Search Results (11,744)

To solve the problem where the low contrast and extremely small target size in the three-sky-screen target-integrated linear array CCD sensor measurement system under low-illumination conditions make it difficult to accurately identify projectile targets, this paper proposes a method of Frequency-Enhanced and Multi-scale Feature Fusion YOLOv11 (FEMFF-YOLOv11). It introduces a frequency-domain enhancement module in the backbone to improve feature discriminability, and deformable offset convolution is incorporated to handle geometric deformations. It also adds a multi-scale attention aggregation module in the neck to strengthen weak target features and suppress false targets such as near-lens flying objects. The detection head is optimized by replacing the low-resolution P5 layer with a high-resolution P2 layer for better projectile target localization. Experiments are conducted on a self-built linear array CCD projectile dataset. The results demonstrate that compared with YOLOv11 and other mainstream algorithms, our method achieves 87.35% precision and 85.13% recall under 300 lx low-illumination conditions. It also maintains 85.91% precision and 82.56% recall even at 50 lx, significantly outperforming all competitors. Full article

Pinoresinol–lariciresinol reductase (PLR) catalyzes a key reductive step in plant lignan biosynthesis. Although flax (Linum usitatissimum L.) seeds are rich in lignans, the PLR gene family and its relationship with lignan accumulation during seed development remain insufficiently characterized. Here, 18 LuPLR genes were identified from the telomere-to-telomere genome assembly of the flax cultivar ‘Gaosi’ using BLASTP and HMMER searches. Their phylogenetic relationships, gene structures, conserved motifs, chromosomal distribution, duplication and syntenic relationships, promoter cis-acting elements, predicted microRNA targets, and expression profiles were analyzed. Seed lignan content at 5, 10, 20, 30, and 40 days after flowering was quantified by high-performance liquid chromatography, and candidate genes were screened using quantitative real-time PCR and Pearson correlation analysis. The LuPLR genes were unevenly distributed across eight chromosomes and exhibited substantial structural and regulatory diversity. Seed lignan content varied dynamically and reached its highest level at 40 days after flowering. LuPLR10, LuPLR11, and LuPLR16 showed positive correlations with lignan content. Among them, LuPLR10 was prioritized because its developmental expression pattern most closely paralleled lignan accumulation. Subcellular localization analysis indicated that the LuPLR10 protein was predominantly associated with chloroplasts. These findings provide a genomic framework for the flax PLR family and identify LuPLR10 as a priority candidate for further functional investigation. Full article

Banana bunchy top virus (BBTV) is a devastating pathogen threatening global banana production. The plant ubiquitin–proteasome system (UPS) governs immune signaling and is frequently subverted by invading viruses, yet the molecular mechanism through which BBTV interferes with host UPS remains unclear. Here, we show that BBTV nuclear shuttle protein (NSP) serves as the core viral effector to disrupt banana ubiquitination homeostasis. RT-qPCR time-series assays confirmed that BBTV infection dynamically remodels the transcription of eight phylogenetically divergent RING-type E3 ubiquitin ligases: four subfamily I E3-SIS3 paralogs and E3-HIP1 are significantly upregulated at 14 dpi and 21 dpi, while E3-BOI and E3-RHA1B are suppressed at 21 dpi. Transient expression screening of all six BBTV-encoded proteins verified that only NSP reproduces the UPS perturbation signature triggered by viral infection. Cross-species sequence alignment identified an evolutionarily conserved FNGSF motif within NSP orthologs of all Nanoviridae members. Alanine substitution mutagenesis (NSP^AAAAA) completely abolished NSP’s capacity to alter E3 ligase transcription. Western blot assays further validated that wild-type NSP induces massive accumulation of ubiquitinated host proteins, whereas the FNGSF-deficient mutant does not disrupt cellular ubiquitination. Phylogenetic analysis revealed that NSP-targeted E3 ligases share low overall sequence similarity but retain conserved catalytic RING domains, indicating that NSP exerts broad-spectrum regulatory effects on host UPS via the FNGSF motif. Collectively, this study reveals a novel pathogenic strategy whereby BBTV NSP recruits diverse host RING E3 ligases via its conserved FNGSF motif to dysregulate plant ubiquitination and elicit plant pathogenicity. Our findings provide two promising targets—the NSP FNGSF motif and defense-associated E3-SIS3 ligases—for developing antiviral agents and breeding BBTV-resistant banana germplasm. Full article

