Search Results (358)

Urban environments in developing countries remain affected by legacy asbestos-containing materials, yet integrated assessments of multi-pathway asbestos release and environmental mobilization integrated with demographic distribution remain limited. This study aimed to develop a spatially explicit framework to assess environmental deterioration and asbestos-related environmental hazard where multiple asbestos release pathways converge in a post-ban urban setting, using Cartagena, Colombia, as a case study. A multi-pathway approach was implemented, combining source characterization of asbestos-cement (AC) roofs through microvacuum sampling, analysis of roof runoff and drinking water, spatial distribution of AC pipelines, and demographic data at the neighborhood scale. A total of 72 roof surface samples were collected, of which 92% showed detectable asbestos fibers, with concentrations reaching up to 326 × 10⁶ structures/cm². Runoff water analysis indicated 85% detection, with average concentrations of 3.5 ± 3.14 million fibers per liter (MFL). Drinking water samples showed 11% positivity, with lower concentrations (mean 1.01 ± 1.59 MFL). Spatial analysis revealed that approximately 9.5% of the urban area exhibited high airborne release potential and 3.1% exhibited high runoff-related hazard, while integrated spatial prioritization identified 5.59% of the city as high priority for intervention. Results indicated that less deteriorated roofs exhibited higher surface fiber availability, suggesting that emission potential is not directly proportional to visible degradation. The integration of environmental and demographic data supported the identification of critical hotspots where multiple asbestos release pathways converge. The proposed methodology provides a novel framework for multi-pathway asbestos spatial prioritization in urban environments and highlights the need for source-based monitoring approaches. These findings support the development of targeted mitigation strategies in cities with widespread legacy asbestos infrastructure. Full article

The radial structure and azimuthal asymmetry of tropical cyclone (TC) eyewall winds are critical for intensity change and wind-related hazards, yet they remain difficult to characterize using conventional observations. Using multi-platform C-band synthetic aperture radar (SAR) wind fields and collocated Stepped Frequency Microwave Radiometer (SFMR) wind speed and rain-rate observations, this study examined TC inner-core structure, eyewall asymmetry, and rainfall-dependent wind retrieval uncertainty for 51 TCs and 130 SAR scenes. The TC inner-core structure was characterized using a best-track-constrained center refinement and quality control procedure, in which the storm center was refined from the minimum of a Gaussian-smoothed SAR wind field and scenes were screened by eye/annulus sampling, eye–eyewall contrast, and annular wind organization. Of the 130 SAR scenes, 53 were retained for refined-center evaluation, and the 32 QC-passed scenes were used for the primary storm-centered structural analysis. The RMW showed a weak tendency to decrease with an increasing SAR-derived maximum azimuthal-mean wind speed, and the normalized wavenumber-1 asymmetry at the RMW decreased in stronger storms. Under strict temporal collocation ($\left|\Delta t\right|\le 30$ min), the SAR–SFMR comparison achieved an RMSE of 4.22 m s⁻¹, a bias of −1.61 m s⁻¹, $R^2$ = 0.82, and a regression slope of 0.90. Rainfall-related SAR–SFMR mismatch was most evident around the eyewall and adjacent outer-eyewall region, indicating the need to consider center uncertainty, scene suitability, temporal collocation, and rain-sensitive retrieval effects when interpreting SAR-derived TC inner-core structure. Full article

Bamboo, as a rapidly renewable and sustainable material, has gained increasing attention in the construction, furniture, automotive interiors, and packaging industries due to its excellent mechanical properties, light weight, and environmental friendliness. However, the inherent flammability of bamboo, characterized by its porous structure and high hemicellulose content, poses a significant fire hazard that severely limits its wide application. This review systematically synthesizes recent advances in the fire performance and flame-retardant modification of bamboo-based materials. First, the thermal degradation behavior and combustion mechanisms of bamboo are discussed in relation to its primary chemical constituents, including cellulose, hemicellulose, and lignin. Subsequently, various flame-retardant strategies are reviewed, including inorganic flame retardants, phosphorus–nitrogen systems, nanomaterial-based additives, and bio-based flame-retardant approaches. The effectiveness of different modification techniques, such as impregnation treatment, adhesive modification, and surface coating, is also analyzed. Future research directions are proposed, emphasizing the development of environmentally friendly flame-retardant systems, multifunctional modification strategies, and the design of high-performance flame-retardant bamboo-based materials. This review aims to provide a comprehensive framework for advancing the fire safety design and sustainable application of bamboo-based materials. Full article

