Search Results (35,257)

Cannabinoids (CBs) derived from Cannabis sativa have attracted growing interest for dermatological applications due to their anti-inflammatory, antiproliferative, antimicrobial, antifibrotic, and antipruritic properties. However, their clinical translation is significantly limited by physicochemical and pharmacokinetic challenges, including poor aqueous solubility, lipophilicity, instability, variable skin penetration, and inconsistent bioavailability. At the molecular level, CBs modulate keratinocyte proliferation, sebocyte activity, fibroblast function, melanocyte balance, and immune signalling through CB1/CB2 receptors, TRP channels, and PPARγ pathways. Evidence supports their potential in the treatment of psoriasis, atopic dermatitis, acne, allergic contact dermatitis, pruritus, scleroderma, and skin cancers. Clinical evidence remains preliminary: topical and oral formulations have demonstrated anti-inflammatory, antiproliferative, antibacterial, and antifibrotic effects, with improvements in pruritus, lesion severity, and quality of life in early-phase studies. However, most trials are small, uncontrolled, and lack placebo comparators, limiting generalisability. To overcome formulation barriers and enhance dermal delivery, advanced pharmaceutical strategies such as liposomes, nanoemulsions, polymeric nanoparticles, micelles, and transdermal systems have been investigated to improve stability, controlled release, and targeted skin deposition while minimising systemic exposure. This review integrates mechanistic insights, clinical evidence, and emerging nanotechnology-enabled delivery approaches, emphasising rational formulation design and translational considerations necessary for advancing CBs toward standardised and clinically reliable dermatological therapeutics. Full article

Gene therapy relies on safe and efficient delivery systems, yet traditional viral vectors and synthetic polymers often fail to meet these requirements due to immunogenicity and biocompatibility concerns. This review highlights self-assembling short peptides as a highly programmable and biocompatible non-viral platform uniquely positioned to overcome these translational bottlenecks. To provide a comprehensive overview of next-generation gene delivery, we systematically trace the trajectory from fundamental chemistry to clinical applications. First, we elucidate the supramolecular interactions and mechanisms driving peptide–nucleic acid co-assembly. Second, we outline concrete design strategies, detailing how sequence engineering and environmental responsiveness dictate the formation of optimized nanomorphologies. Third, we critically analyze how these nanocarriers navigate critical physiological and intracellular barriers, with a specific focus on cellular uptake, endosomal escape, and cargo release. Finally, we demonstrate the platform’s versatility in emerging frontiers, particularly mRNA vaccines and CRISPR/Cas9 gene editing. We conclude by identifying current obstacles to clinical translation and proposing future directions centered on multifunctional integration and stimuli-responsive design. Full article

Multiple sclerosis (MS) reflects a dynamic interplay between peripheral immune activation and compartmentalized inflammation within the central nervous system (CNS). While current disease-modifying therapies effectively reduce relapse activity driven by transient peripheral immune infiltration, their impact on progressive disability remains limited, prompting interest in strategies targeting CNS-resident immune mechanisms. Bruton’s tyrosine kinase (BTK), expressed in B cells and myeloid-derived cells, including microglia, serves as a shared intracellular signaling node linking adaptive and innate immune pathways. Second-generation BTK inhibitors, including evobrutinib, tolebrutinib, fenebrutinib, remibrutinib, and orelabrutinib, have advanced through Phase II-III development in MS. These agents differ in binding mode, selectivity, pharmacokinetics, CNS penetration, and safety profiles, distinctions that may influence stage-specific therapeutic performance. Recent trials across relapsing and progressive phenotypes have yielded heterogeneous outcomes. Divergent signals in primary and secondary progressive MS reflect underlying biological heterogeneity and suggest that therapeutic responsiveness may depend on residual inflammatory activity, lesion biology, and pharmacologic characteristics. Emerging biomarker frameworks further emphasize the importance of stratifying inflammatory activity and degenerative progression when interpreting trial data. This review integrates molecular pharmacology and the most recent clinical evidence available through 2026 to examine how pharmacologic properties translate into stage-dependent therapeutic positioning. We also consider safety constraints within a disease-stage-specific benefit-risk framework, aiming to clarify the evolving role of BTK inhibition in MS. Full article