Drosophila melanogaster shares approximately 75% of human disease-related genes and possesses sophisticated genetic toolkits, including GAL4/UAS, CRISPR-Cas9, and RNA interference (RNAi), making it a rapid, cost-effective, and genetically tractable in vivo platform for natural products (NPs) discovery. This review systematically summarizes the modeling strategies, pathological mechanisms, and therapeutic applications of Drosophila models for six major human diseases, including type 2 diabetes, nephrolithiasis, inflammatory bowel disease, cancer, Alzheimer’s disease, and Parkinson’s disease. Cross-disease analysis identifies five evolutionarily conserved signaling networks—IIS/PI3K/Akt/FOXO, JNK/JAK/STAT, Nrf2/Keap1, mTOR/TORC1, and IMD/Toll—as common molecular targets of bioactive NPs, providing a unified mechanistic framework for understanding their multi-target pharmacological activities and broad therapeutic potential. Critically, we propose a generalizable integrated stepwise pipeline: high-throughput fly screening of crude extracts, bioassay-guided isolation of active monomers, genetic mechanistic dissection via RNAi and mutant rescue, and layered validation in human cells and selective mammalian models. This pipeline addresses key challenges in NPs research, including the identification of bioactive constituents and mechanistic validation, while improving screening efficiency and translational potential. Overall, this review establishes a multi-disease-applicable framework linking disease modeling, conserved signaling mechanisms, and translational pharmacology, providing practical guidance for future mechanism-driven NP discovery and preclinical development using Drosophila. By leveraging Drosophila genetics to bridge evolutionary conservation and human pathology, this framework offers a powerful, paradigm-shifting strategy to accelerate mechanism-driven NP discovery and preclinical development. Full article

Background/Objectives: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and is associated with ischemic stroke, systemic thromboembolism, heart failure, and mortality. Although oral anticoagulation (OAC) remains the cornerstone of stroke prevention, long-term therapy may be limited by bleeding risk, contraindications, intolerance, nonadherence, or thromboembolic events despite treatment. Left atrial appendage closure (LAAC) has therefore emerged as a non-pharmacological alternative for selected patients with nonvalvular AF. This review aimed to synthesize current evidence on LAAC, focusing on comparative efficacy versus OAC, device evolution, imaging-guided strategies, antithrombotic management, procedural optimization, unresolved challenges, and emerging technologies. Methods: This state-of-the-art narrative review was informed by targeted, non-systematic searches of PubMed and Scopus for publications from January 2009 to June 2026. Evidence was selected purposively to represent clinically relevant guidelines, randomized trials, registries, comparative observational studies, systematic reviews, meta-analyses, imaging studies, device-comparison studies, and reports of emerging technologies. The selected evidence was synthesized narratively; no exhaustive screening process, PRISMA flow diagram, formal risk-of-bias assessment, or quantitative synthesis was performed. Results: Randomized evidence was context dependent. OPTION supported LAAC as an alternative to oral anticoagulation in selected anticoagulation-eligible patients undergoing atrial fibrillation ablation. CHAMPION-AF established noninferiority of Watchman FLX to non–vitamin K antagonist oral anticoagulants for its composite efficacy endpoint in a predominantly moderate-risk, anticoagulation-eligible population and demonstrated less non-procedural bleeding, although ischemic stroke occurred numerically more often after LAAC. In contrast, CLOSURE-AF did not establish noninferiority of LAAC to physician-directed medical therapy in an older population at high risks of both stroke and bleeding. These findings indicate that the comparative value of LAAC depends strongly on patient selection, comparator therapy, endpoint composition, procedural risk, and trial design. Observational, registry, and emerging evidence was considered supportive or hypothesis-generating rather than equivalent to randomized evidence. OPTION enrolled only patients undergoing or recently undergoing AF ablation who were suitable for anticoagulation. CHAMPION-AF included 3000 anticoagulation-eligible patients but had relatively low baseline bleeding risk, while CLOSURE-AF studied 912 substantially older, higher-risk patients and did not meet its noninferiority criterion. Conclusions: LAAC has evolved into a precision-guided intervention integrating patient risk, left atrial appendage anatomy, device choice, imaging, antithrombotic therapy, and structured surveillance. Further studies are needed to optimize patient selection, standardize post-procedural therapy, and clarify its long-term role compared with contemporary direct oral anticoagulant therapy. Full article

