Search Results (432)

The human gut microbiota significantly influences host health through its metabolic products and interaction with immune, neural, and metabolic systems. Among these, short-chain fatty acids (SCFAs), especially butyrate, play key roles in maintaining gut barrier integrity, modulating inflammation, and supporting metabolic regulation. Dysbiosis is increasingly linked to diverse conditions such as gastrointestinal, metabolic, and neuropsychiatric disorders, cardiovascular diseases, and colorectal cancer (CRC). Probiotics offer therapeutic potential by restoring microbial balance, enhancing epithelial defenses, and modulating immune responses. This review highlights the physiological functions of gut microbiota and SCFAs, with a particular focus on butyrate’s anti-inflammatory and anti-cancer effects in CRC. It also examines emerging microbial therapies like probiotics, synbiotics, postbiotics, and engineered microbes. Emphasis is placed on the need for precision microbiome medicine, tailored to individual host–microbiome interactions and metabolomic profiles. These insights underscore the promising role of gut microbiota modulation in advancing preventive and personalized healthcare. Full article

Entropy is a foundational concept across scientific domains, playing a role in understanding disorder, randomness, and uncertainty within systems. This study applies Shannon’s entropy in information theory to evaluate and manage complexity in industrial supply chain management. The purpose of the study is to propose a quantitative modeling method, employing Shannon’s entropy model as a proxy to assess the complexity in SCs. The underlying assumption is that information entropy serves as a proxy for the complexity of the SC. The research method is quantitative modeling, which is applied to four focal companies from the agrifood and metalworking industries in Southern Brazil. The results showed that companies prioritizing cost and quality exhibit lower complexity compared to those emphasizing flexibility and dependability. Additionally, information flows related to specially engineered products and deliveries show significant differences in average entropies, indicating that organizational complexities vary according to competitive priorities. The implications of this suggest that a focus on cost and quality in SCM may lead to lower complexity, in opposition to a focus on flexibility and dependability, influencing strategic decision making in industrial contexts. This research introduces the novel application of information entropy to assess and control complexity within industrial SCs. Future studies can explore and validate these insights, contributing to the evolving field of supply chain management. Full article

The development of ceria (CeO_2−x)-based nanoantioxidants requires fine-tuning of structural and surface properties for enhancing antioxidant behavior in biological environments. In this contest, here ultrasmall water-dispersible CeO_2−x nanoparticles (NPs), characterized by a high Ce³⁺/Ce⁴⁺ ratio, were synthesized in a non-polar solvent and phase-transfer to an aqueous environment through ligand-exchange reactions using citric acid (CeO_2−x@Cit) and post-treatment with dopamine hydrochloride (CeO_2−x@Dopa). The concept behind this work is to enhance via surface engineering the intrinsic antioxidant properties of CeO_2−x NPs. For this purpose, thanks to electron transfer reactions between dopamine and CeO_2−x, the CeO_2−x@Dopa was obtained, characterized by increased surface Ce³⁺ sites and surface functionalized with polydopamine bearing o-quinone structures as demonstrated by complementary spectroscopic (UV–vis, FT-IR, and XPS) characterizations. To test the antioxidant properties of CeO_2−x NPs, the scavenging activity before and after dopamine treatment against artificial radical 1,1-diphenyl-2-picrylhydrazyl (DPPH^·) and the ability to reduce the reactive oxygen species in Diencephalic Immortalized Type Neural Cell line 1 were evaluated. CeO_2−x@Dopa demonstrated less efficiency in DPPH^· scavenging (%radical scavenging activity 13% versus 42% for CeO_2−x@Cit before dopamine treatment at 33 μM DPPH^· and 0.13 mg/mL loading of NPs), while it markedly reduced intracellular ROS levels (ROS production 35% compared to 66% of CeO_2−x@Cit before dopamine treatment with respect to control—p < 0.001 and p < 0.01, respectively). While steric hindrance from the dopamine-derived polymer layer limited direct electron transfer from CeO_2−x NP surface to DPPH^·, within cells the presence of o-quinone groups contributed with CeO_2−x NPs to break the autoxidation chain of organic substrates, enhancing the antioxidant activity. The functionalization of NPs with o-quinone structures represents a valuable approach to increase the inherent antioxidant properties of CeO_2−x NPs, enhancing their effectiveness in biological systems by promoting additional redox pathways. Full article

