Search Results (16,830)

Molecular networking (MN) is a novel mass spectrometry data analysis method that has advanced significantly in recent years and has rapidly emerged as a popular technique. By visualizing the connections between structurally similar compounds in mass spectra, MN greatly enhances the efficiency with which harmful substances and bioactive ingredients in cosmetics are screened. In this review, we summarize the principles and main categories of MN technology and systematically synthesize its progress in cosmetic testing applications based on 83 recent studies (2020 to 2025). These applications include screening banned additives, analyzing complex matrix components, and identifying efficacy-related ingredients. We highlight MN’s successful application in detecting prohibited substances, such as synthetic dyes and adulterants, with limits of detection (LOD) as low as 0.1–1 ng/g, even in complex matrices, such as emulsions and colored products. MN-guided isolation has enabled the structural elucidation of over 40 known and novel compounds in the analysis of natural ingredients. We also discuss current challenges, such as limitations in instrument sensitivity, matrix effects, and the lack of cosmetic-specific component databases. Additionally, we outline future prospects for expanding MN’s application scope in cosmetic testing and developing it toward computer-aided intelligence. This review aims to provide valuable references for promoting innovation in cosmetic testing methods and strengthening quality control in the industry. Full article

Data preprocessing and feature engineering play key roles in data mining initiatives, as they have a significant impact on the accuracy, reproducibility, and interpretability of analytical results. This review presents an analysis of state-of-the-art techniques and tools that can be used in data input preparation and data manipulation to be processed by mining tasks in diverse application scenarios. Additionally, basic preprocessing techniques are discussed, including data cleaning, normalisation, and encoding, as well as more sophisticated approaches regarding feature construction, selection, and dimensionality reduction. This work considers manual and automated methods, highlighting their integration in reproducible, large-scale pipelines by leveraging modern libraries. We also discuss assessment methods of preprocessing effects on precision, stability, and bias–variance trade-offs for models, as well as pipeline integrity monitoring, when operating environments vary. We focus on emerging issues regarding scalability, fairness, and interpretability, as well as future directions involving adaptive preprocessing and automation guided by ethically sound design philosophies. This work aims to benefit both professionals and researchers by shedding light on best practices, while acknowledging existing research questions and innovation opportunities. Full article

Diabetic wounds, especially diabetic foot ulcers, pose a major global clinical challenge due to their slow healing and high infection susceptibility. Their typical pathological features include impaired angiogenesis, chronic hypoxia, persistent inflammation, oxidative stress, bacterial colonization, and neuropathy. Traditional treatment methods have limited efficacy, creating an urgent need for innovative therapeutic strategies. In recent years, biomaterials have emerged as a research focus in diabetic wound treatment, owing to their biocompatibility, versatility, and tissue regeneration potential. This article comprehensively reviews the pathological mechanisms of diabetic wounds. It also summarizes the application progress of biomaterials in diabetic wound healing. Over the past decade, researchers have explored the properties, mechanisms of action, and roles of various natural and synthetic biomaterials. These biomaterials include DNA nanomaterials, peptide hydrogels, cells, exosomes, and cytokines. These biomaterials play significant role in promoting angiogenesis, regulating inflammation, inhibiting bacteria, and enhancing cell proliferation and migration. Full article

Camellia oleifera, a member of the Theaceae family and belonging to the Camellia Linn species, is a plant utilized for edible oil production and medicinal value. Its fruit is abundant in various bioactive compounds, including triterpene saponins, flavonoids, lignans, fatty acids, sterols, polysaccharides, and numerous other chemical constituents. Among these, triterpene saponins and flavonoids serve as the primary active ingredients. The pharmacological effects of C. oleifera fruits are diverse, encompassing anti-tumor properties, cardiovascular and cerebrovascular protection, anti-inflammatory, antioxidant activity, lipid-lowering capability, anti-fungal property, and neuroprotective function. In recent years, this area has garnered significant attention from scholars both domestically and internationally. This article reviews the chemical constituents and pharmacological effects of C. oleifera fruits, aiming to provide a comprehensive reference for further research and development. Additionally, it offers a scientific foundation and innovative insights for clinical applications and the identification of relevant bioactive components. Full article

