Nuclear power provides a sustainable energy with high efficiency and develops fast in the past decades. To process the nuclear wastes, the behaviors, structures, coordination number, and average radius of solvated actinide ions are required to be explored theoretically due to the high-level radioactivity. Herein, we developed the TGMin-MLP package and trained the machine learning potentials (MLP) for the mono-nuclear americium-water clusters. Then, the trained MLP was applied to searching the most stable structures of both mono-nuclear Am(H2O)n3+ (n = 1 ~ 20) and poly-nuclear Amn(H2O)503n+ (n = 1 ~ 6) actinide-water clusters. The results reveal the saturated coordination number of the Amn3n+ core is 9, 16, 20, 23, 28 and 32, respectively. In addition, the average radius of solvated Amn3n+ core is ranked as Am3+ (2.52 Å) < Am26+ (3.19 Å) < Am39+ (3.40 Å) < Am412+ (3.62 Å) < Am515+ (3.85 Å) < Am618+ (4.10 Å). This work trained the MLP and searched the most stable structures of clusters, providing new insights on the actinide solution chemistry, especially the structures, solvation number and average radius of solvated Amn3n+ cores. Overall, the TGMin-MLP package and the findings on actinide-water clusters advance both computational actinide chemistry and practical nuclear waste treatment, opening new avenues for the high-throughput study of hydrated actinide clusters, polynuclear speciation, and solution-phase behavior of radioactive heavy elements. We developed the TGMin-MLP package to search the most stable structures of clusters by using the well trained MLP, and investigate the coordination number and average radius of Am3+ ions both for the mono- and poly-nuclear americium-water clusters Amn(H2O)m3n+. The results predict the possible structures, saturated solvation numbers and radius of Amn(H2O)m3n+ clusters. The GM structures were also re-optimized at the DFT ZORA PBE0-D4/def2-TZVP (H, O)/SARC-ZORA-TZVP (Am) level of theory with dispersion, solvation and relativistic effects corrections by using the ORCA (v6.1.0) package.
This study utilized two indirect methods to establish reference intervals (RIs) for four coagulation parameters for the adult population in Tibet, a high-altitude region in Western China. Coagulation Data, Including Activated Partial Thromboplastin Time (APTT), prothrombin Time (PT), thrombin Time (TT), and Fibrinogen (FIB) Obtained From the People's Hospital of Tibet Autonomous Region Between 2019 and 2023, Were Subjected to Box-Cox Transformation for Normalization and Tukey Method for Outlier Removal. the RIs Were Calculated Using Hoffmann and refineR Methods, Respectively. A total of 5086, 5282, 5386, and 5377 test results for APTT, PT, TT, and FIB were included. The Hoffmann and refineR method yielded the following total RIs: APTT 30.54-46.32 and 30.14-44.30 s; PT 10.54-14.51 and 10.32-13.89 s; TT 14.92-19.46 and 14.88-18.93 s; FIB 2.05-4.68 and 2.02-4.40 g/L, respectively. Gender-partitioned RIs were calculated for all four parameters, while age-partitioned RIs were specifically calculated for PT and FIB based on bias ratio values. The lower limits of RIs estimated by the two methods remained consistent. The established RIs for APTT and FIB were significantly higher than those utilized in the plain area and those provided by the manufacturer, whereas the established RIs of TT were significantly lower. The RIs for coagulation parameters in the population living on the Tibetan Plateau exhibited significant divergence from those utilized in the plain area. Specific RIs for high-altitude regions should be established to accurately evaluate the presence of coagulation disorders.
