Search Results (322)

Background: Chronic obstructive pulmonary disease (COPD) is associated with substantial long-term morbidity and mortality. Peripheral blood flow cytometry may provide exploratory information regarding immune-cell distributions and activation-related markers. However, careful interpretation is required when flow cytometry outputs are derived from lymphocyte-gated percentages rather than marker-specific mean fluorescence intensity or sequential lineage-confirmed gating. We investigated whether specific lymphocyte-gated flow cytometry parameters are associated with mortality during follow-up in COPD patients. Methods: In this single-center observational cohort study, 51 consecutive clinically stable outpatients with COPD were enrolled in November 2023 and followed for 24 months. Baseline peripheral blood flow cytometry results were verified against archived original instrument reports. The principal exploratory flow cytometry-derived variables were CD45/SSC-defined lymphocyte-gate percentage and lymphocyte-gated CD138+ events; HLA-DR positivity was evaluated as a secondary exploratory variable. Group comparisons and descriptive receiver operating characteristic (ROC) analyses were performed. Multiplicity was assessed using a hierarchical Benjamini–Hochberg false discovery rate (FDR) framework that separated the two biologically prioritized principal variables from the remaining exploratory screening variables. For transparency, a more conservative pooled FDR correction across all ten flow cytometry-derived variables was also reported. A two-variable analysis was performed only as exploratory signal aggregation, with descriptive internal assessment using leave-one-out cross-validation (LOO-CV) and bootstrap optimism correction. Results: During the 24-month follow-up, 13 of 51 patients died (25.5%). In unadjusted analyses, non-survivors had lower arterial oxygen tension and nominally lower CD45/SSC-defined lymphocyte-gate percentages (median 13.08% vs. 22.63%, p = 0.008) and lymphocyte-gated CD138+ event percentages (median 0.07% vs. 0.39%, p = 0.026) than survivors. Within the hierarchical analytical-family framework, both CD45/SSC-defined lymphocyte-gate percentage and lymphocyte-gated CD138+ events retained significance in the principal-variable family (within-family q = 0.016 and 0.026), whereas no secondary-family parameter, including HLA-DR (within-family q = 0.50), did; significance was not retained under a single correction across all ten parameters (CD45 q = 0.081; CD138 q = 0.129). Descriptive AUCs were 0.749 for CD45/SSC-defined lymphocyte-gate percentage and 0.710 for CD138+ events. The two-variable signal-aggregation analysis yielded an apparent AUC of 0.858, an LOO-CV AUC of 0.796, and a bootstrap optimism-corrected AUC of 0.832. NLR was available for all 51 patients; NLR-adjusted analyses did not establish clinical incremental utility. Conclusions: Lower CD45/SSC-defined lymphocyte-gate percentage and lower lymphocyte-gated CD138+ event percentage showed within-cohort associations with 24-month mortality in this small COPD cohort. These observations should be regarded solely as hypothesis-generating signals. Neither principal finding was retained after pooled correction across all ten flow cytometry-derived parameters, and no incremental prognostic value beyond routine inflammatory indices or established clinical predictors was demonstrated. External validation was absent; prospective replication in larger, appropriately adjusted cohorts is required. Full article

A frequent and sudden two-phase (solid–liquid) geological hazard in mountainous areas, the evolution of debris flows involves the coupling of multiple physical fields, making monitoring and early warning particularly challenging. To accurately reveal the dynamic patterns of debris flow evolution and improve early-warning accuracy, this study focused on the Ni Chang Valley area in Shimian County, Ya’an City, Sichuan Province. Based on the COMSOL Multiphysics coupling simulation platform, a multiphysics bidirectionally strongly coupled numerical model was proposed and constructed, integrating the SPH (smoothed particle hydrodynamics) meshless particle method, FLO-2D shallow-water dynamics, and the MassFlow full-process simulation approach. Using COMSOL as a unified framework, this model employs MassFlow’s deep-integration, continuous medium method to simulate rainfall triggering and material source activation, FLO-2D’s shallow-water equations to describe macroscopic flow-deposition processes, and SPH’s mesh-free particle method to accurately capture large deformations and free-surface flow. The model fully reproduces the entire dynamic chain of debris flow processes, from rainfall triggering and soil mobilization to fluid transport and channel deposition. The reliability and accuracy of the model were verified by comparing it with field measurements from the 20 September 2022 historical debris flow event at Ni Chang Valley. Quantitative analysis indicates that when the viscosity coefficient increases from 0.1 Pa·s to 100 Pa·s, the flow velocity decreases by approximately 47% and the flow depth increases by approximately 62%. When the yield stress increases from 1 Pa to 100 Pa, the deposition area shrinks from 269,900 m² to approximately 109,000 m², a reduction of about 60%. Combining the results of the dynamic analysis, daily maximum temperature, daily precipitation, moisture content, mud-water level, and ground surface displacement were selected as core monitoring indicators. The analytic hierarchy process (AHP) was used to determine the weights of each indicator, and a data- and physics-driven weighted summation model for debris flow monitoring and early warning was constructed to achieve a five-level debris flow monitoring and early-warning system. Historical disaster cases demonstrate that this early-warning model can provide advance predictions of debris flow disasters up to 2 h and 40 min in advance. The warning lead time is sufficient, the grading logic is clear, and the model is capable of accurately capturing precursor information on disasters. Full article

