Impaired endogenous fibrinolysis at high shear using a point-of-care test in STEMI is associated with alterations in clot architecture

© The Author(s) 2019Impaired endogenous fibrinolysis is an adverse prognostic biomarker in acute coronary syndrome (ACS). Abnormally dense in vitro fibrin thrombi have been demonstrated in ACS patients and related to hypofibrinolysis using cumbersome, laboratory-based methods. We aimed to assess endogenous fibrinolysis using a point-of-care technique and relate this to clot architecture. From patients with ST-segment elevation myocardial infarction (STEMI), venous blood was drawn immediately on arrival to assess thrombotic status. Blood was assessed using the point-of-care Global Thrombosis Test which measures occlusive thrombus formation under high shear and subsequently endogenous fibrinolysis (lysis time, LT). Two samples per patient were run in parallel. In one channel, the measurement was allowed to proceed as normal. In the other, after occlusion, thrombus was extracted, washed, fixed in glutaraldehyde, dried, sputter-coated, and assessed using scanning electron microscope. Endogenous fibrinolysis was strongly associated fibrin fibre thickness (p = 0.0001). As LT increased (less efficient fibrinolysis), the fibrin network of the thrombus was significantly more compact and dense, with thinner fibrin fibres and smaller gaps. Fibrin fibre thickness correlated inversely with LT (r = - 0.89, p = 0.001). Adverse clot architecture in vitro is directly related to impaired endogenous fibrinolysis using a relatively new point-of-care technique in patients with STEMI. This may transform the relevance of fibrin clot architecture from an off-line laboratory association to being directly relevant to endogenous fibrinolysis at the patient bedside, which could be used as a near-patient test to guide prognosis and assess the effect of treatment.Peer reviewedFinal Published versio

Village Baseline Study: Site Analysis Report for Segou – Cinzana, Mali (MA0109)

The village baseline study of Tongo village in the CCAFS benchmark site of Cinzana, Mali took place from 12 to 14 July 2011. Focus group discussions were conducted separately for men and women. The village has an abundance of natural resources such as savannah, grassland, ponds, farmlands and several kinds of socio-economic infrastructure. Some of the natural resources, however, are in a state of progressive degradation due to increase in human population; indiscriminate felling of trees; clearing of forests and deforestation; lack of rainfall; drought; and animal pressure

Village Baseline Study: Site Analysis Report for Kollo – Fakara, Niger (NI0111)

The village baseline study of Tigo Zéno village in the CCAFS benchmark site Fakara in Niger took place from 23 to 25 of June 2011. Focus group discussions were conducted separately for men and women. Tigo Zéno’s natural resources are degraded, with sparse tree population. Water is scarce and temporary, the farmlands have eroded, and soil is infertile with low productivity. People are particularly concerned about the presence and expansion of gullies (“koris”) that have created uncultivable areas, major declines in soil fertility, destruction of crops during serious overflow of ponds and heavy rainfall, and significant reduction in the size of farmlands, especially those belonging to women, who have smaller farmlands than men

Kdm6a deficiency restricted to mouse hematopoietic cells causes an age- and sex-dependent myelodysplastic syndrome-like phenotype

Kdm6a/Utx, a gene on the X chromosome, encodes a histone H3K27me3 demethylase that has an orthologue on the Y chromosome (Uty) (Zheng et al. 2018). We previously identified inactivating mutations of Kdm6a in approximately 50% of mouse acute promyelocytic leukemia samples; however, somatic mutations of KDM6A are more rare in human AML samples, ranging in frequency from 2-15% in different series of patients, where their role in pathogenesis is not yet clear. In this study, we show that female Kdm6aflox/flox mice (with allele inactivation initiated by Vav1-Cre in hematopoietic stem and progenitor cells (HSPCs) have a sex-specific phenotype that emerges with aging, with features resembling a myelodysplastic syndrome (MDS). Female Kdm6a-knockout (KO) mice have an age-dependent expansion of their HSPCs with aberrant self-renewal, but they did not differentiate normally into downstream progeny. These mice became mildly anemic and thrombocytopenic, but did not develop overt leukemia, or die from these cytopenias. ChIP-seq and ATAC-seq studies showed only minor changes in H3K27me3, H3K27ac, H3K4me, H3K4me3 and chromatin accessibility between Kdm6a-WT and Kdm6a-KO mice. Utilizing scRNA-seq, Kdm6a loss was linked to the transcriptional repression of genes that mediate hematopoietic cell fate determination. These data demonstrate that Kdm6a plays an important role in normal hematopoiesis, and that its inactivation may contribute to AML pathogenesis

Technology-supported guidance models to stimulate nursing students’ self-efficacy in clinical practice: A scoping review

