Label-efficient Contrastive Learning-based model for nuclei detection and classification in 3D Cardiovascular Immunofluorescent Images

Recently, deep learning-based methods achieved promising performance in nuclei detection and classification applications. However, training deep learning-based methods requires a large amount of pixel-wise annotated data, which is time-consuming and labor-intensive, especially in 3D images. An alternative approach is to adapt weak-annotation methods, such as labeling each nucleus with a point, but this method does not extend from 2D histopathology images (for which it was originally developed) to 3D immunofluorescent images. The reason is that 3D images contain multiple channels (z-axis) for nuclei and different markers separately, which makes training using point annotations difficult. To address this challenge, we propose the Label-efficient Contrastive learning-based (LECL) model to detect and classify various types of nuclei in 3D immunofluorescent images. Previous methods use Maximum Intensity Projection (MIP) to convert immunofluorescent images with multiple slices to 2D images, which can cause signals from different z-stacks to falsely appear associated with each other. To overcome this, we devised an Extended Maximum Intensity Projection (EMIP) approach that addresses issues using MIP. Furthermore, we performed a Supervised Contrastive Learning (SCL) approach for weakly supervised settings. We conducted experiments on cardiovascular datasets and found that our proposed framework is effective and efficient in detecting and classifying various types of nuclei in 3D immunofluorescent images.Comment: 11 pages, 5 figures, MICCAI Workshop Conference 202

PDGF-DD, a novel mediator of smooth muscle cell phenotypic modulation, is upregulated in endothelial cells exposed to atherosclerosis-prone flow patterns

Platelet-derived growth factor (PDGF)-BB is a well-known smooth muscle (SM) cell (SMC) phenotypic modulator that signals by binding to PDGF αα-, αβ-, and ββ-membrane receptors. PDGF-DD is a recently identified PDGF family member, and its role in SMC phenotypic modulation is unknown. Here we demonstrate that PDGF-DD inhibited expression of multiple SMC genes, including SM α-actin and SM myosin heavy chain, and upregulated expression of the potent SMC differentiation repressor gene Kruppel-like factor-4 at the mRNA and protein levels. On the basis of the results of promoter-reporter assays, changes in SMC gene expression were mediated, at least in part, at the level of transcription. Attenuation of the SMC phenotypic modulatory activity of PDGF-DD by pharmacological inhibitors of ERK phosphorylation and by a small interfering RNA to Kruppel-like factor-4 highlight the role of these two pathways in this process. PDGF-DD failed to repress SM α-actin and SM myosin heavy chain in mouse SMCs lacking a functional PDGF β-receptor. Importantly, PDGF-DD expression was increased in neointimal lesions in the aortic arch region of apolipoprotein C-deficient (ApoE−/−) mice. Furthermore, human endothelial cells exposed to an atherosclerosis-prone flow pattern, as in vascular regions susceptible to the development of atherosclerosis, exhibited a significant increase in PDGF-DD expression. These findings demonstrate a novel activity for PDGF-DD in SMC biology and highlight the potential contribution of this molecule to SMC phenotypic modulation in the setting of disturbed blood flow

How do health behaviour interventions take account of social context? A literature trend and co-citation analysis

In recent years, health behaviour interventions have received a great deal of attention in both research and policy as a means of encouraging people to lead healthier lives. The emphasis of such interventions has varied over time, in terms of level of intervention (e.g. individual vs community) and drawing on different disciplinary perspectives. Recently, a number of critiques have focused on how health behaviour interventions sometimes sideline issues of social context, framing health as a matter of individual choice and, by implication, a personal responsibility. Part of this criticism is that health behaviour interventions often do not draw on alternative social science understandings of the structured and contextual aspects of behaviour and health. Yet to our knowledge, no study has attempted to empirically assess the extent to which, and in what ways, the health behaviour intervention field has paid attention to social context. In this article, we undertake this task using bibliometric techniques in order to map out the health behaviour intervention field. We find that the number of health behaviour interventions has grown rapidly in recent years, especially since around 2006, and that references to social science disciplines and concepts that foreground issues of social context are rare and, relatively speaking, constitute less of the field post 2006. More quantifiable concepts are used most, and those more close to the complexities of social context are mentioned least. The document co-citation analysis suggests that pre 2006, documents referring to social context were relatively diffuse in the network of key citations, but post 2006 this influence had largely diminished. The journal co-citation analysis shows less disciplinary overlap post 2006. At present, health behaviour interventions are continuing to focus on individualised approaches drawn from behavioural psychology and behavioural economics. Our findings lend empirical support to a number of recent papers that suggest more interdisciplinary collaboration is needed to advance the field

Imaging in patients with severe mitral annular calcification: insights from a multicentre experience using transatrial balloon-expandable valve replacement

AIMS: To investigate valve sizing and the haemodynamic relevance of the predicted left ventricular outflow tract (LVOT) in patients with mitral annular calcification (MAC) undergoing transatrial transcatheter valve implantation (THV). METHODS AND RESULTS: In total, 21 patients undergoing transatrial THV, multiplanar reconstruction (MPR), maximum intensity projection (MIP), and cubic spline interpolation (CSI) were compared for MA sizing during diastole. In addition, predicted neo-LVOT areas were measured in 18 patients and correlated with the post-procedural haemodynamic dimensions. The procedure was successful in all patients (100%). Concomitant aortic valve replacement was performed in eight patients (43%) (AVR group). Sizing using MPR and MIP yielded comparable results in terms of area, perimeter, and diameter, whereas the dimensions obtained with CSI were systematically smaller. The simulated mean systolic neo-LVOT area was 133.4 ± 64.2 mm2 with an anticipated relative LVOT area reduction (neo-LVOT area/LVOT area × 100) of 59.3 ± 14.7%. The systolic relative LVOT area reduction, but not the absolute neo-LVOT area, was found to predict the peak (r = 0.69; P = 0.002) and mean (r = 0.65; P = 0.004) post-operative aortic gradient in the overall population as well as separately in the AVR (peak: r = 0.91; P = 0.002/mean: r = 0.85; P = 0.002) and no-AVR (peak: r = 0.89; P = 0.003/mean: r = 0.72; P = 0.008) groups. CONCLUSION: In patients with severe MAC undergoing transatrial transcatheter valve implantation, MPR, and MIP yielded comparable annular dimensions, while values obtained with CSI tended to be systematically smaller. Mitral annular area and the average annular diameter appear to be reliable parameters for valve selection. Simulated relative LVOT reduction was found to predict the post-procedural aortic gradients