This study examines why ice covers on the Churchill River in Labrador crack during winter and how weather, river flow, freezing conditions, and riverbed features contribute to these events. Using data from 2010 to 2025 and satellite imagery, the study shows that cracks most often occur in December to February when heavy snow, rapid flow changes, or long cold periods place stress on the ice. Cracking also frequently starts near sandbars where the ice is weaker. The results highlight that no single factor causes cracking. Instead, a combination of snow load, temperature, flow variability, and local river conditions determines when and where cracks form. There is also a disconnect from flow regulation since cracks also formed in 2012 before the construction of the dam began in 2015. A field survey was also carried out employing a combination of borehole jack (BHJ) testing and ground-penetrating radar (GPR) surveys to quantify spatial variations in ice strength and thickness across a portion of the lower Churchill River across two sandbars. In situ BHJ measurements were conducted at multiple sites to determine confined compressive ice strength under both floating and grounded conditions, revealing substantial local variability linked to differences in ice support and the presence of white versus black ice. Complementary GPR transects using 500 MHz and 1000 MHz systems provided high-resolution profiles of ice thickness and internal structure, enabling identification of transitions between grounded and floating ice. The integrated BHJ–GPR approach allowed direct comparison between point-scale strength measurements and spatially continuous thickness and grounding patterns, demonstrating that grounded ice and ice containing higher proportions of white ice exhibited more complex stress states and greater variability in mechanical response. Together, these measurements highlight the importance of combining geophysical surveying with in situ mechanical testing to better understand how environmental conditions control ice integrity and potentially influence ice-jam lodgement propensity along regulated subarctic rivers. Full article

Background: Ascophyllan, a sulfated polysaccharide extracted from brown seaweed, has shown immunomodulatory and antioxidant effects in preclinical studies, yet human clinical evidence remains scarce. This randomized, double-blind, placebo-controlled pilot trial evaluated the safety and exploratory biological effects of daily ascophyllan supplementation in healthy adults. Methods: Twelve participants were randomized to receive either ascophyllan (n = 6) or placebo (n = 6) for 28 days. Safety was monitored through adverse event reporting and repeated laboratory assessments, including hematology, biochemistry, and inflammatory markers. Immune cell populations were analyzed via serial flow cytometry, serum total antioxidant capacity was measured at multiple time points, and gut microbiome composition was profiled using 16S rRNA gene sequencing. All analyses were exploratory in nature. Results: Ascophyllan supplementation proved well tolerated, with no adverse events observed and stable hematologic, renal, and biochemical parameters throughout the study. Exploratory longitudinal analyses suggested directional modulation of NK-cell-associated phenotypes during ascophyllan supplementation, including directional changes in CD57⁺, NKp46⁺, and NKG2D⁺ NK-cell phenotypes; however, group × time interaction analyses did not remain statistically significant after correction for multiple comparisons. Serum antioxidant capacity showed inter-individual variability with a directional but non-significant increase in the ascophyllan group at intermediate time points. Exploratory microbiome analyses suggested modest directional compositional differences involving members of the Bacteroidaceae and Bifidobacteriaceae families; however, no taxon remained statistically significant after correction for multiple comparisons. Conclusions: These preliminary findings indicate that ascophyllan is safe and well tolerated in healthy adults and may be associated with modulation of innate immune phenotypes, subtle microbiome compositional differences, and directional changes in antioxidant capacity. Larger, adequately powered clinical trials are warranted to confirm these observations and further investigate potential biological and clinical effects. Full article