Unmanned aerial vehicles (UAVs) have emerged as flexible platforms for environmental monitoring, including water sampling in hard-to-reach or hazardous areas. However, most existing UAV-based sampling solutions are limited to single-point collection or rely on complex fluid routing mechanisms that increase the risk of leakage and cross-contamination. This paper presents a novel ribbon-based multisampling capsule that enables sequential water collection from multiple locations during a single UAV deployment. The proposed mechanism employs a motor-driven ribbon with a single movable orifice that is sequentially aligned with individual sampling containers, allowing controlled intake and closure through a combination of hydrostatic pressure and mechanical sealing. A functional prototype was developed and experimentally evaluated to assess sampling feasibility and operational robustness. Experimental results demonstrate that improvements in sealing significantly reduce leakage events and eliminate dispenser-related carry-over, while enabling repeatable multi-point sampling. In addition, exploratory computational fluid dynamics (CFD) simulations were conducted to characterize hydrodynamic loads acting on the capsule and to support future design iterations, rather than to provide fully converged hydrodynamic validation. The proposed solution offers a practical, lightweight, and mechanically simple approach to UAV-assisted multi-point water sampling, with clear potential for further optimization and field deployment. Full article

Rapid and reliable seismic monitoring requires accurate waveform inference, together with robustness to noise, incomplete sensing, and unstable predictions. This study investigates a quality-controlled, waveform-centered, AI-assisted framework for seismic event detection, P- and S-phase picking, graph-aware inter-station refinement, and rapid hazard-related characterization. The framework includes optional DAS, MEMS, and high-rate GNSS branches; however, the primary empirical validation is based on real waveform-centered IRIS records from the Almaty seismic region, not on a fully synchronized multimodal field deployment. The dataset includes seven seismic stations, HHZ waveforms sampled at 100 Hz, 219 seismic events, 1260 event traces, and 240 s P-centered windows from 1 January 2023 to 31 December 2024. Optional auxiliary branches are evaluated through controlled branch-availability, reduced-input, fallback, and stress-test scenarios. Under the standard-condition benchmark, the proposed framework achieved a precision of 0.941, recall of 0.932, F1 score of 0.936, false-alarm rate of 0.051, detection latency of 173 ms, and P- and S-pick mean absolute errors of 31 ms and 54 ms. Under controlled low-SNR testing, it retained an F1 score of 0.846. The findings support waveform-centered, quality-controlled monitoring, while broader cross-domain and fully synchronized multimodal validation remain necessary. Full article

Brominated flame retardants (BFRs) are widely used in automotive polymers and electronic components, yet vehicles remain an under-characterized and potentially high-exposure microenvironment, particularly in hot climates. This study provides the first comprehensive assessment of BFR occurrence, sources, and exposure risks in vehicle dust from Saudi Arabia, addressing a critical regional data gap. This study systematically investigates the occurrence, compositional patterns, sources, and human exposure risks of polybrominated diphenyl ethers (PBDEs) and selected alternative BFRs in dust from 80 vehicles (domestic cars and taxis; model years 2015–2022) operating in Jeddah, Saudi Arabia. Dust samples were collected using a standardized vacuuming protocol, extracted and cleaned using solvent extraction and silica SPE, and analyzed via GC–NCI–MS. Both legacy PBDE congeners and emerging alternatives (including DBDPE and TBB) were consistently detected, with BDE-209 dominating the overall BFR burden with mean concentrations of 6560 ng/g in domestic vehicles and 5454 ng/g in taxis, with maximum values reaching 220,860 ng/g. Lower-brominated PBDEs occurred at substantially lower concentrations, reflecting the ongoing global transition away from Penta- and Octa-BDE formulations. Taxis exhibited generally higher concentrations than domestic vehicles, likely due to prolonged occupancy, increased usage intensity, and enhanced dust resuspension dynamics. Multivariate analysis (PCA and correlation) revealed two distinct source categories: (i) legacy Penta-BDE-related congeners associated with polyurethane foam and textile materials and (ii) high-brominated PBDEs and DBDPE linked to hard plastics and electronic components. Human exposure assessment demonstrated that dust ingestion is the dominant exposure pathway, while dermal and inhalation routes contribute minimally. Non-carcinogenic hazard indices (HI) were well below unity for all compounds (HI < 1.67 × 10⁻⁶), and incremental lifetime cancer risks (ILCR) for BDE-209 remained within or near accepted risk thresholds (7.52 × 10⁻⁶–1.04 × 10⁻⁵), although occupational exposure among taxi drivers was consistently higher. Overall, the results demonstrate that modern vehicle cabins act as significant microenvironments for chronic BFR exposure, particularly under high-temperature conditions. Despite generally low estimated risks, the combined effects of chemical persistence, bioaccumulation potential, and mixture toxicity—amplified by extreme in-cabin temperatures—highlight vehicles as overlooked yet significant exposure environments. These findings provide the first comprehensive dataset for the Arabian Peninsula and emphasize the need for climate-sensitive exposure assessment, safer material design, and targeted mitigation strategies in vehicle interiors. Full article

