ABSTRACT Saikosaponin b1 (Ssb1), a natural oleanane‐type triterpenoid saponin, exhibits antifibrosis activity by inhibiting the activation of hepatic stellate cells (HSCs), but the specific underlying molecular mechanisms are unknown. Here, it is found that Ssb1 could directly bind with the signal transducer and activator of transcription 3 (STAT3) and effectively inhibit the activation of HSCs. Proteomic techniques and molecular simulation revealed that Ssb1 is mainly bound to the S319 residues of STAT3 in the coiled‐coil domain. Further studies indicated that Ssb1 binding with STAT3 inhibited its transcriptional activity, and regulated glioma‐associated oncogene‐1 (Gli1) expression in the Hedgehog signaling pathway. Besides, Ssb1 binding blocked interaction between STAT3 and Gli1, which promoted degradation of Gli1 protein by suppressor of fused homolog (SUFU) and the ubiquitin‐proteasome system. The loss function of Gli1 led to decreased expression of Bcl2 and promoted the apoptosis of activated HSCs. Moreover, STAT3 ablation abolished the Ssb1‐mediated antifibrotic effects. These findings show that STAT3 plays a vital role in Ssb1 treatment of liver fibrosis, and Ssb1 as a STAT3 inhibitor might be a promising therapeutic candidate for the treatment of hepatic fibrosis.
Davide Luglietto, Alessandro De Benedictis, Alessandra Marasi
et al.
Over the last decade, the quality of neurosurgical procedures dramatically improved, also thanks to the development and increased accessibility of several technological recourses (e.g., imaging, neuronavigation, neurophysiology, microscopy), allowing to plan increasingly complex approaches, while reducing the risk of postoperative complications. Among these resources, three-dimensional rendering and simulation systems, such as virtual and augmented reality, provide a high-quality visual reconstruction of brain structures and interaction with advanced anatomical models. Although the usefulness of these systems is now widely recognized, the additional availability of proprioceptive (haptic) feedback might help to further enhance the realism of surgical simulation. A systematic literature review on the application of haptic technology in simulation of cranial neurosurgical procedures was made. Inclusion criteria were the usage of simulators with haptic feedback for specific neurosurgical procedures whereas the studies that did not include an evaluation of the surgical simulation system by a surgeon were excluded. According to inclusion and exclusion criteria, 10 studies were selected. Simulation in neurosurgery still lacks a system capable of rehearsing the entire procedure—from skin incision to skin closure—while providing both visual and proprioceptive feedback. Consequently, further advancements in this area are necessary.
Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data formats, analytical complexities, and high labour costs, hindering the achievement of data standardization. Large language models (LLM), featuring powerful performance in natural language processing comprehension and handling complex tasks, have made great academic and industrial progress in recent years. This study initially investigated the application performance of LLMs in information extraction from locomotive overhaul data, with the following three reveals, as the universal information extraction (UIE) LLM is suitable for information extraction in the field of locomotive overhaul; expanding the size of locomotive data helps improve the UIE performance in information extraction from locomotive overhaul data; balancing the types of fault labels does not notably help improve this performance. Subsequent explorations concentrated on difficulties in data annotation. The script writing method was utilized for automated annotation of data, and ChatGLM was leveraged to standardize locomotive overhaul data, yielding Bleu-4, Rouge-1, Rouge-2, and Rouge-L metrics of 86.87%, 89.60%, 87.54%, and 94.26%, respectively, in alignment with the requirements of engineering applications. Further developments introduced an auxiliary data standardization pre-processing tool to streamline the standardization process by encapsulating the LLM.
Control engineering systems. Automatic machinery (General), Technology
Laura A Bray, Lori L Jervis, Amanda E Janitz
et al.
