Liver as a new target organ in Alzheimer's disease: insight from cholesterol metabolism and its role in amyloid-beta clearance.

Alzheimer's disease, the primary cause of dementia, is characterized by neuropathologies, such as amyloid plaques, synaptic and neuronal degeneration, and neurofibrillary tangles. Although amyloid plaques are the primary characteristic of Alzheimer's disease in the central nervous system and peripheral organs, targeting amyloid-beta clearance in the central nervous system has shown limited clinical efficacy in Alzheimer's disease treatment. Metabolic abnormalities are commonly observed in patients with Alzheimer's disease. The liver is the primary peripheral organ involved in amyloid-beta metabolism, playing a crucial role in the pathophysiology of Alzheimer's disease. Notably, impaired cholesterol metabolism in the liver may exacerbate the development of Alzheimer's disease. In this review, we explore the underlying causes of Alzheimer's disease and elucidate the role of the liver in amyloid-beta clearance and cholesterol metabolism. Furthermore, we propose that restoring normal cholesterol metabolism in the liver could represent a promising therapeutic strategy for addressing Alzheimer's disease.

Air quality forecasting using a spatiotemporal hybrid deep learning model based on VMD-GAT-BiLSTM.

The precise forecasting of air quality is of great significance as an integral component of early warning systems. This remains a formidable challenge owing to the limited information of emission source and the considerable uncertainties inherent in dynamic processes. To improve the accuracy of air quality forecasting, this work proposes a new spatiotemporal hybrid deep learning model based on variational mode decomposition (VMD), graph attention networks (GAT) and bi-directional long short-term memory (BiLSTM), referred to as VMD-GAT-BiLSTM, for air quality forecasting. The proposed model initially employ a VMD to decompose original PM2.5 data into a series of relatively stable sub-sequences, thus reducing the influence of unknown factors on model prediction capabilities. For each sub-sequence, a GAT is then designed to explore deep spatial relationships among different monitoring stations. Next, a BiLSTM is utilized to learn the temporal features of each decomposed sub-sequence. Finally, the forecasting results of each decomposed sub-sequence are aggregated and summed as the final air quality prediction results. Experiment results on the collected Beijing air quality dataset show that the proposed model presents superior performance to other used methods on both short-term and long-term air quality forecasting tasks.

A Comprehensive Overview of the Stellate Ganglion Block Throughout the Past Three Decades: A Bibliometric Analysis.

BACKGROUND: Over the past 3 decades, clinicians and scholars have used and studied the stellate ganglion block (SGB) extensively, making this field a highly anticipated research hot spot. To the best of our knowledge, there has been no bibliometric analysis of the SGB until now. OBJECTIVE: Our study aimed to complete multiple tasks regarding SGB research: identify the collaboration and impact of countries, institutions, journals, and authors, evaluate the knowledge base, trace the trends in hot spots, and explore the emerging topics relevant to the field. STUDY DESIGN: A bibliometric analysis. METHODS: Publications that were associated with the SGB and published between the years of 1993 and 2022 were retrieved from the Web of Science Core Collection on September 21st, 2023. CiteSpace 6.1.R6 and VOSviewer 1.6.18 were used to perform bibliometric and knowledge-map analyses. RESULTS: This study found a total of 837 publications originating from 51 countries and 1006 institutions. These articles were published in 393 journals. The United States was the country that produced the most articles focused on SGB, and the University of California, Los Angeles was the institution associated with the greatest number of publications. The anesthesiology and cardiology journals surveyed for this study published the most articles and received the most citations. Among the authors whose works were examined, Kitajima T had the greatest number of published articles, and Lipov E was the most frequently cited co-author. Five main domains of SGB research included electrical storm and refractory ventricular arrhythmia, breast cancer and climacteric medicine, post-traumatic stress disorder, pain management, and cerebrovascular diseases. The latest hot topics involving this field focused on SGB's anti-arrhythmic and anti-cerebral vasospasm effects and its treatment of long COVID syndrome. LIMITATIONS: Data were retrieved only from the WoSCC; therefore, publications in other databases might have been missed. CONCLUSION: This comprehensive bibliometric analysis conducted a complete overview of SGB research, which was helpful in furthering our understanding of research trends and locating research hot spots and gaps in this domain. This field is developing rapidly and will garner significant and continuous attention from future scholars.

The effect of non-insulin-based insulin resistance indices on the prediction of recurrence in patients with atrial fibrillation undergoing radiofrequency catheter ablation.

