Search Results (4,343)

Cystic fibrosis (CF) is a genetic disorder caused by CFTR gene mutations. The elexacaftor/tezacaftor/ivacaftor (ETI) drug combination has markedly improved CF outcomes; however, its impact on gut microbiota (GM) dysbiosis remains poorly investigated. Herein, we examined potential longitudinal effects of ETI treatment on six CF patients' GM before therapy (T0), and after 6 (T1) and 12 months (T2). Patients’ stools were analyzed using 16S rRNA metataxonomy, and GM profiling was characterized by alpha diversity, performed using the Shannon–Weiner, Simpson, and Chao1 indices; beta diversity, based on Bray–Curtis distance; and taxonomic patterns through multivariate and univariate analyses. A longitudinal exploratory assessment of the GM composition of CF patients at T0, T1, and T2 was performed. At baseline, CF patients displayed a distinct genus-level microbial signature compared with healthy controls, including Veillonella_A, Haemophilus_D_735815, Fusobacterium_C, Ruminococcus_B, and Blautia_A_141780. During ETI treatment, alpha diversity showed no significant transient increase at T1 followed by a decrease at T2. Taxonomic profiles showed marked inter-individual heterogeneity. Exploratory longitudinal analyses, assessed by the Friedman test, identified temporal variation in 11 bacterial genera: CAG-177, Clostridium_AP, Coprococcus_A_121497, Copromonas, and Muricomes_149725, showed a progressive decrease in relative abundance from T0 to T2; Haemophilus_D_734546, Eubacterium_B, Lachnoanaerobaculum, Moraxella_C_651924, and Neisseria_563205 displayed a transient increase at T1, followed by a decrease at T2; and Lactococcus_A_346120 showed a transient decrease at T1 followed by an increase at T2. Progressive depletion and transient changes or recovery of bacterial taxa may only represent a rough idea of the ecological changes in the gut microbiota observed during the course of ETI therapy. Longitudinally studies based on large cohorts of CF patients are mandatory to properly interpret these very preliminary results and to search for actual ETI-induced microbiome effects. Full article

Background/Objectives: Streptococcus suis is an important zoonotic pathogen responsible for severe infections in animals and humans, and the emergence of diverse strains has reduced the effectiveness of conventional antimicrobial therapies. Since there is no broadly protective vaccine, there is a need for new vaccination strategies that focus on conserved antigens from a variety of strains. This study aimed to design and evaluate a multi-epitope vaccine candidate against diverse S. suis strains using an integrated pangenome-guided reverse vaccinology approach. Methods: To design a multi-epitope vaccine (MEV) candidate against diverse S. suis, an integrated computational framework was employed, incorporating pangenome analysis, subtractive proteomics, reverse vaccinology, immunoinformatics, structural modeling, molecular docking, molecular dynamics simulation, immune simulation, and in silico cloning. The conserved core proteins were systematically screened for essential, non-homologous, antigenic, non-allergenic and non-toxic vaccine candidates for epitope prediction. Results: A total of 7421 gene families, including 1169 conserved core genes, were identified through pangenome analysis of 24 complete S. suis genomes. Three computationally prioritized candidate proteins were identified through sequential subtractive proteomics: sucrose phosphorylase, peptidoglycan hydrolase PcsB and an RND transporter-associated adaptor protein, annotated in the source database as an RND efflux transporter periplasmic adaptor subunit. We selected eight cytotoxic T-lymphocyte (CTL) epitopes, five helper T-lymphocyte (HTL) epitopes, and three linear B-cell epitopes with favorable predicted immunological properties to develop a 397-amino acid multi-epitope vaccine construct that contains the S. suis 50S ribosomal protein L7/L12 adjuvant with rationally designed peptide linkers. The vaccine construct exhibited favorable physicochemical properties, predicted structural stability, and high antigenicity scores. The predicted combined HLA population coverage of the selected CTL and HTL epitopes was 90.77% across the populations included in the analysis. Immune simulation predicted patterns consistent with humoral and cellular immune activation, including sustained IgG production, elevated IFN-γ and IL-2 secretion, efficient antigen clearance, and generation of immunological memory, whereas molecular docking and molecular dynamics simulations characterized the predicted interaction and conformational behavior of the MEV–TLR1/TLR2 complex. Codon optimization (CAI = 0.996) and in silico cloning into the pET-30a(+) expression vector supported the potential feasibility of recombinant expression in Escherichia coli. Conclusions: In this study, a rationally designed multi-epitope vaccine candidate against diverse S. suis strains was developed using an integrated pangenome-guided reverse vaccinology approach. Based on these computational analyses, the proposed vaccine candidate showed favorable predicted immunogenicity, predicted structural quality, predicted HLA population coverage, and expression feasibility, providing a foundation for future experimental validation and development of a vaccine against diverse S. suis. Full article