Background: Dementia is a progressive neurodegenerative condition that impairs cognitive functions such as memory, language comprehension, and problem-solving. Assistive technologies can provide vital support at various stages of dementia, significantly improving the quality of life by aiding daily activities and care. However, for these technologies to be effective and widely adopted, a human-centred design (HCD) approach is of consequence for both their development and evaluation. Objectives: This scoping review aims to explore how HCD principles have been applied in the design of assistive technologies for people with dementia and to identify the extent and nature of their involvement in the design process. Eligibility Criteria: Studies published between 2017 and 2025 were included if they applied HCD methods in the design of assistive technologies for individuals at any stage of dementia. Priority was given to studies that directly involved people with dementia in the design or evaluation process. Sources of Evidence: A systematic search was conducted across five databases: Web of Science, JSTOR, Scopus, and ProQuest. Charting Methods: Articles were screened in two stages: title/abstract screening (n = 350) and full-text review (n = 89). Data from eligible studies (n = 49) were extracted and thematically analysed to identify design approaches, types of technologies, and user involvement. Results: The 49 included studies covered a variety of assistive technologies, such as robotic systems, augmented and virtual reality tools, mobile applications, and Internet of Things (IoT) devices. A wide range of HCD approaches were employed, with varying degrees of user involvement. Conclusions: HCD plays a critical role in enhancing the development and effectiveness of assistive technologies for dementia care. The review underscores the importance of involving people with dementia and their carers in the design process to ensure that solutions are practical, meaningful, and capable of improving quality of life. However, several key gaps remain. There is no standardised HCD framework for healthcare, stakeholder involvement is often inconsistent, and evidence on real-world impact is limited. Addressing these gaps is crucial to advancing the field and delivering scalable, sustainable innovations. Full article

Plant-based extracts and elicitors (signaling molecules that activate the fruit’s innate defense responses) have emerged as promising and sustainable alternatives to synthetic chemicals for preserving postharvest fruit quality and extending shelf life. This review provides a comprehensive analysis, uniquely complemented by a bibliometric assessment of the research landscape from 2005 to 2025, to identify key trends and effective solutions. This review systematically examined the efficacy of various natural compounds including essential oils (complex volatile compounds with potent antimicrobial activity such as lemongrass and thyme), phenolic-rich botanical extracts like neem and aloe vera, and plant-derived elicitors such as methyl jasmonate and salicylic acid. Their preservative mechanisms are multifaceted, involving direct antimicrobial activity by disrupting microbial membranes, potent antioxidant effects that scavenge free radicals, and the induction of a fruit’s innate defense systems, enhancing the activity of enzymes like superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD). Applications of edible coatings of chitosan or aloe vera gel, nano-emulsions, and pre- or postharvest treatments effectively reduce decay by Botrytis cinerea and Penicillium spp.), delay ripening by suppressing ethylene production, minimize water loss, and alleviate chilling injury. Despite their potential, challenges such as sensory changes, batch-to-batch variability, regulatory hurdles, and scaling production costs limit widespread commercialization. Future prospects hinge on innovative technologies like nano-encapsulation to improve stability and mask flavors, hurdle technology combining treatments synergistically, and optimizing elicitor application protocols. This review demonstrates the potential of continued research and advanced formulation to create plant-based preservatives, that can become integral components of an eco-friendly postharvest management strategy, effectively reducing losses and meeting consumer demands for safe, high-quality fruit. Full article

Therapy with chimeric antigen receptor (CAR)-T cells has revolutionized the treatment of hematological malignancies. However, their application in solid tumors remains a formidable challenge due to obstacles such as the immunosuppressive tumor microenvironment, tumor heterogeneity, and limited T cell persistence. Although second- and third-generation CAR-T cells have shown restricted efficacy in clinical trials, next-generation strategies—including cytokine-armored CAR-T cells (e.g., IL-15, IL-7/CCL19), logic-gated systems, and localized delivery approaches—demonstrate promising potential to overcome these limitations. This review examines the major barriers impeding CAR-T cell efficacy in solid tumors, evaluates clinical outcomes from conventional CAR constructs, and highlights innovative strategies being tested in recent clinical trials. Key advances discussed include the use of dominant-negative receptors (e.g., TGFβRII) to combat immunosuppression and the co-expression of bispecific T cell engagers (BiTEs) to address antigen escape. Full article