Prior research identifies trust as critical to increase vaccine acceptance and uptake. However, few intervention studies have sought to develop or test strategies for bolstering vaccine-related trust. To address this gap, this exploratory study identifies features of COVID-19 vaccine hesitancy interventions that can promote or undermine trust across three interconnected domains: institutional, interpersonal, and product (the vaccine itself). We draw on focus groups (N = 27 participants) with community and university partners involved with hosting COVID-19 testing and vaccine events in underserved Oklahoma communities. Focus groups explored participants' experiences serving community health needs and elicited feedback on proposed vaccine hesitancy interventions. Proposed interventions included two technology-based strategies (text message reminders and tablet-based testimonials and education) and one dialogue-based strategy (anti-body test interpretation). We find that community partners perceived local universities as trustworthy institutions because of their association with popular sports programs, academic credentials, and proximity, creating opportunities to address vaccine-related distrust through community-university partnerships. The most promising intervention strategies for building interpersonal trust included engaging in one-on-one dialogue and using autonomy enhancing approaches. Finally, interventions that successfully encouraged vaccine trust did so by incorporating personalized health information about individuals' potential level of protection and susceptibility to the COVID-19 virus. These findings can inform future public health efforts to create trustworthy vaccine hesitancy interventions.
Preserving Balinese cultural heritage is crucial for sustaining community identity. In Bali, temples (pura) are central to spiritual and cultural life. However, younger generations, especially temple caretakers of Pemerajan Agung Sakti Padangsambian, are increasingly losing knowledge of these sacred spaces, weakening their sense of belonging, to preserve cultural traditions. Current media efforts has failed to engage this demographic. This research addresses this challenge by developing an application-integrated images compiled into books and Android-based AR technology. The application employed a user-centered design approach involving analysis, design, development, testing, and evaluation phases. Results show AR effectively bridges the knowledge gap, with usability scores and a significant increase in user knowledge of 42.43%. This research demonstrates AR's potential for preserving and transmitting cultural heritage, including the reconstruction of damaged historical objects through 3D modeling with the marker detection technology, to ensure seamless integration between the real and virtual worlds.
Alejandro Bermúdez Cifuentes, Paula Alejandra Ramírez Lugo, Yeison Camilo Herrera Mosquera
et al.
This project seeks to propose a drone system to improve security in Bogotá, given that insecurity rates have increasedsignificantly in recent years and even more so in the COVID-19 pandemic. The proposal is based on having an integratedsystem with special characteristics to face different situations, the drones would be equipped with non-lethal weapons,photo captures for facial and vehicle scanning, real-time location sending, aerial patrolling in more frequent areas ofcriminal acts, among other functions.
Engineering (General). Civil engineering (General), Information technology
Big data has unlocked the door to significant advances in a wide range of scientific fields, and it has emerged as a highly attractive subject both in the world of academia and in business as a result. It has also made significant contributions to innovation, productivity gains, and competitiveness enhancements. However, there are many difficulties associated with data collecting, storage, usage, analysis, privacy, and trust that must be addressed at this time. In addition, inaccurate or misleading big data may lead to an incorrect or invalid interpretation of findings, which can negatively impact the consumers' experiences. This article examines the challenges related to implementing big data security and some important solutions for addressing these problems. So, a total of 12 papers have been extracted and analyzed to add to the corpus of literature by concentrating on several critical issues in the big data analytics sector as well as shedding light on how these challenges influence many domains such as healthcare, education, and business intelligence, among others. While studies have proven that big data poses issues, their approaches to overcoming these obstacles vary. The most frequently mentioned challenges were data, process, privacy, and management. To address these issues, this paper included previously discovered solutions.
