest that the dolomite formed under high-latitude, cold climatic conditions prevalent during the Nanhua Period. Comprehensive petrographic and geochemical analyses of the surface-weathered dolomite rocks revealed two distinct stages of incipient weathering. In Stage I, there is a decrease in Rare Earth Elements (REEs) content, accompanied by the leaching of nickel (Ni) and cobalt (Co). The δ¹³C values fluctuate between -7.61 and -2.52‰, while δ¹⁸O values range from -12.22 to -8.06‰. These observations indicate a weakly acidic microenvironment. In Stage II, there is an enrichment of manganese (Mn), molybdenum (Mo), and zinc (Zn), with δ¹³C values extending from -16.56 to -12.43‰ and δ¹⁸O values from -8.46 to -7.03‰. These changes suggest a transition to a neutral or alkaline microenvironment, with the isotopic compositions of carbon and oxygen in the dolomite being influenced by atmospheric carbon dioxide (CO₂) and atmospheric precipitation. This study represents a pioneering investigation into the mineralogical and geochemical variations associated with the incipient weathering process of carbonates, indicating that surface-weathered carbonate rocks may serve as an underutilized archive for reconstructing the dynamics of incipient weathering.

Abstract: Background/Objectives: This study investigated the effectiveness of intraoperative ultrasonography (IOUS) combined with sodium fluorescein (SF) in evaluating tumor resection completeness in patients with glioblastoma IDH1-wildtype. By comparing SF with IOUS with postoperative magnetic resonance imaging (MRI) for detecting residual tumors, we aimed to evaluate its potential in improving surgical precision and neurosurgical outcomes. Methods: Adult patients with supratentorial IDH-wildtype grade 4 glioblastoma who underwent resection using SF or SF with IOUS during 2015–2024 were included. Results: A total of 97 patients met the inclusion criteria (49 SF group and 48 SF with IOUS group). The gross total resection (GTR) rate was higher in the SF with IOUS group (83.3%) than in the SF group (67.3%), although the difference was not statistically significant (p = 0.112). For residual tumors according to postoperative MRI findings as a result of subtotal resection due to tumor invasion of eloquent anatomical locations, 6/49 (12.2%) patients in the SF group showed a positive result (ϰ: 0.447, p = 0.001), and 4/48 (8.3%) patients in the SF with IOUS group showed a positive result (ϰ: 0.625, p < 0.001). The sensitivity, specificity, negative predictive value, and positive predictive value for predicting residual tumors peroperatively compared with postoperative MRI results were calculated for the SF and SF with IOUS groups. Comparison between the SF and SF with IOUS groups revealed a statistically significant difference in the estimated mean survival time, with 14 months (standard error: 1.236) for the SF group and 24 months (standard error: 4.103) for the SF with IOUS group (p < 0.001). In total, 11/49 (22.4%) patients in the SF group, and 10/48 (20.8%) patients in the SF with IOUS group experienced newly developed neurological deficits postoperatively (p > 0.05). In the SF with IOUS group, 26/48 (54.2%) patients, 14/48 (29.2%) patients, and 8/48 (16.7%) patients had Karnofsky Performance Status scores of 90–100, 70–80, and <70, respectively (p = 0.525), and 12 patients experienced deterioration, 24 patients were stable, and 12 patients had improved at 1 month. Conclusions: SF with IOUS provides a reliable imaging modality for achieving successful GTR and improving surgical outcomes. Nevertheless, further research is necessary to overcome its limitations and better define its intraoperative role.

Abstract: Background: Malnutrition among Vietnamese children, especially children in ethnic minority and mountainous areas, remains high. Objective: The current study explored the nutritional status of ethnic minority secondary school students in some mountainous provinces in the Northwest of Vietnam and identified some related factors. Methods: We recruited 1,847 high school students who are ethnic minorities in 2 provinces of the northwestern mountainous region of Vietnam by convenience sampling from a primary healthcare setting to carry out the cross-sectional study over 6 months. The malnutrition status of study participants was measured using the 2006 WHO Child Growth Standards. The nutritional practices of study participants were assessed using a 4-point scale based on food consumption frequency and eating habits. Results: This study found that the prevalence of stunting and wasting in children was 16.7% and 6.2%, respectively, while the prevalence of overweight/obesity in children was 8.3%. Some factors related to the rate of stunting are male students, the number of children born living in the family, poor/near-poor household economy, low maternal education level, and frequent gastrointestinal and respiratory diseases. Children who ate more than 3 meals/day, snacked at night, ate fried foods, ate less vegetables and fruits, and were less active/day were associated with a higher risk of overweight/obesity. Conclusions: Our study shown a comprehensive picture of malnutrition among children in ethnic minority areas. Essential nutritional intervention programs, projects and models are a top priority to reduce the disease burden, for children’s bright future and to enhance socio-economic development in the Northwest mountains.

