The application of chaos theory has positive results in different fields of science. Its nonlinear modeling properties and its vision of dynamic systems have enabled it to capture complex relationships in fields such as physics, financial econometrics, social systems and mathematical demography. This paper reviews the implication of chaos theory in the medical sciences. We carried out a systematic literature review under Cochrane’s international standards. A search strategy was executed with indexed terms (MeSH, DeCS and Emtree) that varied according to each database (Embase, MEDLINE, SciELO, LILACS). The PROSPERO registration number was CRD42023491407. In total, 2598 articles were retrieved, of which 20 were included. Algorithmic applications of chaotic systems were diverse. The medical fields with the largest studies were cardiology, neurology and oncology. The most used software was Matlab, however, in all cases, except one, we did not find open-source codes related to the studies. We found a wide heterogeneity in the studies reviewed, and this was reflected in the scope of research results. While some papers focus on proving the existence of chaotic behavior or understanding the nature of the phenomena being studied, others propose practical implications, such as in prescribing medicines and organizing health units. Not applicable. The online version contains supplementary material available at 10.1186/s42490-026-00111-0.
Parkinson disease (PD) is a progressive neurodegenerative disorder with a rapidly growing global prevalence. Current clinical assessments, such as the Unified Parkinson Disease Rating Scale, are limited by subjectivity and episodic application, creating a need for continuous, objective monitoring solutions. While previous reviews have often focused on single technologies, there is a growing trend toward integrating multiple data sources to provide a more holistic view of PD. This scoping review synthesizes progress in multimodal intelligent monitoring systems for PD, focusing on the quantification of motor and nonmotor symptoms, algorithm development, and the clinical translation of remote monitoring platforms. Furthermore, we propose a novel heuristic framework (Care-Platform Transformation in PD [CPT-PD]) that provides a forward-looking conceptual design for integrating these technologies into clinical workflows, demonstrating promising potential for future development. A targeted literature search was conducted on August 15, 2025, in PubMed, Web of Science, and China National Knowledge Infrastructure for research published between January 1, 2019, and December 31, 2024. The final search was rerun on January 22, 2026, solely to ensure completeness of coverage for this time window; no articles published after December 31, 2024, were included. Wearable sensors (n=9) demonstrated high concordance with clinical scores in validation studies (eg, 99% for tremor detection), while computer vision (n=6) achieved moderate agreement with clinician ratings in controlled assessments (intraclass correlation coefficient 0.74 for bradykinesia). For nonmotor symptoms, intelligent systems (n=7) demonstrated sleep disturbance detection with up to 92.9% accuracy and autonomic dysfunction monitoring (n=7) via heart rate variability (area under the curve 0.90) and voice analysis (94.55% accuracy). Algorithm studies (n=16) explored single-modality feature extraction and cross-modal fusion, with emerging applications in federated learning. Remote platforms (n=22) improved medication adherence (172/201, 85.6%) and reduced outpatient visits (by 29% in one study). A heuristic CPT-PD framework was proposed to integrate key components of diagnosis, treatment, and management. Collectively, these advancements demonstrate the technical viability and clinical benefits of shifting from episodic, subjective assessments toward a data-driven, continuous, and multimodal approach to PD management. While current evidence largely reflects multisensor systems rather than deeply integrated multimodal platforms, the field holds promise for advancing toward genuine data fusion that could further improve clinical decision-making. Persistent challenges include fragmented symptom focus, algorithmic heterogeneity, and barriers to adoption among older adults. Future efforts should build on integrated frameworks such as CPT-PD to develop patient-centered ecosystems, ultimately enabling precision medicine in PD management.
Melanoma is a highly aggressive malignancy, and conventional therapies have limited efficacy in metastatic cases. The advent of immune checkpoint inhibitors (ICIs) has significantly improved patient prognosis. However, challenges such as heterogeneous responses, resistance, and immune-related adverse events (irAEs) necessitate reliable tools for early efficacy prediction and dynamic assessment. As a molecular imaging modality that integrates structural and functional information, Positron Emission Tomography/Computed Tomography (PET/CT)-particularly through 18F-fluorodeoxyglucose (18F-FDG) metabolic imaging-can identify atypical response patterns during immunotherapy, including pseudoprogression, hyperprogression, and immune-detached responses (iDRs). It also enables accurate evaluation of therapeutic efficacy using criteria such as PERCIST and PERCIMT. Moreover, PET/CT shows unique value in the early detection of irAEs, with metabolic alterations (e.g., thyroiditis or colitis) preceding clinical symptoms. In recent years, novel probes targeting immune components such as PD-1/PD-L1 and CD8⁺ T cells (Immuno-PET) have further enhanced the capacity for real-time monitoring of the tumor immune microenvironment. PET/CT represents a valuable imaging modality for comprehensive assessment of immunotherapy in melanoma. With continued refinement of response criteria and the development of immune-targeted tracers, PET-based imaging is expected to further facilitate personalized and dynamic immunotherapy strategies.