BACKGROUND: Atrial fibrillation (AF) is acknowledged as a disease continuum. Despite catheter ablation being recommended as a primary therapy for AF, the high recurrence rates have tempered the initial enthusiasm. Insulin resistance (IR) has been established as an independent predictor for the onset of AF. However, the correlation between non-insulin-based IR indices and late AF recurrence in patients undergoing radiofrequency catheter ablation remains unknown. METHODS: A retrospective cohort of 910 AF patients who underwent radiofrequency catheter ablation was included in the analysis. The primary endpoint was late AF recurrence during the follow-up period after a defined blank period. The relationship between non-insulin-based IR indices and the primary endpoint was assessed using multivariate Cox hazards regression models and restricted cubic splines (RCS). Additionally, the net reclassification improvement and integrated discrimination improvement index were calculated to further evaluate the additional predictive value of the four IR indices beyond established risk factors for the primary outcome. RESULTS: During a median follow-up period of 12.00 months, 189 patients (20.77%) experienced late AF recurrence, which was more prevalent among patients with higher levels of IR. The multivariate Cox hazards regression analysis revealed a significant association between these IR indices and late AF recurrence. Among the four indices, METS-IR provided the most significant incremental effect on the basic model for predicting late AF recurrence. Multivariable-adjusted RCS curves illustrated a nonlinear correlation between METS-IR and late AF recurrence. In subgroup analysis, METS-IR exhibited a significant correlation with late AF recurrence in patients with diabetes mellitus (HR: 1.697, 95% CI 1.397 - 2.063, P < 0.001). CONCLUSION: All the four non-insulin-based IR indices were significantly associated with late AF recurrence in patients undergoing radiofrequency catheter ablation. Addressing IR could potentially serve as a viable strategy for reducing the late AF recurrence rate.

Skeletal Stem Cell-Derived Exosomes Promote Meniscal Tear Healing and Ameliorate Secondary Osteoarthritis.

BACKGROUND: The self-repair ability after meniscal tears is poor, leading to the development of posttraumatic osteoarthritis. Promoting the repair of meniscal injuries remains a great challenge, especially in the avascular region. HYPOTHESIS: Local delivery of skeletal stem cell (SSC)-derived exosomes (SSC-Exos) would promote meniscal healing and prevent secondary osteoarthritis progression. STUDY DESIGN: Controlled laboratory study. METHODS: SSCs were isolated from bone marrow and exosomes were extracted via ultracentrifugation. The cell migration capabilities after incubation with exosomes were validated through in vitro cell culture. Full-thickness longitudinal medial meniscal tears were performed in the avascular region of 40 male Sprague-Dawley rats and 20 male New Zealand White rabbits, which were randomly divided into 2 groups: group treated with phosphate-buffered saline (GCON) and group treated with exosomes (GExosome). The effects of these treatments on meniscal healing and secondary osteoarthritis were evaluated by gross inspection, biomechanical testing, and histological assessment. RNA sequencing of in vitro cell cultures was performed to explore the underlying mechanisms. RESULTS: Exosomes were successfully extracted and identified. These exosomes significantly promoted cell migration capabilities in vitro (P < .01). The GExosome exhibited greater cell proliferation and tissue regeneration with type 2 collagen secretion, and a significantly higher meniscal repair score than that of the GCON at 8 weeks postoperatively (P < .05). In contrast to the degenerative changes in both the meniscus and articular cartilage of the GCON, meniscal tissue in the GExosome exhibited restoration of normal morphology with a smooth and glossy white surface and better mechanical strength at 8 weeks after meniscal repair. Both degeneration scores and synovitis scores were significantly higher in the GCON than in the GExosome (P < .05). Compared with the GCON, the expression of key genes related to cell migration, such as the chemokine family, was enhanced by exosome injection, leading to an upregulation of extracellular matrix expression while downregulating the expression of inflammation-related genes such as CD68 and the matrix metalloproteinase family. CONCLUSION: The administration of SSC-Exos effectively promoted meniscal healing in the avascular region and ameliorated secondary osteoarthritis. The effect might be attributed to inflammation modulation, promotion of cell migration, and secretion of extracellular matrix components. CLINICAL RELEVANCE: Injection of SSC-Exos represents a promising therapeutic option for promoting meniscal healing in the avascular region.

In situ DRIFTs-based comprehensive reaction mechanism of photo-thermal synergetic catalysis for dry reforming of methane over Ru-CeO2 catalyst.

