Artificial intelligence, particularly machine learning, has profoundly reshaped drug discovery, addressing longstanding challenges such as exorbitant costs and protracted timelines. Conventional approaches often exceed $2.6 billion per drug over 12-15 years, with attrition rates nearing 90%; AI mitigates these through advanced target identification, high-throughput virtual screening, and generative molecule design. The present review synthesizes pivotal studies of several years drawn from PubMed, Scopus, and leading journals, including ACS Omega and Nature Reviews. It encompasses supervised quantitative structure-activity relationship models, neural networks, graph convolutional networks, and generative adversarial networks for de novo drug design. Emphasis is placed on machine learning's capacity to process vast omics and cheminformatics datasets, with critical attention to how data quality, measurement uncertainty, and analytical method variability fundamentally constrain predictive accuracy. In practice, AI empowers scientists by automating hypothesis generation, exemplified by AlphaFold's structural predictions and enabling early toxicity forecasting or drug repurposing, yet these computational advances remain dependent on rigorous experimental validation through orthogonal analytical techniques. A distinctive contribution of this review lies in its systematic integration of analytical chemistry as the foundational discipline underpinning reliable AI predictions. We present a conceptual framework, the Analytical Integrity Spectrum, that traces the bidirectional relationship between analytical measurements and computational models, emphasizing how measurement uncertainty, data quality, and experimental validation collectively determine the trustworthiness of AI-driven discoveries. The chemistry-focused synthesis distinguishes the present work from computational reviews by critically examining representative case studies of AI-discovered compounds, including their molecular structures, scaffolds, and experimental outcomes. This review provides a tangible assessment of AI's impact on medicinal chemistry. The review further examines AI's emerging application to climate-resilient supply chains, forecasting disruptions from environmental events while emphasizing the analytical monitoring essential for maintaining pharmaceutical quality during transport. Persistent challenges, including dataset biases, activity cliff insensitivity, and validation uncertainty, are traced to their analytical origins. Future prospects encompass federated learning, quantum-accelerated simulations, and standardized analytical data formats that preserve measurement integrity for machine learning. Ultimately, AI equips researchers with transformative tools for accelerated, equitable therapeutic innovation, provided that computational predictions remain grounded in the experimental reality that analytical chemistry provides.
As a classical prescription, Wuwei Xiaodu Decoction (WWXDD) () is composed of five medicinal components: Lonicerae Japonicae Flos, Taraxaci Herba, Chrysanthemi Indici Flos, Violae Herba, and Semiaquilegiae Radix. Originating from the Qing Dynasty, WWXDD has been widely employed in Traditional Chinese Medicine (TCM) for treating inflammatory diseases. Although numerous studies have explored various aspects of WWXDD, few comprehensive reviews have systematically synthesized its ethnopharmacological basis, phytochemistry, pharmacology, and clinical applications, which hinders the further application and commercialization of WWXDD. This review aims to provide a comprehensive summary of the traditional theory, chemical composition, pharmacological activity, and clinical evidence related to WWXDD, with a focus on current challenges and future perspectives. The literature was systematically searched in databases including Web of Science, PubMed, Scopus, and China National Knowledge Infrastructure (CNKI). The search period covered publications from 2013 to 2025. Keywords included "Wuwei Xiaodu Decoction", "WWXDD", "traditional Chinese medicine", "phytochemistry", "pharmacology", and "clinical application". Original research articles, reviews, and clinical studies relevant to the composition, pharmacological activities, quality control, and clinical applications of WWXDD were included. Duplicates, unrelated studies, and articles lacking sufficient methodological information were excluded. Chemical structures were drawn using ChemDraw 23, and the graphical abstract and schematic illustrations were created using BioRender and PowerPoint. This review firstly summarized the progress of the chemical constituents of WWXDD and discussed the advanced methods in monitoring quality of WWXDD and its herbal ingredients. Meanwhile, the attribution of each herb in WWXDD provides some theoretical basis for its efficacy. Pharmacological investigations reveal that WWXDD exhibits anti-inflammatory, anticancer, and antibacterial properties, attributable to its constituent herbs. Clinically, it has demonstrated efficacy in managing facial acne and preventing postoperative infections. Finally, it is important to note in WWXDD use that even though there is no toxicity, most drugs are cold in nature, so it is important to pay attention to the people for whom the use is contraindicated. Through systematic investigation of WWXDD's herbal components, this study enhances the mechanistic understanding of its therapeutic actions. Both preclinical and clinical evidence underscores its potential in managing complex diseases. On this basis, we summarize an actionable compound-level quality-control framework (chemical fingerprinting/multi-component quantification-spectrum-effect and bioactivity consistency-mutual confirmation with mechanistic and clinical evidence), and highlight that standardization and formula-level indicators remain key bottlenecks. In this review, current issues are discussed to inform and inspire subsequent research of WWXDD and other classical prescriptions.