Black-hole accretion systems exhibit a characteristic coexistence of activities: broad-band X-ray variability, hot coronae, wide-angle winds, and both steady and discrete jets. This coexistence suggests a persistently time-dependent magnetic background in which noisy fluctuations and explosive release are both essential. In this paper, we connect them all to the storage, organization, and intermittent reconnection-mediated release of magnetic energy, and we propose a Synchronized Spin Model (SSM) in which multiple local dynamos in a rotating accretion flow are represented as interacting macro-spins. Their synchronization, partial synchronization, excursion, and reversal define a compact set of collective variables that organize both timing statistics and large-scale morphology. In this picture, multiscale magnetic reconnection converts stored magnetic energy into coronal heating, flares, intermittent outflows, and discrete jet activity, while the same synchronization dynamics produce amplitude modulation and demodulation, providing a route to 1/f-like variability, rms–flux/Taylor-like scaling, and approximately log-normal statistics of the demodulated envelope. We further argue that, although the continuous flux distribution in black-hole systems is more naturally discussed in multiplicative or log-normal terms, broader event-catalog statistics remain useful for describing suitably defined burst hierarchies, particularly by analogy with solar and stellar flare systems. The hard/soft cycle of X-ray binaries is then interpreted as motion through magnetic state space. Full article

This paper evaluates a dense, total-variation-based optical flow method for retrieving wildfire smoke plume motion vectors from geostationary, deep-space, and airborne remote sensing imagery. Using multiple major fire events, we assess the robustness of the approach across a range of spatial resolutions and time intervals. The test cases include Geostationary Operational Environmental Satellite (GOES) observations of the 2025 Los Angeles Fires and the 2024 Park Fire, imagery from NASA’s Enhanced MODIS Airborne Simulator (eMAS) for the 2019 Sheridan and Williams Flats Fires, and a complementary Park Fire image pair from the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR). Optical flow is computed directly on radiance fields, and smoke plumes are isolated using smoke masks derived from the Segmentation, Instance Tracking, and data Fusion Using multi-SEnsor imagery (SIT-FUSE) framework where available. Performance is evaluated by comparing the root mean square error (RMSE) between original image pairs and between the first image and the second image after warping with the retrieved motion field. RMSE is computed both globally and over smoke-only regions. Across GOES and eMAS cases, optical flow systematically reduces RMSE, often by more than a factor of two within smoke regions, indicating substantially improved frame-to-frame alignment of plume structures after motion correction. The DSCOVR/EPIC case, despite its coarser spatial resolution and longer temporal separation, also shows a marked reduction in global RMSE, demonstrating that the method remains informative under a broader range of observational conditions. For a selected subset of 10 consecutive GOES Park Fire pairs, we additionally compare the retrieved smoke motion vectors with collocated winds from the High-Resolution Rapid Refresh (HRRR) model and find the closest agreement in a broad lower-tropospheric layer centered near 875 hPa. These results show that dense optical flow can capture fine-scale plume evolution in high-temporal-resolution datasets while also providing useful motion estimates in coarser, global-view imagery. RMSE reduction is interpreted here as evidence of improved motion-compensated alignment, while the HRRR comparison provides initial physical context rather than independent validation. The resulting smoke motion vector fields provide a foundation for future comparison with model winds and for applications in plume analysis, fire hazard monitoring, and air quality studies. Full article

Fault location in distribution networks is often unreliable when measurements are noisy or incomplete. In actual feeders, synchronized data may be missing or distorted because of unstable edge communication. The proposed method uses physics-aware decoupled inference to locate line faults. The method works on single-time snapshots that capture voltages, currents, power flows, and zero-sequence components. These quantities are organized into an ordered hybrid tensor representing the feeder state at that instant. A one-dimensional convolutional encoder extracts spatial context from the tensor. Node measurements are handled separately and fused at the two terminals of each candidate line. This structure removes dependence on recursive graph message passing and confines the effect of local noise. The method is evaluated on the IEEE 33-bus test system under multiple noise levels, random masking of node features, and different fault resistances. With additive noise ($\sigma =0.3$) and 50% random node loss, the model achieves 92.8% localization accuracy. Average inference time per event is 0.62 ms on the tested GPU. The current implementation assumes a fixed feeder topology and synchronized aggregated measurements at the feeder level. Full article