Solar-driven photo-thermal dry reforming of methane (DRM) is an environmentally friendly production route for high-value-added chemicals. However, the lack of thorough understanding of the mechanism for photo-thermal reaction has limited its further development. Here, we systematically investigated the mechanism of photo-thermal DRM reaction with the representative of Ru/CeO2 catalyst. Through in situ DRIFTs and transient experiments, comprehensive investigation into the reaction steps and their reactive sites in the process of DRM reaction were conducted. Besides, the excitation and migration direction of photo-electron was determined by ISI-XPS experiments, and the change of surface defect structure induced by light was characterized by ISI-EPR experiments. Based on the above results, the photo-enhancement effect on each micro-reaction step was determined. This study provides a theoretical basis for the industrialization of photo-thermal DRM reaction and its development of catalysts.

Surface Reconstruction-Induced Photocatalytic Methanol Reduction Reaction on a Rutile TiO2(001) Surface.

Photochemistry of methanol on TiO2 surfaces is of great importance both fundamentally and industrially. Methanol was previously reported only to occur photogenerated hole-participating oxidation reactions on TiO2 surfaces. Herein, we report that, upon UV light illumination, the methoxy species formed by methanol dissociation at the 5-fold coordinated Ti4+ sites (CH3O(a)Ti5c) of a reconstructed rutile TiO2(001)-(1 × 1) surface also undergoes the C-O bond cleavage into methyl fragments mediated by photogenerated electrons, in addition to the well-established photogenerated hole-participating oxidation reactions. Upon subsequent heating, the resulting methyl species undergoes hydrogenation and coupling reactions into methane and ethane, respectively. Accompanying theoretical calculations showed that the lowest unoccupied molecular orbital (LUMO) of CH3O(a)Ti5c is localized almost at the conduction band minimum of the CH3O-adsorbed reconstructed rutile TiO2(001)-(1 × 1) surface, indicating the likely TiO2 → CH3O(a)Ti5c interfacial photoexcited-electron transfer. These results greatly broaden the photochemistry of methanol on TiO2 surfaces and demonstrate a photocatalytic methanol-to-hydrocarbon reaction route.

CXCR6 expression correlates with radiotherapy response and immune context in triple-negative breast cancer-experimental studies.

BACKGROUND: The chemokine receptor CXCR6 is critical for sustained tumor control mediated by CD8+ cytotoxic T cells (CTLs) in tumors. Previous studies have shown that ionizing radiation induces an inflamed immune contexture by upregulating CXCR6. However, the clinical significance of CXCR6 expression in triple-negative breast cancer (TNBC) and its correlation with radiotherapy remains unknown. This study aimed to clarify the prognostic value of CXCR6 and its role in the breast tumor microenvironment (TME). METHODS: The messenger RNA and protein expression of CXCR6 in human TNBC and their association with survival were analyzed. The role of CXCR6 in the immune context was investigated using a combination of single-cell RNA sequencing, bulk transcriptome sequencing data, and fluorescence-based multiplex immunohistochemistry (mIHC) techniques. RESULTS: Elevated CXCR6 expression correlated with better clinical outcomes and superior response to adjuvant radiotherapy and immunotherapy in TNBC. CXCR6 fostered an immunostimulatory microenvironment characterized by upregulated cytotoxic markers. We also found that CXCR6 plays a crucial role in regulating the differentiation of CD8+ T cells and the intercellular communication of immune cell subtypes, thus shaping the TME. CONCLUSIONS: This study highlights the emerging role of CXCR6 in shaping the TME and targeting CXCR6 may be a promising strategy for improving the effectiveness of radiotherapy and immunotherapy in TNBC.

A computational model for potential microbe-disease association detection based on improved graph convolutional networks and multi-channel autoencoders.

Introduction: Accumulating evidence shows that human health and disease are closely related to the microbes in the human body. Methods: In this manuscript, a new computational model based on graph attention networks and sparse autoencoders, called GCANCAE, was proposed for inferring possible microbe-disease associations. In GCANCAE, we first constructed a heterogeneous network by combining known microbe-disease relationships, disease similarity, and microbial similarity. Then, we adopted the improved GCN and the CSAE to extract neighbor relations in the adjacency matrix and novel feature representations in heterogeneous networks. After that, in order to estimate the likelihood of a potential microbe associated with a disease, we integrated these two types of representations to create unique eigenmatrices for diseases and microbes, respectively, and obtained predicted scores for potential microbe-disease associations by calculating the inner product of these two types of eigenmatrices. Results and discussion: Based on the baseline databases such as the HMDAD and the Disbiome, intensive experiments were conducted to evaluate the prediction ability of GCANCAE, and the experimental results demonstrated that GCANCAE achieved better performance than state-of-the-art competitive methods under the frameworks of both 2-fold and 5-fold CV. Furthermore, case studies of three categories of common diseases, such as asthma, irritable bowel syndrome (IBS), and type 2 diabetes (T2D), confirmed the efficiency of GCANCAE.