Euphorbia milii Des Moul is a plant with a long history of use in traditional medicinal and is widely distributed across tropical and subtropical regions. Traditionally, its sap has been used in folk medicine to treat various conditions such as skin inflammations, pain, and boils. To date, it remains a commonly used herbal medicine in clinical practice. This paper systematically reviews the phytochemistry, pharmacology and toxicology of E. milii to assess its therapeutic potential and guide future studies. A comprehensive literature search was performed based on multiple s databases, including Web of Science, ScienceDirect, PubMed, Elsevier, CNKI, VIP, and Wanfang. Additionally, taxonomic databases such as Flora of China and Plants of the World Online (POWO) were consulted to verify the plant's nomenclature and distribution. To date, 85 compounds have been identified from E. milii, comprising 74 diterpenoids, 6 triterpenoids, 2 steroids, 2 flavonoids, and 1 macrocyclic lactone. These phytochemicals exhibit a broad spectrum of pharmacological activities, including analgesic, anti-inflammatory, antioxidant, antimicrobial, anticancer, anti-gout, molluscicide, and anti-parasitic effects. Given its long history of traditional use, rich phytochemical composition, and diverse pharmacological activities, E. milii can be considered an important botanical resource for applications not only in traditional medicine but also in modern ecological and potential pharmacological contexts. However, in vivo and clinical studies remain limited. Future research should emphasize pharmacokinetic profiling to strengthen the basis for clinical applications and new drug development.
Esketamine, the S-enantiomer of ketamine, has emerged as a rapid-acting antidepressant with unique mechanisms. This narrative review synthesizes current evidence on its clinical applications, safety, and regulatory status based on peer-reviewed literature published between January 2000 and March 2024, searched in PubMed, Web of Science, and the Cochrane Library. Esketamine exerts its effects primarily through noncompetitive antagonism of N-methyl-D-aspartate receptors, leading to rapid modulation of glutamatergic signaling and neuroplasticity. In anesthesia, it provides effective sedation with minimal respiratory depression. In psychiatry, intravenous and intranasal esketamine have demonstrated rapid antidepressant effects in treatment-resistant depression, with response rates of 50% to 70% within 24 hours. However, long-term safety data remain limited, and concerns persist regarding dissociative symptoms, cognitive impairment, and abuse potential. Regulatory approvals vary: the Food and Drug Administration approved intranasal esketamine for treatment-resistant depression in 2019, while European and Asian countries have adopted differing restrictions. Esketamine represents a paradigm shift in depression treatment, but its use requires careful patient selection, monitoring, and risk management. Future research should focus on head-to-head comparisons with other rapid-acting interventions, long-term outcomes, and integration into stepped-care models.
Heterogeneous catalysis is pivotal to modern chemical industries, and molecular-level insights into catalytic processes are essential for developing highly efficient catalysts and advancing energy conversion technologies. Tip-enhanced Raman spectroscopy (TERS), which integrates scanning probe microscopy with plasmon-enhanced Raman spectroscopy, provides chemical and topographic information simultaneously with exceptional sensitivity and nanoscale spatial resolution. This technique is ideally suited for the nanoscale chemical characterization of solid catalysts, enabling direct structure-performance correlations. In this review, we first introduce the fundamental principles of TERS, and then highlight its key applications in probing heterogeneous catalysis, focusing on critical aspects such as active sites, molecular activation pathways, conversion efficiency, chemical selectivity, and operando studies. We conclude by discussing current challenges and potential strategies to advance TERS in heterogeneous catalysis, and by outlining future directions for the field.