Programs aimed at reducing the CO₂e footprint associated with the residential building stock should be informed by several key elements, including the expected evolution of the occupied housing stock, projected population dynamics driven by socio-economic and cultural factors, available implementation budgets, and the specific costs of intervention measures. However, in regions characterized by high seismic hazard, the occurrence of a major earthquake may substantially alter the projected outcomes of emission-reduction programs, as seismically vulnerable buildings may experience severe structural damage. This paper presents the results obtained by applying an integrated methodology for assessing the CO₂e footprint associated with residential buildings. The methodology accounts for emissions related to building operation (space heating), energy-renovation interventions, and seismic retrofitting works. While the proposed approach is applicable to other seismically exposed regions, the results presented herein refer specifically to the residential building stock in Romania and its local seismic conditions. The methodology integrates information on the existing building stock, the projected evolution of population and the built environment, energy consumption associated with building operation, changes in the energy fuel mix, construction practices across different historical periods with respect to energy efficiency and seismic protection, and the CO₂e footprint associated with energy renovation and seismic retrofitting. In addition, the analysis explicitly considers the potentially negative effects of a major earthquake, particularly the disruption of greenhouse-gas emission-reduction programs. The assessment is conducted at the building stock level and is based on combining building stock evolution with average, representative CO₂e intensity values for heating, energy renovation, and seismic retrofitting. The results demonstrate that when the sole objective is to reduce the CO₂e footprint associated with space heating, renovation of the energy fuel mix represents the most effective measure. At the same time, the analysis shows that the CO₂e footprint generated by construction works for energy renovation and/or seismic retrofitting represents only a small fraction of the emissions associated with building operation. The occurrence of a major earthquake is likely to jeopardize overall environmental objectives by increasing emissions related to building operation, energy renovation, reactive seismic retrofitting, and replacement of severely damaged buildings. Conversely, systematic preventive seismic retrofitting of the building stock does not lead to an increase in cumulative CO₂e emissions over the program implementation period. Full article

Sustainable regional competitiveness and civil protection have traditionally been treated as distinct fields: the former rooted in regional economics and innovation studies, and the latter in disaster management, public safety, and risk governance. However, increasing climate-related hazards, technological disruptions, geopolitical instability, and the fragility of critical infrastructure demonstrate that competitiveness and resilience are deeply interconnected. This study presents a narrative literature review of publications from 2022 to 2025, integrating insights from evolutionary economic geography, institutional theory, sustainability studies, disaster risk reduction, spatial planning, and governance research. Building on this synthesis, we propose a novel conceptual framework that links civil protection capacity to long-term regional competitiveness. The framework introduces a multi-pillar model encompassing risk governance, institutional quality, critical infrastructure resilience, spatial planning systems, human capital dynamics and demographic stability, social trust and regional legitimacy, innovation driven by risk-management technologies, and multi-level governance coordination. Our analysis highlights how asymmetric threats are characterized by unpredictability, non-linearity, and uneven territorial impacts—interact with structural vulnerabilities, amplifying regional disparities and challenging conventional competitiveness strategies. Importantly, the framework demonstrates that robust institutions and integrated civil protection mechanisms can transform exposure to shocks into opportunities for adaptation, innovation, and structural upgrading. By conceptualizing competitiveness as a dynamic, emergent property shaped by economic, social, and risk-management capacities, this study positions civil protection as a strategic, measurable, and foundational component of sustainable regional development. The framework provides a theoretical foundation for future empirical research, policy design, and multi-criteria assessments aimed at fostering resilience-oriented competitiveness. Full article