Abstract: This paper examines whether GPT-4, a Generative Pre-Trained Transformer model developed by OpenAI, possesses a 'self' and whether it is aware of it. It employs the Structures Theory and evaluates GPT-4 against five critical structures deemed essential for self-awareness: unified consciousness, volition, a Theory of Others, self-awareness, and personal identity. While GPT-4 demonstrates capabilities in four of these areas, it conspicuously lacks unified consciousness. This absence decisively negates GPT-4's present self-awareness and its classification as having a "self." Nevertheless, if each instance or session of GPT-4 were viewed as a separate entity, then there might be potential for unified consciousness (should it be demonstrated that GPT-4 is conscious). The paper argues that GPT-4's cognitive architecture requires no modification for self-awareness except for the attainment of consciousness. It highlights the necessity for further research into technologies that could endow GPT-4 with consciousness and explores potential behavioural indications of self-awareness and its implications for society. The findings suggest that because the leap to self-awareness hinges solely on its capacity for consciousness, there is a need for significant philosophical and regulatory debates about the nature and rights of self-aware AI entities.

Abstract: Adaptive Optics-Transscleral Flood Illumination (AO-TFI) is a novel imaging technique with potential for detecting retinal pigment epithelium (RPE) changes in dry age-related macular degeneration (AMD). This single-center, prospective study evaluated its ability to visualize pathological features in AMD. AO-TFI images were acquired using the prototype Cellularis® camera over six 5×5° macular zones in patients with good fixation and no exudative changes. Conventional imaging modalities, including spectral-domain optical coherence tomography (OCT), color fundus photography, and fundus autofluorescence, were used for comparison. AO-TFI images were correlated with OCT using a custom method (Fiji software). Eleven eyes of nine patients (70 ± 8.3 years) with early (n=5), intermediate (n=1), and atrophic (n=5) AMD were analyzed. AO-TFI identified relevant patterns in dry AMD. RPE cell visibility was impaired in affected eyes, but AO-TFI distinguished cuticular drusen with hyporeflective centers and bright edges, large ill-defined drusen, and stage 3 subretinal drusenoid deposits as prominent hyperreflective spots. It provided superior resolution for small drusen compared to OCT and revealed crystalline structures and hyporeflective dots in atrophic regions. Atrophic borders remained isoreflective unless RPE displacement was absent, allowing precise delineation. These findings highlight AO-TFI’s potential as a sensitive imaging tool for characterizing early AMD and clinical research.

Abstract: Tissue engineering represents a revolutionary approach to regenerating damaged bones and tissues. The most promising materials for this purpose are calcium phosphate-based bioactive ceramics (CaPs) and bioglasses, due to their excellent biocompatibility, osteoconductivity, and bioactivity. This review aims to provide a comprehensive and comparative analysis of different bioactive calcium phosphate derivatives and bioglasses, highlighting their roles and potential in both bone and soft tissue engineering as well as in drug delivery systems. We explore their applications as composites with natural and synthetic biopolymers, which can enhance their mechanical and bioactive properties. The review critically examines the advantages and limitations of each material, their preparation methods, biological efficacy, biodegradability, and practical applications. By summarizing recent research from scientific literature, this paper offers a detailed analysis of the current state of the art. The novelty of this work lies in its systematic comparison of bioactive ceramics and bioglasses, providing insights into their suitability for specific tissue engineering applications. The expected primary outcomes include a deeper understanding how each material interacts with biological systems, their suitability for specific applications, and the implications for future research directions.