Machine Learning Big Data Set Analysis Reveals C-C Electro-Coupling Mechanism.

Carbon-carbon (C-C) coupling is essential in the electrocatalytic reduction of CO2 for the production of green chemicals. However, due to the complexity of the reaction network, there remains controversy regarding the underlying reaction mechanisms and the optimal direction for catalyst material design. Here, we present a global perspective to establish a comprehensive data set encompassing all C-C coupling precursors and catalytic active site compositions to explore the reaction mechanisms and screen catalysts via big data set analysis. The 2D-3D ensemble machine learning strategy, developed to target a variety of adsorption configurations, can quickly and accurately expand quantum chemical calculation data, enabling the rapid acquisition of this extensive big data set. Analyses of the big data set establish that (1) asymmetric coupling mechanisms exhibit greater potential efficiency compared to symmetric coupling, with the optimal path involving the coupling CHO with CH or CH2, and (2) C-C coupling selectivity of Cu-based catalysts can be enhanced through bimetallic doping including CuAgNb sites. Importantly, we experimentally substantiate the CuAgNb catalyst to demonstrate actual boosted performance in C-C coupling. Our finding evidence the practicality of our big data set generated from machine learning-accelerated quantum chemical computations. We conclude that combining big data with complex catalytic reaction mechanisms and catalyst compositions will set a new paradigm for accelerating optimal catalyst design.

Earing Prediction of AA5754-H111 (Al-Alloy) with Linear Transformation-Based Anisotropic Drucker Yield Function under Non-Associated Flow Rule (Non-AFR).

The yield behavior of aluminum alloy 5754-H111 under different stress conditions for three kinds of plastic work is studied using an anisotropic Drucker model. It is found that when the plastic work is 30 MPa, the anisotropic Drucker model has the most accurate prediction. Comparing the Hill48 and Yld91 models with the Drucker model, the results show that both the anisotropic Drucker and Yld91 models can accurately predict the yield behavior of the alloy. Cylinder drawing finite element analysis is performed under the AFR, but it is not possible to accurately predict the position and height of earing appearance. The anisotropic Drucker model is used to predict the earing behavior under the non-AFR, which can accurately predict the earing phenomenon. Numerical simulation is conducted using three different combinations of yield functions: the anisotropic yield function and the anisotropic plastic potential function (AYAPP), the anisotropic yield function and the isotropic plastic potential function (AYIPP), and the isotropic yield function and the anisotropic plastic potential function (IYAPP). It is concluded that the influence of the plastic potential function on predicting earing behavior is more critical than that of the yield function.

Cost-effective and natural-inspired lotus root/GelMA scaffolds enhanced wound healing via ROS scavenging, angiogenesis and reepithelialization.

Skin wounds, prevalent and fraught with complications, significantly impact individuals and society. Wound healing encounters numerous obstacles, such as excessive reactive oxygen species (ROS) production and impaired angiogenesis, thus promoting the development of chronic wound. Traditional clinical interventions like hemostasis, debridement, and surgery face considerable challenges, including the risk of secondary infections. While therapies designed to scavenge excess ROS and enhance proangiogenic properties have shown effectiveness in wound healing, their clinical adoption is hindered by high costs, complex manufacturing processes, and the potential for allergic reactions. Lotus root, distinguished by its natural micro and macro porous architecture, exhibits significant promise as a tissue engineering scaffold. This study introduced a novel scaffold based on hybridization of lotus root-inspired and Gelatin Methacryloyl (GelMA), verified with satisfactory physicochemical properties, biocompatibility, antioxidative capabilities and proangiogenic abilities. In vivo tests employing a full-thickness wound model revealed that these scaffolds notably enhanced micro vessel formation and collagen remodeling within the wound bed, thus accelerating the healing process. Given the straightforward accessibility of lotus roots and the cost-effective production of the scaffolds, the novel scaffolds with ROS scavenging, pro-angiogenesis and re-epithelialization abilities are anticipated to have clinical applicability for various chronic wounds.

Vitamin B6 prevents heart failure with preserved ejection fraction through downstream of kinase 3 in a mouse model.