Letrozole is a non-steroidal aromatase inhibitor commonly used for the treatment of postmenopausal estrogen receptor-positive breast cancer. We report a novel case of bilateral panuveitis associated with letrozole therapy. Retrospective chart review. A 39-year-old female with a history of breast cancer presented with bilateral anterior chamber and vitreous inflammation, perivenular sheathing, retinal hemorrhages, and a focal area of retinal whitening in the left eye six weeks after starting letrozole therapy. Extensive infectious and systemic inflammatory work-up was negative. With letrozole cessation and corticosteroid therapy, the inflammation resolved, and the visual acuity improved to 20/20 bilaterally. Letrozole-associated panuveitis has not previously been reported. This case highlights the importance of detailed medication history as well as the need for interdisciplinary collaboration when managing drug-induced uveitis. Early recognition and appropriate therapy can result in favorable visual outcomes.
Superhalogens, characterized by exceptionally high electron affinity (EA) and strong oxidizing capacity, play a critical role in energy conversion and catalysis. Conventional design strategies based on electron-counting rules, however, offer limited tunability for continuous and precise modulation of electronic structure. Herein, we employ density functional theory to systematically investigate the influence of oriented external electric fields (OEEF) on the Co4P4 cluster, with emphasis on electronic properties, small-molecule adsorption, and CO oxidation. Our results reveal that OEEF elevates the cluster EA from non-superhalogen to superhalogen levels while preserving its core-shell geometry, magnetic characteristics, and superatomic orbital arrangement. A polynomial relationship between OEEF intensity and EA enables geometrically noninvasive, precise regulation of electronic affinity. Directional OEEF further induces field-strength-dependent charge redistribution, thereby modulating active-site distribution and reaction energetics to govern catalytic behavior. In CO oxidation, OEEF reversibly switches the cluster surface between activated and passivated states by tuning CO and O2 adsorption affinities, and reaction pathway analysis confirms systematic modulation of reaction barriers. This work introduces a novel strategy for synchronously optimizing electronic structure, molecular adsorption, and reaction kinetics through OEEF parameterization, thereby advancing the rational design of efficient nonprecious metal catalysts.
Dengue fever, a mosquito-borne disease caused by dengue virus (DENV), has become a global health problem, and no FDA-approved drug is currently available. Qingwen Baidu Decoction (QBD) is used to treat the critical phase of dengue fever in China, but its mechanism of action remains unclear. In this work, we integrated bioinformatics analysis, machine learning, and network pharmacology to investigate the possible molecular targets and potential active chemical components of QBD. Common targets between differentially expressed genes from DENV infected samples and predicted targets of QBD were identified by bioinformatics analysis and refined by machine learning algorithms including LASSO, random forest and SVM-RFE. Three core genes, CXCL10, EZH2 and EPHB2 were significantly overexpressed in dengue fever patients, indicating their potential diagnostic and therapeutic value. Single cell transcriptome analysis further revealed that QBD primarily targets dendritic cells, monocytes and macrophages. Immune infiltration analysis using ssGSEA showed that these three core genes were significantly associated with CD4+ and CD8+ T cell subtypes, suggesting their involvement in host immune regulation. Molecular docking and molecular dynamics simulations identified eight chemical components of QBD as potential active ingredients. Based on these computational predictions, we hypothesize that QBD may exert its therapeutic effects through dual mechanisms, including directly binding to DENV proteins to inhibit viral replication, while also regulating the function of CXCL10 and EZH2 to alleviate DENV-induced inflammatory responses and modulate host immunity. These results provide a theoretical reference for future experimental validation and drug development.
The patient presented with severe hypoglycemia and convulsions 43 h after birth. The clinical features were typical, with the presence of obvious hyperinsulinemic hypoglycemia and asymptomatic hyperammonemia, and it was sensitive to the treatment of diazoxide. The diagnosis of HI/HA was confirmed by genetic testing.
In this work, compound 8 bearing ortho-amino-nitro groups in the ring bridge exhibits an ultra-high onset decomposition temperature, high detonation velocity and acceptable sensitivity, thereby outperforming the classic heat-resistant explosive PYX.
