Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.

Rationale and design of the PACIFIC-PRESERVED (PhenomApping, ClassIFication and Innovation for Cardiac dysfunction in patients with heart failure and PRESERVED left ventricular ejection fraction) study.

BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome that is poorly defined, reflecting an incomplete understanding of its pathophysiology. AIM: To redefine the phenotypic spectrum of HFpEF. METHODS: The PACIFIC-PRESERVED study is a prospective multicentre cohort study designed to perform multidimensional deep phenotyping of patients diagnosed with HFpEF (left ventricular ejection fraction≥50%), patients with heart failure with reduced ejection fraction (left ventricular ejection fraction≤40%) and subjects without overt heart failure (3:2:1 ratio). The study proposes prospective investigations in patients during a 1-day hospital stay: physical examination; electrocardiogram; performance-based tests; blood samples; cardiac magnetic resonance imaging; transthoracic echocardiography (rest and low-level exercise); myocardial shear wave elastography; chest computed tomography; and non-invasive measurement of arterial stiffness. Dyspnoea, depression, general health and quality of life will be assessed by dedicated questionnaires. A biobank will be established. After the hospital stay, patients are asked to wear a connected garment (with digital sensors) to collect electrocardiography, pulmonary and activity variables in real-life conditions (for up to 14 days). Data will be centralized for machine-learning-based analyses, with the aim of reclassifying HFpEF into more distinct subgroups, improving understanding of the disease mechanisms and identifying new biological pathways and molecular targets. The study will also serve as a platform to enable the development of innovative technologies and strategies for the diagnosis and stratification of patients with HFpEF. CONCLUSIONS: PACIFIC-PRESERVED is a prospective multicentre phenomapping study, using novel analytical techniques, which will provide a unique data resource to better define HFpEF and identify new clinically meaningful subgroups of patients.

A hybrid approach based on multipath Swin transformer and ConvMixer for white blood cells classification.

White blood cells (WBC) play an effective role in the body's defense against parasites, viruses, and bacteria in the human body. Also, WBCs are categorized based on their morphological structures into various subgroups. The number of these WBC types in the blood of non-diseased and diseased people is different. Thus, the study of WBC classification is quite significant for medical diagnosis. Due to the widespread use of deep learning in medical image analysis in recent years, it has also been used in WBC classification. Moreover, the ConvMixer and Swin transformer models, recently introduced, have garnered significant success by attaining efficient long contextual characteristics. Based on this, a new multipath hybrid network is proposed for WBC classification by using ConvMixer and Swin transformer. This proposed model is called Swin Transformer and ConvMixer based Multipath mixer (SC-MP-Mixer). In the SC-MP-Mixer model, firstly, features with strong spatial details are extracted with the ConvMixer. Then Swin transformer effectively handle these features with self-attention mechanism. In addition, the ConvMixer and Swin transformer blocks consist of a multipath structure to obtain better patch representations in the SC-MP-Mixer. To test the performance of the SC-MP-Mixer, experiments were performed on three WBC datasets with 4 (BCCD), 8 (PBC) and 5 (Raabin) classes. The experimental studies resulted in an accuracy of 99.65% for PBC, 98.68% for Raabin, and 95.66% for BCCD. When compared with the studies in the literature and the state-of-the-art models, it was seen that the SC-MP-Mixer had more effective classification results.

Spatial-attention ConvMixer architecture for classification and detection of gastrointestinal diseases using the Kvasir dataset.

Gastrointestinal (GI) disorders, encompassing conditions like cancer and Crohn's disease, pose a significant threat to public health. Endoscopic examinations have become crucial for diagnosing and treating these disorders efficiently. However, the subjective nature of manual evaluations by gastroenterologists can lead to potential errors in disease classification. In addition, the difficulty of diagnosing diseased tissues in GI and the high similarity between classes made the subject a difficult area. Automated classification systems that use artificial intelligence to solve these problems have gained traction. Automatic detection of diseases in medical images greatly benefits in the diagnosis of diseases and reduces the time of disease detection. In this study, we suggested a new architecture to enable research on computer-assisted diagnosis and automated disease detection in GI diseases. This architecture, called Spatial-Attention ConvMixer (SAC), further developed the patch extraction technique used as the basis of the ConvMixer architecture with a spatial attention mechanism (SAM). The SAM enables the network to concentrate selectively on the most informative areas, assigning importance to each spatial location within the feature maps. We employ the Kvasir dataset to assess the accuracy of classifying GI illnesses using the SAC architecture. We compare our architecture's results with Vanilla ViT, Swin Transformer, ConvMixer, MLPMixer, ResNet50, and SqueezeNet models. Our SAC method gets 93.37% accuracy, while the other architectures get respectively 79.52%, 74.52%, 92.48%, 63.04%, 87.44%, and 85.59%. The proposed spatial attention block improves the accuracy of the ConvMixer architecture on the Kvasir, outperforming the state-of-the-art methods with an accuracy rate of 93.37%.