Campylobacter jejuni and Campylobacter coli are major foodborne pathogens whose accurate species-level discrimination is important for outbreak investigations as well as rapidly assessing putative antimicrobial resistance profiles and the pathogenic potential of the bacterium. To facilitate species differentiation, a novel assay that integrates the nucleic acid-sensing capability of the oligo-Alpha with the multiplexing capacity of the AlphaPlex bead chemistries was developed. This wash-free system (designated as oligo-Plex) enables the detection and differentiation of C. jejuni and C. coli within a single reaction and can be completed in approximately 75 min. It works by using custom oligonucleotides modified for bead attachment, which hybridize sequentially along Campylobacter’s glyA gene and ultimately bridge the donor and acceptor beads. Improvements in assay stringency were made by increasing incubation temperatures, thus allowing the resolution of target from non-target. Comparisons of FITC–europium and DIG–terbium labeling systems revealed superior performance by the FITC–europium pair and suggested that helical positioning and steric accessibility likely influence donor–acceptor efficiency. Maximized signal separation was seen when using terbium for the detection of C. coli and europium for the detection of C. jejuni. Testing was performed in a Tris-based buffer and milk to confirm matrix tolerance, with potential areas for further optimization identified. The oligo-Plex presented here establishes a streamlined, adaptable platform suitable for high-throughput screening of multiple nucleic acid analytes that is readily extendable to a diverse array of pathogens through appropriate oligo selection. Full article

Reliable identification of pest developmental stages provides a foundation for investigating aphid development and adaptive mechanisms and informs the selection of timely interventions in integrated pest management. In this study, eight morphological indicators of Uroleucon gobonis were distinguishing under a stereomicroscope. Additionally, six candidate genes identified from transcriptomic data were selected to characterize their expression profiles across five developmental instars. These results showed that the body length enabled distinguishing of the aphids from the first instar to the fourth instar, while antennal length and cauda length facilitated distinction between the second–fourth instar nymphs; cornicle length allowed separation of the third instar and subsequent instars. In contrast, body width permitted discrimination primarily between the first and second instars; head width, foreleg length, and hindleg length exhibited substantial overlap across instars, limiting their utility for instar discrimination. Elevated expression of DN1031, DN1019, and DN1093 was a prominent feature of first instar nymphs. DN1098 was persistently increased from the first to the third instar, which facilitated discrimination among these three developmental stages. The fourth instar was characterized by the concurrent down-regulation of DN1098 and DN1031 relative to the third instar, whereas adults exhibited a distinct expression peak of DN136 compared to other developmental stages. This study establishes an integrated instar-identification system for U. gobonis, combining rapid morphological screening with molecular characterization. This framework provides a valuable methodological basis for investigating developmental plasticity and supports the development of targeted pest management strategies. Full article

Aggregate origin–destination data and summary load factors do not identify train-specific flows; imposing each load factor as an exact margin can therefore overstate precision. We develop an auditable high-speed rail pricing framework combining pooled passenger-kilometer entropy completion, an occupancy-aware pivot logit, link-load equilibrium, and exact-grid Pareto enumeration. Historical train shares guide a sensitivity-tested prior, and target elasticities index fare response. For a reconstructed Beijing–Wuhan case, 97,336 discount vectors are evaluated in each of three core scenarios and candidates are screened across 729 crossed baseline and behavioral scenarios. Under the reference scenario (unit elasticity, crowding-equivalent ratio 0.10, threshold 0.80), the closest-to-ideal admissible vector $(0.94,0.99,0.97)$ increases modeled-service revenue by 0.106% and yields a full-corridor-fare-equivalent surplus gain of 0.803%, with maximum link occupancy of 77.27%. It is admissible in only 368 scenarios and reaches 104.45% occupancy in the most adverse case; only the status quo is admissible in all scenarios. The framework thus identifies scenario-specific opportunities while separating exact numerical evaluation from empirical identification and operational robustness under aggregate-data limitations. Full article

