We carefully investigate the gravitational equations of the brane world, in which all the matter forces except gravity are confined on the 3-brane in a 5-dimensional spacetime with $Z_2$ symmetry. We derive the effective gravitational equations on the brane, which reduce to the conventional Einstein equations in the low energy limit. {}From our general argument we conclude that the first Randall & Sundrum-type theory (RS1) [hep-ph/9905221] predicts that the brane with the negative tension is an anti-gravity world and hence should be excluded from the physical point of view. Their second-type theory (RS2) [hep-th/9906064] where the brane has the positive tension provides the correct signature of gravity. In this latter case, if the bulk spacetime is exactly anti-de Sitter, generically the matter on the brane is required to be spatially homogeneous because of the Bianchi identities. By allowing deviations from anti-de Sitter in the bulk, the situation will be relaxed and the Bianchi identities give just the relation between the Weyl tensor and the energy momentum tensor. In the present brane world scenario, the effective Einstein equations cease to be valid during an era when the cosmological constant on the brane is not well-defined, such as in the case of the matter dominated by the potential energy of the scalar field.
Bahig A. El deeb, Gerges G. Faheem, Mahmoud S. Bakhit
The study investigated the capacity of the endophytic fungus Talaromyces funiculosus to biosynthesize extracellular AgNPs and assess their safety. The fungus was identified through morphological and phylogenetic analyses. The biosynthesized AgNPs were spherical crystalline, stable (6 months), and mono-dispersed (PDI: 0.007), exhibiting SPR at 422.5 nm, average diameter of 34.32 nm, and Zeta potential of -18.41 mV. The optimal biosynthesis conditions are 1 mM AgNO3, 5 g biomass, pH 5.5, and a reaction temperature of 60 °C. Escherichia coli (bacterial strains) and Candida tropicalis (yeast strains) exhibited the highest susceptibility with inhibition zones of 26.3 mm and 22.3 mm, respectively, at 50 µg/mL of AgNPs, and MICs of 3.7 µg/mL and 6.3 µg/mL, respectively. AgNPs exhibited cytotoxicity with IC50 values of 48.11 ppm for HEK-293 and 35.88 ppm for Hep-G2 cells, showing selective toxicity toward cancer cells. They demonstrated antioxidant activity by increasing GSH (10.29 to 14.76 mmol/g) and reducing MDA (40.57 to 26.28 nmol/ml) at 48.11 ppm. AgNPs also enhanced IL-10 production (96.47 to 177.0 pg/mL) and reduced TNF-α levels (55.77 to 41.06 pg/mL), indicating their anti-inflammatory properties. These results support the safe use of low-dose AgNPs, however, further studies are needed to evaluate AgNPs for clinical uses.
Jéssica Ferraz, Maria Fernanda Ortolani Pollini, Vinicius Martinho Borges Cardoso
et al.
Achieving precise drug release in the colon remains a key objective in therapies for inflammatory bowel disease (IBD). Natural polysaccharides, including high-amylose starch (HAS) and pectin, offer relevant characteristics for localized drug delivery due to their biocompatibility, biodegradability, and adaptability. In this work, high-esterified pectin (HEP) was incorporated during the retrogradation of HAS to further form cohesive films without the need for organic solvents or high temperatures. The resulting matrices showed improved mucoadhesive performance, particularly under colonic conditions, where hydrophobic ester groups in HEP enhanced tissue adherence. This feature is critical for prolonged residence time in inflamed mucosa. Variations in HEP content directly influenced matrix density, fluid interaction, and mechanical resistance, without compromising film integrity. The high degree of esterification limited pH-dependent swelling and promoted alternative release mechanisms potentially related to enzymatic degradation. Such behavior contrasts with traditional low-esterified pectin (LEP) systems, suggesting that HEP may act as a structural modifier rather than a neutral excipient. Despite its widespread use in food systems, HEP remains underexplored in pharmaceutical matrices, especially in combination with retrograded starch (RS). The physicochemical and biointerfacial properties observed here underscore their applicability for the rational design of colonic delivery systems and provide a foundation for formulation strategies tailored to chronic intestinal disorders.
Paul Richmond, C. Papageorgakis, V. Niarchos
et al.
We present specialized large language models (LLMs) for theoretical high-energy physics, obtained as 20 fine-tuned variants of the 8 billion parameter Llama-3.1 model. Each variant was trained on arXiv abstracts (through August 2024) from different combinations of hep-th, hep-ph and gr-qc. For a comparative study, we also trained models on datasets that contained abstracts from disparate fields such as the q-bio and cs categories. All models were fine-tuned using two distinct low-rank adaptation fine-tuning approaches and varying dataset sizes, and outperformed the base model on hep-th abstract completion tasks. We compare performance against leading commercial LLMs (ChatGPT, Claude, Gemini, DeepSeek) and derive insights for further developing specialized language models for high-energy theoretical physics.
Heparin (HEP) is one of the oldest anticoagulant drugs, widely used in clinical settings, particularly in surgery and dialysis machines. Despite its long history, it remains extensively employed in medical practice. This study introduces a selective and cost-effective method for the rapid detection of HEP using red-emission carbon dots (R-CDs). These R-CDs were synthesized through a one-pot hydrothermal method, utilizing neutral red and thiourea for photostability, biocompatibility, and low cytotoxicity. Key parameters affecting the sensing process, including nanoprobe volume, pH, buffer type, and incubation time, were optimized to achieve potential assay conditions. The fluorescence intensity of the nanoprobe at 625 nm gradually decreased as the concentration of HEP increased from 60 to 240 nM. These changes in fluorescence intensity showed a linear relationship with HEP concentration within this range, achieving a limit of detection (LOD) of 5 nM. The proposed nanoprobes facilitate both quantitative and qualitative non-invasive analysis of HEP in various human biofluids, suggesting their potential for broader bioanalytical applications.
