Evaluation of a Low-Cost Photogrammetric System for the Retrieval of 3D Tree Architecture

\ua9 Author(s) 2023.Reconstruction of major branches of a tree is an important first step for the monitoring of tree sway and assessment of structural stability. Photogrammetric systems can provide a low-cost alternative for the acquisition of three-dimensional data, while also enabling long-term monitoring of a tree of interest. This study introduces a low-cost photogrammetric system based on two Raspberry Pi cameras, which is used to reconstruct the tree architecture for the purpose of stability monitoring. Images of five trees are taken at a range of distances and the resulting point clouds are evaluated in terms of point density and distribution with the reference to TLS. While the photogrammetric point clouds are sparse, it was found that they are capable of reconstructing the tree trunk and lower-order branches, which are most relevant for sway monitoring and tree stability assessment. The most optimal distance for the reconstruction of the relevant branches was found to be 9-10 m, with a baseline of 120 cm

Measuring Forest Canopy Water Mass in Three Dimensions Using Terrestrial Laser Scanning

\ua9 Author(s) 2023.Canopy water mass is an important plant characteristic that can indicate the water status of vegetation. However, the parameter remains under-investigated because measuring it requires defoliating the canopy. This study introduced a non-destructive approach to estimate canopy water mass using terrestrial laser scanning data. Tree 3D models were generated from dual-wavelength TLS data for six forest canopies, then the models were utilized in estimating the canopy LAI, total leaf area, and vertical profiles of canopy leaf area. The estimates were then coupled with canopy equivalent water thickness estimates and vertical profiles of canopy water mass were generated. The results revealed some over- and underestimation in the estimated LAI, but the obtained accuracy was considered sufficient as leaf-on point clouds were used to generate the 3D models. The vertical profiles of canopy water mass showed that the leaf area distribution within the canopy, and the canopy architecture were the main parameters affecting the water mass distribution within the canopy, with mid canopy layers having higher water mass than the other canopy layers. This study showed the potential of TLS to estimate canopy water mass, but controlled experiments that include defoliating canopies are still needed for a direct and accurate validation of the TLS estimates of canopy water mass

Chemical databases: curation or integration by user-defined equivalence?

There is a wealth of valuable chemical information in publicly available databases for use by scientists undertaking drug discovery. However finite curation resource, limitations of chemical structure software and differences in individual database applications mean that exact chemical structure equivalence between databases is unlikely to ever be a reality. The ability to identify compound equivalence has been made significantly easier by the use of the International Chemical Identifier (InChI), a non-proprietary line-notation for describing a chemical structure. More importantly, advances in methods to identify compounds that are the same at various levels of similarity, such as those containing the same parent component or having the same connectivity, are now enabling related compounds to be linked between databases where the structure matches are not exact

Individual tree segmentation from UAS Lidar data based on hierarchical filtering and clustering

Accurate Individual Tree Segmentation (ITS) is fundamental to fine-scale forest structure and management studies. Light detection and ranging(Lidar) from Unoccupied Aerial Systems (UAS) has shown strengths in ITS and tree parameter estimation at stand and landscape scales. However, dense woodlands with tightly interspersed canopies and highly diverse tree species challenge the performance of ITS, and current research has not delved into the impact of mixed tree species and different leaf conditions on algorithm accuracy. Therefore, this study firstly evaluates the performance of open-source ITS methods, including both deep learning and non-deep learning algorithms, on data with mixed tree species and different leaf conditions, then proposes a hierarchical filtering and clustering (HFC) algorithm to mitigate the influence and improve the robustness. Hierarchical filtering consists of intensity filtering, Singular Value Decomposition (SVD) filtering, and Statistical Outlier Removal (SOR). Hierarchical clustering involves point-based clustering, cluster merging, and filtered point assignment. Through experiments on three distinct UAS Lidar datasets of forests with mixed tree species and different leaf conditions, HFC achieved the optimal segmentation results while maintaining high robustness. The variations of F1-score are 1–3 percentage points for mixed tree species and 1–2 percentage points for different leaf conditions across different datasets

Allele-specific NKX2-5 binding underlies multiple genetic associations with human electrocardiographic traits.

The cardiac transcription factor (TF) gene NKX2-5 has been associated with electrocardiographic (EKG) traits through genome-wide association studies (GWASs), but the extent to which differential binding of NKX2-5 at common regulatory variants contributes to these traits has not yet been studied. We analyzed transcriptomic and epigenomic data from induced pluripotent stem cell-derived cardiomyocytes from seven related individuals, and identified ~2,000 single-nucleotide variants associated with allele-specific effects (ASE-SNVs) on NKX2-5 binding. NKX2-5 ASE-SNVs were enriched for altered TF motifs, for heart-specific expression quantitative trait loci and for EKG GWAS signals. Using fine-mapping combined with epigenomic data from induced pluripotent stem cell-derived cardiomyocytes, we prioritized candidate causal variants for EKG traits, many of which were NKX2-5 ASE-SNVs. Experimentally characterizing two NKX2-5 ASE-SNVs (rs3807989 and rs590041) showed that they modulate the expression of target genes via differential protein binding in cardiac cells, indicating that they are functional variants underlying EKG GWAS signals. Our results show that differential NKX2-5 binding at numerous regulatory variants across the genome contributes to EKG phenotypes