Acacetin (5,7-dihydroxy-4'-methoxyflavone) is a primary active flavonoid extracted from traditional medicinal plants such as Agastache rugosa and Saussurea involucrata. Historically, these herbs have been utilized in Traditional Chinese Medicine to clear heat, eliminate dampness, and treat inflammatory and kidney-related ailments. Despite its potent anti-inflammatory properties, the direct molecular targets of Acacetin and its specific mechanisms regarding mitochondrial quality control (MQC) in the progression of renal fibrosis (RF) remain undefined. This study aimed to evaluate the anti-fibrotic efficacy of Acacetin and elucidate whether it directly targets the cGAS-STING cascade to restore organelle homeostasis by balancing mitophagy and protective nucleoid-phagy. Molecular dynamics (MD) simulations, microscale thermophoresis (MST), and drug affinity responsive target stability (DARTS) assays were utilized to verify the direct binding between Acacetin and STING. In vivo, wild-type (WT) and STING-knockout (STING-/-) mice were subjected to unilateral ureteral obstruction (UUO) and folic acid nephropathy (FAN) models, and administered Acacetin (40 and 80 mg/kg/d). In vitro, human renal tubular epithelial (HK-2) cells were stimulated with TGF-β or cGAMP. Mitochondrial function, ultrastructure, and dynamic autophagic flux were evaluated using Seahorse XF analysis, transmission electron microscopy (TEM), bafilomycin A1 (BafA1) blockade, tandem fluorescence imaging, and immunofluorescence. Protein and gene expressions were measured via Western blotting and RT-qPCR. Biophysical assays identified Acacetin as a direct STING inhibitor that bound to the STING protein pocket (Kd = 1.57 μM) and effectively antagonized its cGAMP-induced phosphorylation. Consequently, Acacetin dose-dependently alleviated UUO- and FA-induced renal fibrogenesis, suppressed oxidative stress, and restored mitochondrial respiratory capacity. Mechanistically, Acacetin promoted a functional shift in MQC: it suppressed the initiation phase of maladaptive PINK1/Parkin-mediated "exhaustive over-mitophagy" while facilitating TFAM-LC3-associated "nucleoid-phagy" to selectively clear immunogenic leaked mitochondrial DNA (mtDNA). Crucially, the anti-fibrotic, anti-inflammatory, and MQC-restoring benefits of Acacetin were completely abolished in STING-/- mice, establishing STING as its indispensable pharmacological target. Acacetin ameliorates renal fibrogenesis by directly inhibiting STING, thereby regulating the balance between pathological over-mitophagy and protective nucleoid-phagy. These findings validate the traditional use of Acacetin-rich herbs in treating inflammatory conditions and highlight the monomer as a promising mechanism-based therapeutic candidate for the treatment of chronic kidney disease.
Background: Predicting mutation-induced changes in binding free energy (ΔΔG) is important for understanding drug resistance and prioritizing resistant variants, yet real-world generalization remains unclear. In clinical diagnosis and early-stage drug screening, mutant complex structures are often unavailable. However, many existing methods rely on paired wild-type (WT) and mutant structures and are evaluated under random splits that may permit substantial protein-level train-test overlap. Methods: We established a WT-complex-structure-only setting, in which mutant structural coordinates are unavailable but mutation annotations are provided, and conducted a controlled comparison of graph- and vector-based configurations under both random and strict UniProt-based splits. We further analyzed graph context, message passing, representation bias, and dataset noise to identify factors limiting protein-disjoint generalization. Results: On MdrDB, random splits yielded apparently moderate performance (Pearson R ≈ 0.55), whereas strict UniProt-based evaluation simulating unseen proteins led to a marked drop (Pearson R ≈ 0.15), indicating that random splits substantially overestimate generalization. Graph-based modeling retained a weak but nonzero signal relative to the vector baseline, although the differences were limited and not statistically significant. Ablation analyses suggested that full-protein structural context was more useful than local pocket-plus-mutation context, whereas full-protein message passing did not provide a clear additional advantage. ΔESM representations reduced protein-background clustering, but overall strict-split performance remained low. Conclusions: WT-only prediction of mutation-induced drug resistance from static structures remains far from solved under realistic protein-disjoint evaluation. Experimental label inconsistency, sparse protein coverage, and missing dynamic structural information may further limit performance, underscoring the need for split-aware evaluation protocols and stronger physical priors.