The PACIFIC ontology for heterogeneous data management in cardiology.

With the emergence of health data warehouses and major initiatives to collect and analyze multi-modal and multisource data, data organization becomes central. In the PACIFIC-PRESERVED (PhenomApping, ClassIFication, and Innovation for Cardiac Dysfunction - Heart Failure with PRESERVED LVEF Study, NCT04189029) study, a data driven research project aiming at redefining and profiling the Heart Failure with preserved Ejection Fraction (HFpEF), an ontology was developed by different data experts in cardiology to enable better data management in a complex study context (multisource, multiformat, multimodality, multipartners). The PACIFIC ontology provides a cardiac data management framework for the phenomapping of patients. It was built upon the BMS-LM (Biomedical Study -Lifecycle Management) core ontology and framework, proposed in a previous work to ensure data organization and provenance throughout the study lifecycle (specification, acquisition, analysis, publication). The BMS-LM design pattern was applied to the PACIFIC multisource variables. In addition, data was structured using a subset of MeSH headings for diseases, technical procedures, or biological processes, and using the Uberon ontology anatomical entities. A total of 1372 variables were organized and enriched with annotations and description from existing ontologies and taxonomies such as LOINC to enable later semantic interoperability. Both, data structuring using the BMS-LM framework, and its mapping with published standards, foster interoperability of multimodal cardiac phenomapping datasets.

HCG18, LEF1AS1 and lncCEACAM21 as biomarkers of disease severity in the peripheral blood mononuclear cells of COVID-19 patients.

BACKGROUND: Even after 3 years from SARS-CoV-2 identification, COVID-19 is still a persistent and dangerous global infectious disease. Significant improvements in our understanding of the disease pathophysiology have now been achieved. Nonetheless, reliable and accurate biomarkers for the early stratification of COVID-19 severity are still lacking. Long noncoding RNAs (LncRNAs) are ncRNAs longer than 200 nucleotides, regulating the transcription and translation of protein-coding genes and they can be found in the peripheral blood, thus holding a promising biomarker potential. Specifically, peripheral blood mononuclear cells (PBMCs) have emerged as a source of indirect biomarkers mirroring the conditions of tissues: they include monocytes, B and T lymphocytes, and natural killer T cells (NKT), being highly informative for immune-related events. METHODS: We profiled by RNA-Sequencing a panel of 2906 lncRNAs to investigate their modulation in PBMCs of a pilot group of COVID-19 patients, followed by qPCR validation in 111 hospitalized COVID-19 patients. RESULTS: The levels of four lncRNAs were found to be decreased in association with COVID-19 mortality and disease severity: HLA Complex Group 18-242 and -244 (HCG18-242 and HCG18-244), Lymphoid Enhancer Binding Factor 1-antisense 1 (LEF1-AS1) and lncCEACAM21 (i.e. ENST00000601116.5, a lncRNA in the CEACAM21 locus). Interestingly, these deregulations were confirmed in an independent patient group of hospitalized patients and by the re-analysis of publicly available single-cell transcriptome datasets. The identified lncRNAs were expressed in all of the PBMC cell types and inversely correlated with the neutrophil/lymphocyte ratio (NLR), an inflammatory marker. In vitro, the expression of LEF1-AS1 and lncCEACAM21 was decreased upon THP-1 monocytes exposure to a relevant stimulus, hypoxia. CONCLUSION: The identified COVID-19-lncRNAs are proposed as potential innovative biomarkers of COVID-19 severity and mortality.

Firalink: A bioinformatics pipeline for long non-coding RNA data analysis.