Multiple-fault events can initiate overload propagation and cascading outages, resulting in severe load loss and reduced system resilience. Therefore, beyond conventional protection concepts based on the (n − 1) criterion, there is also a need to address multiple-fault events to minimize loss of load. This paper presents an optimized overload tripping scheme to mitigate cascading outages in high-voltage grids under multiple-fault conditions, where selected line switches or circuit breakers are opened in a controlled manner to isolate limited grid sections, minimize interrupted load, and prevent further overload propagation. The method combines inverse definite minimum time relay modeling with a heuristic graph-search algorithm implemented in pandapower to identify feasible switching actions that minimize load loss while preventing overload propagation. The approach is demonstrated on SimBench high-voltage urban and mixed benchmark grids under double-line fault scenarios. In the urban grid, the proposed scheme reduces the maximum load loss from 34.0% to 2.4%, while in the mixed grid, the reduction is from 50.3% to 5.2%. A SAIFI-inspired resilience proxy is introduced to quantify the reduction in customer/load interruptions, showing a resilience improvement factor of about 3.6 for cascading scenarios. In addition, thermal inertia analysis indicates that corrective switching must be completed within approximately 5 min to remain within line-temperature limits. The analysis is based on quasi-steady-state power-flow and relay simulations; transient stability effects are outside the scope of this study. The results demonstrate that the optimized overload tripping scheme is a promising adaptive protection strategy for improving grid resilience under severe contingency conditions. Full article

Background: Hypoplastic left heart syndrome (HLHS) is defined as “a spectrum of congenital cardiovascular malformations with normally aligned great arteries without a common atrioventricular junction, characterized by underdevelopment of the left heart with significant hypoplasia of the left ventricle including atresia, stenosis, or hypoplasia of the aortic or mitral valve, or both valves, and hypoplasia of the ascending aorta and aortic arch”. Without treatment, HLHS is usually lethal in the neonate. Many hypotheses have been advanced to explain the etiology of HLHS; however, no single theory appears to fully explain the phenotypic variability seen in HLHS. Furthermore, many of these theories offer no explanations regarding the precipitating events which lead to the development of HLHS. Objective: This review considers and critically evaluates the strengths and weaknesses of the leading theories proposed to explain the pathogenesis of HLHS—including hemodynamic disturbances, primary myocardial structural defects, valvar malformations, and genetic or epigenetic alterations that may provoke developmental and anatomic abnormalities. After presenting each model, we propose a novel, comprehensive, and data-driven framework which may assist researchers in developing models for the pathogenesis of the various subtypes of HLHS. Methods: Key findings from human fetal imaging, histopathology, genetic studies, and animal models were considered, as well as the hypothetical contribution of each in observed HLHS phenotypes. The rationales for these findings as causal factors initiating individual HLHS patterns, as well as how they might contribute to HLHS in general, were critically analyzed. Results: The flow theory is strongly supported by animal models and in utero interventions that demonstrate the impact of altered hemodynamics on cardiac morphogenesis. However, the flow theory fails to identify initial causes of disturbed flow or related histological features of HLHS like endocardial fibroelastosis. The myocardial and valve-first models suggest an important role in developmental defects, but do not necessarily have a strong experimental basis that provides explanations for how they mediate HLHS. Genetic studies in patients with HLHS have identified several candidate causal mutations. However, such genetic causes of HLHS exhibit incomplete phenotypic penetrance and clinical impact. A multifactorial framework attempts to integrate these diverse mechanisms and may provide the most coherent explanation that can accommodate the heterogeneity and variable presentation of HLHS. Such a framework may identify multiple forces that drive disease but does not provide useful pathways for future research about HLHS. Conclusions: No single hypothesis has fully explained how HLHS is initiated, progresses, and presents with the clinical conditions that are encountered by cardiac surgeons and cardiologists. The most current models suggest that the spectrum of HLHS reflects acomplex interaction between genetic susceptibility, flow-dependent cardiac remodeling, and environmental factors in utero. A multifactorial model integrates these diverse mechanisms and may provide the most coherent explanation for the various phenotypic variations in HLHS. Based on our analysis of the most current data and the strengths and weaknesses of the current theoretical frameworks, we propose a novel research strategy aimed at identifying specific cardiac progenitor cell populations whose dysregulation may represent a unifying explanation for the etiology of the various phenotypes of HLHS. Based on the arguments made throughout this manuscript that evaluate the various genetic, structural, and hemodynamic models of initiation of disease, we believe that the significant phenotypic variability across the spectrum of HLHS (i.e., the different anatomic subtypes for “classic” HLHS) most likely reflects different underlying etiologies and mechanisms. At the very least, it is very likely that the timing of the insult is critical in determining anatomic subtype. Based on the published data and the arguments within this manuscript, it seems naive to think that there is a single unifying mechanism explain all forms of HLHLS. Full article