Fish have become increasingly prominent as experimental models due to their unique capacity to bridge basic biological research with translational applications across diverse scientific disciplines. Their biological traits, such as external fertilization, high fecundity, rapid embryonic development, and optical transparency, facilitate in vivo experimentation and real-time observation, making them ideal for integrative research. Species like zebrafish (Danio rerio) and medaka (Oryzias latipes) have been extensively validated in genetics, toxicology, neuroscience, immunology, and pharmacology, offering robust platforms for modeling human diseases, screening therapeutic compounds, and evaluating environmental risks. This review explores the multidisciplinary utility of fish models, emphasizing their role in connecting molecular mechanisms to clinical and environmental outcomes. We address the main species used, highlight their methodological advantages, and discuss the regulatory and ethical frameworks guiding their use. Additionally, we examine current limitations and future directions, particularly the incorporation of high-throughput omics approaches and real-time imaging technologies. The growing scientific relevance of fish models reinforces their strategic value in advancing cross-disciplinary knowledge and fostering innovation in translational science. Full article

The Never-in-Mitosis A-Related Kinase (NEK) family is an important, yet largely understudied, family of protein kinases involved in the regulation of a variety of critical cellular processes. Consequently, dysregulation of NEK function has been linked to the etiology and progression of several disorders, including cancer, ciliopathies, neurodegenerative disorders, inflammatory disorders, and other pervasive diseases. In this review, we have summarized recent findings to provide an overview of the NEK family and their diverse functions within various cellular contexts. In parallel, we have highlighted the emerging roles of NEK family members in human health, identifying potential therapeutic targets within the NEK family and exploring their potential for future clinical applications. Finally, we have addressed ongoing challenges and emerging research directions in this rapidly evolving field, aiming to pave the way for future discoveries and innovations. Full article

Dams are currently confronted with severe risks from frequent extreme climates and expanding aging deterioration, with traditional mitigation measures struggling to balance efficient prevention/control and long-term management. As an innovative solution, fiber-reinforced polymer (FRP) composites support improved dam safety governance. To address the lack of systematic integration in existing dam-related studies, this paper promotes the development of an FRP in the dam field by comprehensively analyzing and summarizing the material properties, interfacial bonding properties of the FRP, as well as the flexural and compressive characteristics of FRP bar–concrete members and FRP sheet–concrete members while systematically organizing their practical engineering application cases. It also explores the FRP’s potential in hydraulic structures and suggests its wider application therein based on the FRP’s superior properties. Full article

This paper offers an innovative exploration of variational informational principles by incorporating complexification and studying norms of arbitrary order, thereby surpassing the limitations of the conventional $L^2$ norm. For years, variational principles have been vital for deriving fundamental results in both physics and information theory; however, our proposed framework represents a significant advancement by utilizing complex variables to enhance our understanding of information measures. By employing complex numbers, we introduce a sophisticated structure that captures phase information, thereby significantly improving the potential applicability and scope of variational principles. The inclusion of norms of arbitrary order further expands the scope of optimization problems in information theory, leading to the potential for more creative solutions. Our findings indicate that this extended framework not only maintains the essential characteristics of traditional variational principles but also reveals valuable insights into the complex interplay between complexity, information, and optimization. We conclude with a thoughtful discussion of potential applications and future research directions, emphasizing the transformative impact that complexified variational principles, together with norms of arbitrary order, could have on the study of quantum dynamics. Full article

There is an urgent need to develop new anti-inflammatory compounds due to the versatility of their applications and the side effects associated with currently used nonsteroidal anti-inflammatory drugs (NSAIDs). Compounds containing the 1,2-benzothiazine 1,1-dioxide moiety in their structure have demonstrated a broad range of pharmacological activities, among which the anti-inflammatory effect is the most well-documented. Numerous in vivo studies have confirmed the effectiveness of these compounds in alleviating pain and inflammation. In turn, in vitro studies have shown that 1,2-benzothiazine derivatives exhibit anti-inflammatory activity not only through the classical mechanism involving the inhibition of cyclooxygenase (COX) but also through modern, more complex mechanisms. These innovative mechanisms include inhibition of microsomal prostaglandin E₂ synthase-1 (mPGES-1) or 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), suppression of pro-inflammatory cytokines, and modulation of kinase activity involved in inflammatory processes. Importantly, many studies have shown that some new 1,2-benzothiazine 1,1-dioxide derivatives exhibit even stronger anti-inflammatory activity than traditional NSAIDs, making them promising candidates for new drugs targeting inflammation-related diseases. This paper presents a review of 1,2-benzothiazine 1,1-dioxide derivatives investigated for their anti-inflammatory activity in both in vivo and in vitro models, taking into account their various mechanisms of action and potential directions for further research. Full article

