LPA Genotypes and Haplotypes Are Associated with Lipoprotein(a) Levels but Not Arterial Wall Properties in Stable Post-Coronary Event Patients with Very High Lipoprotein(a) Levels

Lipoprotein(a) [Lp(a)] levels are an independent risk factor for coronary artery disease (CAD). Two single-nucleotide polymorphisms (rs10455872, rs3798220) and number of KIV-2 repeats in the gene encoding Lp(a) (LPA) are associated with Lp(a) and CAD. Our aim was to investigate whether in patients with stable CAD and high Lp(a) levels these genetic variants are associated with increased Lp(a) and arterial wall properties. Blood samples underwent biochemical and genetic analyses. Ultrasound measurements for the functional and morphological properties of arterial wall were performed. Genotypes of rs10455872 and haplotypes AT and GT showed significant association with Lp(a) levels. Patients with GG showed significantly higher Lp(a) levels compared with those with AG genotype (2180 vs. 1391 mg/L, p = 0.045). Patients with no AT haplotype had significantly higher Lp(a) compared to carriers of one AT haplotype (2158 vs. 1478 mg/L, p = 0.023) or two AT haplotypes (2158 vs. 1487 mg/L, p = 0.044). There were no significant associations with the properties of the arterial wall. Lp(a) levels significantly correlated also with number of KIV-2 repeats (r = −0.601; p < 0.0001). In our patients, these two LPA polymorphisms and number of KIV-2 repeats are associated with Lp(a), but not arterial wall properties.

Image processing to delineate the boundaries of peripheral arterial walls

The analysis of the arterial wall properties is vital in the prediction of stroke events and arterial hypertension in humans. Numerous researchers have experimented with several approaches to model arterial vessels and to analyse their biomechanical behaviour for many years now. Our study is focussed on image processing of peripheral arterial cross sections to detect and isolate the distinct layers. These boundaries will enable the creation of FEM models for further analysis of arterial wall properties. In a clinical setting, it facilitates doctors to identify the optimum pressure that can be applied to the artery for the treatment of stenosis without damaging the morphology of the blood vessels. This paper aims at distinguishing the various layers of arterial walls from images by minimizing human intervention. Cross section images of arteries from various sources were collected[10][11]. The boundaries from the image were obtained using image processing techniques of MATLAB(R2021a). The approach identified was to convert the input RGB images to grayscale, thresholding and applying morphological operators to delineate the Intima, Media, and Adventitia. These regions of interests (ROI) were then superimposed to generate an image with differentiated boundaries and void of unnecessary noise and inhomogeneity. This approach gave us an insight of the differences in various methods of boundary detection and to infer the optimum approach for accurate demarcation of boundaries of the three layers of arterial walls. It paves a pathway for forward modelling and to perform detailed FEM analysis in in-vitro diagnostics. In a nutshell, it was observed that the edge detection procedure implemented could be used for healthy and stenotic arteries. Further studies must be conducted to test the efficiency across a wide range of images and hence generalise its usage. Upon satisfactory boundary detection, forward modelling could be performed using the identified geometric forms.

Functional Analysis of Poplar SOMBRERO-type NAC Transcription Factors Yields a Strategy to Modify Woody Cell Wall Properties

Woody cells generate lignocellulosic biomass, which is a promising sustainable bioresource for wide industrial applications. Woody cell differentiation in vascular plants, including the model plant poplar (Populus trichocarpa), is regulated by a set of NAC family transcription factors, the VNS (VND, NST/SND, and SMB-related) proteins, but the precise contributions of each VNS protein to wood quality are unknown. Here, we performed a detailed functional analysis of the poplar SMB-type VNS proteins PtVNS13–PtVNS16. PtVNS13–PtVNS16 were preferentially expressed in roots in young poplar plantlets, similarly to the Arabidopsis thaliana SOMBRERO (SMB) gene. PtVNS13 and PtVNS14, as well as the NST-type PtVNS11, suppressed the abnormal root cap phenotype of the Arabidopsis sombrero-3 mutant, whereas the VND-type PtVNS07 gene did not, suggesting a functional gap between SMB- or NST-type VNS proteins and VND-type VNS proteins. Overexpressing PtVNS13–PtVNS16 in Arabidopsis seedlings and poplar leaves induced ectopic xylem-vessel-like cells with secondary wall deposition, and a transient expression assay showed that PtVNS13–16 transactivated woody-cell-related genes. Interestingly, although any VNS protein rescued the pendant stem phenotype of the Arabidopsis nst1-1 nst3-1 mutant, the resulting inflorescence stems exhibited distinct cell wall properties: poplar VNS genes generated woody cell walls with higher enzymatic saccharification efficiencies compared with Arabidopsis VNS genes. Together, our data reveal clear functional diversity among VNS proteins in woody cell differentiation and demonstrate a novel VNS-based strategy for modifying woody cell wall properties toward enhanced utilization of woody biomass.