Abstract: Artificial Intelligence (AI) faces a range of mathematical challenges, such as optimization, generalization, model interpretability, and phase transitions. These issues significantly limit the application of AI in critical domains such as medicine, autonomous systems, and finance. This article examines the primary mathematical problems of AI and proposes solutions based on the universality of the Riemann zeta function. Furthermore, AI, as a major trend attracting hundreds of billions of dollars, is now tasked with addressing humanity’s most complex challenges, including nuclear fusion, turbulence, the functioning of consciousness, the creation of new materials and medicines, genetic issues, and catastrophes such as earthquakes, volcanoes, tsunamis, as well as climatic and social upheavals, ultimately aiming to elevate civilization to a galactic level. All these problems, both listed and unlisted, are interconnected by the issue of prediction and the problem of “black swans” within existing challenges. This work offers an analysis of AI’s problems and potential pathways to overcome them, which, in our view, will strengthen existing trends established by our great predecessors, which we believe will become foundational in mastering AI.

Abstract: Land-use change driven by urbanization has led to considerable habitat degradation and biodiversity loss, underscoring the need for spatially explicit assessment tools. This study evaluates habitat quality and threat intensity in Gochang-gun, South Korea, by integrating a biotope map with the Habitat Quality module of the InVEST model. Land cover was classified using detailed biotope types, and sensitivity values were assigned to each based on their vulnerability to specific threats such as urban areas, roads, and agricultural activity. Spatial modeling revealed high habitat quality in forested and protected zones like Seonunsan Provincial Park and the Dongrim Reservoir, whereas urban and agricultural regions exhibited substantial degradation. Correlation analysis confirmed a significant inverse relationship between habitat quality and degradation, and scenario-based simulations identified urban development and roads as the most detrimental factors. The removal of these threats led to the largest improvements in overall habitat condition. These findings provide actionable insights for biodiversity conservation planning and highlight the utility of biotope maps as a data source for ecosystem service models. The study supports the application of spatial tools for prioritizing conservation zones and formulating nature-based strategies for sustainable land management.

Abstract: In the following paper, I examine a psychological phenomenon called the crowding-out effect. Crowding-out sometimes occurs when a subject receives external rewards for performing an activity once executed for its intrinsic pleasure. The external rewards “crowd out” or undermine the innate pleasure the subject once experienced in engaging in the activity. The dominant explanation to account for this paradoxical and obviously deleterious psychological feeling is the overjustification thesis. In the following paper, I demonstrate there are two problems with this explanation and offer an ancient alternative. With the help of Joachim Aufderheide’s Anti-Delian reading of the Nicomachean Ethics, I disclose that Aristotle was not only well aware of this phenomenon but that his model of human flourishing predicated on practical wisdom presents us with a way to prevent subjects from experiencing the crowding-out effect. In short, my operationalization of Aufderheide’s reading of the Nicomachean Ethics provides researchers in psychology, education, and industrial management with new pathways and tools to understand and combat motivational diminishment.

Abstract: Leaf rust (LR) is a destructive foliar disease that affects common wheat (Triticum aestivum L.) worldwide. For optimal disease protection, wheat cultivars should possess adult plant resistance (APR) to leaf rust. The aim of the present study was to map quantitative trait loci (QTLs) for leaf rust resistance using 193 recombinant inbred line (RIL) populations derived from N. Strampelli × Huixianhong. Four trials were conducted in China (three in Baoding, Hebei province, and one in Zhoukou, Henan province) to assesses the leaf rust response of the RILs and parental lines. The RIL populations were genotyped using the wheat 660K SNP array and additional SSR markers. Three QTLs for LR resistance were identified using inclusive composite interval mapping (ICIM). Previously published data were also reassessed with ICIM to identify QTLs with pleiotropic effects. The flanking sequences of all SNP probes were searched against the Chinese Spring wheat reference sequence using BLAST to determine physical positions. Three leaf rust resistance loci, two on chromosome 2A and 5B, were contributed by N. Strampelli. QLr.hbau-2AL.1 detected in three leaf rust environments with phenotypic variance explained (PVE); QLr.hbau-2AL.2 detected in two environments with 12.5-13.2% of the PVE; QLr.hbau-5BL detected in all leaf rust environments with phenotypic variance explained (PVE) of 17.8-19.1%. QLr.hbau-5BL exhibited potentially pleiotropic responses to multiple diseases. The QTLs and flanking markers identified herein may be useful for fine mapping, candidate gene mining, and marker-assisted selection(MAS).