Accurate modeling of product lifetimes is vital in reliability analysis and engineering to ensure quality and maintain competitiveness. This paper proposes the progressively randomly censored Maxwell distribution, which incorporates both progressive Type-II and random censoring within the Maxwell distribution framework. The model allows for the planned removal of surviving units at specific stages of an experiment, accounting for both deliberate and random censoring events. It is assumed that survival and censoring times each follow a Maxwell distribution, though with distinct parameters. Both frequentist and Bayesian approaches are employed to estimate the model parameters. In the frequentist approach, maximum likelihood estimators and their corresponding confidence intervals are derived. In the Bayesian approach, Bayes estimators are obtained using an inverse gamma prior and evaluated through a Markov Chain Monte Carlo (MCMC) method under the squared error loss function (SELF). A Monte Carlo simulation study evaluates the performance of the proposed estimators. The practical relevance of the methodology is demonstrated using a real data set. Full article

Ultra-high-molecular-weight polyethylene (UHMWPE) is a pivotal material in engineering and biomedical applications due to its exceptional mechanical strength, wear resistance, and impact performance. However, its extreme melt viscosity, caused by extensive chain entanglements, severely limits processability via conventional melt-processing techniques. Recent advances in catalytic synthesis have enabled the production of disentangled UHMWPE (dis-UHMWPE), which exhibits enhanced processability while retaining superior mechanical properties. Notably, heterogeneous catalytic systems, utilizing supported fluorinated bis (phenoxy-imine) titanium (FI) catalysts, polyhedral oligomeric silsesquioxanes (POSS)-modified Z-N catalysts, and other novel catalysts, have emerged as promising solutions, combining structural control with industrial feasibility. Moreover, optimizing polymerization conditions further enhances chain disentanglement while maintaining ultra-high molecular weights. These systems utilize nanoscale supports and ligand engineering to spatially isolate active sites, tailor the chain propagation/crystallization kinetics, and suppress interchain entanglement during polymerization. Furthermore, characterization techniques such as melt rheology and differential scanning calorimetry (DSC) provide critical insights into chain entanglement, revealing distinct reorganization kinetics and bimodal melting behavior in dis-UHMWPE. This development of hybrid catalytic systems opens up new avenues for solid-state processing and industrial-scale production. This review highlights recent advances concerning interaction between catalyst design, polymerization control, and material performance, ultimately unlocking the full potential of UHMWPE for next-generation applications. Full article

The growing consumption of oil and gas resources and the increasing difficulty of extraction have created major challenges for traditional manufacturing and maintenance, particularly in the timely supply of critical components, customized production, and complex structure fabrication. Additive manufacturing (AM) technology, with its high design freedom, precision, and rapid prototyping, provides new approaches to address these issues. However, systematic reviews of related efforts are scarce. This paper reviews the applications and progress of metal and non-metal AM technologies in oil and gas extraction and gathering engineering, focusing on the just-in-time (JIT) manufacturing of failed components, the manufacturing and repair of specialized equipment and tools for oil and gas extraction and gathering, and artificial core and reservoir geological modeling fabrication. AM applications in this field remain exploratory and face challenges with regard to their standards, supply chains, materials, and processes. Future research should emphasize developing materials and processes for extreme conditions, optimizing process parameters, establishing standards and traceability systems, and integrating AM with digital design and reverse engineering to support efficient, safe, and sustainable industry development. This work aims to provide a reference for advancing AM research and engineering applications in the oil and gas sector. Full article