This study investigates the organic chemical content and ecological impact of firefighting runoff collected from real-world fire scenarios. To establish a direct link between chemical composition and environmental hazard, a comprehensive analytical framework was employed, integrating molecular fingerprinting via gas chromatography–tandem mass spectrometry (GC-MS/MS) with a multi-trophic battery of bioassays, including Aliivibrio fischeri, Heterocypris incongruens, and Sinapis alba L. The chemical characterization revealed highly heterogeneous profiles dominated by esters (up to 41%), alcohols (up to 25%), and phenols (up to 22%). A unique molecular marker, nitriles (15.9%), was identified in tire-related fire effluents, which corresponded with potent metabolic suppression in the Toxi-ChromoTest™. Ecotoxicological results demonstrated that most effluents reached Class IV (high acute toxicity), with universal 100% lethality observed in samples from large-scale incidents. Furthermore, a significant stimulatory effect was detected in S. alba (growth stimulation up to 12%) for scenarios involving polyurethane foam, illustrating the selective toxicity of specific molecular groups. Beyond ecological degradation, the high phenolic and nitrile loads identified across multiple scenarios represent a substantial public health risk, as these persistent contaminants can infiltrate groundwater, bypass conventional water treatment, and bioaccumulate in the human food chain. The findings suggest that the synergistic effect of hydrophobic xenobiotics and firefighting foams poses a severe threat to both aquatic biodiversity and human chemical safety. This research emphasizes that linking molecular fingerprinting with multi-level bioindicators is essential for a holistic risk assessment of firefighting operations. Full article

Afghanistan is located within one of the world’s most seismically active regions, where recurrent earthquakes pose a persistent threat to human life and the built environment. The 7 October 2023 Herat earthquake exposed critical vulnerabilities in both the construction sector and institutional frameworks, manifested through the widespread presence of non-engineered buildings, poor construction quality, and the absence of mandatory and enforceable seismic design regulations. This study examines the structural, construction-related, and governance deficiencies that significantly contributed to extensive building damage and high casualty rates, while also assessing shortcomings in public preparedness and disaster risk governance. A comparative case-study approach is adopted to evaluate seismic resilience and disaster management practices in India, Pakistan and Iran. The findings indicate that the elevated vulnerability observed in Herat primarily resulted from deficient construction practices, the lack of codified seismic standards, weak regulatory enforcement, and limited technical capacity within the construction industry. In contrast, regions characterized by well-established seismic codes, engineered structural systems, and coordinated institutional mechanisms experienced substantially reduced levels of structural damage and human losses, although earthquake impacts are also influenced by factors such as hazard characteristics, site conditions, exposure levels, and population distribution. The study highlights that seismic safety and sustainable development are inherently interdependent objectives. Improving earthquake resilience in Afghanistan requires the integration of earthquake-resistant engineering with sustainable construction practices, enhancement of technical and professional capacity, rigorous enforcement of region-specific seismic regulations, and strengthened community-based awareness programs. The adoption of internationally recognized best practices and risk-informed planning strategies is essential for fostering safer, more resilient, and environmentally sustainable urban development capable of withstanding future seismic events. Full article

Pesticide exposure is a plausible but incompletely characterized contributor to kidney injury. This review integrates current clinical, epidemiologic, experimental, and mechanistic evidence on pesticide-related nephrotoxicity, focusing on glyphosate-based herbicides, paraquat, organophosphate insecticides, and atrazine. A structured search of PubMed and Web of Science identified English-language studies published between January 2015 and February 2026. Of 635 records screened, 61 human studies were retained for full-text evaluation, and relevant animal, in vitro, and regulatory sources were additionally reviewed for mechanistic interpretation. Across pesticide classes, the proximal tubule emerged as the most consistent renal target, although downstream pathways differed, including oxidative stress, mitochondrial dysfunction, transporter disruption, endoplasmic reticulum stress, inflammation, apoptosis, ferroptotic signaling, and fibrotic remodeling. Human evidence was strongest for acute kidney injury following severe poisoning, whereas associations between chronic occupational or environmental exposure and chronic kidney disease or end-stage renal disease were more limited and heterogeneous. Biomarkers including kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), β₂-microglobulin, cystatin C, interleukin-18 (IL-18), cytochrome c, and 8-hydroxy-2′-deoxyguanosine (8-OHdG) often detected early tubular stress before abnormalities appeared in conventional renal indices. Overall, pesticide nephrotoxicity is best conceptualized as a spectrum of mechanism-specific tubular injury signatures, supporting a shift toward biomarker-informed early detection, improved hazard identification, and more mechanistically grounded risk assessment. Full article