Lassa fever remains a major public health threat in West Africa, requiring coordinated scientific, policy, and financing responses. Regional scientific convenings are increasingly used to connect research evidence with policy action, yet their contribution to epidemic preparedness is not well documented. We conducted a qualitative health systems and policy analysis of the 2nd ECOWAS Lassa Fever International Conference (ELFIC 2025) in Abidjan, Côte d'Ivoire. Data sources comprised 302 scientific abstracts, plenary and ministerial session records, and the official Ministerial Joint Communiqué. Using the conference's six thematic pillars as a deductive framework, we conducted a thematic content analysis and synthesized findings into four domains: scientific advances; surveillance and laboratory systems; policy and financing insights; and cross-cutting lessons for regional preparedness. Progress was noted in diagnostics, therapeutics, vaccine development, decentralized laboratory capacity, genomic surveillance, and digital reporting. Persistent gaps remain at sub-national and community levels, in surveillance coverage, workforce capacity, and operational readiness. A major outcome was the Ministerial Joint Communiqué endorsing regional co-financing for Lassa fever vaccine development. ELFIC 2025 demonstrates the role of regional scientific platforms in aligning evidence with policy commitments. Sustained impact will require institutionalized coordination, strengthened accountability, and targeted investments in frontline capacity.
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To address clinical bottlenecks of traditional antipsychotic drugs, including delayed onset of action, significant peripheral side effects, and poor patient compliance, nanodelivery systems offer a feasible approach through their unique physicochemical properties to improve drug solubility, optimize in vivo transport, and enhance blood-brain barrier (BBB) penetration efficiency. This review focuses on the application potential and translational value of nanodelivery systems in psychiatric disorders. We systematically summarize recent advances in the construction strategies of mainstream nanocarriers, including lipid‑based, polymer‑based, inorganic nanomaterials, Metal-Organic Frameworks (MOFs), and Extracellular Vesicles (EVs), as well as commonly used nanoparticle preparation and characterization techniques. We briefly discuss key challenges facing nanoformulations, such as long‑term safety, large‑scale production, and batch‑to‑batch consistency, and highlight future directions driven by artificial intelligence and precision medicine. This review aims to provide insights for the rational design of nanodelivery systems for psychiatric disorders and to advance the development of precision psychiatry.
Inflammatory bowel disease (IBD) is a chronic, relapsing condition associated with diagnostic delays, disease misclassification, and variable treatment response. Conventional diagnostic and monitoring tools remain limited in capturing the biological complexity of IBD, prompting growing interest in metabolomics as a complementary approach. This systematic review aimed to examine the role of metabolomics in enhancing the diagnosis and management of IBD across adult and pediatric populations. Systematic review. The review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. PubMed, Web of Science Core Collection, ScienceDirect, Cochrane Library, and Google Scholar were searched from inception to identify eligible studies. Observational studies and clinical trials assessing metabolomics in IBD diagnosis or management were included. Methodological quality was appraised using the Newcastle-Ottawa Scale, RoB 2, and ROBINS-I. Due to substantial heterogeneity, a narrative synthesis was performed. Fourteen studies involving approximately 3700 participants met the inclusion criteria. Metabolomic analyses of serum, feces, urine, and plasma consistently identified disease-associated metabolic perturbations, particularly in amino acids, bile acids, lipids, and short-chain fatty acids. Only two studies reported formal diagnostic performance, with sensitivity and specificity exceeding 80% for distinguishing IBD subtypes. Several studies demonstrated metabolomic changes associated with treatment response and remission; however, outcome definitions varied widely across studies. Metabolomics shows significant potential to enhance IBD diagnosis and management, particularly for disease differentiation and treatment monitoring. Nonetheless, clinical translation is constrained by methodological heterogeneity and limited diagnostic validation. Future research should prioritize standardized protocols and robust diagnostic accuracy studies. This review explores metabolomics’ role in enhancing IBD diagnosis and management for both adults and children. The systematic review followed PRISMA 2020 guidelines, searching PubMed, Web of Science, Cochrane Library, ScienceDirect, and Google Scholar. Two reviewers independently screened studies and assessed risk of bias using Cochrane’s RoB 2, ROBINS-I, and NOS. A narrative synthesis was conducted due to study heterogeneity. Out of 2,630 records screened, 14 studies met eligibility criteria. These included ten observational studies, one case-control, one longitudinal observational, one RCT, and one nonrandomized trial. Six observational studies were of high quality. Metabolomics shows potential for enhancing IBD diagnosis and treatment, but high heterogeneity and a lack of diagnostic accuracy studies limit practical insights. The identified biomarkers/metabolites are consistent with previous studies, showing metabolomics’ potential in diagnosing and treating IBD in both pediatric and adult populations. Recent observational studies report sensitivity and specificity, indicating progress. Comprehensive diagnostic protocols should be developed based on previously identified biomarkers/metabolites before conducting rigorous diagnostic accuracy studies to evaluate their accuracy and improve clinical application of research findings.