Sabine Crépé-Renaudin, Alexander Kohls, Micha Moskovic
et al.
The INSPIRE platform -- the most widely-used discovery service specifically tailored to the needs of researchers in High Energy Physics (HEP) -- has become a central component of the information infrastructure for the discipline. Despite this, INSPIRE's continued sustainability is frequently endangered by resource constraints, recently made more acute by the loss of support from historical funders changing their research priorities. If the European particle physics community wishes to ensure INSPIRE's long-term sustainability, the community should secure international support and ensure appropriate funding.
The increasing complexity of modern neural network architectures demands fast and memory-efficient implementations to mitigate computational bottlenecks. In this work, we evaluate the recently proposed BitNet architecture in HEP applications, assessing its performance in classification, regression, and generative modeling tasks. Specifically, we investigate its suitability for quark-gluon discrimination, SMEFT parameter estimation, and detector simulation, comparing its efficiency and accuracy to state-of-the-art methods. Our results show that while BitNet consistently performs competitively in classification tasks, its performance in regression and generation varies with the size and type of the network, highlighting key limitations and potential areas for improvement.
Sima Darvishi, Hossein Hosseinzadeh, Fahimeh Kazeminava
et al.
In this study, by innovative combining the unique characteristics of Cu-based metal-organic framework (MOF) with the versatile attributes of saccharides (i.e., heparin, Hep), a promising approach is established for active and passive targeting DDS, Cu-MOF/Hep, with a pH-controlled release profile and enhanced drug efficacy. The characterization of the synthesized materials (i.e., FT-IR, XRD, SEM, EDX, TEM, DLS, and TGA) confirms the successful synthesis of Cu-MOF/Hep. In vitro studies concerning the loading and release of DOX observed that a higher amount of DOX was released at pH 5 (>90 % on 96 h, 41 °C) compared to pH 7.4 (<10 % on 96 h, 37 °C). The sensitive feature of the used MOF to the pH conditions increased the drug release in environmental conditions similar to cancer tissues. Furthermore, cytotoxicity assessments indicated notable cytotoxicity effects of DOX-loaded Cu-MOF/Hep on MCF-7 cells (IC50: ~10 μg/mL in 48 h) with a significant apoptosis rate. The existence of CD44 receptors on the surfaces of cells underscores the significance of Hep-modified systems in facilitating the apoptosis of cancerous cells. The results suggest that the combined Cu-MOF and Hep have the potential to be a viable option for creating platforms that deliver anticancer treatments.
Macrophages are innate immune cells that interact with complex extracellular matrix environments, which have varied stiffness, composition, and structure, and such interactions can lead to the modulation of cellular activity. Collagen is often used in the culture of immune cells, but the effects of substrate functionalization conditions are not typically considered. Here, we show that the solvent system used to attach collagen onto a hydrogel surface affects its surface distribution and organization, and this can modulate the responses of macrophages subsequently cultured on these surfaces in terms of their inflammatory activation and expression of adhesion and mechanosensitive molecules. Collagen was solubilized in either acetic acid (Col-AA) or N-(2-hydroxyethyl)piperazine-N′-ethanesulfonic acid (HEPES) (Col-HEP) solutions and conjugated onto soft and stiff polyacrylamide (PA) hydrogel surfaces. Bone marrow-derived macrophages cultured under standard conditions (pH 7.4) on the Col-HEP-derived surfaces exhibited stiffness-dependent inflammatory activation; in contrast, the macrophages cultured on Col-AA-derived surfaces expressed high levels of inflammatory cytokines and genes, irrespective of the hydrogel stiffness. Among the collagen receptors that were examined, leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) was the most highly expressed, and knockdown of the Lair-1 gene enhanced the secretion of inflammatory cytokines. We found that the collagen distribution was more homogeneous on Col-AA surfaces but formed aggregates on Col-HEP surfaces. The macrophages cultured on Col-AA PA hydrogels were more evenly spread, expressed higher levels of vinculin, and exerted higher traction forces compared to those of cells on Col-HEP. These macrophages on Col-AA also had higher nuclear-to-cytoplasmic ratios of yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ), key molecules that control inflammation and sense substrate stiffness. Our results highlight that seemingly slight variations in substrate deposition for immunobiology studies can alter critical immune responses, and this is important to elucidate in the broader context of immunomodulatory biomaterial design.
Many high-energy-physics (HEP) simulations for the LHC rely on Monte Carlo using importance sampling by means of the VEGAS algorithm. However, complex high-precision calculations have become a challenge for the standard toolbox, as this approach suffers from poor performance in complex cases. As a result, there has been keen interest in HEP for modern machine learning to power adaptive sampling. While previous studies have shown the potential of normalizing-flow-powered neural importance sampling (NIS) over VEGAS, there remains a gap in accessible tools tailored for non-experts. In response, we introduce ZüNIS, a fully automated NIS library designed to bridge this divide, while at the same time providing the infrastructure to customise the algorithm for dealing with challenging tasks. After a general introduction on NIS, we first show how to extend the original formulation of NIS to reuse samples over multiple gradient steps while guaranteeing a stable training, yielding a significant improvement for slow functions. Next, we introduce the structure of the library, which can be used by non-experts with minimal effort and is extensivly documented, which is crucial to become a mature tool for the wider HEP public. We present systematic benchmark results on both toy and physics examples, and stress the benefit of providing different survey strategies, which allows higher performance in challenging cases. We show that ZüNIS shows high performance on a range of problems with limited fine-tuning.