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ABSTRACT Background Novel thrombotic molecular markers are significantly linked to acute ischemic stroke (AIS). However, the relationship between thrombin‐antithrombin complex (TAT), tissue plasminogen activator–inhibitor complex (t‐PAIC), plasmin‐α2 plasmin inhibitor complex (PIC), thrombomodulin (TM), and early neurological deterioration (END) remains unclear. Therefore, we developed a prediction model for END based on these markers and evaluated its accuracy and clinical utility. Methods Retrospective analysis of patients diagnosed with AIS in our hospital from 2023–2024. The above patients were divided into a training set (N = 577) and a test set (N = 246) in a 7:3 ratio. Least absolute shrinkage and selection of operator regression (LASSO) valid predictors were used. The coefficients of the predictors in logistic regression were used to develop a nomogram and to validate its differentiation, calibration, and clinical utility. Results The prevalence of END in AIS patients was 24.3%. Predictors screened according to LASSO regression analysis included age, the National Institutes of Health Stroke Scale (NIHSS) score, t‐PAIC, PIC, lymphocyte, and platelet. The resulting nomograms had the area under the curve (AUC) of 0.867 (95% CI, 0.834‐0.9) and 0.825 (95% CI, 0.757‐0.892) in the training and test sets, respectively, which had good differentiation. In addition, the calibration curve and decision curve analysis (DCA) showed that the model had good calibration and clinical utility. Conclusion A predictive model for END was developed using the serological markers t‐PAIC (male >17.13 ng/mL;female >10.52 ng/mL), PIC >0.85 µg/mL, Lymph ≤ 3.2×10^9/L, NIHSS, age, and platelet. The model has significant predictive value for END occurrence in patients with AIS. This study developed a predictive nomogram for early neurological deterioration (END) in acute ischemic stroke (AIS) using serum biomarkers tissue plasminogen activator–inhibitor complex (t‐PAIC) and plasmin ‐α2 plasmin inhibitor complex (PIC), age, National Institutes of Health Stroke Scale (NIHSS) score, lymphocyte (lymph), and platelet (PLT). The model demonstrated strong predictive accuracy with well‐calibrated and clinical utility for END risk assessment.

Background Coagulation and fibrinolysis are distinct processes that are highly correlated. Cells control coagulation and fibrinolysis by expression of tissue factor and urokinase-type plasminogen activator receptor on their surface. Tumor cells express these proteins, adjust their microenvironment and induce tumor exacerbation. We hypothesized that the expression of plasma markers for coagulation and fibrinolysis in patients with soft tissue sarcomas (STSs) was dependent on the level of tumor malignancy. To elucidate which markers are predictive of recurrence, metastasis and prognosis, coagulation or fibrinolysis, we analyzed the correlation between plasma levels of thrombin-antithrombin III complex (TAT), soluble fibrin (SF), plasmin-α2 plasmin inhibitor complex (PIC), D-dimer (DD) and clinical parameters in patients with STSs. Methods TAT, SF, PIC or DD were measured in pre-treatment blood samples from 64 patients with primary STSs and analyzed with clinicopathological parameters, and 5-year recurrence free survival (RFS), 5-year metastasis free survival (MFS) and 5-year overall survival (OS) were evaluated. Results The metastasis group had significantly higher DD (p = 0.0394), PIC (p = 0.00532) and SF (p = 0.00249) concentrations than the group without metastasis. The group that died of disease showed significantly higher DD (p = 0.00105), PIC (p = 0.000542), SF (p = 0.000126) and TAT (p = 0.0373) than surviving patients. By dividing the patients into low and high groups, the group with high DD, PIC, SF and TAT showed significantly lower 5-year MFS and 5-year OS than the corresponding low group. Furthermore, in multivariate COX proportional hazard analysis of continuous variables for 5-year MFS, only PIC was found to be a significant factor (HR: 2.14). Conclusion Fibrinolysis was better than coagulation at reflecting the disease condition of patients with STS. Notably, PIC levels ≥ 1.1 can not only predict the risk of metastasis and poor prognosis, but also increasing PIC levels correspond to further increases in risks of metastasis and poor prognosis.