With the intensified exploration of marine resources, marine bioactive peptides have become one of the research focuses in biomedicine, food science, and materials science because of their structural diversity, unique biological activities, and broad application potential. At present, the extraction of marine peptides has expanded beyond conventional chemical extraction and enzymatic hydrolysis, with microbial fermentation and gastrointestinal simulation technologies further broadening peptide diversity. In addition, the integration of multiple chromatographic techniques with advanced detectors has significantly improved the efficiency of marine peptide identification. Owing to their diverse biological activities, including immunoregulatory, antioxidant, antibacterial, antitumor, hypotensive, and hypoglycemic effects, marine peptides not only enrich the pool of candidates for marine drug development but also provide new perspectives for addressing numerous health challenges. Importantly, substantial progress has been made in the screening, identification, and mechanistic elucidation of marine bioactive peptides, driven by advances in high-throughput technologies and the bioinformatics. However, marine peptide research still faces several challenges, including complex sourcing, difficulties in large-scale acquisition, and insufficient exploration of biological activities. Therefore, this article concisely reviews recent progress in the extraction, purification, and identification of marine bioactive peptides, summarizes current research on their biological activities, and highlights the application of bioinformatics in marine peptide studies.
The maternal mortality ratio (MMR) is a core indicator of health-system performance and equity. In China, interpretation of recent maternal mortality trends is increasingly influenced by differences between modeled global estimates and national surveillance data. We aimed to characterize the maternal mortality transition and subnational inequities in China from 1990 to 2023 by comparing Global Burden of Disease (GBD) 2023 estimates with data from the National Maternal Mortality Surveillance System (NMMSS). We integrated model-based estimates from the GBD 2023 with real-world data from China's NMMSS. Assessment focused on key burden metrics, including disability-adjusted life years, MMR, mortality and incidence. Joinpoint regression was used to identify temporal trend changes. Scenario-based projections and Bayesian age-period-cohort (BAPC) models were applied to forecast progress toward the "Healthy China 2030 target". Subnational inequalities in maternal healthcare service coverage were also examined. GBD estimates showed China's MMR declined from 121.9 (1990) to 10.7 (2023) per 100,000 live births, while NMMSS reported 15.1 per 100,000 live births in 2023. According to GBD, the leading cause shifted from maternal hemorrhage to indirect disorders, whereas NMMSS consistently identified obstetric hemorrhage as the primary cause. The urban-rural disparity narrowed substantially, but subnational inequities persisted, particularly in western provinces. The MMR rapid decline during 2004-2015 was followed by a plateau. Scenario-based projections indicate that sustaining recent progress would enable China to achieve the Healthy China 2030 target (MMR <12 per 100,000 live births). China has made remarkable progress in maternal health and significantly reduced urban-rural disparities. However, critical differences between GBD estimates and NMMSS data underscore the need for improved local data collection. Targeted strategies, such as integrating cardiovascular risk screening in eastern provinces and strengthening obstetric emergency capacity in western regions, are essential to further reduce maternal mortality and achieve the Healthy China 2030 goal.