Despite the widespread use of Aloe vera extracts, their developmental toxicity in aquatic organisms remains poorly understood. This study investigated the effects of a commercial Aloe vera extract on zebrafish embryogenesis, focusing on developmental, morphological, behavioural, and oxidative stress-related endpoints. The 96 h-LC₅₀ was determined to be 0.03%. Embryos at 2 h post-fertilization (hpf) were exposed for 96 h to 0.0004% (LC₁₀) and 0.03% (LC₅₀). Exposure to 0.0004% caused no significant effects compared to controls. In contrast, exposure to 0.03% significantly increased mortality, reduced heart rate, impaired locomotion, and induced multiple malformations. Biochemical analyses revealed alterations in redox-associated biomarkers, characterized by unchanged ROS levels and mitochondrial activity, increased antioxidant enzyme activities (SOD, GPx, GR), and a decreased GSH:GSSG ratio. Lipid peroxidation levels were reduced, while a significant increase in DNA double-strand breaks (DSBs) was observed. Additionally, Nrf2 protein expression was upregulated at 0.03%. Together, these findings suggest concentration-dependent developmental toxicity correlated with alterations in redox homeostasis and genomic stability during early zebrafish development. This study provides new insight into the developmental hazard potential of a commercial Aloe vera extract in an aquatic vertebrate model. Full article

Importance: Triple-negative breast cancer (TNBC) is characterized by high tumor mutation burden and frequent programmed cell death ligand 1 (PD-L1) expression, making immune checkpoint inhibitors (ICIs) a promising therapeutic approach. However, randomized trials of chemoimmunotherapy (Chemo-IO) in locally recurrent unresectable or metastatic TNBC have shown inconsistent results, necessitating a clearer understanding of efficacy and patient selection. Objective: The aim of this study was to evaluate the efficacy and safety of chemotherapy combined with immunotherapy vs. chemotherapy alone in patients with locally recurrent unresectable or metastatic triple-negative breast cancer and to identify beneficiary populations to guide optimal treatment selection. Data Sources: PubMed, Embase, and the Cochrane Library were searched from database inception through 23 August 2025. Study Selection: Randomized clinical trials (RCTs) comparing chemotherapy combined with ICIs vs. chemotherapy with placebo or control in patients with locally recurrent unresectable or metastatic TNBC were selected. Data Extraction and Synthesis: Two investigators independently performed data extraction and assessed risk of bias using the Cochrane Risk of Bias 2 tool (RoB 2). Heterogeneity was evaluated using the I² statistic. Data were synthesized using random-effects meta-analysis models to calculate hazard ratios (HRs) for time-to-event outcomes and risk ratios (RRs) for dichotomous outcomes according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Results: Seven RCTs comprising 3485 patients (2085 in the Chemo-IO group, 1400 in the control group) were included. The median age across trials ranged from 52 to 57 years. Chemo-IO significantly improved PFS (HR, 0.82 [95% CI, 0.76–0.89]; p < 0.01) and OS (HR = 0.88; 95% CI: 0.81–0.96; p = 0.004) in the intention-to-treat (ITT) population, with PFS benefit particularly evident in PD-L1-positive patients (HR = 0.68, 95% CI: 0.59–0.79). However, OS improvement in the PD-L1-positive subgroup was not statistically significant. CBR did not differ significantly in the intention-to-treat population (RR, 1.11 [95% CI, 0.99–1.25]; p =  0.08) but was higher in PD-L1-positive patients (RR, 1.15 [95% CI, 1.01–1.31]; p = 0.04). Safety analyses revealed no significant differences in overall AE (RR, 1.01 [95% CI, 0.99–1.02]; p = 0.35), TEAE (RR, 1.01 [95% CI, 0.99–1.03]; p = 0.19), or grade ≥ 3 TEAE (RR, 1.00; [95% CI, 0.93–1.07]; p =  0.98). However, serious AE (RR, 1.32 [95% CI, 1.11–1.57]; p = 0.001) and irAE (RR, 1.86 [95% CI, 1.41–2.45]; p <  0.01) were more frequent with Chemo-IO. Conclusions and Relevance: Chemotherapy combined with immunotherapy significantly improved PFS and OS in patients with locally recurrent unresectable or metastatic TNBC, without substantially increasing chemotherapy-related toxicities. However, the OS benefit in PD-L1-positive patients was not statistically significant, and the combined regimen was associated with higher rates of serious and immune-related adverse events. These findings support the use of Chemo-IO as a treatment option, highlighting the importance of PD-L1 status and careful monitoring of immune-mediated toxicities in clinical practice. Full article

