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Last update 23 Jan 2025

F13A1

Last update 23 Jan 2025

Basic Info

Synonyms

coagulation factor XIII A chain, Coagulation factor XIIIa, F13A

+ [3]

Introduction

Factor XIII is activated by thrombin and calcium ion to a transglutaminase that catalyzes the formation of gamma-glutamyl-epsilon-lysine cross-links between fibrin chains, thus stabilizing the fibrin clot. Also cross-link alpha-2-plasmin inhibitor, or fibronectin, to the alpha chains of fibrin.

Drugs associated with F13A1

ZED-3197

Target

F13A1

Mechanism

F13A1 inhibitors

Active Org.

Zedira GmbH

Originator Org.

Zedira GmbH

Active Indication

Thrombosis

Inactive Indication-

Drug Highest PhasePreclinical

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

100 Clinical Results associated with F13A1

100 Translational Medicine associated with F13A1

0 Patents (Medical) associated with F13A1

758

Literatures (Medical) associated with F13A1

01 Mar 2025·Current Pharmaceutical Design

Establishment of an Integrated Population Pharmacokinetic/Pharmacodynamics Model of Apixaban in Chinese Healthy Population Adjusting for Key Genetic Variants

Article

Author: Meng, Xianmin ; Liu, Zhiyan ; Wang, Zining ; Mu, Guangyan ; Xiang, Qian ; Zhou, Shuang ; Cui, Yimin ; Song, Jinfang ; Liu, Yaou ; Wang, Zhe ; Zhao, Xia ; Zhang, Hanxu ; Hu, Kun ; Bao, Jiachun ; Liao, Maoxing ; Xie, Qiufen

Aims:To improve the understanding of pharmacokinetic/pharmacodynamic (PK/PD) profiles of apixaban, supporting personalised drug prescriptions for future patients.Background:Genetic as well as nongenetic factors can affect the predictable PK and PD characteristics of apixaban.Objective:Establish a integrated popPK/PD model that adjusts for critical genetic variant.Methods:The integrated PK/PD models was characterized on the basis of PK (apixaban blood concentration) and PD (prothrombin time (PT), activated partial thromboplastin time (APTT), and anti-FXa activity) data from 181 healthy Chinese volunteers. Other investigated covariate variables included: Meaningful intrinsic and extraneous determinants, correlated genetic factors (ABCG2, F13A1, C3, etc.). A total of 2877 PK concentration observations were included in the modeling dataset.Results:The PK model of apixaban is adopted by single compartment model with first-order oral absorption. The estimated values of total clearance rate (CL/F), apparent distribution volume (V/F), and absorption rate constant (KA) in the final model are 3.37 L/h, 28.2 L, and 0.781 1/h, respectively. The PK model includes significance covariates such as FOOD, RBC, WT, and gene (ABCG2). The PD model of apixaban is adopted by a linear direct effect model with additive error, which was used to describe the relationship between markers such as APTT, PT, anti-FXa, versus plasma concentration. PK simulation within the modelled dose range is similar to clinical real date, while PD simulation results also show that the simulated exposure parameters is within the range of the literature.Conclusion:We established a comprehensive PK/PD model and used it to simulate markers level such as APTT, PT, and anti-FXa of apixaban. Individual predictive values with a dose of 2.5 mg are basically within the expected recommended range.

01 Dec 2024·Clinical and Translational Medicine

Single‐cell dissection reveals immunosuppressive F13A1+ macrophage as a hallmark for multiple primary lung cancers

Article

Author: Cai, Songhua ; Wu, Jingting ; Meng, Yiran ; Zhang, Lishen ; Guo, Xiaotong ; Liu, Wenyi ; Qu, Jiahao ; Yang, Chenglin ; Zheng, Liuqing ; Wang, Li ; Deng, Youjun