With the increasing frequency of extreme weather and rapid growth of civil aviation, severe convective weather (thunderstorms, short-term heavy precipitation, and strong winds) poses growing threats to flight safety. This study proposes a multi-label CNN-ConvLSTM framework that fuses airport Doppler radar echoes, Himawari-8 satellite imagery, surface observations, and radar optical flow features to nowcast multiple severe convective events within the next 30 min. The model uses 2D-CNN for spatial extraction, ConvLSTM for temporal dynamics, and a weighted joint loss (Focal Loss and Dice Loss) to address class imbalance. Trained on 396 samples (positive-to-negative ratio 1:2.5) from 83 events at Guanghan Airport (2021–2024), incorporating optical flow features significantly boosted performance: macro-F1 increased from 0.719 to 0.792, and Threat Score (TS) from 0.567 to 0.705. Notably, false negatives for minority classes dropped sharply, with strong winds F1-score rising from 0.15 to 1.00. Ablation analysis showed optical flow as the top contributor (Mean Decrease in TS ≈ 0.5). Through multi-modal fusion and motion enhancement, this interpretable model provides high-precision nowcasting for airport severe convective weather, offering substantial value for aviation safety. Full article

Extracellular vesicles (EVs) are lipid bilayer-bound structures capable of transporting molecular markers from their cell of origin and are secreted by multiple cell types, including malignant cells. EVs have emerged as promising tools for developing less invasive diagnostic approaches. In B-cell acute lymphoblastic leukemia (B-ALL), immunophenotypic characterization of extracellular vesicle-enriched populations (EVEPs) in peripheral blood (PB) may provide complementary information for disease detection and monitoring. This exploratory study aimed to characterize EVEPs obtained from PB and bone marrow (BM) of adult patients with B-ALL and to compare them with the clinical immunophenotype (CIP). A total of 12 individuals were initially recruited (eight with B-ALL, one with T-ALL, and three healthy controls). The study focused on the eight B-ALL patients and three controls, while the T-ALL sample was used as a specificity control. EVEPs were isolated by differential centrifugation and analyzed by flow cytometry and confocal microscopy, primarily evaluating CD3 and CD19 expression. EVEPs derived from PB samples of patients with B-ALL showed a higher percentage of marker-positive events by flow cytometry (CD45, CD34, CD19, CD20, and CD10), consistent with the leukemic phenotype identified in the CIP. Additionally, CD3⁺CD19⁺ EVEPs were occasionally detected. These findings suggest that EVEPs partially reflect the leukemic immunophenotype and may serve as a complementary source of biological information. The detection of CD3⁺CD19⁺ events highlights complex cellular interactions within the leukemic niche and warrants further investigation. Full article

Urbanization, together with shifts in rainfall patterns, has become an increasingly important driver of hydrological extremes in many rapidly developing tropical regions. In the Cimanceuri River Basin, Tangerang Regency, Indonesia, these processes have intensified over the last decade, raising concerns regarding flood risk. This study examines the combined influence of urban expansion and rainfall variability on flood dynamics over 2013–2025. Multi temporal land use classification based on Landsat imagery indicates a pronounced growth of impervious surfaces, primarily driven by rapid urban development and the conversion of agricultural land. To assess the hydrological consequences of these changes, rainfall–runoff processes and flood inundation were simulated using the Soil Conservation Service Curve Number (SCS–CN) method within a coupled HEC-HMS and HEC-RAS 2D modelling framework. Simulations were performed for multiple temporal conditions and design rainfall scenarios. Model calibration relied on observed flood events recorded in March 2025 in the Mustika Residential Area, Tangerang. The results suggest that urbanization has contributed to measurable increases in both peak discharge and inundation extent. Between 2013 and 2025, impervious surface coverage expanded by approximately 67%, accompanied by a rise in the composite Curve Number from 85.86 to 86.63 and an estimated 5.2% increase in flood extent. Also, the design rainfall increased from 85.01 to 90.95 with an average increase of 7.34%. Comparison between simulated inundation patterns and aerial imagery shows satisfactory agreement, with an average deviation of less than 10%, indicating acceptable model performance. Hydrologic analyses generated two discharge scenarios, consisting of event-based flow from the 5 March 2025 rainfall data and return-period flows derived from design rainfall under different rainfall-shift periods. The rainfall-shift analysis quantified changes in design rainfall and corresponding discharge using progressively updated rainfall records. Together, the results emphasize the combined effects of urban expansion and shifting rainfall patterns on flood dynamics, underscoring the need for adaptive land-use planning and climate-responsive water management in rapidly urbanizing catchments. Full article