Exosomes are small extracellular vesicles (EVs) that play an important role in intercellular communication among multiple cell types. In recent years, they have emerged as a novel and promising class of cancer biomarkers, offering significant potential to increase diagnostic and therapeutic strategies. These bilayer nano-vesicles are actively secreted by living cells into various biological fluids and carry a diverse cargo of proteins, nucleic acids, and other biomolecules that reflect the physiological and pathological state of their cells of origin. The molecular composition of exosomes mirrors the dynamic processes and unique cargo of molecular and genetic data, reflecting the complex activities within cancer cells, making them a promising alternative for cancer detection and treatment monitoring. Although the mechanisms underlying exosome biogenesis, secretion, and cargo selection in cancer remain incompletely understood, growing evidence highlights their importance in tumor progression and therapeutic response. Exosomal proteins have gained considerable attention as potential therapeutic targets. These proteins can regulate immune responses, reshape the tumor microenvironment, and influence cancer cell proliferation and survival. Consequently, targeting exosome-associated proteins represents a promising strategy for developing innovative anticancer therapies. Advances in exosomal protein analysis have provided a promising approach for unraveling the complex molecular networks underlying cancer biology. A wide range of analytical techniques is available to identify and quantify exosomal proteins, enabling characterization of cancer-specific molecular signatures. As an expanding field in cancer research, exosomes have the potential to revolutionize both therapies and diagnostics. By deciphering the diverse molecular and functional cargos of exosomes, exosomes offer new insights that may lead to more precise, effective, and personalized approaches to cancer management.
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Genetically engineered mouse models have advanced cancer research, but they fail to mimic some human diseases. Rats offer a powerful alternative for modeling human cancers that are inadequately represented in mice, yet their use has been constrained by technical barriers to genome editing. Here, we report somatic genome editing in rats and apply this approach to model estrogen receptor (ER)-positive breast cancer, which accounts for approximately 70% of human cases but remains poorly represented in mice. The resulting rat tumors reproduce hallmarks of human ER+ breast cancer, including ductal histology, hormone responsiveness, and immune microenvironment features. By contrast, identical genetic alterations in mice failed to yield ER+ tumors, underscoring critical species differences in tumorigenesis. Together, this work establishes a versatile platform for the rapid generation of clinically relevant rat tumor models, opening avenues to study tumor biology, therapeutic response, and immune interactions in cancer subtypes previously inaccessible to experimental modeling.