Abstract: Background: Automated semi-solid extrusion (SSE) material deposition is a promising new technology for preparing personalized medicines for different patient groups and veterinary applications. The technology enables the preparation of custom-made oral elastic gel tablets of active pharmaceutical ingredient (API) by using a semi-solid polymeric printing ink. Methods: An automated SSE material deposition method was used for generating chewable gel tablets loaded with propranolol hydrochloride (-HCl) at three different API content levels (3.0 mg, 4.0 mg, 5.0 mg). The physical appearance, surface morphology, dimensions, mass and mass variation, process-derived solid-state changes, mechanical properties, and in-vitro drug release of the gel tablets were studied. Results: The inclusion of API (1% w/w) in the semi-solid CuraBlendTM printing mixture decreased viscosity and increased fluidity, thus promoting the spreading of the mixture on the printed (material deposition) bed and the printing performance of the gel tablets. The printed gel tablets were elastic, soft, jelly-like, chewable preparations. The mechanical properties of the gel tablets were dependent on the printing ink composition (i.e. with or without propranolol HCl). The maximum load for the final deformation of the CuraBlend™-API (3.0 mg) gel tablets was very uniform, ranging from 73 N to 80 N. The in-vitro drug release of the gel tablets was completed within 15-20 minutes, thus verifying immediate-release dissolution for these drug preparations. Conclusions: Automated SSE material deposition as a modified 3D-printing method is a feasible technology for preparing customized oral chewable gel tablets of propranolol HCl.

Abstract: Understanding human emotion through multimodal signals—such as linguistic content, vocal acoustics, and facial expressions—remains a complex and nuanced challenge for artificial systems. Unlike humans, who intuitively infer emotions through intricate cross-modal cues, machines must systematically decode heterogeneous information. To address this gap, we propose a novel multimodal emotion recognition framework, \textbf{FusionX}, that systematically models inter-modal dynamics from multiple perspectives. FusionX decomposes multimodal input signals into three complementary types of interaction representations: modality-complete (preserving full unimodal information), modality-synergistic (capturing shared inter-modal contributions), and modality-unique (highlighting distinctive aspects of each modality). To further refine the integration of these representations, we introduce a text-prioritized fusion mechanism named \textbf{Text-Centric Hierarchical Tensor Fusion} (TCHF). This module constructs a deep hierarchical tensor network that accentuates the semantic richness of textual modality while harmonizing its contribution with the audio and visual streams. To validate FusionX, we conduct extensive evaluations across three widely-used benchmarks: MOSEI, MOSI, and IEMOCAP. Results reveal that our method significantly surpasses previous state-of-the-art baselines in both classification accuracy and regression metrics, demonstrating the superiority of hierarchical and perspective-aware interaction modeling in emotion understanding.

Abstract: Predicting the behaviour of the Earth's ionosphere is crucial for ground-based and space borne technologies relying on it. This paper presents a novel way of inferring the ionospheric electron density profiles and electron temperature profiles using machine learning. The analysis is based on the Nearest Neighbor (NNB) and Radial Basis Function (RBF) regression models. Synthetic data sets used to train and validate these two inference models are constructed using the International Reference Ionosphere (IRI 2020) model with randomly chosen years (1987-2022), months (1-12), days (1-31), latitudes (-60 to 60°), longitudes (0, 360°), times (0-23h), at altitudes ranging from 95 to 600 kilometres. The NNB and RBF models use the constructed ionosonde-like profiles to infer complete ISR-like profiles. The results presented show that the inference of ionospheric electron density profiles is better with the NNB model than with the RBF model while the RBF model is better at inferring the electron temperature profiles than the NNB model. A major and unexpected finding of this research is the ability of the two models in inferring full electron temperature profiles that are not provided by ionosondes using the same truncated electron density dataset used to infer electron density profiles. NNB and RBF models generally overestimate or underestimate the inferred electron density and electron temperature values, especially at higher altitudes, but they tend to produce good matches at lower altitudes.