Summary: The Firalink bioinformatics pipeline has been developed to analyse long non-coding RNA (lncRNA) data generated by targeted sequencing. This pipeline has been first implemented for use with the FIMICS panel containing 2906 lncRNAs useful for investigations in cardiovascular disease. It has been subsequently tested and validated using a panel of lncRNAs targeting brain disease. The pipeline can be adapted to other targeted sequencing panels or other transcriptomics data (e.g. whole transcriptome) through a change of the reference genome/panel. Therefore, Firalink can be applied to different lncRNA panels and transcriptomics data targeting multiple diseases. Availability and implementation: The Firalink pipeline works on Linux and is freely available to non-commercial users at https://gitlab.lcsb.uni.lu/covirna/covirna-ext/covirna-firalink-pipeline. Access will be granted after contacting bioinformatics@firalis.com. The pipeline is implemented with the Nextflow workflow manager using Python and R scripts. It will remain available for at least two years following publication and will be regularly updated and upgraded. Supplementary information: For an example of the application of the Firalink pipeline using the FIMICS panel, see www.covirna.eu.

FIMICS: A panel of long noncoding RNAs for cardiovascular conditions.

Cardiovascular disorders such as heart failure are leading causes of mortality. Patient stratification via identification of novel biomarkers could improve management of cardiovascular diseases of complex etiologies. Long-noncoding RNAs (lncRNAs) are highly tissue-specific in nature and have emerged as important biomarkers in human diseases. In this study, we aimed to identify cardiac-enriched lncRNAs as potential biomarkers for cardiovascular conditions. Deep RNA sequencing and quantitative PCR identified differentially expressed lncRNAs between failing and non-failing hearts. An independent dataset was used to evaluate the enrichment of lncRNAs in normal hearts. We identified a panel of 2906 lncRNAs, named FIMICS, that were either cardiac-enriched or differentially expressed between failing and non-failing hearts. Expression of lncRNAs in blood samples differentiated patients with myocarditis and acute myocardial infarction. We hereby present the FIMICS panel, a readily available tool to provide insights into cardiovascular pathologies and which could be helpful for diagnosis, monitoring and prognosis purposes.

Association of miR-144 levels in the peripheral blood with COVID-19 severity and mortality.

Coronavirus disease-2019 (COVID-19) can be asymptomatic or lead to a wide symptom spectrum, including multi-organ damage and death. Here, we explored the potential of microRNAs in delineating patient condition and predicting clinical outcome. Plasma microRNA profiling of hospitalized COVID-19 patients showed that miR-144-3p was dynamically regulated in response to COVID-19. Thus, we further investigated the biomarker potential of miR-144-3p measured at admission in 179 COVID-19 patients and 29 healthy controls recruited in three centers. In hospitalized patients, circulating miR-144-3p levels discriminated between non-critical and critical illness (AUCmiR-144-3p = 0.71; p = 0.0006), acting also as mortality predictor (AUCmiR-144-3p = 0.67; p = 0.004). In non-hospitalized patients, plasma miR-144-3p levels discriminated mild from moderate disease (AUCmiR-144-3p = 0.67; p = 0.03). Uncontrolled release of pro-inflammatory cytokines can lead to clinical deterioration. Thus, we explored the added value of a miR-144/cytokine combined analysis in the assessment of hospitalized COVID-19 patients. A miR-144-3p/Epidermal Growth Factor (EGF) combined score discriminated between non-critical and critical hospitalized patients (AUCmiR-144-3p/EGF = 0.81; p < 0.0001); moreover, a miR-144-3p/Interleukin-10 (IL-10) score discriminated survivors from nonsurvivors (AUCmiR-144-3p/IL-10 = 0.83; p < 0.0001). In conclusion, circulating miR-144-3p, possibly in combination with IL-10 or EGF, emerges as a noninvasive tool for early risk-based stratification and mortality prediction in COVID-19.

Biomarkers Associated with Atrial Fibrillation in Patients with Ischemic Stroke: A Pilot Study from the NOR-FIB Study.