Bupleurum marginatum Wall. (B. marginatum) has a long history of use as a traditional medicine among Chinese ethnic minorities. It is characterized by a pungent and bitter taste, slightly cold in nature, and is associated with the liver, gallbladder, and lung meridians. Its functions include releasing the exterior and harmonizing the interior, soothing the liver and relieving depression, as well as uplifting middle qi. This review comprehensively reviews the traditional applications, chemical constituents, pharmacological effects, and quality control of Bamboo-leaf Bupleurum, and provides an outlook on future research directions. The literature for this review was compiled from two main sources: authoritative texts in traditional medicine (Diannan Bencao, Bencao Gangmu, Dictionary of Chinese Ethnic Medicine) and major scientific databases (PubMed, Web of Science, CNKI). Using keywords including "Bupleurum marginatum" and "Dian Chaihu" elevant pharmacological, clinical, and ethnomedical studies were identified and subsequently subjected to critical analysis. B. marginatum is a traditional Chinese medicinal herb with a bitter and pungent taste, slightly cold in nature, and is associated with the liver and gallbladder meridians. Its functions include harmonizing the exterior and interior, soothing the liver and relieving depression, as well as lifting yang qi. Modern research has confirmed that its core active components include saikosaponins, flavonoids, volatile oils, and polysaccharides, which exhibit well-defined pharmacological effects such as antipyretic, anti-inflammatory, liver-protecting, cholagogue, and immunomodulatory actions. As an important locally customary medicinal material, the practical experience of using the whole herb for medicinal purposes is supported by scientific evidence (the aerial parts are rich in flavonoids). Current quality control focuses on key indicators such as total saikosaponins, total flavonoids, and specific saikosaponins a and d, utilizing techniques like fingerprint chromatograms. Future research should center on the therapeutic evaluation of B. marginatum in specific diseases such as cholecystitis and pharyngitis, elucidate the mechanisms of its bioactive saikosaponins and flavonoids, and integrate organoid models with AI-driven platforms to establish a precision screening system. Furthermore, developing a quality marker system rooted in traditional efficacy will facilitate the precision-oriented research and clinical translation of this medicinal herb. The current research bottlenecks for Bamboo-leaf Bupleurum are primarily reflected in: the lack of a distinctive material basis (high similarity to Bupleurum chinense, absence of exclusive markers), unified quality standards (market confusion, lack of an independent evaluation system), bottlenecks in germplasm resources and cultivation (seed characteristics hindering large-scale cultivation), and insufficient clinical evidence (traditional efficacy lacking support from modern pharmacology and evidence-based medicine). These pain points are interconnected, collectively impeding its transformation from a "locally customary medicinal material" to standardized and precise clinical application. Future research must focus on addressing these core deficiencies. Future research on B. marginatum can deeply integrate technologies such as AI, multi-omics, and knowledge graphs to construct a new data-driven research paradigm. Through AI-enabled intelligent mining of the complex relationships between components and activities, and leveraging multi-omics and knowledge graphs to systematically analyze the "component-target-pathway" interaction network, its traditional efficacy can be scientifically elucidated. Ultimately, the systematic integration of these technologies will drive the transformation of research toward intelligence and precision, providing core momentum for clarifying its unique value and achieving precise clinical application.
Conventional computational methods for modeling chemical and materials systems are limited by system size and timescale, forcing a trade-off between quantum-mechanical accuracy and the sampling needed for realistic observables. Large language and vision foundation models - pre-trained on massive datasets using transformer architectures - have revolutionized many fields. It is thus interesting to ask whether a foundation model - subject to suitable data, parameter scaling and training - could enable learned simulations of chemistry and materials. Here, we review the field of machine-learned interatomic potentials (MLIPs) and posit that scaling up large and diverse chemical and materials datasets and highly expressive architectures using advanced training strategies should result in models that are: more efficient, transferable, robust to out-of-distribution scenarios, and easier to fine-tune to a variety of downstream physical observables than models trained from scratch on small datasets corresponding to specific, targeted atomistic simulation tasks. We provide specific criteria for creating such large-scale MLIP foundation models, coordinated strategies for their development, evaluation and deployment, and highlight potential emergent capabilities that could transform predictive simulations in chemistry and materials science and accelerate discovery across multiple technological domains.