The excessive use of chemical fertilizers is a primary driver of soil degradation in agricultural systems. Planting green manure during fallow periods offers a sustainable alternative for soil conservation. The present study investigated the effects of different green manure cropping systems (Ryegrass (TR), Chinese milk vetch (TM), and Spinach (TS)) on soil physicochemical properties, biological activity, and microbial communities, compared to a control (CT). Results demonstrated that green manure treatments significantly enhanced soil fertility by increasing the content of soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), and available potassium (AK). Notably, the TR treatment increased SOM, AN, and AP by 23.0%, 60.0%, and 44.6% (p < 0.05), respectively. Concurrently, key soil enzyme activities (urease, dehydrogenase, catalase) were significantly boosted (p < 0.05), with TR showing the most pronounced effect. Earthworm indicators (such as earthworm biomass and abundance) were significantly higher in the Ryegrass plots (p < 0.05). Microbial analysis revealed that TM enhanced bacterial diversity, whereas TR increased fungal richness (p < 0.05). Beneficial bacterial phyla, particularly Proteobacteria, exhibited a marked increase under the TM and TR treatments, while the fungal community underwent a favorable shift. Consequently, a significant elevation was observed in the overall Soil Quality Index (SQI) across all green manure treatments. Notably, the TR treatment resulted in a substantial 150% increase. In summary, ryegrass emerged as the most effective treatment in enhancing soil fertility, biological activity, and microbial diversity, underscoring its considerable potential as a green manure for sustainable soil management during fallow periods in paddy fields. Full article

Graft-versus-host disease (GVHD) is one of the principal complications seen in the recipients of allogenic hematopoietic stem cell transplantation (allo-HSCT), and persists as a leading cause of post-transplant morbidity and mortality. Increasing evidence highlights the crucial influence of the gut microbiome (GM) on transplant outcomes. Microbial dysbiosis, characterized by reduced bacterial diversity and pathogenic overgrowth, is strongly associated with higher rates of complications and mortality. Patients with lower microbial diversity exhibit poorer overall survival (OS) and an increased incidence of acute GVHD (aGVHD). Conversely, restoration of beneficial commensal communities has been shown to enhance immune homeostasis, mitigate GVHD severity, and decrease infection risk. Emerging therapeutic strategies now focus on modulating the intestinal microbiome through dietary interventions, probiotics, prebiotics, and fecal microbiota transplantation (FMT). It has been demonstrated that bacterial metabolites, such as short-chain fatty acids (SCFAs) from the diet, especially a diet rich in fibers, reduce the occurrence/severity of GVHD by inducing regulatory T cells (Tregs), which release anti-inflammatory cytokines and regulate the host immune system. Hence, the implementation of dietary fibers (DFs) could increase beneficial commensals, Treg induction, and improve outcomes such as GVHD and OS in recipients of allo-HCT. Hereupon, this review addresses how a fiber-rich diet modulates GM composition, reinforces epithelial barrier integrity, and improves the efficacy of Treg-based immunotherapy by stabilizing their regulatory phenotype and increasing their functional persistence, ultimately leading to a reduction in GI complications associated with GVHD. Unlike prior reviews that primarily cover the microbiome–GVHD axis or Treg therapies in isolation, this review emphasizes fermentable dietary fibers as a mechanistically grounded, clinically actionable strategy to support Treg stability and persistence via microbiota-derived metabolites. We integrate mechanistic evidence with emerging clinical feasibility data and ongoing trials of prebiotic supplementation in allogeneic HSCT. Full article