To validate a novel VISULYZE-based nomogram for high myopia in small incision lenticule extraction (SMILE) surgery. This prospective, nonrandomized controlled trial included 118 eyes of 71 high-myopia patients treated with SMILE using a VisuMax 500-kHz femtosecond laser. High myopia was defined as a spherical equivalent refraction ≤ -6.00 D. Treated eyes were divided into two groups, according to different nomograms received: the conventional surgeon-adjusted nomogram group (n = 71 eyes) and the VISULYZE-based nomogram group (n = 47 eyes). The VISULYZE nomogram was generated by the data from 108 myopic eyes that underwent SMILE surgery at 3 months. The visual outcomes followed up for 3 months for both groups were compared for efficacy, safety, predictability, stability, and higher-order aberrations (HOAs). Preop-SE was -6.58 ± 0.50 D in the conventional group and -6.79 ± 0.61 D in the VISULYZE group. At 3 months postoperatively, the SE in the conventional group and the VISULYZE group was -0.16 ± 0.34 D and 0.05 ± 0.40 D (p < 0.05), respectively. It was found that 72% and 100% had a UDVA of 20/20 in the conventional group and VISULYZE group, respectively, while 89% and 99% had an SE within ±0.5 D and ±1.0 D in the conventional group and 89% and 100% in the VISULYZE group. The efficacy indexes were 0.97 ± 0.07 in the conventional group and 1.02 ± 0.06 in the VISULYZE group (p < 0.05). The safety indexes were 1.15 ± 0.10 in the conventional group and 1.15 ± 0.15 in the VISULYZE group (p > 0.05), respectively. The VISULYZE-based nomogram was associated with lower induction of 3rd-order vertical/horizontal coma, total coma, 4th-order spherical aberration, and root mean square (RMS) HOAs. The VISULYZE-based nomogram demonstrated comparable safety to the conventional nomogram while achieving significantly superior efficacy and predictability. Additionally, it provided a supportive condition for reducing RMS HOAs after SMILE compared to the conventional approach. Trial Registration: ClinicalTrials.gov: NCT06982807.
We present a case of fast-growing, recurrent orbital mass which was ultimately diagnosed as sarcoidosis in a patient who lacked systemic symptoms. A case report was conducted. A 58-year-old woman from Pakistan presented with a ortbial mass that is hyperintense orbital mass on MRI. Excisional biopsy and pathology revealed non-necrotizing granulomatous inflammation. Negative AFB culture, GMS, and flow cytometry ruled out TB and lymphoma. Chest X-ray was unremarkable. ACE and Lysozyme levels were marginally elevated. She presented with symptomatic recurrence of mass requiring repeat excision. Chest CT confirmed the presence of pulmonary nodules and hilar lymphadenopathy. She was started on corticosteroids and methotrexate with resolution of local inflammation and residual mass effect. Chest CT has higher sensitivity to aid definitive diagnosis in the setting of negative chest X-ray. Surgical treatment may be useful for diagnostic and therapeutic purposes. Subsequent long-term treatment with corticosteroids and antimetabolites has shown great response.
To ensure the stability of the artificial frozen wall during the underground excavation of a proposed subway station using the artificial ground freezing method in soft soil strata, and to guarantee the construction safety of the proposed station under-crossing beneath an existing operating station. Based on the project of a proposed subway station under-crossing an existing station via underground excavation with artificial ground freezing method, four typical soft soils, namely silty clay, mucky soil, residual cohesive soil, and fully weathered ignimbrite, were selected to conduct systematic physical and mechanical tests of frozen soil under the temperature range of -20°C to -5°C. The influence mechanism of temperature and confining pressure on the thermodynamic behavior of frozen soil was revealed through the transient hot wire method, unidirectional frost heave and thaw settlement test, and triaxial shear test. The results show that the thermal conductivity of soil samples increases significantly at low temperatures, with the largest increase observed in fully weathered ignimbrite and the smallest in mucky soil. The freezing temperature of soil samples under natural moisture content ranges from -2.25°C to -0.8°C, with the lowest value recorded for residual cohesive soil. The creep of frozen soil exhibits obvious stress dependence: it presents typical three-stage creep characteristics at the stress level of 0.5σs, and its long-term strength is approximately 0.5-0.7 times the instantaneous strength. In engineering practice, lower freezing temperature or strict control of loading duration should be adopted for soil layers with high creep potential. The triaxial shear strength of frozen soil increases with the decrease of temperature, and the most significant increase occurs in the temperature range of -5°C to -10°C. The strength of the tested soils ranks as follows: fully weathered ignimbrite > residual cohesive soil > silty clay > mucky soil. The influence of confining pressure on strength varies with soil types. During construction, differentiated freezing and support control measures shall be implemented according to the characteristics of soil layers, and monitoring shall be strengthened for sections with abnormal confining pressure response. The research results can provide an important basis for design optimization and construction risk control of subway underground excavation projects using artificial ground freezing method in soft soil areas.