In advanced manufacturing, nanotechnology, and aerospace fields, the demand for precision is increasing. Driven by this demand, multi-degree-of-freedom grating encoders have become particularly crucial in high-precision displacement and angle measurement. Over the years, these encoders have evolved from one-dimensional systems to complex multi-degree-of-freedom measurement solutions that can achieve real-time synchronization. There can also be high-resolution feedback. Its structure is relatively compact, the signal output is also very stable, and the integration degree is high. This gives it a significant advantage in complex measurement tasks. Recently, there have been new developments. The functions of grating encoders in terms of principle, system architecture, error modeling, and signal processing strategies have all been expanded. For instance, accuracy can be improved by integrating multiple reading-heads, while innovative strategies such as error decoupling and robustness enhancement have further advanced system performance. This article will focus on the development of two-dimensional, three-dimensional and multi-degree-of-freedom grating encoders, exploring how the measurement degrees of freedom have evolved, and emphasizing key developments in spatial decoupling, error compensation and system integration. At the same time, it will also discuss some challenges, such as error coupling, system stability and intelligent algorithms for integrating real-time error correction. The future of grating encoders holds great potential. Their applications in precision control, semiconductor calibration, calibration systems, and next-generation intelligent manufacturing technologies can bring promising progress to both industrial and scientific fields. Full article

Photocatalytic membrane reactors (PMRs), which combine photocatalysis with membrane separation, represent a pivotal technology for sustainable water treatment and resource recovery. Although extensive research has documented various configurations of photocatalytic-membrane hybrid processes and their potential in water treatment applications, a comprehensive analysis of the interrelationships among reactor architectures, intrinsic physicochemical mechanisms, and overall process efficiency remains inadequately explored. This knowledge gap hinders the rational design of highly efficient and stable reactor systems—a shortcoming that this review seeks to remedy. Here, we critically examine the connections between reactor configurations, design principles, and cutting-edge applications to outline future research directions. We analyze the evolution of reactor architectures, relevant reaction kinetics, and key operational parameters that inform rational design, linking these fundamentals to recent advances in solar-driven hydrogen production, CO₂ conversion, and industrial scaling. Our analysis reveals a significant disconnect between the mechanistic understanding of reactor operation and the system-level performance required for innovative applications. This gap between theory and practice is particularly evident in efforts to translate laboratory success into robust and economically feasible industrial-scale operations. We believe that PMRs will realize their transformative potential in sustainable energy and environmental applications in future. Full article

In lithium-ion battery charging, balancing charging speed with efficiency and state of health (SOH) is paramount. First, a multi-state electric-thermal-aging coupling model was developed to accurately reflect battery operating conditions. Second, a voltage-based multi-stage constant current-constant voltage (VMCC-CV) strategy was implemented, incorporating an innovative V-SOC-R_int conversion mechanism—integrating voltage, state of charge (SOC), and internal resistance—to effectively mitigate thermal buildup during transitions. To optimize the VMCC-CV currents, an innovative enhancement was applied to the moth-flame optimization (MFO) algorithm, demonstrating superior performance over its traditional counterpart across diverse charging scenarios. Finally, three practical strategies were devised: rapid charging, multi-objective balanced charging, and enhanced safety performance charging. Relative to the manufacturer’s 0.75 C-CCCV protocol, the balanced strategy significantly accelerates charging, reducing time by 34.11%, while sustaining 93.54% efficiency and limiting SOH degradation to 0.006856%. Compared to conventional CCCV methods, the proposed approach offers greater versatility and applicability in varied real-world scenarios. Full article