Originally published in JMIR Nursing (https://nursing.jmir.org), 08.03.2024. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Nursing, is properly cited. The complete bibliographic information, a link to the original publication on https://nursing.jmir.org/, as well as this copyright and license information must be included.Background: In nursing education, bridging the gap between theoretical knowledge and practical skills is crucial for developing competence in clinical practice. Nursing students encounter challenges in acquiring these essential skills, making self-efficacy a critical component in their professional development. Self-efficacy pertains to individual’s belief in their ability to perform tasks and overcome challenges, with significant implications for clinical skills acquisition and academic success. Previous research has underscored the strong link between nursing students’ self-efficacy and their clinical competence. Technology has emerged as a promising tool to enhance self-efficacy by enabling personalized learning experiences and in-depth discussions. However, there is a need for a comprehensive literature review to assess the existing body of knowledge and identify research gaps. Objective: The aim of this study is to systematically map and identify gaps in published studies on the use of technology-supported guidance models to stimulate nursing students’ self-efficacy in clinical practice. Methods: This scoping review followed the framework of Arksey and O’Malley and was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR). A systematic, comprehensive literature search was conducted in ERIC, CINAHL, MEDLINE, Embase, PsycINFO, and Web of Science for studies published between January 2011 and April 2023. The reference lists of the included papers were manually searched to identify additional studies. Pairs of authors screened the papers, assessed eligibility, and extracted the data. The data were thematically organized. Results: A total of 8 studies were included and four thematic groups were identified: (1) technological solutions for learning support, (2) learning focus in clinical practice, (3) teaching strategies and theoretical approaches for self-efficacy, and (4) assessment of self-efficacy and complementary outcomes. Conclusions: Various technological solutions were adopted in the guidance models to stimulate the self-efficacy of nursing students in clinical practice, leading to positive findings. A total of 7 out of 8 studies presented results that were not statistically significant, highlighting the need for further refinement of the applied interventions. Nurse educators play a pivotal role in applying learning strategies and theoretical approaches to enhance nursing students’ self-efficacy, but the contributions of nurse preceptors and peers should not be overlooked. Future studies should consider involving users in the intervention process and using validated instruments tailored to the studies’ intervention objectives, ensuring relevance and enabling comparisons across studies.publishedVersio

Machine Learning Predicting Atrial Fibrillation as an Adverse Event in the Warfarin and Aspirin in Reduced Cardiac Ejection Fraction (WARCEF) Trial

Background: Atrial fibrillation and heart failure commonly coexist due to shared pathophysiological mechanisms. Prompt identification of patients with heart failure at risk of developing atrial fibrillation would allow clinicians the opportunity to implement appropriate monitoring strategy and timely treatment, reducing the impact of atrial fibrillation on patients’ health. Methods: Four machine learning models combined with logistic regression and cluster analysis were applied post hoc to patient-level data from the Warfarin and Aspirin in Patients with Heart Failure and Sinus Rhythm (WARCEF) trial to identify factors that predict development of atrial fibrillation in patients with heart failure. Results: Logistic regression showed that White divorced patients have a 1.75-fold higher risk of atrial fibrillation than White patients reporting other marital statuses. By contrast, similar analysis suggests that non-White patients who live alone have a 2.58-fold higher risk than those not living alone. Machine learning analysis also identified “marital status” and “live alone” as relevant predictors of atrial fibrillation. Apart from previously well-recognized factors, the machine learning algorithms and cluster analysis identified 2 distinct clusters, namely White and non-White ethnicities. This should serve as a reminder of the impact of social factors on health. Conclusion: The use of machine learning can prove useful in identifying novel cardiac risk factors. Our analysis has shown that “social factors,” such as living alone, may disproportionately increase the risk of atrial fibrillation in the under-represented non-White patient group with heart failure, highlighting the need for more studies focusing on stratification of multiracial cohorts to better uncover the heterogeneity of atrial fibrillation

cDNA array-CGH profiling identifies genomic alterations specific to stage and MYCN-amplification in neuroblastoma

BACKGROUND: Recurrent non-random genomic alterations are the hallmarks of cancer and the characterization of these imbalances is critical to our understanding of tumorigenesis and cancer progression. RESULTS: We performed array-comparative genomic hybridization (A-CGH) on cDNA microarrays containing 42,000 elements in neuroblastoma (NB). We found that only two chromosomes (2p and 12q) had gene amplifications and all were in the MYCN amplified samples. There were 6 independent non-contiguous amplicons (10.4–69.4 Mb) on chromosome 2, and the largest contiguous region was 1.7 Mb bounded by NAG and an EST (clone: 757451); the smallest region was 27 Kb including an EST (clone: 241343), NCYM, and MYCN. Using a probabilistic approach to identify single copy number changes, we systemically investigated the genomic alterations occurring in Stage 1 and Stage 4 NBs with and without MYCN amplification (stage 1-, 4-, and 4+). We have not found genomic alterations universally present in all (100%) three subgroups of NBs. However we identified both common and unique patterns of genomic imbalance in NB including gain of 7q32, 17q21, 17q23-24 and loss of 3p21 were common to all three categories. Finally we confirm that the most frequent specific changes in Stage 4+ tumors were the loss of 1p36 with gain of 2p24-25 and they had fewer genomic alterations compared to either stage 1 or 4-, indicating that for this subgroup of poor risk NB requires a smaller number of genomic changes are required to develop the malignant phenotype. CONCLUSIONS: cDNA A-CGH analysis is an efficient method for the detection and characterization of amplicons. Furthermore we were able to detect single copy number changes using our probabilistic approach and identified genomic alterations specific to stage and MYCN amplification