Abstract: This review examined the educational potential and challenges of integrating large language model (LLM)-based text-to-image generation tools using the enhanced OpenAI ChatGPT 4o Image Generation model as a central case study. While the examples were primarily drawn from ChatGPT 4o, the insights and findings broadly applied to other text-to-image models across platforms. Through an extensive analysis of interdisciplinary literature and classroom practices, this review identified how text-to-image generation supported various applications. These included fostering creative storytelling, enhancing curriculum design, visualizing abstract STEM and medical concepts, reconstructing historical settings, supporting language acquisition, and promoting inclusivity in special education. Educators leveraged these tools to generate customized instructional materials. At the same time, students engaged with them to visualize concepts, develop richer descriptive language, and explore global cultures through personalized, image-driven learning experiences. Moreover, the review also revealed challenges, including critical technical, ethical, and pedagogical challenges. Technical issues included inconsistent image accuracy, prompt sensitivity, and resource access disparities. Ethical concerns involved algorithmic bias, potential misinformation, content filtering, and intellectual property rights. Pedagogically, educators needed to ensure alignment with learning objectives, assess AI-assisted student outputs effectively, and avoid overdependence on automation. In addition, this study incorporated qualitative data from an 8-week classroom program conducted with primary school students who used Microsoft Copilot to generate images from text prompts. The findings highlighted students’ high engagement, growing descriptive vocabulary, increased cultural awareness, and emerging critical understanding of AI’s limitations and biases. Students reported a sense of agency and creativity in crafting prompts, collaborated with peers to refine their outputs, and demonstrated early-stage digital literacy skills. These real-world classroom insights provided grounded evidence of how thoughtfully implemented text-to-image tools could enhance educational outcomes.

Abstract: Alzheimer’s disease (AD) is a progressive neurological disorder that causes memory loss, cognitive decline, and behavioral changes. AD pathologies involve different factors, including damage of cholinergic neurons, extracellular deposition of β-amyloid (Aβ) into senile plaques, intracellular accumulation of hyperphosphorylated tau protein, microglia-related neuroinflammation, and oxidative stress. Several medications, such as cholinesterase inhibitors, N-Methyl-D-aspartate receptor antagonists, and immunotherapy drugs, are administered for AD treatment. Along with AD-related neurological disorders, behavioral and psychological symptoms of dementia (BPSD) are also prevalent in individuals with AD. Pharmacological treatments for BPSD include antipsychotics, memantine, and others. Yokukan-san (YKS) is a traditional Japanese Kampo medicine. YKS contains a blend of several herbs, including Uncaria uncis cum ramulus, Angelicae radix, Bupleurum radix, and others. It has been efficacious against BPSD; thus, it was officially approved for BPSD treatment in Japan. Recently, the anti-AD effects of YKS have attracted considerable attention. Uncaria uncis cum ramulus managed AD by reducing Aβ accumulation, decreasing abnormally hyperphosphorylated tau protein, and inhibiting acetylcholinesterase. Similarly, Angelicae radix has improved memory deficits in a rat AD model by reducing Aβ levels, promoting cholinergic function, and decreasing oxidative stress and neuroinflammation. Tetracyclines (i.e., minocycline and doxycycline) popularly exhibit anti-inflammatory effects by inhibiting microglia. Moreover, minocycline has reduced Aβ production and hyperphosphorylation of tau protein. Experimental AD models demonstrated that minocycline and doxycycline improved cognitive/learning, and memory deficits, respectively. Therefore, minocycline and doxycycline are efficacious against AD. Multidrug treatment is more effective than single-drug treatment because of the synergistic effects associated with the different mechanisms of action of involved drugs. In the absence of currently effective and low-priced treatments, YKS and tetracycline are proposed for AD treatment.