Antimicrobial resistance (AMR) represents one of the foremost global public health threats, undermining the efficacy of antibiotic therapies across all clinical disciplines, including dentistry. The oral cavity, housing one of the most diverse microbial ecosystems in the human body, contains a largely underappreciated reservoir of antibiotic resistance genes (ARGs), collectively defined as the oral resistome. This review synthesises current evidence on the oral resistome across five thematic areas. First, we contextualise the global burden of AMR, highlighting its scale and implications for oral healthcare. Second, we define the oral resistome and characterise its composition, distribution across oral microhabitats, and the principal determinants that govern its structure and dynamics. Third, we critically appraise metagenomic approaches, from early culture-based and PCR-targeted methods to shotgun metagenomics and functional screening, that have expanded the resolution of resistome characterisation. Fourth, we examine multi-omics integration, including genomics, transcriptomics, and metabolomics, and its capacity to reveal the ecological and molecular drivers of resistance within the oral ecosystem. Finally, we explore how resistome profiling can inform precision oral health, enabling individualised antimicrobial stewardship, microbiome-based risk stratification, and patient-tailored preventive and therapeutic strategies in the era of personalised dentistry. Full article

Antimicrobial resistance (AMR) has emerged as a critical global health concern that transcends human, animal, and environmental boundaries. The extensive and often indiscriminate use of antibiotics for disease control and growth promotion has accelerated the evolution and spread of resistant pathogens within the aquaculture sector. This review examines aquaculture-associated AMR through a One Health framework. We explore the molecular mechanisms of resistance such as efflux pumps, enzymatic degradation, mobile genetic elements, and horizontal gene transfer that drive the dissemination of antimicrobial resistance genes among aquatic microorganisms. The review synthesizes evidence linking AMR in aquaculture to public health impacts, including the transmission of resistant bacteria through seafood and environmental exposure. Current regulatory measures and stewardship policies are assessed to identify gaps in implementation, particularly in developing regions where enforcement and public awareness remain limited. Review highlights emerging alternatives such as bacteriophage therapy, engineered probiotics, synthetic microbial communities, and CRISPR-based systems as sustainable approaches to reduce antibiotic dependence. Future research priorities include the integration of genomics, artificial intelligence, and environmental DNA monitoring for precision surveillance. This review emphasis the need for cross-sectoral collaboration, innovation, and global policy coherence to mitigate AMR in aquaculture and safeguard food, environmental, and public health security. Full article

The kidney is an essential organ that has a crucial role in preserving homeostasis within the human body. Kidney cancer is considered a major clinical challenge owing to its resistance to traditional treatments such as chemotherapy, radiotherapy, and immunotherapy. Nanoparticles (NPs) gain great attention in cancer therapy due to their low toxicity, biocompatibility, and targeted drug delivery capability. This review focuses on the current role of green-synthesized NPs in renal cell carcinoma management and their applications in targeted drug delivery and cancer-specific targeting mechanisms with the demonstration of the environmentally friendly green synthesis approaches utilizing biological resources such as plant extracts and microorganisms, highlighting their advantages over conventional synthesis methods in terms of biocompatibility, sustainability, and reduced toxicity. Moreover, the therapeutic potential of nanomaterials is discussed, including magnetic NP-mediated thermal therapy, photothermal therapy, gene delivery systems, and RNA interference-based strategies. We underscore the challenges and limitations of NPs, including in vivo toxicity, biodistribution, clinical translation, large-scale production, batch-to-batch variability, long-term safety, scalability, repeatability, regulation, and reproducibility. There is growing potential to improve the treatment of kidney cancer. Hence, the promising prospects of nanotechnology in kidney cancer treatment provide a foundation for future research and clinical application. This comprehensive article highlights the significant contributions of nanomedicine to oncology and shows an optimistic perspective for more effective and precise treatment strategies for kidney cancer. Full article