The development of interoperable and reusable information models is a key challenge for digitalization in manufacturing domains with heterogeneous and complex process chains. Ensuring seamless data exchange requires the standardization of both data syntax and semantics, while maintaining compatibility with existing industry standards. This paper presents a methodology for deriving standardizable and generalizable OPC UA information models tailored to domains with high process variability and interdisciplinary requirements. The methodology integrates system analysis, parameter mapping, and the development of modular submodels, supported by expert input and validation. It emphasizes the reuse and extension of existing OPC UA Companion Specifications to reduce complexity, avoid redundancy, and enable long-term standardization. The approach is exemplified by its application to battery cell production, an emerging manufacturing domain combining process and mechanical engineering with continuous and discrete processes. Its high degree of heterogeneity and lack of domain-specific standards pose significant challenges for model development. Through iterative expert workshops and structured model validation, a dedicated and transferable OPC UA framework is created. The resulting layered model structure combines a cross-industry standard with newly developed, process-aware model elements. This enables both broad applicability and the depth required for complex production environments, while supporting use cases such as traceability, regulatory reporting (e.g., EU Battery Passport), and process optimization. The resulting model improves interoperability, transparency, and data integration, offering a scalable blueprint for other complex manufacturing sectors. Full article

Despite growing interest in integrating Lean Construction (LC) and Building Information Modeling (BIM) to advance sustainability in the Architecture, Engineering, and Construction (AEC) industry, research remains fragmented and lacks a unified implementation framework. This study bridges this gap by conducting a systematic literature review (2010–2024) of 96 journal articles to (1) analyze research trends in BIM-LC integration; (2) evaluate its benefits for sustainable built environments; and (3) identify barriers to adoption. A key contribution is the development of a novel four-dimensional BIM-LC integration framework, encompassing information integration, supply chain management, waste management, and life cycle management, which synergizes LC principles with BIM’s technical capabilities to reduce waste, enhance resource efficiency, and support carbon neutrality goals. The findings reveal that while BIM-LC integration significantly improves construction productivity and reduces environmental impacts, technical challenges in data interoperability and fragmented lifecycle management persist. Actionable solutions are further proposed, including semantic model standardization, AI-driven supply chain resilience, and circular economy integration. This framework provides both scholars and practitioners with a roadmap to advance BIM-LC adoption for sustainable construction. Full article

Microelement deficiencies, often termed “hidden hunger”, represent a significant global health challenge. Optimal human health relies on adequate dietary intake of essential microelements, including selenium (Se), zinc (Zn), copper (Cu), boron (B), manganese (Mn), molybdenum (Mo), iron (Fe), nickel (Ni), and chlorine (Cl). In recent years, there has been a growing focus on vitality and longevity, which are closely associated with the sufficient intake of essential microelements. This review focuses on these nine elements, whose bioavailability in the food chain is critically determined by their geochemical behavior in soils. There is a necessity for an understanding of the sources, soil–plant transfer, and plant uptake mechanisms of these microelements, with particular emphasis on the influence of key soil properties, including pH, redox potential, organic matter content, and mineral composition. There is a dual challenge of microelement deficiencies in agricultural soils, leading to inadequate crop accumulation, and the potential for localized toxicities arising from anthropogenic inputs or geogenic enrichment. A promising solution to microelement deficiencies in crops is biofortification, which enhances nutrient content in food by improving soil and plant uptake. This strategy includes agronomic methods (e.g., fertilization, soil amendments) and genetic approaches (e.g., marker-assisted selection, genetic engineering) to boost microelement density in edible tissues. Moreover, emphasizing the need for advanced predictive modeling techniques, such as ensemble learning-based digital soil mapping, enhances regional soil microelement management. Integrating machine learning with digital covariates improves spatial prediction accuracy, optimizes soil fertility management, and supports sustainable agriculture. Given the rising global population and the consequent pressures on agricultural production, a comprehensive understanding of microelement dynamics in the soil–plant system is essential for developing sustainable strategies to mitigate deficiencies and ensure food and nutritional security. This review specifically focuses on the bioavailability of these nine essential microelements (Se, Zn, Cu, B, Mn, Mo, Fe, Ni, and Cl), examining the soil–plant transfer mechanisms and their ultimate implications for human health within the soil–plant–human system. The selection of these nine microelements for this review is based on their recognized dual importance: they are not only essential for various plant metabolic functions, but also play a critical role in human nutrition, with widespread deficiencies reported globally in diverse populations and agricultural systems. While other elements, such as cobalt (Co) and iodine (I), are vital for health, Co is primarily required by nitrogen-fixing microorganisms rather than directly by all plants, and the main pathway for iodine intake is often marine-based rather than soil-to-crop. Full article