Biomineralization, a process wherein biomolecules precisely regulate inorganic mineral formation, has inspired nature-derived biomineralization strategies widely applied in materials science and biomedicine. In recent years, this approach has gradually made inroads into food science, offering innovative solutions to critical challenges in the food industry, including packaging, processing, safety detection, and nutrient fortification. This article systematically reviews advances in biomineralization strategies, from molecular mechanisms to food applications over the past 25 years, highlighting its contributions in: (1) intelligent packaging, (2) controlled release of functional ingredients, and (3) functional food development. Research demonstrates that the biomineralization approach, leveraging its biocompatibility, structural tunability, and green synthesis characteristics, enhances the mechanical properties and antimicrobial functions of food packaging while optimizing food texture and flavor profiles. Furthermore, organic template-regulated mineralization and physicochemical strategies have opened new avenues for targeted delivery and controlled release of bioactive components/additives. Despite persistent challenges in scaling production and safety evaluation, the deep integration of biomineralization with synthetic biology, nanotechnology, and artificial intelligence has the potential to support the transformation of the food industry toward greater efficiency, automation, and sustainability. This strategy holds significant potential for reshaping food production methodologies and providing interdisciplinary support for precision nutrition and food safety initiatives.
The development of magnetoelectric multiferroic materials, which combine and couple (ferro)magnetism and ferroelectricity in the same material, are discussed from a chemist's perspective. The chemical challenges that must be overcome to combine (ferro)magnetism and ferroelectricity are highlighted and the developments in crystal chemistry that have enabled identification of new multiferroics are outlined. The chemical applications of multiferroic materials are described and open questions that are particularly amenable to chemical solutions are discussed.
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Substitution is a vital strategy for developing high-performance sodium layered oxides (SLOs), which demonstrates great potential for making sodium-ion batteries a viable alternative to lithium-ion batteries. Numerous studies have been conducted on substituted SLOs; however, each substitute exhibits varied effects on the structure and electrochemical performance of the SLOs, and no clear design principles have been established. Clarifying the relationship among substitution, structure and performance is therefore important to enable a rational design strategy for high-performance SLOs. In this Review, the up-to-date substitution guidelines and the current understanding of how substitution affects the structure and electrochemistry in SLOs are discussed, and the site preference and characteristic redox features of different types of substitutes are outlined. The inherent challenges and opportunities for the innovation of better-performing SLOs are summarized, paving the way for accelerating the commercialization of SLO-based sodium-ion batteries and the realization of their applications ranging from electric vehicles to grid energy storage systems.
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Nature showcases extraordinary wisdom through the creation of diverse species, with plants and animals evolving complex adaptive structures to survive in extreme environments. In today's world, where global water resources are increasingly scarce, finding innovative technologies for effective water collection has become an urgent challenge. Fog collection, proven effective in arid and foggy regions, is receiving widespread attention. In particular, biomimetic surfaces, which mimic the fog collection mechanisms found in nature-such as spider silk, desert beetles, and cacti-show immense potential. This study delves into these natural prototypes, uncovering their microstructures and the scientific principles behind their fog collection abilities. Using the theory of interfacial tension, the paper provides a comprehensive explanation of their fog collection mechanisms. Additionally, the article reviews the latest advancements in the manufacturing techniques for biomimetic surfaces and fog collection devices, offering a detailed comparison between single-surface and multi-surface designs in terms of performance. Finally, the paper evaluates the current challenges faced in this field and envisions the future development of this technology, aiming to drive the practical application of next-generation fog collection devices and address the global water crisis.