To evaluate the disease-modifying potential of SM03, a novel humanized anti-CD22 monoclonal antibody, for B cell-mediated autoimmune diseases by investigating its mechanism for suppressing B cell dysregulation in autoimmune milieu. SM03's mechanism was assessed in-vitro using functional assays on stimulated human PBMC from healthy donors and patients with Systemic Lupus Erythematosus (SLE)/Sjögren's Syndrome (SS). The efficacy of SM03 to attenuate autoimmunity was then evaluated in-vivo in a humanized pristane-induced SLE mouse model as well as a preventive collagen-induced Rheumatoid Arthritis (RA) model in cynomolgus monkeys. Disease-specific biomarkers, histopathology, and immune cell phenotypes were analyzed. SM03 attenuated T cell-dependent B cell activation by reducing class-switched B cells, plasmablast differentiation, and pro-inflammatory cytokine production in B cell lines, healthy and disease PBMCs, without inducing B cell depletion. In the SLE model, SM03 suppressed key disease manifestations (splenomegaly, anti-dsDNA, proteinuria, glomerular deposits) and reduced activated T cells without broad B cell depletion. In the RA model, SM03 dose-dependently suppressed joint scores, cartilage damage, synovial hyperplasia, anti-collagen II antibodies, and IL-6. By enhancing CD22's inhibitory signalling to disrupt autoreactive B-T cell interactions, SM03 functions as a disease-modifying therapy that attenuates dysregulation of lymphocytes in autoimmunity. This non-depleting mechanism supports its translational potential for SLE and RA and implicates its broader utility for other B cell-driven autoimmune diseases.
Osteosarcoma remains a major treatment challenge, especially for patients with recurrent, refractory or metastatic diseases. Adoptive cell therapy (ACT), including CAR-T cells, TCR engineered T cells, CAR-NK cells and macrophage based cell therapy, provides a promising strategy for redirecting immune effector cells to fight osteosarcoma. However, clinical translation has been limited by antigen heterogeneity, on-target/off-tumor toxicity, insufficient tumor trafficking, poor persistence, functional exhaustion, and the immunosuppressive tumor microenvironment. This mini review discusses emerging innovations designed to overcome these safety and efficacy barriers. First, engineering strategies such as multi-antigen recognition, logic-gated CAR systems, suicide switches, transient CAR expression, armored cytokine circuits, checkpoint-resistant designs, and chemokine receptor modification may improve precision, controllability, and durability. Second, vaccination approaches may serve as programmable amplifiers of ACT by promoting in vivo expansion, immune memory, antigen spreading, and local inflammatory priming. Third, tumor microenvironment remodeling through stromal modulation, vascular normalization, myeloid reprogramming, checkpoint blockade, and metabolic intervention may convert osteosarcoma into a more permissive niche for cellular therapy. Collectively, next-generation ACT for osteosarcoma will likely require modular, biomarker-guided combinations that integrate cellular engineering, vaccine-based boosting, and microenvironmental remodeling to achieve safer and more durable antitumor responses.
The occurrence of quaternary ammonium compounds (QACs) in the environment has received increasing attention due to their widespread applications. Indoor dust is an important medium for human exposure, yet knowledge regarding the influence of dust exposure and human metabolism on the composition profiles of QACs in excretions remains limited. In this study, an integrated workflow combining targeted analysis and suspect screening was developed to comprehensively identify QACs in paired indoor dust and urine samples collected across China. A total of 69 compounds were detected in indoor dust, including 23 target analytes and 46 emerging analogues spanning both traditional hydrocarbon-based structures and subclasses bearing additional functional groups, such as choline, betaine, ester, amide, aryl, and pyridine. In urine, both traditional (n = 12) and emerging (n = 15) analogues were also detected, along with four hydroxyl or carboxyl metabolites of benzalkonium chlorides (BAC). Several influencing factors derived from the questionnaire survey (e.g., household income and frequency of personal care product use) were positively associated with QAC concentrations in indoor dust. After controlling for these covariates, the total concentration of BACs in dust remained positively correlated with that of the carboxyl metabolites in urine, suggesting these metabolites could serve as exposure biomarkers. By exploring the chemical space of QACs in paired samples, this study provides the first evidence linking indoor dust exposure to human urinary excretion.