Background The intimate relationship between coagulation and fibrinolysis in malignant tumors is a well-known phenomena, with the malignant phenotype enhancing coagulation and fibrinolysis. We hypothesized that soft tissue sarcoma (STS) affects the expression of coagulation and fibrinolysis markers, which could be used to distinguish STS from benign soft tissue tumors. We analyzed the correlations between plasma levels of D-dimer (DD), plasmin-α2 plasmin inhibitor complex (PIC), soluble fibrin (SF), and thrombin-antithrombin III complex (TAT) in benign soft tissue tumors and STS to elucidate whether these markers can be used to predict STS. Methods Plasma DD, PIC, SF and TAT levels in primary soft tissue tumors (benign 67, STS 68) were measured before biopsy or treatment. The marker levels were analyzed and compared to various clinicopathological parameters. Results In malignancy (STS), the average DD, PIC and SF levels were significantly higher than in benign tumors. Multivariate logistic analysis of continuous variables indicated that only PIC exhibited a significant difference (OR: 24.5, 95%CI: 3.55–170, p  = 0.0012). Receiver operating characteristic curve analysis produced area under the curve values for DD: 0.691, PIC: 0.784, SF: 0.734 and TAT: 0.588. Youden’s index was used to establish thresholds of 0.37 (DD), 0.80 (PIC), 0.90 (SF) and 0.82 (TAT). Threshold values for PIC and SF indicated high specificity (0.881, 0.791) and high positive predictive value (0.818, 0.745), respectively. The highest accuracy value among the markers was observed for PIC (0.704). Significant differences in multivariate analysis of binary variables were demonstrated by categorizing low and high groups based on their threshold, PIC (≥0.80) (OR: 3.36, 95%CI: 1.19–9.43, p  = 0.0212) and SF (≥0.90) (OR: 2.63, 95%CI: 1.04–6.66, p  = 0.0404) . Conclusions Of the coagulation and fibrinolysis markers studied, increased PIC levels were related to STS and over 0.80 PIC was the most suitable for the prediction of STS, which, along with other diagnostic tools, represents a helpful subsidiary tool for the prediction of STS.

Although recent technical advances in thrombectomy have revolutionised acute stroke treatment, prevalence of disability and death related to stroke remain high. Therefore, plasminogen activators—eukaryotic, bacterial, or engineered forms that can promote fibrinolysis by converting plasminogen into active plasmin and facilitate clot breakdown—are still commonly used in the acute treatment of ischaemic stroke. Hence, plasminogen activators have become a crucial area for clinical investigation for their ability to recanalise occluded arteries in ischaemic stroke and to accelerate haematoma clearance in haemorrhagic stroke. However, inconsistent results, insufficient evidence of efficacy, or reports of side-effects in trial settings might reduce the use of plasminogen activators in clinical practice. Additionally, the mechanism of action for plasminogen activators could extend beyond the vessel lumen and involve plasminogen-independent processes, which would suggest that plasminogen activators have also non-fibrinolytic roles. Understanding the complex mechanisms of action of plasminogen activators can guide future directions for therapeutic interventions in patients with stroke.

Fibrinolysis is an important process in hemostasis responsible for dissolving the clot during wound healing. Plasmin is a central enzyme in this process via its capacity to cleave fibrin. The kinetics of plasmin generation (PG) and inhibition during fibrinolysis have been poorly understood until the recent development of assays to quantify these metrics. The assessment of plasmin kinetics allows for the identification of fibrinolytic dysfunction and better understanding of the relationships between abnormal fibrin dissolution and disease pathogenesis. Additionally, direct measurement of the inhibition of PG by antifibrinolytic medications, such as tranexamic acid, can be a useful tool to assess the risks and effectiveness of antifibrinolytic therapy in hemorrhagic diseases. This review provides an overview of available PG assays to directly measure the kinetics of plasmin formation and inhibition in human and mouse plasmas and focuses on their applications in defining the role of plasmin in diseases, including angioedema, hemophilia, rare bleeding disorders, COVID-19, or diet-induced obesity. Moreover, this review introduces the PG assay as a promising clinical and research method to monitor antifibrinolytic medications and screen for genetic or acquired fibrinolytic disorders.

Background and aims Thrombolytic therapy is widely used to treat acute ischemic stroke (AIS) patients. As intracerebral hemorrhage is a life‐threatening complication of this therapy, monitoring the fibrinolytic and coagulation systems is imperative. However, existing studies on plasmin inhibitor complex (PIC) and thrombin‐antithrombin III complex (TAT) mostly apply the enzyme‐linked immunosorbent assay (ELISA) method. The aim of this study is to establish the baseline of thrombolytic treatment for AIS patients; to monitor the fibrinolytic and coagulation system following alteplase administration; to ascertain the proper time point to predict intracerebral hemorrhage. Methods The method used to assess a patient's intravascular situation, namely chemiluminescence, was used to quantitatively assess the PIC, TAT, and thrombomodulin (TM). Immuno‐turbidimetric was used to assess the concentration of D‐dimer, fibrin/fibrinogen degradation products (FDP), and the Von Willebrand factor (vWF). The Clauss clotting method was used to assay the activated partial thromboplastin time (APTT), prothrombin time (PT) and FIB. Results PIC increased to its peak concentration at 3 hours post intravenous (IV) alteplase infusion and decreased by nearly 50% every 3 hours thereafter. After 24 hours, PIC returned to its normal range, while D‐dimer and FDP decreased 3 hours later compared to PIC. PT and APTT exhibited no obvious change during the 24‐hour period. TM also exhibited no changes during the treatment. Conclusion PIC decreased 3 hours earlier than D‐dimer and FDP. The combined test of PIC, D‐dimer, and fibrinogen can be used to monitor the fibrinolytic system after the IV alteplase infusion. The use of IV alteplase had no impact on the endothelium. Creating a patient's individual data curve could assist in the prediction of hemorrhagic transformation (HT) and a stroke occurring.