Gene therapy is undergoing continued clinical translation and technological development. This progress has been marked by regulatory approvals and broadened therapeutic indications across genetic, metabolic, and oncologic diseases and disorders. The field has evolved over decades from early viral-mediated gene addition to approaches capable of targeted editing, regulation, or replacement of genetic information. These systems include base and prime editors, epigenetic modulators, CRISPR-Cas, RNA therapeutics and programmable integration platforms. When paired with increasingly sophisticated viral and nonviral delivery strategies, these technologies enable greater control over tissue targeting, duration of activity, and therapeutic exposure. Recent clinical successes, including approved ex vivo CRISPR-based therapies for hemoglobinopathies, in vivo CRISPR editing for transthyretin amyloidosis, and emerging clinical applications of base and prime editing, provide growing clinical evidence for the feasibility of genetic medicines. However, technological advancement has also made platform selection increasingly complex. Therapeutic performance is determined not by editing efficiency alone, but by the interaction among genetic precision, temporal control, dosage tunability, delivery efficiency, durability, and disease-specific safety requirements. A molecularly efficient platform may still have limited therapeutic value if it cannot reach the disease-relevant cell population at sufficient and safe exposure. In this review, we examine recent technological and clinical advances in genetic medicine with particular emphasis on developments during the past approximately five years. We propose a multidimensional framework in which gene therapy platforms are evaluated according to three intrinsic properties—genetic precision, temporal control, and dosage tunability—while delivery, clinical maturity, and disease context act as major translational constraints. This framework highlights that no single platform is universally optimal; rather, successful therapeutic design depends on matching the biological characteristics of the intervention to the requirements of the disease and target tissue. Remaining challenges in extrahepatic delivery, genomic safety, immunogenicity, manufacturing, and long-term monitoring remain important determinants of broader clinical implementation. Full article

As the crisis of antibiotic resistance escalates, phage therapy has regained attention as an alternative strategy. Artificial intelligence (AI) technologies offer new avenues to overcome the bottlenecks inherent in traditional bacteriophage research. This review summarizes the multi-dimensional innovative applications of machine learning, deep learning, and large biological models in phage studies. In the fields of phage recognition and genomics, support vector machines (SVMs), convolutional neural networks (CNNs), and pre-trained protein language models can all achieve recognition accuracy rates of over 90%. Furthermore, tools such as DeepHost and VirSorter2 can efficiently identify phage sequences, annotate functional genes, and predict hosts at the species or strain levels. For clinical translation, AI integrates patient characteristics, bacterial phenotypes, and phage profiles to customize cocktail regimens for individualized phage therapy. Graph neural network-based models like DeepPBI-KG integrate multi-omics knowledge graphs to precisely predict phage-host interactions (PHIs), whereas agent-based simulation and defense protein predictors forecast phage resistance evolution. Additionally, generative AI can support the de novo design of functional phage genomes and mine massive unannotated virome dark matter. Nevertheless, this cross-disciplinary field faces significant constraints, including uneven and biased sequencing datasets, insufficient model interpretability, and dual-use biosafety ethical risks accompanied by unclear algorithm accountability and incomplete global supervision systems. Future research should optimize standardized multimodal databases, develop explainable AI algorithms, and establish cross-disciplinary ethical governance frameworks to facilitate closed-loop verification between computational prediction and wet-lab experiments. In conclusion, the deep integration of AI and phage biology provides revolutionary strategies to tackle multidrug-resistant infections and advances the clinical transformation of phage precision medicine. Full article