The repair of soft tissue defects remains a leading clinical challenge for patients with active lifestyles, unintentional falls and injuries, cancer, and age-related diseases. Tissue engineering and 3D printing have been developed over the last decades as strategies to create personalized tissue mimics by precisely depositing biomaterials and cells to fabricate static constructs. However, long-term clinical solutions call for increasing the complexity of engineered models to incorporate bioactive processes that mimic the dynamic nature of human tissues. 4D printing has therefore become a growing strategy for building soft tissue constructs that exert function with time. The critical challenge lies in balancing biologically relevant tissue-specific function with programmable material capabilities in response to environmental stimuli. This review highlights the technological advancements that have improved progress in soft tissue engineering to build complex skin, cardiovascular, nerve, skeletal muscle, and connective tissue constructs. We first discuss mechanisms for 4D material actuation through external stimuli, which, when combined with advanced additive manufacturing tools, can assemble and program responsive tissue mimics. We next address progress in engineering functional soft tissues, which are characterized by tissue type, and discuss their limitations. Finally, the challenges associated with the fabrication of next generation 4D printed soft tissues are defined, and emerging frontiers are highlighted. STATEMENT OF SIGNIFICANCE: Soft tissue regeneration remains a clinical reconstructive challenge due to the hierarchical nature and intricate mechanics of native tissue. While 3D printing is an effective strategy for short-term healing outcomes, most tissues in the human body rely on dynamic properties to support normal physiological function. 4D printing strategies offer improvements in complexity to embed tissue-specific function into bioprinted constructs. Many existing reviews thoroughly cover 4D printing technologies and stimuli; however, their applications in soft tissue engineering toward prototyping functional tissue mimics remain underexplored. This review explores programmable stimuli for 4D printed soft tissues, advancements and limitations in function classified by soft tissue type, and insights and strategies for future challenges to work toward 4D printed functional, engineered soft tissues.
The present study addressed the complex nature of fatigue in soccer, examining its physical, psychological, neuromuscular, and metabolic dimensions. It evaluated the impact of these different types of fatigue on players' performance, highlighting the importance of comprehensive fatigue-management strategies for enhancing performance and reducing injury risk among soccer players. The primary aim of this study was to investigate the effects of various types of fatigue on performance of male soccer players across different competitive levels, through a systematic review and meta-analysis of randomized controlled trials. A total of 37 randomized controlled trials involving male soccer players were included, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to assess the multifaceted impacts of fatigue. Key findings revealed that neuromuscular fatigue had the highest mean effect size (0.63), with substantial consistency across studies (95% CI: 0.45-0.80, I2 = 99.79%). Physical and metabolic fatigue both showed a mean effect size of 0.38, though they differed in variability; metabolic fatigue demonstrated considerable heterogeneity (I2 = 98.73%), reflecting diverse physiological responses, while physical fatigue showed moderate consistency (I2 = 98.20%). Psychological fatigue had a significant impact on performance (mean effect size: 0.57), with variability (I2 = 97.08%) suggesting context-dependent effects. These results underscore the necessity of a multimodal approach that integrates physical, metabolic, neuromuscular, and psychological interventions to optimize soccer performance and mitigate injury risk. Practical implications include the adoption of targeted recovery strategies such as inter-set recovery intervals and whole-body vibration techniques, as well as the implementation of mental resilience and cognitive training to manage psychological fatigue. Such strategies are essential for developing individualized training and recovery protocols that enhance athletic performance and support long-term career sustainability.
Natural food pigments primarily originate from two sources: chemical synthesis and plant-derived production. With the rapid advancement of society and technology, there is a growing demand for environmentally friendly and healthy food options. Consequently, the demand for safe, nontoxic, and sustainable sources of natural pigments has risen sharply. Natural pigments are biosynthesized during the growth and metabolic processes of plant tissues, and compounds derived from these pigments exhibit a wide range of biological activities that are beneficial to human health and disease treatment. However, due to their inherent instability and low abundance, increasing research efforts have been directed toward the bioengineering of natural pigment production. This review classifies natural pigments into five major structural categories: pyrrole, isoprenoids, quinones, phenols, and betalains. Unlike previous reviews that focused on a single pigment component or specific application fields, this review systematically integrates the biosynthetic pathways, synthetic biology strategies, pharmacological activity mechanisms, and application progress in medicine, health care, and cosmetics of natural pigment-containing medicinal materials. It emphasizes their multiple potentials as "functional pigments" in the development of natural medicines. Additionally, the review combines emerging technologies such as metabolic engineering, artificial intelligence (AI)-assisted screening, and biosensing, proposing a cross-disciplinary development path from basic synthesis to high-value applications and demonstrating strong systematicity and a forward-looking nature. It provides a new integrated perspective for innovative research on natural pigment components.