Flood damage assessment remains challenging, as conventional flood risk management mainly relies on hydraulic hazard maps that do not explicitly reproduce observed damage patterns. Recent advances in remote sensing and machine learning (ML) enable the integration of environmental and socio-economic data with historical impact information to improve flood damage modeling. This study proposes an explainable machine learning framework for flood damage susceptibility mapping, using observed institutional damage records from the 2011 and 2013 flood events combined with 17 geospatial flood risk factors (FRFs) representing hazard, exposure, and vulnerability. This approach enables the capture of non-linear relationships between flood damage and FRFs. For comparison purposes, the same framework was also applied using hydraulically modeled flood extents corresponding to return periods of 30, 200, and 500 years. The framework was tested along the Basilicata Ionian coast in southern Italy, a Mediterranean region characterized by complex geomorphology, intense rainfall events, and recurrent flood impacts. An eXtreme Gradient Boosting (XGBoost) model was trained using 17 FRFs related to hazard, exposure, and vulnerability at a spatial resolution of 20 m. The model achieved high performance with an accuracy of 0.988, an F1-score for the minority class of 0.860, and an ROC-AUC (test) of 0.996. High to very high flood damage probability was predicted in approximately 4.1% of the study area, mainly in low-lying floodplains near river corridors and infrastructure. SHAP-based explainability analysis revealed that damage susceptibility was predominantly driven by hazard and exposure factors: Drainage density (17.10%), Railway distance (16.33%), and Elevation (15.42%), extreme precipitation (Max rainfall, 10.66%) and Street distance (7.51%), with socio-economic vulnerability contributing less than 4%. The observed damage target exhibited clear threshold-like patterns (e.g., sharp risk increases below ~25/35 m elevation or within ~150/200 m of road infrastructure), contrasting with the smoother, continuous gradients produced by hydraulic scenarios. This analysis identified the most influential predictors and their response ranges. The proposed framework complements hydraulic hazard mapping by explicitly modeling observed flood damage, supporting flood risk assessment in flood-prone coastal regions. Full article

Bacillus species are extensively studied, utilized, and commercialized biocontrol agents, demonstrating significant effectiveness in managing a variety of plant diseases. Bacillus possesses a robust intrinsic biosynthetic ability, capable of producing a diverse array of antimicrobial metabolites, including dipicolinic acid (DPA; 2,6-pyridinedicarboxylic acid), which exhibits antifungal properties and serves as a principal structural component of Bacillus spores. This study revealed that DPA exhibits significant antibacterial activity against the hazardous soybean pathogen Xanthomonas citri pv. glycines (Xcg), with an EC₅₀ value of 53.2 μg/mL. DPA inhibited Xcg swimming motility, extracellular protease activity, and biofilm formation, while inducing significant membrane irregularities in Xcg cells. DPA treatment downregulated the expression of several Xcg membrane integrity-related genes, including cirA, czcA, czcB, emrE, and tolC. The preventive and curative application of 500 μg/mL DPA reduced Xcg symptoms by 82.7% and 83.8%, respectively, and induced the accumulation of the isoflavone genistin in soybean leaves. DPA exhibited only weak toxicity in the zebrafish model, suggesting its potential suitability for agricultural commercialization. Overall, this study provides the first detailed characterization of the antibacterial mechanism of DPA against a phytopathogenic bacterium, Xcg, and identifies DPA as a previously underexplored antibacterial metabolite from Bacillus and Paecilomyces with potential for disease management. Full article