Array-based sensing technology holds immense potential for the rapid identification of pathogenic bacteria. Nevertheless, developing a universal strategy that simultaneously achieves high-throughput discrimination of diverse foodborne pathogens while maintaining mechanistic interpretability poses substantial challenges. Herein, we introduce an intelligible sensing platform that synergizes dual-recognition nanoassemblies with interpretable machine learning for the instantaneous discrimination of 10 clinically relevant foodborne pathogens. Three aggregation-induced emission luminogens (AIEgens), functionalized with ethynyl, aldehyde, and phenylboronic acid moieties, are assembled with lysozyme to generate six cross-reactive sensing elements. Molecular docking and dynamics simulations reveal that the binding modes, ranging from purely hydrophobic to synergistically hydrophobic-polar interactions, govern the differential fluorescence responses toward bacterial surfaces. Upon exposure to bacteria, the sensor array produces unique fingerprints, enabling 100% classification accuracy across 7 machine learning algorithms. Crucially, the integration of XGBoost with SHapley additive explanations transcends conventional black-box analytics, unraveling the contribution of individual sensors and unveiling feature importance, which determines the dominant sensing elements and infers the pivotal role of aldehyde and phenylboronic acid groups in bacterial recognition. Their application potential is validated in the complex milk matrices, maintaining 100% classification accuracy and revealing the shifts of detection environment-dependent feature importance. This work establishes a new paradigm for intelligent pathogen surveillance, where the analytical performance and molecular insight converge to guide the rational design of next-generation sensing systems.
Sepsis is a critical illness characterized by pronounced temporal dynamics and marked heterogeneity of organ perfusion. Current hemodynamic management relies largely on global macro-circulatory variables such as MAP and CO, but these measures provide limited insight into inter-organ blood-flow redistribution and often fail to detect occult hypoperfusion in vulnerable tissues. Consequently, organ dysfunction may continue to progress even when systemic targets appear to be achieved. The arterial resistance index (RI) can be repeatedly assessed in specific organs with relatively high temporal resolution, it provides a practical signal for tracking perfusion heterogeneity in sepsis. On this basis, this review reframes sepsis as a process dominated by dynamic blood-flow redistribution rather than a single, homogeneous state of circulatory failure and proposes the Arterial Resistance Index Series in Echography (ARISE) framework. ARISE focuses on four representative vascular beds that capture key dimensions of circulatory regulation-including central control, vulnerable organs, and peripheral perfusion: the cerebral, renal, and superior mesenteric arteries, as well as the anatomical snuffbox artery. The framework emphasizes RI trajectories over time, inter-organ flow distribution, and the structured integration of these patterns. Available evidence indicates that arterial RI in different organs exhibits pronounced temporal variation and inter-organ heterogeneity during sepsis. Distinct trajectories are observed across central, vulnerable, and peripheral vascular beds, reflecting ongoing redistribution of blood flow as the disease evolves. Multi-organ RI assessment can reveal pathophysiological phenomena not captured by conventional macro-circulatory indices, including occult hypoperfusion, macro-microcirculatory uncoupling, and "sacrificial" redistribution. Advances in critical care ultrasonography now enable bedside, real-time, quantitative monitoring of multi-organ RI, providing the technical foundation for dynamic perfusion assessment. Overall, ARISE shifts sepsis assessment from a static pressure-flow paradigm to a dynamic framework centered on organ blood-flow distribution and evolving perfusion patterns.