Sammar Fathy ELhabal,1 Hanan Mohamed Elwy,2 Soha Hassanin,3 Ahmed A El-Rashedy,4 Alaaeldin Ahmed Hamza,5 Mohammad Ahmad Khasawneh6 1Department of Pharmaceutics and Industrial Pharmacy, Modern University for Technology and Information, Cairo, Egypt; 2Pharmaceutical Chemistry Department, National Organization for Drug Control and Research, Cairo, Egypt; 3Biochemistry Department, Modern University for Technology and information, Cairo, Egypt; 4Chemistry of Natural and Microbial Products Department, National Research Center (NRC), Giza, Egypt; 5Biology Department, National Organization for Drug Control and Research, Giza, Egypt; 6Department of Chemistry, United Arab Emirates University, Al-Ain, United Arab EmiratesCorrespondence: Mohammad Ahmad Khasawneh; Alaaeldin Ahmed Hamza, Email mohammad.khasawneh@uaeu.ac.ae; alaa17mm@gmail.comIntroduction: Metal nanoparticle synthesis using plant has emerged as an eco-friendly, clean, and viable strategy alternative to chemical and physical approaches.Methods: The fruit extract of Salvadora persica (SP) was utilized as a reducing and stabilizing agent in the synthesis of gold (AuNPs) and copper (CuNPs) nanoparticles.Results: UV–Vis spectra of the AuNPs and CuNPs showed peaks at the wavelengths of 530 nm and 440 nm, respectively. Transmission electron microscopy showed that nanoparticles exhibited a mainly spherical form, with a distribution range of 100 to 113 nm in diameter for AuNPs and of 130 to 135 nm in diameter for CuNPs. While energy-dispersive X-ray spectroscopy was able to confirm the existence of AuNPs and CuNPs. The alcoholic extract of the fruit SP was analyzed by GC-MS in order to identify whether or not it contained any active phytochemicals. Fourier-transform infrared spectra confirmed the presence capping functional biomolecules of SP on the surface of nanoparticles that acts as stabilizers. Analysis of the zeta potential revealed that NPs with high degree of stability, as demonstrated by a strong negative potential value in the range of 25.2 to 28.7 mV. Results showed that both green AuNPs and CuNPs have potential antimicrobial activity against human pathogens such gram-negative bacteria and gram-positive bacteria, with CuNPs having antimicrobial activity higher than AuNPs. In addition, AuNPs and CuNPs have promising antioxidant and anticancer properties when applied to MCF-7 and MDA-MB-231 breast cancer cells. Studies of molecular docking of SP bioactive compounds were conducted against methenyl tetrahydrofolate synthetase. Among all of them, Beta – Sitosterol was the most prominent.Conclusion: These AuNPs and CuNPs are particularly appealing in a variety of applications in the pharmaceutical and medicinal industries due to their economical and environmentally friendly production.Keywords: Salvadora persica, green nanoparticles, antioxidant, antibacterial, anticancer
Intertidal vegetation plays an essential role in habitat provision for waterbirds but suffers great losses due to human activities. However, it is challenging in tracking the human-driven loss and degradation of intertidal vegetation due to rapid urbanization in a high temporal resolution. In this study, a methodological framework based on full Landsat time-series (FLTS) is proposed to detect the year of change (YOC) of intertidal vegetation converted to impervious surfaces (ISs) and artificial ponds (APs), and the condition of the remaining intertidal vegetation was also assessed by FLTS, in the Fujian province, a subtropical coastal area lying in southeast China. The accuracies of the YOC detection of intertidal vegetation converted to IS and AP were 91.84% and 72.73%, with mean absolute errors of 0.26 and 1.06, respectively. The total areas of intertidal vegetation encroached by IS and AP were 31.68 km2 and 23.85 km2, respectively. Most ISs were developed later than 2010, and most APs were developed earlier than 2005, which are highly related to the implementation of local policies for economic development. The remaining intertidal vegetation in growing, stable, and degraded conditions were 43.05%, 56.38%, and 0.57%, respectively. The results indicated that areas of intertidal vegetation were reclaimed for anthropogenic uses at a considerable rate, although the intertidal vegetation still increased owing to natural development after the establishment of natural reserves. The study demonstrates that the FLTS has capacities in monitoring the dynamics in coastal zones solely for its dense earth observations.