Electric dynamometer test benches generate heterogeneous multi-channel logs whose structural completeness, physical consistency, and operating-condition support vary across files. We propose Coupling-Gated Data Quality Index (CG-DQI) sample weighting, a fold-local preparation protocol for 60 s next-window temperature-change prediction. Deployable weights use training-side structural and physical quality signals, while a target-magnitude coupling gate screens candidate association with the absolute target. The dataset contains 30,093 valid windows from 134 files and 30 date-defined campaigns. File-level leave-one-file-out validation reduced Ridge MAE from 0.7035 to 0.6932 °C and the mean MAE across three fixed Random Forest initializations from 0.4556 to 0.4489 °C per window. Strict nested leave-one-campaign-out analysis retained sparse CG-DQI in all 30 folds and yielded a campaign-level Ridge MAE difference of 0.0152 °C with a 95% bootstrap confidence interval (CI) of 0.0054–0.0309, while the 99th percentile absolute error (P99) increased by 0.0710 °C. Fixed-parameter XGBoost preserved a positive mean MAE direction, although its campaign interval crossed zero. CG-DQI, therefore, provides a traceable MAE-oriented preparation option within the present bench and campaign range; tail-sensitive and cross-device use requires an explicit constraint or recalibration. Full article

A naive Bayesian classifier (NBC) combined with principal component analysis (PCA) effectively differentiates the dose-dependent effects of certain groups of psychoactive drugs based on their impact on the amplitude–spectral characteristics of electrocorticograms (ECoG) in rats. This approach has been shown to be useful for pharmacological screening of agents with unknown or poorly understood activity. Despite previously obtained optimistic results, classification determination for some drugs was inaccurate, necessitating the search for possible ways to improve the predictive effectiveness of the proposed algorithm. One possible approach would be to use as input quantitative data not only the impact of the psychoactive drugs studied on the amplitude–spectral characteristics of ECoG but also connectivity changes, including the average coherence power of different pairs of leads. The aim of this study was to compare the accuracy of NBC in classifying the pharmacological mechanism of action of agents with well-known mechanisms (test set) using pharmaco-EEG data on changes in the amplitude–spectral characteristics of ECoG, coherence, and the combined use of two data sets. Materials and methods. Experiments were performed on Wistar rats with chronically implanted ECoG electrodes. The training set, relative to which the effects of the pharmacological agents from the test set were classified, were the matrices of effects of 12 pharmacological agents: the NMDA antagonist dizocilpine, the D2/D3 antagonists haloperidol and sulpiride, the M-anticholinergic tropicamide, the H1/5HT2A receptor blocker hydroxyzine, the acetylcholinesterase inhibitor galantamine, the alpha-2 adrenergic agonist dexmedetomidine, the alpha-2 adrenergic antagonist atipamezole, the adenosine receptor blocker caffeine and the GABA-mimetics aminophenylbutyric acid (phenibut), bromdihydrochlorophenylbenzodiazepine (phenazepam) and 5-ethyl-5-phenyl-2,4,6(1H,3H,5H)-pyrimidinetrione. The test set included various drugs with tropism for the targets of the training set drugs: dopamine receptor antagonists chlorpromazine, droperidol, tiapride and raclopride, H1-histamine blockers diphenhydramine and promethazine, 5-HT2-receptor blockers ritanserin and glemenserin, acetylcholinesterase inhibitor ipidacrine, alpha2-adrenergic receptor antagonist yohimbine, alpha2-adrenergic agonists medetomidine and xylazine, GABA-mimetics 5-ethyl-5-(1-methylbutyl)-2,4,6(1H,3H,5H)-pyrimidinetrione and chloral hydrate. The analysis of the ECoG signal included the calculation of 132 amplitude–spectral characteristics and 75 coherence indicators, which, using the PCA, led to new integrative indicators used for further classification of the NBC. Results and discussion. For each drug in the test set, the median similarity probability with a particular group from the training set was calculated, which was used to assess the classification quality. It was found that, when using the amplitude–spectral characteristics of ECoG, the proposed methodological approach allows for the identification of the ECoG effects of several groups of psychoactive drugs, including D2/D3-dopamine, M-cholinergic, H1-histamine, and 5-HT2-serotonin receptor blockers, AChE inhibitors, GABA-mimetics, and alpha-2-adrenergic receptor agonists and antagonists. This approach enabled the correct classification of 18 of 24 groups in the test set. When using changes in coherence indices as the initial data, the classification accuracy also amounted to 18 of 24 groups. When combining the two data sets, the number of correctly identified NBC groups was 20 of 24 groups. When comparing the classification during training (confusion matrix), it was found that coherence data or adding coherence data to the data based on changes in amplitude–spectral characteristics leads to a statistically significant (p < 0.01 in both cases) increase in accuracy. Conclusions. The obtained data demonstrated high accuracy in classifying the pharmacological activity of the test sample drugs using any of the three compared approaches. Despite the lack of statistically significant differences between them, classification based on the combined dataset demonstrated a higher number of “correct” similarities. This allows us to recommend the approach based on combined data of drug effects on amplitude–spectral characteristics and coherence as the most promising for further studies using pharmaco-EEG screening. Full article