The increasing adoption of virtual reality (VR) in medical education offers substantial opportunities for immersive, practice-oriented training that complements traditional teaching methods. In particular, VR enables repeated, risk-free exposure to complex clinical scenarios and supports the development of clinical reasoning, communication skills, and procedural competence. However, implementing VR-based courses remains challenging due to high development costs, technical complexity, and the need for close interdisciplinary collaboration. This tutorial presents key insights and best practices from the medical tr.AI.ning project, a 3-year interdisciplinary initiative funded by the German Federal Ministry of Education and Research. The project's objective was to develop an artificial intelligence (AI)-supported, VR-based training platform that allows medical students to practice clinical decision-making in immersive, interactive scenarios. The paper is structured as a tutorial and offers recommendations for planning, developing, and integrating VR courses into medical curricula. Each recommendation is illustrated with concrete examples from our project, serving as a practical blueprint to guide educators and developers in applying these guidelines in their own contexts. Successful implementation of a VR project in medical education requires strategic planning and collaboration, starting with a thorough identification of curricular gaps that VR can address and a clear justification of its added educational value. An interdisciplinary consortium that combines expertise from medical didactics experts, computer science, and design is essential to ensure the development of high-quality, pedagogically sound simulations and intuitive user interfaces. Key factors for success include defining specific learning objectives aligned with competency-based frameworks; iterative development with continuous feedback from medical experts, educators, and students; and structured pilot testing with systematic collection of quantitative and qualitative data to assess usability, immersion, and learning outcomes. Early engagement and walkthroughs with end users help identify practical challenges and inform iterative improvements. A dedicated authoring tool within the project allows medical teachers to create and adapt VR scenarios without prior technical experience, supporting the scalability and sustainability of the approach. Effective project management frameworks facilitate collaboration, clear task allocation, and adaptive progress throughout development. Additionally, considerations for hardware selection, technical infrastructure, and sustainable dissemination strategies, including open-access publications, project websites, and professional networking, are crucial to ensure long-term viability and broad adoption across institutions. By combining a tutorial format with practical, step-by-step recommendations, this article provides a comprehensive guide for educators and developers on implementing immersive, AI-supported VR courses to enhance medical education. It highlights key lessons learned in interdisciplinary collaboration, iterative testing, systematic evaluation, and alignment with educational objectives, thereby facilitating the effective, evidence-based, and sustainable integration of VR into medical curricula across diverse institutions.
Spiral ganglion neurons (SGNs) relay auditory sensory information from the cochlea to the brain. Their loss results in permanent hearing impairment in humans due to their limited regenerative capacity. Progress in hearing restoration has been constrained by the inaccessibility of human inner ear tissue and challenges in generating functionally mature human SGN-like neurons from stem cells in vitro. To generate human SGN-like neurons from human induced pluripotent stem cells (hiPSCs), we recapitulated key signaling pathways involved in human inner ear development. On day (D) 11 of differentiation, nerve growth factor receptor-positive cells (precursors of pre-placodal ectoderm and neural crest) were isolated using magnetic sorting. From D18 to D25, cultures were treated with sonic hedgehogs to induce otic neural progenitors. Neuronal maturation was subsequently promoted by a cocktail of brain-derived neurotrophic factor, neurotrophin-3, and insulin-like growth factor-1, which supports SGN development. Cellular identity and functionality were assessed using single-cell RNA sequencing, immunocytochemistry, whole-cell patch-clamp electrophysiology, co-culture assays, and calcium ion (Ca²⁺) imaging. hiPSC-derived SGN-like neurons exhibited morphological, molecular, electrophysiological, and functional characteristics of SGNs in vivo. Neurons acquired bipolar morphology and were wrapped by glial cells. Transcriptomic analysis revealed that SGN-like neurons were distinct from other neuronal lineages and showed similarity to type I and type II SGNs based on expression of synaptic and intrinsic excitability-related genes. Electrophysiological recordings revealed progressive hyperpolarization of resting membrane potential and emergence of overshooting action potentials, consistent with neuronal maturation. In co-culture systems, human SGN-like neurons formed functional synaptic connections with mouse cochlear hair cells and cochlear nucleus neurons, evidenced by Ca2+ transients and induction of the immediate early gene c-Fos. This study reports a robust and reproducible protocol for generating human SGN-like neurons from hiPSCs, providing a versatile platform for studying human auditory development, disease modeling, drug screening, and cell-based therapies for hearing restoration.
Electrochemiluminescence (ECL) imaging has emerged as a highly sensitive and spatially resolved bioanalytical technique that bridges electrochemical control and optical microscopy. With its unique surface-confined emission, minimal background noise, and tunable activation, ECL imaging offers distinct advantages over fluorescence and chemiluminescence, especially for cellular and single-particle analysis. In this review, advanced strategies and wireless, multiplexed, and high-throughput bioimaging platforms, such as bipolar electrochemistry, single-electrode electrochemical system, and multielectrode array are summarized. Applications of ECL imaging methods in the single-cell analysis, nanoparticle electrocatalysis studies, intracellular and in vivo detection, and high-resolution bioassays are described in detail. This review has comprehensively outlined recent progress in these advanced technologies and presenting some emerging tools such as miniaturized devices, wireless energy transmission, and next-generation materials driving the transformation of ECL imaging into a robust platform for diagnostics and research. This work has not only summarized past progress but also explored future breakthroughs in precision diagnostics and electrochemical microscopy.