Background: Genetic eye diseases (GEDs) comprise a heterogeneous group of hereditary and de novo disorders that involve all ocular structures, including the retina, optic nerve, vitreous, anterior segment, and ocular development. Their marked clinical and genetic heterogeneity frequently delays diagnosis and access to genetic counseling, multidisciplinary management, and emerging gene-based therapies. Although ophthalmic deep phenotyping remains essential, we propose an approach that prioritizes genetic analysis, particularly in under-resourced healthcare settings with limited access to advanced imaging and electrophysiological tests. Methods: We conducted a retrospective observational study of 101 consecutive patients with suspected genetic eye diseases. All were evaluated at a tertiary referral center in northeastern Mexico between January 2020 and August 2023 through comprehensive ophthalmologic examination supplemented by optical coherence tomography, visual-field testing, and fundus photography when clinically indicated. All patients were offered early molecular testing while awaiting future tests, such as electrophysiological testing or further referral visits. Molecular testing consisted of an ophthalmology-focused next-generation sequencing multigene panel. Results: The primary outcome was molecular diagnostic yield. A clinically actionable molecular diagnosis was established in 45 patients, corresponding to an overall molecular diagnostic yield of 44.6%. A total of 165 variants were identified, including 70 pathogenic, 16 likely pathogenic, 43 variants of uncertain significance, and 36 likely benign variants. Usher syndrome was the most frequent molecular diagnosis (10/45, 22.2%), comprising nine patients with USH2A-associated Usher syndrome type 2 and one patient with MYO7A-associated Usher syndrome type 1B, followed by Stickler syndrome (8/45, 17.8%), oculocutaneous albinism (3/45, 6.7%), and Alström syndrome (2/45, 4.4%). Autosomal recessive disorders represented the predominant inheritance pattern (68.9%). Conclusions: Our findings support ophthalmology-focused multigene panels as an effective first-line diagnostic strategy for patients with suspected genetic eye diseases. Early molecular testing may shorten the diagnostic odyssey, optimize resource utilization, facilitate precision diagnosis and genetic counseling, and guide future targeted deep phenotypic evaluation, prognosis, and eligibility for emerging gene-specific therapies. Full article

Atopic dermatitis is a common inflammatory skin disease affecting up to 10% of adults. Whether atopic dermatitis exhibits a strong systemic inflammatory signature remains debated. We characterized peripheral whole-blood alterations in adults with moderate-to-severe atopic dermatitis undergoing treatment with dupilumab or baricitinib therapy. Blood samples were collected at weeks 0, 4, and 16. Whole-blood proteins were measured using Olink, transcriptomic profiling was performed by RNA sequencing, and torque teno virus plasma levels were quantified by qPCR. During targeted atopic dermatitis therapy with dupilumab or baricitinib, clustering of samples based on gene expression levels showed no separation by time or treatment, with only a limited number of differentially expressed genes. Proteomic changes were similarly modest; however, treatment was consistently associated with decreased CCL17/TARC levels. Teno torque virus plasma load remained stable throughout therapy, indicating preserved immunocompetence. These findings suggest that the dominant inflammatory processes in atopic dermatitis may be largely tissue-restricted, supporting the use of peripheral biomarkers for pragmatic monitoring rather than mechanistic discovery. Full article

Resistance to BRAF inhibitors (BRAFi), alone or with MEK inhibitors (MEKi), limits durable responses in BRAF-mutant melanoma. To characterize resistance-associated cell-state evolution, we analyzed 674 melanoma cells from six mice bearing tumors from a single patient-derived BRAF V600E-mutant melanoma xenograft (PDX) lineage before treatment, during initial regression, at minimal residual disease, and at resistant regrowth. Unsupervised clustering based on a BRAF-centered network feature set comprising 2506 candidate genes identified six transcriptional states, which were characterized using transcriptomic analyses. Cluster 4 was detected exclusively at resistant regrowth, a phase marked by MAPK pathway reactivation, and exhibited enhanced JAK-STAT/interferon signaling and increased STAT1, STAT2, IRF7, IRF9, and RELB regulon activities. Network inference predicted STAT1-BRAF and IRF7-MET regulatory links, suggesting candidate routes to MAPK reactivation through BRAF overexpression and MET-mediated bypass signaling. External analyses partially recapitulated the resistance-associated transcriptional program in independent melanoma cell-line datasets and yielded limited, inconclusive evidence for the predicted STAT1-BRAF association in public perturbation datasets. Cluster 2 represented a pre-existing proliferative state whose signature was associated with shorter progression-free survival in pretreatment clinical cohorts. Together, these findings distinguish a therapy-associated acquired-resistance state from a pre-existing proliferative resistance-associated state and nominate the predicted STAT1-BRAF and IRF7-MET links for functional validation. Full article