In the context of global climate change and the deepening of ecological civilization construction, forestry, as an ecological security barrier and green economic engine, faces many challenges to the enhancement of its ecological total factor productivity in the traditional development model. As a new type of production factor, the data factor provides a new path to crack the bottleneck of forestry eco-efficiency improvement. Based on China’s provincial annual panel data from 2014 to 2022, this study systematically examines the impact and mechanism of data factors on forestry ecological total factor productivity by using the SBM-GML model and dual machine learning model. It was found that data factors have a significant contribution to forestry ecological total factor productivity, a conclusion that passes a series of robustness tests and endogeneity tests. The analysis of the mechanism shows that the data factor enhances the total factor productivity of forestry ecology mainly through three paths: promoting the progress of forestry technology and promoting the rationalization and advanced structure of the forestry industry. Further analysis showed that the promotional effect of data elements is more obvious in regions with a high level of green finance development, high intensity of environmental regulation, and strong financial autonomy. It is recommended to systematically promote the in-depth application of data elements in forestry, build a data element-driven innovation system for the whole chain of forestry, and implement regionally differentiated data element-enabling strategies. Full article

Digital agriculture has rapidly developed in the last decade in many countries where the share of agricultural production is a significant part of the total volume of gross production. Digital agroecosystems are developed using a variety of IT solutions, software and hardware tools, wired and wireless data transmission technologies, open source code, Open API, etc. A special place in agroecosystems is occupied by electronic payment technologies and blockchain technologies, which allow farmers and other agricultural enterprises to conduct commodity and monetary transactions with suppliers, creditors, and buyers of products. Such ecosystems contribute to the sustainable development of agriculture, agricultural engineering, and management of production and financial operations in the agricultural industry and related industries, as well as in other sectors of the economy of a number of countries. The introduction of crypto solutions in the agricultural sector is designed to create integrated platforms aimed at helping farmers manage supply lines or gain access to financial services. At the same time, there are risks of illegal use of computing power for cryptocurrency mining—cryptojacking. This article offers a thorough risk assessment of cryptojacking attacks on endpoint systems, focusing on identifying critical vulnerabilities within IT infrastructures and outlining practical preventive measures. The analysis examines key attack vectors—including compromised websites, infected applications, and supply chain infiltration—and explores how unauthorized cryptocurrency mining degrades system performance and endangers data security. The research methodology combines an evaluation of current cybersecurity trends, a review of specialized literature, and a controlled experiment simulating cryptojacking attacks. The findings highlight the importance of multi-layered protection mechanisms and ongoing system monitoring to detect malicious activities at an early stage. Full article

Public health crises triggered by viral infections pose severe threats to individual health and disrupt global socioeconomic systems. Against the backdrop of global pandemics caused by highly infectious diseases such as COVID-19 and Ebola virus disease (EVD), the development of innovative prevention and treatment strategies has become a strategic priority in the field of biomedicine. Neutralizing antibodies, as biological agents, are increasingly recognized for their potential in infectious disease control. Among these, nanobodies (Nbs) derived from camelid heavy-chain antibodies exhibit remarkable technical advantages due to their unique structural features. Compared to traditional neutralizing antibodies, nanobodies offer significant cost-effectiveness in production and enable versatile administration routes (e.g., subcutaneous injection, oral delivery, or aerosol inhalation), making them particularly suitable for respiratory infection control and resource-limited settings. Furthermore, engineered modification strategies—including multivalent constructs, multi-epitope recognition designs, and fragment crystallizable (Fc) domain fusion—effectively enhance their neutralizing activity and suppress viral immune escape mechanisms. Breakthroughs have been achieved in combating pathogens such as the Ebola virus and SARS-CoV-2, with mechanisms involving the blockade of virus–host interactions, induction of viral particle disintegration, and enhancement of immune responses. This review comprehensively discusses the structural characteristics, high-throughput screening technologies, and engineering strategies of nanobodies, providing theoretical foundations for the development of novel antiviral therapeutics. These advances hold strategic significance for addressing emerging and re-emerging infectious diseases. Full article