ESTIMATION OF THE SPECTRAL SENSITIVITY FUNCTIONS OF UN-MODIFIED AND MODIFIED COMMERCIAL OFF-THE-SHELF DIGITAL CAMERAS TO ENABLE THEIR USE AS A MULTISPECTRAL IMAGING SYSTEM FOR UAVS

Commercial off-the-shelf (COTS) digital cameras on-board unmanned aerial vehicles (UAVs) have the potential to be used as multispectral imaging systems; however, their spectral sensitivity is usually unknown and needs to be either measured or estimated. This paper details a step by step methodology for identifying the spectral sensitivity of modified (to be response to near infra-red wavelengths) and un-modified COTS digital cameras, showing the results of its application for three different models of camera. Six digital still cameras, which are being used as imaging systems on-board different UAVs, were selected to have their spectral sensitivities measured by a monochromator. Each camera was exposed to monochromatic light ranging from 370 nm to 1100 nm in 10 nm steps, with images of each step recorded in RAW format. The RAW images were converted linearly into TIFF images using DCRaw, an open-source program, before being batch processed through ImageJ (also open-source), which calculated the mean and standard deviation values from each of the red-green-blue (RGB) channels over a fixed central region within each image. These mean values were then related to the relative spectral radiance from the monochromator and its integrating sphere, in order to obtain the relative spectral response (RSR) for each of the cameras colour channels. It was found that different un-modified camera models present very different RSR in some channels, and one of the modified cameras showed a response that was unexpected. This highlights the need to determine the RSR of a camera before using it for any quantitative studies

Lipid-Induced Epigenomic Changes in Human Macrophages Identify a Coronary Artery Disease-Associated Variant that Regulates \u3cem\u3ePPAP2B\u3c/em\u3e Expression through Altered C/EBP-Beta Binding

Genome-wide association studies (GWAS) have identified over 40 loci that affect risk of coronary artery disease (CAD) and the causal mechanisms at the majority of loci are unknown. Recent studies have suggested that many causal GWAS variants influence disease through altered transcriptional regulation in disease-relevant cell types. We explored changes in transcriptional regulation during a key pathophysiological event in CAD, the environmental lipid-induced transformation of macrophages to lipid-laden foam cells. We used a combination of open chromatin mapping with formaldehyde-assisted isolation of regulatory elements (FAIRE-seq) and enhancer and transcription factor mapping using chromatin immuno-precipitation (ChIP-seq) in primary human macrophages before and after exposure to atherogenic oxidized low-density lipoprotein (oxLDL), with resultant foam cell formation. OxLDL-induced foam cell formation was associated with changes in a subset of open chromatin and active enhancer sites that strongly correlated with expression changes of nearby genes. OxLDL-regulated enhancers were enriched for several transcription factors including C/EBP-beta, which has no previously documented role in foam cell formation. OxLDL exposure up-regulated C/EBP-beta expression and increased genomic binding events, most prominently around genes involved in inflammatory response pathways. Variants at CAD-associated loci were significantly and specifically enriched in the subset of chromatin sites altered by oxLDL exposure, including rs72664324 in an oxLDL-induced enhancer at the PPAP2B locus. OxLDL increased C/EBP beta binding to this site and C/EBP beta binding and enhancer activity were stronger with the protective A allele of rs72664324. In addition, expression of the PPAP2B protein product LPP3 was present in foam cells in human atherosclerotic plaques and oxLDL exposure up-regulated LPP3 in macrophages resulting in increased degradation of pro-inflammatory mediators. Our results demonstrate a genetic mechanism contributing to CAD risk at the PPAP2B locus and highlight the value of studying epigenetic changes in disease processes involving pathogenic environmental stimuli

Decreased STARD10 expression is associated with defective insulin secretion in humans and mice

Genetic variants near ARAP1 (CENTD2) and STARD10 influence type 2 diabetes (T2D) risk. The risk alleles impair glucose-induced insulin secretion and, paradoxically but characteristically, are associated with decreased proinsulin:insulin ratios, indicating improved proinsulin conversion. Neither the identity of the causal variants nor the gene(s) through which risk is conferred have been firmly established. Whereas ARAP1 encodes a GTPase activating protein, STARD10 is a member of the steroidogenic acute regulatory protein (StAR)-related lipid transfer protein family. By integrating genetic fine-mapping and epigenomic annotation data and performing promoter-reporter and chromatin conformational capture (3C) studies in β cell lines, we localize the causal variant(s) at this locus to a 5 kb region that overlaps a stretch-enhancer active in islets. This region contains several highly correlated T2D-risk variants, including the rs140130268 indel. Expression QTL analysis of islet transcriptomes from three independent subject groups demonstrated that T2D-risk allele carriers displayed reduced levels of STARD10 mRNA, with no concomitant change in ARAP1 mRNA levels. Correspondingly, β-cell-selective deletion of StarD10 in mice led to impaired glucose-stimulated Ca2+ dynamics and insulin secretion and recapitulated the pattern of improved proinsulin processing observed at the human GWAS signal. Conversely, overexpression of StarD10 in the adult β cell improved glucose tolerance in high fat-fed animals. In contrast, manipulation of Arap1 in β cells had no impact on insulin secretion or proinsulin conversion in mice. This convergence of human and murine data provides compelling evidence that the T2D risk associated with variation at this locus is mediated through reduction in STARD10 expression in the β cell