Rabbit odontogenic abscesses are among the most challenging chronic infections encountered in exotic animal medicine because of their polymicrobial etiology, biofilm-associated persistence, and poor response to conventional antimicrobial therapy. Biofilm formation plays a central role in disease pathogenesis by promoting bacterial adhesion, extracellular polymeric substance (EPS) production, quorum sensing (bacterial cell-to-cell communication), metabolic heterogeneity, and the persister-cell formation (transiently antibiotic-tolerant bacterial subpopulations), collectively reducing antimicrobial susceptibility and contributing to treatment failure and recurrence. In addition to biofilm-mediated tolerance, antimicrobial resistance (AMR) further complicates disease management through mechanisms including horizontal gene transfer, efflux pump activation, enzymatic antibiotic degradation, reduced membrane permeability, and target modification. This review summarizes current knowledge on the microbiology, biofilm dynamics, and resistance mechanisms associated with rabbit odontogenic infections while examining recent advances in molecular diagnostics, including culture-independent sequencing technologies, metagenomics, and advanced imaging approaches. Current and emerging anti-biofilm strategies, such as local antimicrobial delivery systems, enzymatic biofilm disruption, quorum-sensing inhibitors, bacteriophage therapy, antimicrobial peptides, photodynamic therapy, and nanotechnology-based approaches, are critically discussed in the context of their potential application in rabbits. Comparative evidence from human endodontic infections and other veterinary biofilm-associated diseases highlights the translational relevance of rabbit odontogenic abscesses as a naturally occurring model for chronic polymicrobial infections. Finally, key research gaps are identified, emphasizing the need for standardized experimental models, integrated multi-omics analyses, combining genomic, transcriptomic, proteomic, and metabolomic data, longitudinal clinical investigations, and evidence-based antimicrobial stewardship. By integrating microbiology, biofilm biology, antimicrobial resistance, and One Health concepts, this review provides a comprehensive framework to support future research and improve the diagnosis, treatment, and prevention of rabbit odontogenic infections. Full article

The hepatocyte growth factor (HGF)/c-Met signaling pathway plays a central role in cellular proliferation, survival, migration, invasion, angiogenesis, and therapeutic resistance. Aberrant c-Met activation, driven by gene amplification, overexpression, activating mutations, exon 14-skipping alterations, or ligand-dependent stimulation, drives the development and progression of many solid tumors, positioning c-Met as a key target for anticancer drug development. The clinical effectiveness of c-Met-targeted treatments such as crizotinib, capmatinib, tepotinib, savolitinib, and cabozantinib has confirmed c-Met as a viable oncogenic driver for therapy, leading to the development of various next-generation inhibitors with different structures. This review provides a comprehensive perspective on small-molecule c-Met inhibitors from the perspectives of medicinal chemistry and structure-based drug design, encompassing approved drugs, investigational agents, natural-product-inspired leads, and emerging multitarget anticancer therapeutics. Particular emphasis is given to the principles of molecular recognition that govern c-Met inhibition. This includes the structure of the kinase domain, interactions at the ATP-binding site, recognition of the hinge region, and the different binding modes of Type I, Type II, and allosteric inhibitors. The design, synthesis, biological evaluation, and structure–activity relationships of diverse heterocyclic scaffolds that have shaped c-Met inhibitor discovery are critically analyzed. Key medicinal chemistry strategies, including scaffold hopping, bioisosteric replacement, conformational optimization, molecular hybridization, and multitarget pharmacophore integration, are discussed in the context of potency, selectivity, resistance management, and drug-like properties. Particular attention is given to the integration of structural biology, molecular docking, binding-mode analysis, and structure-guided optimization approaches that have enabled the development of potent c-Met-directed inhibitors. In addition, recent advances in dual- and multitarget agents that simultaneously modulate c-Met and complementary therapeutic targets, including VEGFR-2, EGFR, AXL, MER, PARP1, CDK2, and tubulin, are highlighted as promising strategies for overcoming pathway redundancy and acquired resistance. This review summarizes contemporary structure-based and medicinal chemistry principles underlying c-Met inhibitor discovery, critically evaluates the relationship between biochemical potency and therapeutic efficacy, and provides a framework for the rational design of next-generation c-Met-targeted and multitarget anticancer agents. Full article