Bauxite mining causes severe soil degradation in the ecologically fragile karst region of Southwest China, yet targeted vegetation restoration schemes remain poorly developed. This study aimed to screen promising selected restoration species and preliminarily explore their soil improvement characteristics in karst bauxite mine wastelands through a field observational survey. We investigated six vegetation-soil conditions at 0–10 cm topsoil (two-year monocultures of Robinia pseudoacacia, Ligustrum lucidum, Zea mays, Miscanthus sinensis, topsoil from >15-year Z. mays with straw return, and unvegetated bare land), alongside paired 10–20 cm subsoil from the same long-term Z. mays stand as a depth-profile reference, and analyzed soil physicochemical properties, enzyme activities, and bacterial/fungal communities via high-throughput sequencing. Results showed that vegetation cover neutralized strongly acidic mine soil and significantly increased soil organic matter (SOM), total nitrogen (TN), and available nutrients compared with the bare control (p < 0.05). The long-term Z. mays cropland showed the strongest soil nutrient accumulation, with topsoil SOM, available phosphorus, and available potassium, increased by 428.6%, 250.0%, and 65.3%, respectively, relative to the bare control. Notably, the subsoil of long-term Z. mays also maintained high nutrient levels, but its absolute values are not directly comparable with topsoil treatments due to different sampling depths. All vegetation conditions elevated soil enzyme activities and microbial alpha diversity and significantly shifted bacterial and fungal community structure (beta diversity) compared with the control. Several bacterial phyla (including Chloroflexi and Proteobacteria) that have been associated with carbon-cycling functions in prior studies were relatively more abundant in revegetated soils; however, their functional roles in this system remain to be verified. Redundancy analysis identified SOM, TN, and available potassium as key environmental correlates of bacterial community variation. Overall, the long-term crop–straw return pattern shows comprehensive soil improvement effects, providing observational baseline data and reference for ecological restoration of karst bauxite mining areas in Southwest China. Full article

Drug discovery is still an expensive and time-consuming process where finding the right drug associations is important for therapeutic development. In this paper, a new system is proposed for drug design called PharmaGraphFormer (PGF). It consists of five stages: (i) Data acquisition and preprocessing (DAP), (ii) Feature extraction and feature fusion (FEF), (iii) Molecular representation (MR), (iv) Multi-task prediction, and (v) Explainable artificial intelligence (XAI). This study employs a hybrid graph neural network (GNN)-transformer architecture that combines structural and sequence-based representations. Through DAP, several processes are executed, including the imputation or removal of missing values, outlier rejection, and class balancing. Next, through FEF1, features are extracted to represent the input data efficiently. Initially, compound-protein features are generated to document the interactions and relationships between chemical compounds and their corresponding target proteins. Secondly, drug characterizations are computed to encapsulate the physical, chemical, and structural attributes of each drug. After that, MR is performed using a graph-based molecule representation. Then, a novel model integrating GNNs and graph transformers, termed GNN-T, is proposed. Initially, GNNs represent the most promising deep learning models adept at processing non-Euclidean data. The Graph Transformer layer enhances atom representations by consolidating the representations of adjacent atoms through an attention mechanism. Finally, XAI is applied to explain the internal mechanisms of AI systems, rendering them comprehensible and interpretable. Across five independent runs, the proposed model achieved an accuracy of $0.963\pm 0.002$, a precision of $0.971\pm 0.002$, a recall of $0.958\pm 0.003$, an F1-score of $0.964\pm 0.002$, and a ROC-AUC of $0.993\pm 0.001$. These results demonstrate an outstanding performance when compared with all other models and emphasize that the proposed model is reliable in solving the problems of prioritizing compounds in line with the latest developments in AI-powered virtual screening and drug–target interaction modeling. Full article