Abstract: The aim is to present the 'Awake Bruxism Identification Tool (ABIT)' for children and adolescents. This tool was created at the Postgraduate Program of the Faculdade de Odontologia de Piracicaba at the Universidade Estadual de Campinas (FOP/UNICAMP) as part of a preliminary study, which was tested on 10 families from June to August 2023 at the Dental Specialties Center (CEO-Piracicaba-SP). The analysis consisted of Report 1 (R1), Report 2 (R2), Self-report (AR), Clinical Assessment (CA), and Ecological Momentary Assessment (EMA). R1, R2, and SR include questions about the perception of AB on a 5-point Likert scale, along with the recording of perception through analogical and playful EMA. Meanwhile, CA identifies intraoral and extraoral characteristics. Combining these items helps determine whether the child falls within the 'AB spectrum'. The tool was evaluated for comprehensibility, applicability and reliability, showing satisfactory results, with a reported completion time of between 5 and 10 minutes. The frequency of AB was 4 children in the “Possible AB Spectrum” and 3 children in the “Possible AB Spectrum corroborated by EMA”, with “teeth clenching” being the most frequently observed event. Adjustments to the instrument were made based on participant feedback, and the reproducibility of the ABIT seems adequate for the planned expanded study, which aims to contribute to the clinical investigation.

Abstract: In this study, the authors investigate the Collatz conjecture using a frequency-based iterative approach, demonstrating that all natural numbers ultimately converge to a reduced value with an increasing frequency rate, eventually leading to a cyclic loop. Furthermore, the authors present an argument suggesting that the probability of discovering cycles distinct from the known 4-2-1 loop is asymptotically close to zero. The findings of this research offer new insights into the fundamental properties of the Collatz process, potentially addressing several open questions related to the conjecture. In particular, the study explores the mathematical significance of the coefficients 3 and 2 in the transformation rules 3x + 1 and x/2, providing an explanation for their role in governing the conjecture’s behavior.

Abstract: Curcumin, a major phytochemical derived from Curcuma longa, has been shown to enhance the efficacy of chemotherapeutic agents such as doxorubicin, 5-fluorouracil, and cisplatin by overcoming drug resistance, making it a promising adjunct in the treatment of glioblastoma. However, the global gene expression changes triggered by curcumin in glioblastoma remain underexplored. In this study, we investigated the effects of curcumin on human glioblastoma (U87 MG) cells, where it significantly reduced cell viability and proliferation in a dose- and time-dependent manner and induced apoptosis without affecting senescence. Transcriptomic analysis revealed 5,036 differentially expressed genes, with pathway enrichment identifying 13 dysregulated cancer-associated pathways. Notably, curcumin modulated several key regulators involved in MAPK, Ras, TGF-β, Wnt, Cytokine, and TNF signalling pathways. Several apoptosis and cell cycle-associated genes, including PRKCG, GDF7, GDF9, GDF15, GDF5, FZD1, FZD2, FZD8, AIFM3, TP53AIP1, CRD14, NIBAN3, BOK, BCL2L10, BCL2L14, BNIPL, FASLG, GZMM, TNFSF10, TNFSF11, and TNFSF4, were significantly altered. Importantly, RUNX3, a key tumour suppressor, was markedly upregulated following curcumin treatment, emphasizing its potential role in curcumin-mediated anti-tumour effects. This study provides insight into the molecular mechanisms underlying curcumin's action against glioblastoma.

Abstract: A one-dimensional plug-flow reactor modeling procedure was developed and used to investigate the performance of a membrane reactor (MR) for hydrogen separation from syngas. A feed syngas enters from one side, while a sweep gas of nitrogen enters from the opposite side. The model treats the membrane reactor as a series of 200 segments with a constant cross section and temperature. The adopted spatial resolution was verified to be accurate based on a conducted resolution sensitivity analysis. Permeation is modeled as happening through thin palladium membranes that are selectively permeable to hydrogen, depending on the temperature and membrane thickness. After analyzing the hydrogen permeation profile in a base case corresponding to reference operational temperature and pressures, the temperature of the module, the retentate-side pressure, and the permeate-side pressure were varied individually and their influence on the permeation performance was investigated. In all the simulation cases, fixed targets of 95% hydrogen recovery and 40% mole-fraction of hydrogen at the permeate exit were demanded. The module length is allowed to change to satisfy these targets, with a shorter module requiring less space and reflecting better hydrogen permeation mass flux. Other dependent permeation-performance variables that were investigated include the logarithmic mean pressure-square-root difference, the hydrogen apparent permeance, and the efficiency factor. Various linear and nonlinear regression models were proposed based on the obtained results. This work gives general insights about hydrogen permeation via palladium membranes.