Industrialization has led to the substantial release of heavy metals and organic pollutants into soil and groundwater, resulting in severe contaminated site issues that pose significant threats to ecosystems and human health. This review aims to systematically review the current development status and challenges of contaminated site remediation technologies, and explore the potential of artificial intelligence (AI) applications in site remediation, to provide a theoretical reference for advancing intelligent remediation. Conventional remediation technologies mainly include physical methods (e.g., solidification/stabilization (S/S), soil vapor extraction (SVE), thermal desorption, pump and treat (P&T), groundwater circulation wells (GCWs)), chemical methods (e.g., chemical oxidation/reduction, electrokinetic remediation (EKR), soil washing), and biological methods (phytoremediation, microbial remediation), along with combined strategies that integrate multiple approaches. Although these technologies have achieved certain successes in engineering practice, they still face common challenges such as risks of secondary pollution, long remediation periods, high costs, poor adaptability to complex hydrogeological conditions, and insufficient long-term stability, making it difficult to fully meet the remediation demands of complex contaminated sites. Subsequently, the potential of emerging technologies—including nanomaterial-based remediation, bioelectrochemical systems, and molecular biology-assisted remediation—is introduced. On this basis, the forefront applications of AI in contaminated site remediation are discussed, covering site monitoring and characterization, risk assessment, remedial strategy selection, process prediction and parameter optimization, material design, and post-remediation intelligent stewardship. Machine learning (ML), explainable AI (XAI), and hybrid modeling approaches have markedly improved remediation efficiency and decision-making. Looking forward, with advancements in XAI, mechanism-data fusion models, and environmental foundation models, AI is poised to drive a paradigm shift toward intelligent and precision remediation. However, challenges related to data quality, model interpretability, and interdisciplinary expertise remain key barriers to overcome. Full article

The rapid growth in the spectrum of cyber threats, coupled with the evolution of digital uses, services and infrastructures in the healthcare sector, means that security measures need to be reassessed to ensure that they are in step with the reality on the ground and adapted accordingly, as smart healthcare systems show a dearth of privacy and security in the digitization and sharing of health records. Blockchain, being a new decentralized infrastructure, is one of the leading revolutionary emerging technologies that can be used to improve data integrity and traceability in healthcare systems. This study investigates how blockchain technology is affecting the healthcare domain, comprehensively analyzing its implications, challenges, and capabilities. The results indicate that blockchain is a revolutionary technology for creating transparent personal health records that can address the limitations of smart healthcare system management and provide a decentralized environment for exchanging healthcare data. However, there are still plenty of difficulties and obstacles that prevent it from being more widely accepted by healthcare stakeholders. Full article

Laminated bamboo (LB) has emerged as a promising sustainable structural material due to its rapid renewability, high strength-to-weight ratio, and favorable mechanical performance. Drawing on a comprehensive review of over 90 published experimental and analytical studies, this paper provides a critical synthesis of the structural behavior of LB, with emphasis on its compression, tension, flexure, shear, and creep responses. Reported mechanical properties exhibit variability, largely influenced by bamboo species, fiber orientation, processing methods, adhesives, lamination quality, and loading configuration. While LB demonstrates high tensile and flexural strengths comparable to or exceeding conventional timber products, pronounced anisotropy and brittle failure modes are consistently observed, particularly under shear and rolling shear loading. Recent studies on cross-laminated bamboo (CLB) highlight the significant role of interlaminar behavior and adhesive performance in controlling failure mechanisms, indicating that rolling shear capacities often govern the design of planar elements. Beyond mechanical behavior, this review synthesizes available research on thermal and fire performance. Emerging research on LB connections indicates that joint behavior often governs global structural performance, with strength and ductility strongly influenced by fastener type and embedment behavior. Key knowledge gaps are identified, underscoring the need for unified design frameworks to enable broader structural adoption of laminated bamboo systems. Full article