Background and Clinical Significance: Chromothripsis represents a catastrophic genomic event in plasma cell myeloma (PCM) associated with poor prognosis. We report a case of newly diagnosed PCM with complex cytogenetic abnormalities indicative of genomic instability. Case Presentation: A 67-year-old man presented with acute dyspnea and was found to have severe acute kidney injury, anemia, hypercalcemia, and IgG lambda monoclonal gammopathy. Bone marrow biopsy revealed plasma cell infiltration. Comprehensive FISH analysis demonstrated a complex pattern with gain of 1q, monosomy 13, and multiple numeric and structural abnormalities affecting chromosomes 5, 9, and 15, suggestive of a chromothripsis-like pattern. Despite requiring hemodialysis, the patient achieved complete renal recovery and >99% reduction in serum-free light chains after one cycle of CyBorD plus daratumumab, which was continued for four cycles. Follow-up bone marrow evaluation at three months confirmed complete histologic, flow cytometric, and cytogenetic remission, allowing for preparation for autologous stem cell transplantation. Conclusions: This case demonstrates that exceptional clinical responses can be achieved in high-risk disease with contemporary quadruplet regimens. While the long-term durability of such responses in genomically unstable cases remains uncertain, this case highlights the importance of comprehensive cytogenetic characterization to identify and monitor genomic instability in PCM. Full article

Geological hazards are characterized by their sudden occurrence, high destructiveness, and wide spatial impact. In particular, landslides and debris flows triggered by earthquakes and intense rainfall often lead to severe casualties and substantial property losses. Therefore, the rapid delineation of affected areas is crucial for disaster assessment and post-disaster reconstruction. To this end, several geohazard datasets have been developed from remote sensing imagery, focusing on specific regions, disaster types, and data sources, providing valuable support for geohazard detection and risk assessment. Our study addresses the diversity of real-world geological disasters in terms of their types, causes, and spatial distribution and constructs the Composite Geological Hazards Dataset (CGHD), a dual-temporal geohazard dataset that enhances generalisation and practical applicability. CGHD incorporates pre- and post-disaster remote sensing images of 14 landslide and debris flow events that occurred worldwide between 2017 and 2024, collected using four remote sensing platforms and encompassing multiple spatial scales and land-cover categories. The affected areas varied significantly in size and shape, with land-cover types including roads, buildings, vegetation, farmland, and water bodies. This resulted in 3963 pairs of pre- and post-disaster images, each with a size of 1024 × 1024 pixels. We validated the reliability of the CGHD through experiments with nine change-detection models and further evaluated its generalisation capability using an unseen dataset. The experimental results demonstrate that CGHD achieves high recognition accuracy and strong generalisation across diverse geographic environments, providing comprehensive data support for intelligent geohazard recognition and disaster assessment. Full article

The middle and lower reaches of the Yangtze River Basin occupy a strategically pivotal position in regional development; yet extreme drought-runoff events pose severe threats to water supply and ecological security. Despite this, systematic research gaps persist, including the lack of a unified definition, standardized identification criteria, and clear understanding of formation mechanisms for extreme drought-runoff. To address these limitations, this study focused on extreme drought-runoff in the basin, utilizing 1956–2024 discharge data from four mainstream hydrological stations and meteorological data from 171 stations. Quantitative discrimination criteria were established via Pearson-III frequency analysis; meteorological characteristics were analyzed using the Meteorological Drought Comprehensive Index; and formation mechanisms were explored through partial correlation analysis and multiple linear regression. This study innovatively proposed a basin-wide three-level quantitative discrimination criterion for drought-runoff based on the June–November flow frequency of key mainstream stations, which is distinguished from single-indicator drought identification methods (SPI/SPEI/SSI) by integrating basin-scale hydrological coherence and seasonal drought characteristics. The results revealed basin-wide extreme drought-runoff in 2006 and 2022, severe drought-runoff in 1972 and 2011, and relatively severe drought-runoff in 1959, 1992, and 2024. Typical extreme drought-runoff events were characterized by sustained low precipitation and high temperatures. Meteorological factors emerged as the primary driver during June–September, while reservoir operation and riverine water intake played secondary roles. Notably, the large-scale reservoir group in the Yangtze River Basin (53 key control reservoirs) helped alleviate drought-runoff impacts from December to May (non-flood season) via water supplementation. These findings provide a robust scientific basis for precise drought-runoff prediction and the development of targeted adaptation strategies in the Yangtze River Basin. Full article