BACKGROUND: There is an urgent need to develop an efficient therapeutic strategy for heart failure with preserved ejection fraction (HFpEF), which is mediated by phenotypic changes in cardiac macrophages. We previously reported that vitamin B6 (VB6) inhibits macrophage-mediated inflammasome activation OBJECTIVE: We sought to examine whether the prophylactic use of VB6 prevents HFpEF METHODS: HFpEF model was elicited by a combination of high fat diet and Nω-nitro-l-arginine methyl ester in mice. Cardiac function was assessed using conventional echocardiography and Doppler imaging. Immunohistochemistry and immunoblotting were used to detect changes in the macrophage phenotype and myocardial remodeling-related molecules RESULTS: Co-administration of VB6 with HFpEF mice mitigated HFpEF phenotypes, including diastolic dysfunction, cardiac macrophage phenotypic shifts, fibrosis, and hypertrophy. Echocardiographic improvements were observed, with the E/E' ratio decreasing from 42.0 to 21.6 and the E/A ratio improving from 2.13 to 1.17. The exercise capacity also increased from 295.3 m to 657.7 m. However, these beneficial effects were negated in downstream of kinase 3 (DOK3)-deficient mice. Mechanistically, VB6 increased DOK3 protein levels and inhibited macrophage phenotypic changes, which were abrogated by an AMP-activated protein kinase inhibitor CONCLUSION: VB6 increases DOK3 signaling to lower the risk of HFpEF by inhibiting phenotypic changes in cardiac macrophages.

Typical alien invasive aquatic-plant species changed the stability rather than the diversity of plankton community in fresh water.

Alien invasive aquatic-plant (AIA) species are severely threatening the aquatic ecosystems worldwide, especially biodiversity. Although plankton have been used to monitor and address biodiversity, some gaps remain in understanding of the relationships between plankton communities and AIA species. Here, the effects of two typical AIA species (Pistia stratiotes and Eichhornia crassipes) on plankton communities in freshwater with a native plant Vallisneria natans were investigated using a 50-d microcosm experiment. Results showed that AIA species significantly decreased water pH and dissolved oxygen while increased oxidation-reduction potential (p < 0.05). AIA species, especially P. stratiotes, significantly inhibited dry biomass accumulation in V. natans by an average rate of 39.0 %, decreased water pH by up to 14.62 %, and increased aboveground lengths and chlorophyll contents of V. natans by up to 36.2 % and 63.7 % (p < 0.05), respectively. These species further modified the growth strategy of V. natans from dry biomass accumulation to aboveground elongation. Although the AIA species did not alter plankton diversity (p > 0.05), but they changed their dominant species, functional communities (e.g., Groups D and TB), and co-occurrence networks. P. stratiotes decreased the average degree of the networks by 12.37-19.02 % and the graph density by 10.53-14.47 %, while E. crassipes decreased the modularity of the networks by 10.24 % compared with the control (without AIA species), respectively. Overall, AIA species inhibited the growth of V. natans and decreased the stability of plankton communities and their resistance to environmental disturbances. These findings enhance our understanding of how AIA species affect the growth of native plants and variations in plankton communities, thereby providing a theoretical basis for improving the ecological function and safety of freshwater.

Better performance of the APPLE score for the prediction of very early atrial fibrillation recurrence post-ablation.

BACKGROUND: The benefits of rhythm control in the early atrial fibrillation (AF) are increasingly recognized. This study aimed to investigate whether early AF ablation contributes to long-term sinus rhythm maintenance and to identify a suitable predictive score. METHODS: According to the diagnosis-to-ablation time, this study prospectively enrolled 245 very early AF patients, 262 early AF patients, and 588 late AF patients for radiofrequency ablation from June 2017 to December 2022. Clinical data, risk scores and follow-up results were collected and analyzed. RESULTS: Baseline characteristics were similar among the three cohorts. During a median follow-up period of 26 months, AF recurrence was observed in 61 (24.9%), 66 (25.2%), and 216 (36.7%) patients in the very early, early, and late AF cohorts, respectively. In the multivariable-adjusted model, very early and early AF were associated with a reduced risk of AF recurrence, with hazard ratios of 0.72 (95% confidence interval [CI]: 0.52-0.99) and 0.57 (95% CI: 0.41-0.78), respectively. The APPLE score demonstrated the highest predictive power for very early AF, with an area under the curve (AUC) of 0.74. However, its predictive power decreased with time from diagnosis, and a low predictive power for late AF (AUC=0.58). In addition, the time-dependent concordance index showed consistent results. For very early AF, the Akaike information criterion and decision curve analysis showed that APPLE had the highest predictive value. CONCLUSION: Very early AF ablation was associated with a lower recurrence rate, and the APPLE score can provide a higher predictive value for them. (URL: https://www.chictr.org.cn/; Unique identifier: ChiCTR-OIN-17013021).