Background: Prostate cancer (PCa) arises from complex interactions among host genetics, androgen signaling, and microbial communities. Emerging genomic evidence supports the presence of microbial consortia within prostate tissue, suggesting that microbial genes, metabolites, and host–microbe interactions may contribute to chronic inflammation, oncogenic signaling, and therapeutic resistance. Methods: We conducted a narrative review using targeted searches of PubMed and Google Scholar for studies published between 2020 and 2025, complemented by selected mechanistic reports published in March 2026. Human studies and experimental research providing mechanistic insights into prostate models were prioritized. Due to the heterogeneous methodologies, evidence was synthesized qualitatively, with an emphasis on genomic and signaling perspectives. Results: Low-biomass microbial DNA is consistently detected in prostate tissue. Proteomic analyses of Corpora amylacea suggest a “fossil record” of past infections through sequestered microbial DNA and antimicrobial proteins, potentially priming tissue for long-term carcinogenic processes, although contamination remains a key limitation. Recurrent bacterial and viral signals, including Cutibacterium acnes, Escherichia coli, Pseudomonas, Acinetobacter, human papillomavirus, Epstein–Barr virus, and cytomegalovirus, appear to converge on a restricted set of tumor-relevant pathways, including TLR–NF-κB, MAPK, PI3K/AKT/mTOR, cGAS–STING, and p53/pRb disruption. These interactions may promote cytokine production, oxidative stress, DNA damage, epithelial–mesenchymal transition, extracellular matrix remodeling, immune evasion, and resistance to therapy. The gut–prostate axis further links intestinal dysbiosis and microbial metabolites with systemic IGF-1 signaling and castration resistance. Conclusions: Microbial genomic consortia in the prostate and gut may shape inflammatory, metabolic, and immune networks that influence PCa initiation and progression. However, most available data remain correlative and are limited by low-biomass sampling, contamination risk, and heterogeneous study designs. Future research should prioritize rigorous contamination control, longitudinal and prostate-specific mechanistic studies, and integrated multi-omic approaches to clarify causality and identify actionable microbial targets for prevention, diagnosis, and therapy. Full article

Background/Objectives: Spondylarthritis (SA) is characterized by high clinical heterogeneity, often resulting in a discrepancy between systemic inflammation and patient-reported symptoms. While hematologic indices are emerging as cost-effective biomarkers, their role in phenotypic differentiation remains unclear. We investigated the utility of traditional inflammatory markers, including the novel fibrinogen-to-platelet ratio (FPR), in differentiating SA subtypes and predicting patient-reported disease activity. Methods: This cross-sectional study included 64 patients with spondylarthritis: axial SA (n = 32), peripheral SA (n = 8), and psoriatic SA (n = 24). Clinical assessments included the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Functional Index (BASFI). Systemic inflammation was evaluated via C-reactive protein (CRP), fibrinogen, and calculated ratios (NLR, PLR, MLR, and FPR). Principal Component Analysis (PCA) was employed to map the inflammatory architecture, while Receiver Operating Characteristic (ROC) curves evaluated the predictive power for high disease activity (BASDAI ≥ 4). Results: Significant phenotypic differences were observed with the FPR demonstrating superior discriminative capacity (p = 0.003). Patients with peripheral SA exhibited significantly higher FPR (median 1.88) compared to axial (1.33) and psoriatic (1.32) subtypes, and the dedicated ROC analysis for phenotypic discrimination yielded an AUC of 0.866 (95% CI: 0.745–0.987) (1.36, p = 0.039). HLA-B27 prevalence was low overall (31.3%) and in psoriatic SA (4.2%, p = 0.012). Correlation analysis revealed strong associations between BASDAI and BASFI (ρ = 0.79), NLR and MLR (ρ = 0.78), and CRP and fibrinogen (ρ = 0.66). PCA identified two independent inflammatory dimensions explaining 74.8% of variance: neutrophil-hypercoagulable axis (41.4%, driven by NLR, PLR, and MLR), and an acute-phase/fibrinogen axis (33.4%, driven by CRP, fibrinogen, and FPR). Notably, FPR clustered with acute-phase reactants rather than leukocyte-derived ratios, supporting its role as a marker of systemic inflammatory burden. Although fibrinogen is involved in the coagulation cascade, the absence of direct coagulation markers precludes definitive characterization of this component as hypercoagulable. ROC analysis revealed that fibrinogen showed the highest discriminative ability for disease activity (BASDAI ≥ 4), with an AUC of 0.690 (95% CI: 0.519–0.861), followed by NLR (0.621), MLR (0.592), and FPR (0.583). However, overall discriminative performance remained modest, with most 95% confidence intervals crossing 0.5. Conclusions: FPR emerges as a robust phenotypic biomarker capable of discriminating against SA subtypes, particularly identifying peripheral SA with high accuracy and excellent negative predictive value. In contrast, its ability to predict patient-reported disease activity remains limited, reinforcing the distinction between trait and state biomarkers. Exploratory PCA revealed that FPR clusters with acute-phase reactants rather than leukocyte-derived ratios, supporting its biological link to systemic inflammatory burden. These findings advocate for a dual-purpose biomarker approach in SA: FPR for phenotypic stratification and fibrinogen for activity assessment, while clinical indices remain indispensable for symptom monitoring. Validation in larger, prospective cohorts is warranted. Full article