BACKGROUND AND PURPOSE: Cardioembolic stroke due to paroxysmal atrial fibrillation (AF) may account for 1 out of 4 cryptogenic strokes (CS) and transient ischemic attacks (TIAs). The purpose of this pilot study was to search for biomarkers potentially predicting incident AF in patients with ischemic stroke or TIA. METHODS: Plasma samples were collected from patients aged 18 years and older with ischemic stroke or TIA due to AF (n = 9) and large artery atherosclerosis (LAA) with ipsilateral carotid stenosis (n = 8) and age- and sex-matched controls (n = 10). Analyses were performed with the Olink technology simultaneously measuring 184 biomarkers of cardiovascular disease. For bioinformatics, acquired data were analyzed using gene set enrichment analysis (GSEA). Selected proteins were validated using ELISA. Individual receiver operating characteristic (ROC) curves and odds ratios from logistic regression were calculated. A randomForest (RF) model with out-of-bag estimate was applied for predictive modeling. RESULTS: GSEA indicated enrichment of proteins related to inflammatory response in the AF group. Interleukin (IL)-6, growth differentiation factor (GDF)-15, and pentraxin-related protein PTX3 were the top biomarkers on the ranked list for the AF group compared to the LAA group and the control group. ELISA validated increased expression of all tested proteins (GDF-15, PTX3, and urokinase plasminogen activator surface receptor [U-PAR]), except for IL-6. 19 proteins had the area under the ROC curve (AUC) over 0.85 including all of the proteins with significant evolution in the logistic regression. AUCs were very discriminant in distinguishing patients with and without AF (LAA and control group together). GDF-15 alone reached AUC of 0.95. Based on RF model, all selected participants in the tested group were classified correctly, and the most important protein in the model was GDF-15. CONCLUSIONS: Our results demonstrate an association between inflammation and AF and that multiple proteins alone and in combination may potentially be used as indicators of AF in CS and TIA patients. However, further studies including larger samples sizes are needed to support these findings. In the ongoing NOR-FIB study, we plan further biomarker assessments in patients with CS and TIA undergoing long-term cardiac rhythm monitoring with insertable cardiac monitors.

MicroRNAs: Key Regulators to Understand Osteoclast Differentiation?

MicroRNAs (miRNAs) are small non-coding single-stranded RNAs that represent important posttranscriptional regulators of protein-encoding genes. In particular, miRNAs play key roles in regulating cellular processes such as proliferation, migration, and cell differentiation. Recently, miRNAs emerged as critical regulators of osteoclasts (OCs) biology and have been involved in OCs pathogenic role in several disorders. OCs are multinucleated cells generated from myeloid precursors in the bone marrow, specialized in bone resorption. While there is a growing number of information on the cytokines and signaling pathways that are critical to control the differentiation of osteoclast precursors (OCPs) into mature OCs, the connection between OC differentiation steps and miRNAs is less well-understood. The present review will first summarize our current understanding of the miRNA-regulated pathways in the sequential steps required for OC formation, from the motility and migration of OCPs to the cell-cell fusion and the final formation of the actin ring and ruffled border in the functionally resorbing multinucleated OCs. Then, considering the difficulty of working on primary OCs and on the generation of robust data we will give an update on the most recent advances in the detection technologies for miRNAs quantification and how these are of particular interest for the understanding of OC biology and their use as potential biomarkers.

Administration of the Mitochondrial Permeability Transition Pore Inhibitor, TRO40303, prior to Primary Percutaneous Coronary Intervention, Does Not Affect the Levels of Pro-Inflammatory Cytokines or Acute-Phase Proteins.

OBJECTIVES: In the MITOCARE study, reperfusion injury was not prevented after administration of the mitochondrial permeability transition pore (mPTP) opening inhibitor, TRO40303, in patients with ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (pPCI). The effects of TRO40303 on pro-inflammatory cytokines and acute-phase proteins were assessed. METHODS: STEMI patients (n = 163, mean age 62 years) with chest pain within 6 h before admission for pPCI were randomized to intravenous bolus of TRO40303 (n = 83) or placebo (n = 80) prior to reperfusion. We tested whether the groups differed in levels of IL-1ß, IL-6, IL-10, TNF, and high-sensitive C-reactive protein at various time points (0, 12, and 72 h) after PCI. Further, potential differences between groups in the change of biomarker levels between 0 and 72 h, 0 and 12 h, and 12 and 72 h were tested. RESULTS: There were no statistically significant differences between the two groups, neither in levels of pro-inflammatory cytokines nor in levels of acute-phase proteins, and there were no statistically significant differences in the change of biomarker levels between the groups considering the time intervals from 0 to 72 h, from 0 to 12 h, and from 12 to 72 h. CONCLUSION: The administration of the mPTP, TRO40303, prior to reperfusion does not alter the pharmacokinetics of pro-inflammatory cytokines or acute-phase proteins during the first 72 h after PCI.