ZCNC Beaded Heterostructure toward High-Performance Aluminum Batteries.

We designed and prepared the ZnSe/CoSe2@NC/CNTs (ZCNC) cathode material for aluminum batteries (ABs). The ZCN (ZnSe/CoSe2@NC) is connected by the interwoven carbon nanotube (CNT) conductive network to form a beaded structure. CNTs and the carbon formed by carbonization of organic ligands is beneficial to improving the electrical conductivity of the material and reducing structural damage during cycling. The internal electric field generated at the interface of heterostructures can promote the transfer of electrons/ions. This special structure promotes ZCNC excellent electrochemical properties. At 100 mA/g, the specific capacity of the first discharge reaches 338 mAh/g, while the specific capacity after 500 cycles still reaches 217 mAh/g. Compared with ZCN and CN(CoSe2@NC), it demonstrates a great advantage.

Characteristics and mechanisms of T-cell senescence: A potential target for cancer immunotherapy.

Immunosenescence, the aging of the immune system, leads to functional deficiencies, particularly in T cells, which undergo significant changes. While numerous studies have investigated age-related T-cell phenotypes in healthy aging, senescent T cells have also been observed in younger populations during pathological conditions like cancer. This review summarizes the recent advancements in age-associated alterations and markers of T cells, mechanisms, and the relationship between senescent T cells and the tumor microenvironment. We also discuss potential strategies for targeting senescent T cells to prevent age-related diseases and enhance tumor immunotherapy efficacy.

Room-temperature high-power laser emission of erbium-doped fluorite crystals at 2.8†µm.

We report on a high-power continuous-wave (CW) laser at 2.8 µm employing erbium (Er)-doped fluorite crystals as gain materials. With an optimized Er3+ ion concentration, thin "slab" geometry of the sample matching with the tailored pump beam profile and compensated negative thermal lens using a pair of concave mirrors cavity configuration, a highest power of 14.5 W is achieved from a dual-end-pumped Er:CaF2 laser, which, to the best of our knowledge, presents the record power from the room-temperature Er-bulk lasers in the 3-µm spectral range. In addition, 8.05 W output power is obtained from the Er:SrF2 laser with an RMS power stability of 0.35%. This work indicates that Er-doped fluorite crystals with large-scale available fabrication are promising candidates for high-power laser emission at ∼3 µm.

Pharmacological inhibition of Septins with Forchlorfenuron attenuates thrombus formation in experimental thrombotic mice models with modulating multiple signaling pathways in platelets.

INTRODUCTION: The Septin family of cytoskeletal proteins is abundant in platelets. When these proteins are functionally blocked using the compound forchlorfenuron (FCF), it hampers the normal activation processes of purified human platelets. OBJECTIVES: To evaluate the in vivo effects of FCF on physiological haemostasis and pathological thrombosis in mice and to investigate possible molecular mechanisms. METHODS: The impact of FCF on haemorrhage risk in the brain, liver, and tail of mice was investigated. Using several experimental models, thrombus development in the lung, mesenteric arteries, and postcava was studied. Functional assays were performed on mice and human platelets, both with and without FCF pretreatment. These tests included aggregation, granule release, ROS production, integrin αIIbß3 activation, cytoskeletal remodeling imaging, and clot retraction. RESULTS: Neither oral nor intravenous administration of FCF showed any apparent impairment of haemostasis in the tissues studied, but only later administration resulted in a significant reduction in thrombus formation in different mice vessel types. FCF generally inhibited agonist-induced platelet aggregation, degranulation, ROS burst, morphological expansion on the fibrinogen matrix with completely disordered dynamic organizations of the cytoskeleton for septin, tubulin and actin. In addition, FCF was found to antagonise agonist-induced dephosphorylation of VASP (Ser239) and PI3K/AKT and ERK1/2 phosphorylation. CONCLUSION: FCF showed preferences in attenuating pathological thrombus formation, apart from physiological haemostasis, with possible mechanisms to prevent cytoskeletal remodelling and signal transduction of AKT, ERK1/2 and VASP signalling pathways, suggesting that Septin may serve as a promising target for the prevention and treatment of thrombotic diseases.