The efficacy of traditional antimicrobial treatments has been largely compromised due to the high occurrence of multidrug-resistant (MDR) pathogens, therefore underlining the limitations of existing drug delivery mechanisms. Pathogens resist pharmacological treatment via different mechanisms, including efflux pump overexpression, biofilm formation, and enzymatic destruction. The application of nanorobotics or controllable nanoscale devices has gained considerable attention for overcoming shortcomings while connecting biomedical engineering, materials science, and microbiology. Despite advancements in nanomedicine, there is still no suitable nanorobotic system applicable against MDR pathogens. Previous studies highlighted device categories and materials but did not explain the detailed nanorobotic mobility, sensing, and programmability to counteract biological resistance. This review combines cross-disciplinary discoveries to design a mechanistic and translational model for nanorobotics effective in controlling infectious diseases while focusing on the advancements in nanorobotic technologies over the past six years (2020–2025), with emphasis on translational readiness, biosafety issues, scalability, regulation, and their mechanistic ability to overwhelm MDR complications. Databases from different publishers, including PubMed, Scopus, and Web of Science, were used to select studies focusing on the potential of emerging nanorobotic therapeutic technologies, such as magnetic microrobots, catalytic nanoswimmers, and DNA origami nanodevices, and their application to bacterial biofilms and antibiotic drug delivery. Evidence from the literature shows that magnetically driven microrobots, catalytic nanoswimmers, and DNA origami structures can actively destroy biofilms, enhance antibiotic penetration, and perform site-specific antimicrobial administration. Nevertheless, most of these innovations remain in the preclinical or prototype stage, hindered by biosafety issues, immunological reactivity, poor routing precision, energy source optimization, and a lack of regulatory and ethical frameworks, which are major challenges for clinical translation. Full article

To address the challenge of balancing economic growth with carbon emission reduction, improving regional Carbon Emission Efficiency (CEE) has emerged as a central pathway to achieving the “dual carbon” goals. While most existing studies focus on inter-regional CEE linkages through pairwise interaction networks, such approaches fall short in capturing the high-order mechanisms of multi-regional collaboration. This study integrates the Super-SBM model with a modified gravity model to construct a CEE correlation network across 30 provincial administrative regions in China from 2007 to 2023. To overcome the limitations of traditional pairwise networks, simplicial complex theory is introduced to establish a high-order topological representation framework. Furthermore, by applying the multiorder Laplacian to assess the synchronization stability of the network, a directed second-order degree swap strategy is proposed to optimize its high-order structure. The findings reveal that the CEE correlation network has evolved from a single-pole aggregation pattern toward a multi-center equilibrium. Provinces with high connectivity play a dominant role in both pairwise and triadic synergies, though their collaborative advantages are gradually diffusing to central and western regions. Notably, with only a limited number (approximately five) of second-order degree swaps among key node pairs, the network’s synchronization stability can be substantially improved. When first-order and second-order interaction strengths reach comparable levels (coupling strength ${\alpha }^{*}\approx 0.5$), the system achieves optimal resistance to external perturbations. This study highlights the pivotal role of high-order collaboration in shaping regional CEE linkages and offers a practical optimization pathway for structurally enhancing CEE through coordinated efforts in pursuit of the “dual carbon” goals. Full article