Myocardial fibrosis: biomedical research from bench to bedside.

Myocardial fibrosis refers to a variety of quantitative and qualitative changes in the interstitial myocardial collagen network that occur in response to cardiac ischaemic insults, systemic diseases, drugs, or any other harmful stimulus affecting the circulatory system or the heart itself. Myocardial fibrosis alters the architecture of the myocardium, facilitating the development of cardiac dysfunction, also inducing arrhythmias, influencing the clinical course and outcome of heart failure patients. Focusing on myocardial fibrosis may potentially improve patient care through the targeted diagnosis and treatment of emerging fibrotic pathways. The European Commission funded the FIBROTARGETS consortium as a multinational academic and industrial consortium with the primary aim of performing a systematic and collaborative search of targets of myocardial fibrosis, and then translating these mechanisms into individualized diagnostic tools and specific therapeutic pharmacological options for heart failure. This review focuses on those methodological and technological aspects considered and developed by the consortium to facilitate the transfer of the new mechanistic knowledge on myocardial fibrosis into potential biomedical applications.

Effect of intravenous TRO40303 as an adjunct to primary percutaneous coronary intervention for acute ST-elevation myocardial infarction: MITOCARE study results.

AIM: The MITOCARE study evaluated the efficacy and safety of TRO40303 for the reduction of reperfusion injury in patients undergoing revascularization for ST-elevation myocardial infarction (STEMI). METHODS: Patients presenting with STEMI within 6 h of the onset of pain randomly received TRO40303 (n = 83) or placebo (n = 80) via i.v. bolus injection prior to balloon inflation during primary percutaneous coronary intervention in a double-blind manner. The primary endpoint was infarct size expressed as area under the curve (AUC) for creatine kinase (CK) and for troponin I (TnI) over 3 days. Secondary endpoints included measures of infarct size using cardiac magnetic resonance (CMR) and safety outcomes. RESULTS: The median pain-to-balloon time was 180 min for both groups, and the median (mean) door-to-balloon time was 60 (38) min for all sites. Infarct size, as measured by CK and TnI AUCs at 3 days, was not significantly different between treatment groups. There were no significant differences in the CMR-assessed myocardial salvage index (1-infarct size/myocardium at risk) (mean 52 vs. 58% with placebo, P = 0.1000), mean CMR-assessed infarct size (21.9 g vs. 20.0 g, or 17 vs. 15% of LV-mass) or left ventricular ejection fraction (LVEF) (46 vs. 48%), or in the mean 30-day echocardiographic LVEF (51.5 vs. 52.2%) between TRO40303 and placebo. A greater number of adjudicated safety events occurred in the TRO40303 group for unexplained reasons. CONCLUSION: This study in STEMI patients treated with contemporary mechanical revascularization principles did not show any effect of TRO40303 in limiting reperfusion injury of the ischaemic myocardium.

Translation strategy for the qualification of drug-induced vascular injury biomarkers.

Drug-induced vascular injury (DIVI) is a common preclinical toxicity usually characterized by hemorrhage, vascular endothelial and smooth muscle damage, and inflammation. DIVI findings can cause delays or termination of drug candidates due to low safety margins. The situation is complicated by the absence of sensitive, noninvasive biomarkers for monitoring vascular injury and the uncertain relevance to humans. The Safer And Faster Evidence-based Translation (SAFE-T) consortium is a public-private partnership funded within the European Commission's Innovative Medicines Initiative (IMI) aiming to accelerate drug development by qualifying biomarkers for drug-induced organ injuries, including DIVI. The group is using patients with vascular diseases that have key histomorphologic features (endothelial damage, smooth muscle damage, and inflammation) in common with those observed in DIVI, and has selected candidate biomarkers associated with these features. Studied populations include healthy volunteers, patients with spontaneous vasculitides and other vascular disorders. Initial results from studies with healthy volunteers and patients with vasculitides show that a panel of biomarkers can successfully discriminate the population groups. The SAFE-T group plans to seek endorsement from health authorities (European Medicines Agency and Food and Drug Administration) to qualify the biomarkers for use in regulatory decision-making processes.

A generic operational strategy to qualify translational safety biomarkers.