Silicon carbide (SiC) materials have demonstrated promising application prospects in modern manufacturing due to their outstanding physical and chemical properties. With its process flexibility and formation feasibility, binder jetting 3D printing technology has become a crucial technical approach to meet the demand for mass production of complex, high-performance SiC components. Addressing the technical challenges of traditional manufacturing techniques in achieving high-quality, complex-shaped SiC components, this paper systematically reviews the application of binder jetting 3D printing technology in fabricating high-quality SiC-based ceramic components, with a particular focus on the regulation of key process parameters affecting SiC green body formation quality and the optimization of post-densification processes. Firstly, this paper elaborates on the powder pretreatment, green part formation process, and post-processing chain involved in this technology, establishes an evaluation index system for formation quality, and provides research directions for rapid prototyping of SiC powders. Secondly, it provides an in-depth analysis of the influence patterns of jetting parameters (e.g., jetting conditions, powder characteristics, binder properties) and various post-processing techniques on the quality of SiC-based components, along with optimization methods to enhance the dimensional accuracy and mechanical properties of 3D-printed SiC components. Furthermore, this paper systematically summarizes advanced characterization methods for evaluating formation quality and demonstrates the technology’s application potential across multiple industrial fields through representative engineering cases. Finally, it predicts the future development trends of this technology and discusses potential application expansion directions and key scientific issues in current research, aiming to provide theoretical references for promoting in-depth development of this technology. Full article

This study investigates the impact of hydroxyapatite (HA) nanoparticles (NPs) on the cellular responses of poly(L-lactide-co-ε-caprolactone) (PLCL) scaffolds in bone tissue engineering applications. Three types of PLCL scaffolds were fabricated, varying in HANPs content. Saos-2 osteoblast-like cells (OBs) and THP-1-derived osteoclast-like cells (OCs) were co-cultured on the scaffolds, and cell proliferation was assessed using the MTS assay. The amount of double-stranded DNA (dsDNA) was quantified to evaluate cell proliferation. Expression levels of OBs and OCs markers were analyzed via quantitative polymerase chain reaction (qPCR) and the production of Collagen type I was visualized using confocal microscopy. Additionally, enzymatic activity of alkaline phosphatase (ALP) and tartrate-resistant acid phosphatase (TRAP or ACP5) was measured to assess OB and OC function, respectively. Interestingly, despite the scaffold’s structured character supporting the growth of the Saos-2 OBs and THP-1-derived OCs coculture, the incorporation of HANPs did not significantly enhance cellular responses compared to scaffolds without HANPs, except for collagen type I production. These findings suggest the need for further investigation into the potential benefits of HANPs in bone tissue engineering applications. Nevertheless, our study contributes valuable insights into optimizing biomaterial design for bone tissue regeneration, with implications for drug screening and material testing protocols. Full article

Rare-earth elements (REEs) are strategic resources that have been extensively utilized in industrial manufacturing, aerospace engineering, and defense technology. Beyond their technological applications, REEs have been demonstrated to enhance agricultural productivity through growth promotion mechanisms in various crops, leading to their recognition as valuable trace element fertilizers in modern farming practices. Consequently, REEs have been increasingly introduced into ecosystems, where they are continuously accumulated in soil and transmitted into food chains, resulting in REE pollution, which has become a significant environmental concern. However, the regulatory mechanisms controlling REE contamination are not well understood. In recent years, the environmental impacts of REEs have attracted increasing attention, especially in their pollution mitigation from industrial and agricultural REE emissions. Bioremediation is regarded as a promising method for contaminated soil treatment. The application of plants and microorganisms to REE-polluted environments has been explored as an emerging research field that combines the synergistic advantages of plant rhizospheric microorganisms and vegetation systems. The combination of phytoremediation and microbial remediation approaches has been shown to enhance soil health restoration, thereby improving the purification efficiency of REE-contaminated soil. This paper, citing 179 references, reviews the roles of plants, microorganisms, and plant–microbe interactions in REE-contaminated soil remediation, and summarizes the available practical methods with which to address REE pollution and the fundamental mechanisms involved. Full article