Despite significant advancements in communication systems, inherent limitations persist in providing reliable data transmission for emerging applications with massive data exchanges. Semantic communication offers promising solutions by extracting and transmitting meaningful information rather than raw bit sequences. However, it faces challenges from high mobility and dynamic channel conditions in wireless environments. In this paper, we design a ground-to-air network architecture that integrates a rotary-wing unmanned aerial vehicle (UAV) and ground terminals to maximize semantic transmission efficiency while maintaining low energy consumption. This approach leverages the high mobility of the UAV for flexible deployment and the data reduction capabilities of semantic communication. Therefore, we formulate a multi-objective optimization problem to simultaneously balance the total semantic transmission rate and the UAV propulsion energy consumption by jointly optimizing the UAV hovering position, semantic encoding lengths, and resource block (RB) allocation. The problem is complex, with mixed continuous and discrete variables, which necessitates an advanced optimization method. To address these challenges, we propose a novel greedy-enhanced adaptive multi-objective cellular genetic algorithm (GEAMOCell), which utilizes an adaptive neighborhood selection mechanism to balance exploration and exploitation, and employs a crowding-guided archive feedback mechanism to maintain population diversity. The simulation results demonstrate that the proposed GEAMOCell algorithm outperforms baseline algorithms in terms of convergence, semantic transmission rate, and energy efficiency. Full article

Oral lichen planus (OLP) is a chronic, T cell-mediated inflammatory disorder classified by the World Health Organization as an oral potentially malignant disorder (OPMD). Despite decades of research, its precise etiology remains incompletely understood and involves a complex interplay between genetic predisposition, environmental triggers, and autoimmune-like responses. This review provides a comprehensive update on OLP pathogenesis, emphasizing the role of CD8 positive cytotoxic T lymphocyte-driven basal keratinocyte apoptosis and the skewing of the T-cell receptor (TCR) repertoire. We highlight the significance of the epidermal growth factor receptor (EGFR) signaling pathway as a molecular bridge between chronic inflammation and epithelial proliferation. Furthermore, we discuss a stepwise therapeutic approach that prioritizes the management of the oral microenvironment—specifically Candida colonization and periodontal health—before escalating to immunosuppressive agents. Finally, we explore emerging precision medicine frontiers, including IL-17/IL-23 inhibitors and JAK inhibitors, alongside traditional Japanese Kampo medicine (Hange-shashin-to) and systemic adjuncts like Cepharanthine, offering a contemporary perspective on modern OLP management. This integrative framework redefines OLP not merely as a chronic inflammatory disorder, but as an immunologically sustained, microenvironment-driven, potentially malignant condition. Full article

Lyme disease (LD) is classically defined as a tick-borne infection caused by Borrelia burgdorferi sensu lato (Bbsl). However, accumulating evidence indicates that, beyond microbial persistence, Bbsl infection can initiate sustained immune dysregulation and post-infectious inflammatory phenotypes in a subset of patients. This narrative review integrates open-access experimental, translational, and clinical data and discusses LD within the spectrum of infection-triggered, immune-mediated processes. We review key immunopathogenic mechanisms, including dysregulated innate immune activation, type I interferon (IFN-I) signaling, T helper 1 and T helper 17 (Th1/Th17) polarization with regulatory T-cell (Treg) insufficiency, antigen persistence (notably borrelial peptidoglycan), and pathways linking infection to autoimmunity such as molecular mimicry, epitope spreading, and human leukocyte antigen (HLA)-restricted susceptibility. These mechanisms are integrated with immune-mediated clinical manifestations affecting the central nervous system (CNS), peripheral nervous system (PNS), musculoskeletal system, heart, skin, and hematologic compartment. Finally, we discuss translational implications for diagnosis, biomarker-guided stratification, and emerging therapeutic strategies that extend beyond antimicrobial therapy, while addressing current controversies and limitations. This framework supports a mechanistic model in which Lyme disease-associated morbidity in selected patients reflects persistent immune activation and dysregulated host responses triggered by infection. Full article