The embedded atom method (EAM) is a widely used interatomic potential model in molecular dynamics (MD) simulations in solids and alloys. However, the optimization of EAM potential parameters is a complex global optimization problem that traditional methods struggle to solve efficiently. In this work, we present GAEAM, a novel package developed for optimizing EAM potentials of solids using a genetic algorithm (GA) and global optimization. To validate the performance of GAEAM, five typical alloy systems were selected as test cases. MD simulations were performed using the optimized EAM potentials from GAEAM for 1.0 µs (1.0 × 109 fs). Dominant results of simulations including radial distribution functions (RDFs), coordination numbers (CN), root-mean-squared displacements (RMSD), and energy evolution, were analyzed to evaluate the accuracy of the optimized potentials. Detailed MD simulation results revealed that the optimized EAM potentials from GAEAM can accurately reproduce the structural and dynamic properties of the selected alloys. This work demonstrates that GAEAM provides a robust and efficient tool for EAM potential optimization, which can be extended to a wide range of solid and alloy systems. This package also reduces the manual effort required for potential parameter tuning, facilitating progress in computational materials science research.
Tooth loss remains a major unmet clinical challenge, and current prosthetic approaches cannot restore the biological complexity, sensory function, or regenerative capacity of natural teeth. Recent progress in stem cell biology, developmental engineering, and regenerative biomaterials has opened new possibilities for biological tooth regeneration. This review integrates advances across three major research domains that together define the current landscape of translational regenerative dentistry. First, we discuss stem cell-based, scaffold-guided strategies for tooth regeneration. These approaches combine dental and nondental stem cells, including DPSCs, SCAPs, PDLSCs, SHED, and iPSC-derived lineages, with bioactive materials such as HA/TCP ceramics, dentin-derived extracellular matrix scaffolds, and natural or synthetic polymers to promote odontogenic differentiation, vascularization, and periodontal attachment. Second, we summarize emerging tooth organoid and bioengineered tooth germ technologies that recapitulate epithelial-mesenchymal interactions and enable controlled reconstruction of dentin-pulp and periodontal compartments for modeling human odontogenesis. Third, we highlight molecular regulation-driven therapeutic strategies, focusing on the modulation of Wnt, BMP, FGF, TGF-β, and USAG-1 pathways to stimulate endogenous tooth regeneration and correct developmental defects. Despite marked progress, challenges remain, including stable neurovascular integration, optimization of stem cell-material crosstalk, precise control of spatiotemporal signaling, and long-term functional stability in vivo. Finally, we outline future directions involving smart biomaterials, gene- and protein-based molecular targeting, organoid-guided regeneration, and iPSC-enabled personalized therapies, which may further accelerate the clinical translation of stem cell-based tooth regeneration.
The gut microbiome supports digestion, immunity, and metabolism; its imbalance (dysbiosis) drives inflammation and metabolic dysfunction, contributing to chronic diseases such as diabetes, cardiovascular disease, inflammatory bowel disease, and autoimmune disorders. Medicinal plants provide a wide range of phytochemicals (such as polyphenols, flavonoids, alkaloids, saponins), which reach the colon and undergo two-sided interactions with microbes in the gut, acting as potential microbiome modulators and substrates of biotransformation into bioactive metabolites. This structured narrative review synthesises evidence from peer-reviewed studies indexed in PubMed, Scopus, and Web of Science over the last 10 years on the role of medicinal plants in microbiome-mediated chronic disease modulation. This literature is organised into three mechanistic axes: (i) perturbations, defined here as measurable shifts in microbial diversity or taxonomic composition relative to a baseline or healthy reference state, together with beneficial taxa enrichment; (ii) alterations in microbial metabolite output, especially short-chain fatty acids (SCFAs) and other immunometabolic mediators; and (iii) downstream host metabolic and immune signalling. Rather than broad descriptive summaries, the literature is organised using an axis-based mechanistic framework, highlighting key translational constraints such as botanical heterogeneity, dose/formulation variability, and inconsistent microbiome endpoint standardisation, that must be addressed to strengthen human evidence and clinical relevance. Illustrative microbiome-mediated processes involve botanicals such as turmeric (curcumin), ginseng (ginsenosides), and green tea (catechins), though evidence strength varies by study design. Future progress requires standardised phytochemical characterisation, microbiome-stratified trials, and integration of multi-omics with artificial intelligence analytics to enhance mechanistic insight, identify responders, and enable personalised plant-based microbiome therapies.