The safe manufacture, transport and use of chemicals - in short, the entire chemistry enterprise - depends on high-quality chemical safety information. That information must be accurate, audience-appropriate, comprehensive and based on data derived from research. The globally harmonized system of classification and labelling has standardized how chemical hazards are determined by manufacturers and then communicated to users through the use of labels and safety data sheets, but it has not been globally adopted. To lower risk to acceptable levels, users of chemicals rely on authoritative information to complete risk assessments. Safety data sheets are important tools, but they are merely a starting point for the risk assessment process - they can be insufficiently detailed, poorly curated and difficult to search. There is also an unrealistic expectation that users have the appropriate competencies to apply the information to risk-based safety principles such as RAMP (recognize hazards, assess risks, minimize risks and prepare for emergencies). The primary emphasis of this article is to raise awareness of persistent challenges with accessing and applying chemical safety information and to present a call to action for key stakeholders and expert groups to address these issues.
The combination of Li-rich layered oxide cathodes and lithium metal anodes enables lithium metal batteries (LMBs) to achieve specific energies exceeding 600 Wh kg-1, which is a crucial threshold requiring the activation of anionic oxygen-redox of cathode. The specific energy is attained owing to oxygen-redox reactions at the cathode and reversible Li plating-stripping at the anode, but these processes also induce distinct failure mechanisms. Structural destabilization at the cathode and anodic dendrite growth cause cell-level failures that impact the lifespan of LMBs more profoundly than material degradation alone. Moreover, the presence of lithium metal anodes obscures the detection of active Li loss, often leading to misinterpretations related to capacity fading and cycle life. This Review examines the progress in realizing 600 Wh kg-1 LMBs and understanding their lifespan failure mechanisms. We discuss the challenges in accurately assessing the lifespan and Li loss pathways of LMBs, and we elucidate the fundamental chemistry mechanisms driving both material-level and cell-level failures. In particular, the electrochemical implications of cell parameters, cell assembly and operating conditions on the lifespan are highlighted. We also outline the gaps in knowledge and advanced techniques required to decipher detailed failure modes for LMBs with oxygen-redox reactions and Li plating-stripping.
The need for environmentally friendly antifouling coatings to inhibit the growth of biofouling which can disrupt the ship's hydrodynamic system, increase fuel consumption, and contribute to exhaust gas emissions has become increasingly urgent since the International Maritime Organization banned the use of Tributyltin-based antifouling coatings in 2008 due to their toxic nature. This article presents a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, which involves the identification, screening, eligibility, and inclusion stages, to examine the structured interrelation between biofouling, ship hydrodynamics, and the role of natural active compounds derived from corals and algae in inhibiting biofouling growth. The analysis of experimental and modeling results concerning biofouling, antifouling coatings, corals, algae, and ship hydrodynamics were analyzed based on selected literature sources. The findings indicate that biofouling can adversely affect a ships hydrodynamic system by increasing resistance due to hull surface roughness and fluid flow imbalances. However, this issue can be mitigated through preventive measures, particularly by applying environmentally friendly antifouling coatings on the ships surface. Several coral and algal species have shown promising potential as antifouling agents. The coral Sarcophyton glaucum and algae species Padina pavonica and Colpomenia sinuosa possess significant natural active compounds with strong antifouling properties, whereas other coral and algal species exhibit varying biological characteristics in inhibiting biofouling growth. Overall, this review emphasizes the substantial potential of corals and algae as natural sources of active compounds for future antifouling agents. Nevertheless, to support their application in marine transportation, continuous research, long-term evaluation, and the development of efficient large-scale production methods are required.
Intermediate filaments (IFs) are central to the mechanical integrity of metazoan cells and play critical roles in various fundamental cellular and multicellular processes, including cell motility, signal transduction, and wound healing. To perform their functions, IF proteins self-assemble into nanoscale biopolymers, each exhibiting unique properties that are finely tuned to their specific roles across different tissue types. However, the 3D structure of IFs has remained largely unresolved due to their intrinsic flexibility and polymorphism. This chapter reviews recent advances in the structural analysis of IFs, with a focus on vimentin IFs (VIFs), which are featuring a helical tube with a central luminal fiber. We discuss how AlphaFold-based modeling, chemical cross-linking data, and cryo-electron microscopy (cryo-EM) reconstructions have been integrated to generate a detailed structural model of VIFs, highlighting key features such as the helical symmetry of the filaments and the nature of the luminal fiber. Additionally, we explore potential sources of IF polymorphism and their implications for the analysis of IF structures.