The global emergence of multidrug-resistant fungal pathogens, including Candida auris, Candida albicans, Aspergillus fumigatus, Cryptococcus neoformans, and Pneumocystis jirovecii, poses a growing threat to public health, particularly among immunocompromised individuals. The limited number of available antifungal drug classes and the rapid evolution of resistance mechanisms, including target-site mutations, efflux pump activation, biofilm formation, metabolic adaptation, and stress-response signaling, have substantially reduced treatment efficacy. This review provides a comprehensive overview of current antifungal therapies, their limitations, and emerging molecular targets for next-generation antifungal drug discovery. We highlight promising targets involved in fungal cell wall biosynthesis, membrane integrity, mitochondrial metabolism, virulence regulation, and host–pathogen interactions, emphasizing their interconnected roles within adaptive resistance networks. Attention is given to small-molecule isothiazolone-based inhibitors, including phosphoglucomutase-targeting compounds, as novel candidates capable of disrupting multiple fungal survival pathways. We further discuss advances in combination therapies, anti-virulence approaches, nanotechnology-based delivery systems, and artificial intelligence-driven drug discovery pipelines that integrate multi-omics data, structural modeling, molecular docking, and virtual screening to accelerate therapeutic development. These advances support a transition from conventional single-target strategies toward systems-level, precision-guided antifungal therapies, providing a framework for overcoming multidrug resistance and improving clinical outcomes in invasive fungal infections. Full article

Candida albicans biofilms are a major cause of persistent infections and contribute to antifungal resistance as well as limitations in drug delivery. Targeting virulence traits such as biofilm formation and hyphal transition represents an effective strategy for controlling fungal pathogenicity without exerting strong selective pressure on planktonic growth. In this study, a library of structurally diverse benzophenone derivatives was screened to identify compounds with antibiofilm and anti-hyphal activities against azole-resistant C. albicans. Most benzophenone derivatives exhibited weak antifungal activity (MIC ≥ 200 µg/mL). However, several halogenated benzophenones markedly suppressed biofilm formation. Among them, decafluorobenzophenone at 10 µg/mL displayed the strongest inhibition, reducing biofilm formation to approximately 1–2% of control levels while maintaining substantial planktonic cell viability. Microscopy confirmed hyphal suppression, while qRT-PCR showed a 36-fold reduction in ALS3 expression. These findings indicate that multi-halogenated benzophenones act primarily as anti-virulence agents targeting biofilm formation and hyphal development. Molecular docking suggested a possible interaction of decafluorobenzophenone with the Als3 binding pocket. Decafluorobenzophenone showed low toxicity, with unaffected Caenorhabditis elegans viability at 10 µg/mL, plant germination at 100 µg/mL, and only slight hemolysis at 100 µg/mL. The results highlight halogen substitution as a key structural determinant and identify benzophenone scaffolds as promising leads for developing novel antibiofilm strategies against azole-resistant Candida infections. Full article

Background and Objectives: Stenting isolated Medina 0,0,1 ostial side-branch lesions can result in geographic miss or protrusion into the main vessel. Drug-coated balloon (DCB) angioplasty avoids a permanent implant, but lesion-specific outcome data remain limited. We assessed procedural performance, bailout stenting, and 6- and 12-month outcomes after an intended DCB-only strategy. Materials and Methods: In this retrospective, single-center observational cohort study, we screened 170 patients who underwent coronary DCB treatment at a single center between 1 January 2023 and 31 July 2025. Thirty-one patients with de novo isolated Medina 0,0,1 lesions were included. The primary endpoint was 12-month target lesion failure (TLF), defined as cardiovascular death, target-vessel myocardial infarction, or clinically driven target lesion revascularization (TLR). Results: DCB-only strategy success was achieved in 29/31 patients (93.5%), post-DCB angiographic success in 29/31 (93.5%), and study-defined overall procedural success in 31/31 (100%). Final TIMI grade 3 flow after DCB was present in 30/31 patients; no flow-limiting dissection occurred. Two patients required bailout stenting, one because of deterioration to TIMI grade 2 flow and one because of residual stenosis >30% with recoil. Thirty patients were alive with documented follow-up at 12 months; one patient died from a non-cardiovascular cause at month 1. No TLF was recorded within 12 months. One clinically driven TLR for target-lesion restenosis occurred at month 20, outside the prespecified window. Conclusions: In this selected cohort, an intended DCB-only strategy avoided stent implantation in most patients and had a low bailout rate. The findings support procedural feasibility but do not establish comparative efficacy. Larger prospective studies are required. Full article