AbstractBackgroundThe increasing prevalence of multiple primarylung cancers (MPLCs) presents challenges to current diagnostic and clinicalmanagement approaches. However, the molecular mechanisms driving MPLCdevelopment and distinguishing it from solitary primary lung cancers (SPLCs)remain largely unexplored.MethodsWe performed a comparative single‐cell RNAsequencing (scRNA‐seq) analysis on tumour and adjacent para‐tumour tissues fromMPLC and SPLC patients to comparatively evaluate their immunological landscapes.Additionally, multiplex immunofluorescence (mIF) staining and independentvalidation datasets were used to confirm findings.ResultsMPLCs and SPLCs share significant similarities in genetic, transcriptomic and immune profiles, suggesting common therapeutic strategies such as EGFR‐TKIs andICIs. Notably, an immunosuppressive macrophage subtype, F13A1+ Macrophage (Mϕ), is specifically enriched in MPLCs. This subtype overexpresses M2 macrophagemarkers and exhibits up‐regulation of SPP1‐CD44/CCL13‐ACKR1 interactions, indicatingits role in shaping the immunosuppressive tumour microenvironment and promotingtumour growth in MPLCs.ConclusionsThis study unveils shared molecular mechanismsbetween MPLCs and SPLCs, while identifying MPLC‐specific cellular and molecularfeatures, such as the role of F13A1+ macrophages. The findings provide novelinsights into MPLC pathogenesis, supporting the development of targetedtherapeutic strategies.Key points

Comparative scRNA‐seq analysis reveals significant similarities in genetic, transcriptomicand immune profiles between MPLCs and SPLCs.

Identification of a unique immunosuppressive F13A1+ macrophage subtype, preferentially enriched in MPLCs, linked to immune evasion and tumourprogression.

SPP1‐CD44/CCL13‐ACKR1 interactions are crucial in MPLC tumour microenvironment, indicating potential targets for therapeutic intervention.

01 Dec 2024·Clinical and Translational Allergy

M2 macrophage derived HMOX1 defines chronic rhinosinusitis with nasal polyps

Article

Author: Li, Ying ; Hong, Yu ; Wang, Ming ; Wang, Chengshuo ; Wang, Yang ; Zhang, Luo ; Hao, Yanghe ; Yuan, Jing ; Wang, Enhao ; Song, Jing

AbstractBackgroundMolecular signatures of chronic rhinosinusitis with nasal polyps (CRSwNP) related to macrophages remain unclear. This study aimed to develop a macrophage‐associated diagnostic signature for CRSwNP.MethodsTranscriptome data from 54 patients with CRSwNP and 37 healthy controls across GSE136825, GSE36830, and GSE72713 were used to identify differentially expressed genes (DEGs) between two groups. Gene Set Enrichment Analysis and Weighted Gene Co‐Expression Network Analysis pinpointed crucial pathways and gene clusters. A diagnostic model was created from these analyses and receiver operating characteristic curve (ROC), and further validated in our transcriptome data from 29 samples. Immune cell infiltration analysis was performed and linked those diagnostic genes to macrophages and verified by single‐cell RNA sequencing data. Immunofluorescence co‐staining of CD163 and HMOX1 was performed in nasal tissues. Mouse bone marrow‐derived macrophage (BMDMs) cultures were used in functional experiments. Correlations between the expression of HMOX1 and eotaxin genes were investigated.ResultsDEGs of CRSwNP versus control group were enriched in the INTERLEUKIN_4_AND_13_SIGNALING pathways. A four‐gene diagnostic model (HMOX1, ALOX5, F13A1 and ITGB2) was developed and demonstrated high diagnostic precision with an area under ROC curve of 0.980 for training dataset and 0.895 for test dataset. M2 macrophage presence and HMOX1 expression significantly correlated with CRSwNP (p < 0.001). Single‐cell RNA sequencing data underscored the altered cellular composition in CRSwNP, with HMOX1 notably expressed in M2 macrophages. Immunofluorescence staining highlighted the increased infiltration of CD163+ M2 macrophages in nasal mucosa samples of eosinophilic CRSwNP, which correlated with HMOX1 protein levels (p < 0.05). The HMOX1 inhibitor zinc protoporphyrin reduced the ratio of CD163 + HMOX1 + M2 macrophages in mouse BMDM cultures (p < 0.05). HMOX1 expression showed a strong positive correlation with the expression of eotaxin genes (CCL11, CCL24, and CCL26; p < 0.05 respectively).ConclusionM2 macrophage‐derived HMOX1 can be used as an innovative diagnostic signature for CRSwNP, which might be a potential regulator of eosinophilic inflammation.

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F13A1

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