Introduction/Objectives: Implicated in the regionalization of the anterior central nervous system (CNS) and the progression of pallial astrogliogenesis, the transcription factor gene EMX2 has been reported to be specifically silenced in several tumors, both non-neural and neural. Based on that, its overexpression has been proposed as a tool for the treatment of a subset of these malignancies, including glioblastoma. Here we tested this proposal. Methods/Results: We found that Emx2 overexpression in human glioblastoma cells transplanted into the striatum of immunotolerant mice significantly prolonged animals’ survival, outperforming their treatment by temozolomide. However, this approach did not eradicate the tumor, because of in vivo silencing of the therapeutic Emx2 transgene. Notably, silencing of this transgene (or of a reporter designed to monitor its competence to be expressed) also occurred during long-term in vitro culture of GBM cells and was exacerbated by coculture with murine pallial glia under hypoxic conditions. Remarkably, partial insulation of the transgene and the use of a specific combination of epigenetic drugs substantially counteracted the progressive activatability decline undergone by the Emx2-transgene expression reporter, suggesting a promising strategy for overcoming a major limitation of Emx2-based therapy for GBM. Conclusions: An Emx2-encoding transgene, protected by insulation and appropriate epigenetic drugs, can provide a substantial benefit in experimental therapy for glioblastoma. Full article

Klotho is a longevity-associated and tissue-protective protein involved in mineral metabolism, oxidative stress, inflammation, fibrosis, cellular senescence, and neurovascular homeostasis. However, nearly three decades after its discovery, no Klotho-based therapy has been approved, highlighting a translational gap that extends beyond biological validation. This review reframes Klotho translation as a pharmaceutical sciences challenge, focusing on how to convert Klotho into a druggable, manufacturable, deliverable, and clinically controllable therapeutic product. We summarize the isoform-specific properties of membrane-bound α-Klotho, soluble α-Klotho, and β-Klotho that are relevant to product design, and review the current clinical and preclinical landscape dominated by gene-, mRNA-, and antibody-based approaches. We further distinguish confirmed developability barriers, including renal handling and limited systemic persistence, from plausible risks common to macromolecular biologics, such as aggregation, chemical degradation, immunogenicity, and poor tissue penetration. Finally, we evaluate emerging delivery and formulation strategies, including viral and non-viral gene delivery, extracellular vesicles, hydrogels, ultrasound-targeted microbubbles, osmotic pumps, and long-acting protein engineering. An integrated roadmap combining molecular engineering, disease-specific delivery, pharmacokinetic/pharmacodynamic biomarkers, manufacturability assessment, and repeated-dose safety evaluation may help transform Klotho from a promising anti-aging molecule into a clinically viable biologic platform. Full article

Background/Objectives: Endothelial dysfunction is increasingly recognized as a key contributor to vascular complications in β-thalassemia but remains insufficiently integrated into clinical assessment and therapeutic trial design. This review summarizes current evidence on the mechanisms, biomarkers, vascular imaging findings, and therapeutic perspectives of endothelial dysfunction across the clinical spectrum of β-thalassemia. Methods: A focused PubMed search was conducted using predefined terms related to endothelial dysfunction, nitric oxide, oxidative stress, adhesion molecules, extracellular vesicles, vascular imaging, and therapeutics in β-thalassemia. Original studies and systematic reviews evaluating endothelial dysfunction, vascular biomarkers, imaging, or cardiovascular outcomes in β-thalassemia were included. Results: Endothelial dysfunction arises from the interplay of hemolysis-driven nitric oxide depletion, free heme- and iron-mediated oxidative injury, chronic inflammation, extracellular vesicle-mediated vascular activation, and hypercoagulability. Meta-analyses demonstrate significant elevations in intercellular adhesion molecule-1, vascular cell adhesion molecule-1, E-selectin, P-selectin, and endothelin-1. Emerging biomarkers include endothelial activation and stress index, adipocytokines, and serum metabolomics. Vascular imaging demonstrates impaired flow-mediated dilation, increased carotid intima-media thickness, elevated pulse-wave velocity, and pulmonary hypertension, with distinct vascular phenotypes in transfusion-dependent thalassemia (TDT) and non-transfusion-dependent thalassemia (NTDT). Iron chelation, luspatercept, mitapivat, and curative gene-based therapies have strong biological rationale for improving endothelial function, although vascular endpoints have rarely been evaluated. Conclusions: Endothelial dysfunction is a multidimensional and potentially modifiable component of β-thalassemia vasculopathy. Future clinical trials should incorporate standardized endothelial biomarkers and vascular imaging as predefined endpoints and evaluate TDT and NTDT separately to advance mechanism-based vascular therapies. Full article