Background To conduct a comprehensive performance evaluation of a fully automated analyzer for measuring thrombomodulin (TM), thrombin‐antithrombin complex (TAT), plasmin‐α2‐antiplasmin complex (PAP), and t‐PA: PAI‐1 complex (tPAI‐C). Methods According to the Clinical and Laboratory Standards Institute (CLSI) EP05‐A2, EP06‐A specifications, TM, TAT, PAP, and tPAI‐C were analyzed to evaluate intraassay variability and interassay variability, linear range, carryover rate, reference range, sample stability, and interferences. Results The intraassay variability and interassay variability of the four factors were all below 5%. The carryover rates were below 1%. Linear verification analysis revealed correlation coefficients of 0.998‐0.999. The recommended reference ranges of TM, TAT, and PAP were appropriate for our laboratory, whereas the reference of tPAI‐C should be established by each laboratory. Stability assessment revealed that TM is stable for 2 days at room temperature but lacks stability at colder temperatures. In contrast, TAT is stable for 5 days at 4°C and −20°C but has poor stability at room temperature. PAP and tPAI‐C are stable for 3 days at all three temperatures. The measurement of TM, TAT, PAP, and tPAI‐C is not altered by the presence of 510 mg/dL hemoglobin, 1490 FTU triglycerides, or 21.1 mg/dL conjugated and free bilirubin. Conclusion The determination of TM, TAT, PAP, and tPAI‐C using a high‐sensitivity chemiluminescence analyzer performs well in terms of precision, carryover rate, linear range, and interference. Thus, this method is suitable for the detection of these substances in clinical specimens.

The structural integrity of tissue proteins is damaged in processes ranging from remodeling of the extracellular matrix to destruction by microbial pathogens. Leukocytes play a prominent role in tissue surveillance and repair. However, it remains enigmatic what features of structurally decayed proteins prompt recognition by leukocyte cell-surface receptors. Here, we report that adhesion of human neutrophil granulocytes to fibrinogen is greatly increased by plasmin digestion in a mode where α X β 2 dominates the integrin-dependent binding. The bacterial protease subtilisin also enhances binding by α X β 2 . The α X ligand binding domain has an unusually high affinity for carboxyl groups, with K D at ≈100 μM. Our findings implicate enhanced accessibility of negatively charged residues in structurally decayed proteins as a pattern recognition motif for α X β 2 integrin. Comparisons among integrins show relevance of these findings to the large number of ligands recognized by α M β 2 and α X β 2 but not α L β 2 . The observations suggest that the pericellular proteolysis at the leading edge of neutrophils not only facilitates passage through the extracellular matrix but also manufactures binding sites for α X β 2 .

Leptospirosis is a widespread zoonosis caused by pathogenic Leptospira spp. It is considered a neglected infectious disease of human and veterinary concern. Our group has been investigating proteins annotated as hypothetical, predicted to be located on the leptospiral surface. Because of their location, these proteins may have the ability to interact with various host components, which could allow establishment of the infection. These proteins act as adherence factors by binding to host receptor molecules, such as the extracellular matrix (ECM) components laminin and glycosaminoglycans to help bacterial colonization. Leptospira also interacts with the host fibrinolytic system, which has been demonstrated to be a powerful tool for invasion mechanisms. The interaction with fibrinogen and thrombin has been shown to reduce fibrin clot formation. Additionally, the degradation of coagulation cascade components by secreted proteases or by acquired surface plasmin could also play a role in reducing clot formation, hence facilitating dissemination during infection. Interaction with host complement system regulators also plays a role in helping bacteria to evade the immune system, facilitating invasion. Interaction of Leptospira to cell receptors, such as cadherins, can contribute to investigate molecules that participate in virulence. To achieve a better understanding of the host-pathogen interaction, leptospiral mutagenesis tools have been developed and explored. This work presents several proteins that mediate binding to components of the ECM, plasma, components of the complement system and cells, to gather research achievements that can be helpful in better understanding the mechanisms of leptospiral-host interactions and discuss genetic manipulation for Leptospira spp. aimed at protein function validation.