Plant-derived architectures provide a unique reservoir of hierarchical, anisotropic, and transport-optimized design principles that can be systematically translated into functional biomaterials for regenerative implants. Unlike conventional scaffold engineering approaches that rely on artificially generated porosity and isotropic architectures, plant tissues exhibit evolutionarily optimized vascular networks, graded mechanical stiffness, and stimulus-responsive morphologies that directly address challenges in mass transport, stress distribution, and adaptive integration in biomedical implants. This review critically examines how plant structural hierarchies, from cellulose microfibril alignment to multichannel vascular bundles, are mechanistically mapped onto modern biofabrication platforms, including decellularization, extrusion-based 3D printing, direct ink writing, electrospinning, and 4D printing. Particular emphasis is placed on quantitative structure-property-function relationships, such as anisotropic modulus ratios (E||/E⊥), channel diameter-diffusion coupling, swelling-induced curvature programming, and surface energy-biofouling interactions, that govern biological outcomes including angiogenesis, osteogenesis, myogenic alignment, and anti-infective performance. Representative case studies demonstrate that plant-inspired multichannel scaffolds enhance vascular infiltration and bone regeneration in vivo, aligned cellulose-based systems enable programmable shape morphing for minimally invasive deployment, and biomimetic surface microtopographies reduce fouling without antibiotic reliance. However, critical translational challenges remain, including immunological validation of decellularized plant matrices, mechanical fatigue under cyclic physiological loading, lubricant stability in slippery interfaces, and scalability under Good Manufacturing Practice (GMP) conditions. By integrating plant biomechanics, materials science, and advanced biofabrication, plant-inspired biomaterials emerge as a promising, yet early-stage strategy for engineering adaptive, vascularized, and multifunctional implants. Future progress will depend on rigorous quantitative validation, long-term in vivo performance studies, and standardized manufacturing frameworks that bridge biomimetic design with clinical translation.
Heart failure remains a leading global cause of morbidity and mortality, with limited capacity for myocardial regeneration following infarction. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have become a promising therapeutic resource due to their scalability, differentiation potential, and immunologic adaptability. Engineered cardiac patches, three-dimensional constructs of hiPSC-CMs combined with supporting cells and scaffolds, offer a strategy to deliver organized myocardium directly to injured hearts, overcoming the limitations of cell injection therapies. This review synthesizes evidence from 2010 to early 2025, spanning rodent, porcine, and non-human primate models, as well as the first clinical trials of hiPSC-CM patches. We highlight recent advances in maturation protocols, vascularization strategies, and scaffold engineering, while discussing two distinct translational paradigms: short-term paracrine support versus long-term remuscularization under sustained immunosuppression. Preclinical studies show that engineered patches improve graft survival, with engraftment rates ranging from 5 to 15%, alongside enhanced vascularization, electrical coupling, and left ventricular function. In large animal models, patches scaled to clinically relevant sizes achieved durable integration and improved hemodynamics. Of note, arrhythmogenic risk was lower than in intramyocardial injection models. Early human trials in Japan and Germany confirm feasibility and safety, with preliminary evidence of efficacy, including preliminary evidence of improved left ventricular ejection fraction and upgrades in NYHA functional class. Immunogenicity, graft maturation, and manufacturing scalability remain key hurdles, though innovations such as gene-edited hypoimmunogenic lines, multipronged maturation strategies, and bioreactor-based production offer potential solutions. Engineered hiPSC-CM cardiac patches represent a rapidly advancing frontier in regenerative cardiology. While early data indicate technical feasibility and measurable functional benefits, broader adoption will depend on resolving challenges of immune compatibility, arrhythmia prevention, and large-scale manufacturing. With coordinated progress in science, engineering, and regulation, cardiac patches may evolve into a transformative therapy for heart failure.