The importance of using translational safety biomarkers that can predict, detect and monitor drug-induced toxicity during human trials is becoming increasingly recognized. However, suitable processes to qualify biomarkers in clinical studies have not yet been established. There is a need to define clear scientific guidelines to link biomarkers to clinical processes and clinical endpoints. To help define the operational approach for the qualification of safety biomarkers the IMI SAFE-T consortium has established a generic qualification strategy for new translational safety biomarkers that will allow early identification, assessment and management of drug-induced injuries throughout R&D.

Ultrastructural and morphological analyses of the in vitro and in vivo hemostatic effects of Ankaferd Blood Stopper.

Ultrastructural and morphological analyses of a novel hemostatic agent, Ankaferd Blood Stopper (ABS), in comparison to its in vitro and in vivo hemostatic effects were investigated. High-resolution scanning electron microscopy (SEM) images accompanied with morphological analysis after topical application of ABS revealed a very rapid (<1 second) protein network formation within concurrent vital erythroid aggregation covering the classical coagulation cascade. Histopathological examination revealed similar in vivo ABS-induced hemostatic network at the porcine hepatic tissue injury model. Instantaneous control of bleeding was achieved in human surgery-induced dental tissue injury associated with primary and secondary hemostatic abnormalities. Ankaferd Blood Stopper could hold a great premise for clinical management of surgery bleedings as well as immediate cessation of bleeding on external injuries based on upcoming clinical trials.

The efficacy of Ankaferd Blood Stopper in antithrombotic drug-induced primary and secondary hemostatic abnormalities of a rat-bleeding model.

Ankaferd comprises a standardized mixture of plants Thymus vulgaris, Glycyrrhiza glabra, Vitis vinifera, Alpinia officinarum and Urtica dioica. Ankaferd Blood Stopper (ABS) as a medicinal product has been approved in the management of external hemorrhage and dental surgery bleedings in Turkey. This study aimed to evaluate the in-vivo hemostatic effect of ABS in rats pretreated with acetylsalicylic acid or enoxaparin. Wistar rats (210-270 g) of both sexes were used in this study. The animals were pretreated with acetylsalicylic acid (10 mg/kg) orally for 4 days or enoxaparin sodium (8 mg/kg) subcutaneously for 3 days or did not receive any anticoagulant before tail cut at 4th day. ABS was administered topically [a total of 4 ml (1 ml/puff x 4)] to the cut tail in the studied animals. The duration of bleeding and the amount of bleeding were measured in order to evaluate the hemostatic effect of ABS. In acetylsalicylic acid-treated animals, topical ABS reduced both the duration and also the amount of bleeding volume by 68.4 and 54.6%, respectively. It was also effective in shortening the duration of bleeding (30.6%) and decreasing the amount of bleeding (32.8%) in enoxaparin-treated animals. ABS, a traditional folkloric medicinal plant extract, has in-vivo hemostatic actions, which may provide a therapeutic potential for the management of patients with deficient hemostasis in the clinical medicine.

In vivo hemostatic effect of the medicinal plant extract Ankaferd Blood Stopper in rats pretreated with warfarin.

AIM: Ankaferd comprises a mixture of Thymus vulgaris, Glycyrrhiza glabra, Vitis vinifera, Alpinia officinarum and Urtica dioica. Ankaferd Blood Stopper (ABS) has been approved in the management of bleedings. This study aimed to evaluate in vivo hemostatic effect of ABS in rats pretreated with warfarin. MATERIALS AND METHODS: Wistar rats (210-270 g) were treated either with warfarin (2 mg/kg) or vehicle (0.9% NaCl) orally before bilateral hind leg amputation. ABS was administered topically to one of the amputed legs. The duration of bleeding and the amount of bleeding were measured to evaluate the hemostatic effect of ABS. RESULTS: Topical ABS administration to amputed leg shortened the duration of bleeding markedly in both untreated and warfarin-treated rats by 31.9% [1.42 min (95% CI: 0.35-2.49)] and 43.5% [5.12 min (95% CI: 2.16-8.07)] respectively. The amount of bleeding in ABS-administered amputed leg showed a decrease by 53.8% in warfarin-treated group. CONCLUSIONS: ABS has in vivo hemostatic actions that may provide a therapeutic potential for the management of patients with deficient primary hemostasis in clinical medicine.