The landscape of allelic expression and DNA methylation at the bovine SGCE/PEG10 locus

Genomic imprinting is an epigenetic regulation in mammals in which a small subset of genes is monoallelically expressed dependent on their parental origin. A large imprinted domain, SGCE/PEG10 locus, is located on human chromosome 7q21s and mouse proximal chromosome 6. However, genomic imprinting of bovine SGCE/PEG10 cluster has not been systematically studied. In this study, we investigated allele expression of 14 genes of the SGCE/PEG10 locus in bovine somatic tissues and term placenta using a single nucleotide polymorphism (SNP)-based sequencing method. In addition to SGCE and PEG10, two conserved paternally expressed genes in human and mice, five other genes (TFPI2, GNG11, ASB4, PON1, and PON3) were paternally expressed. Three genes, BET1, COL1A2, and CASD1, exhibited tissue-specific monoallelic expression. CALCR showed monoallelic expression in tissues but biallelic expression in the placenta. Three genes, GNGT1, PPP1R9A, and PON2, showed biallelic expression in cattle. Five differentially methylated regions (DMRs) were found to be associated with the allelic expression of TFPI2, COL1A2, SGCE/PEG10, PON3, and ASB4 genes, respectively. The SGCE/PEG10 DMR is a maternally hypermethylated germline DMR, but TFPI2, COL1A2, PON3, and ASB4 DMRs are secondary DMRs. In summary, we identified five novel bovine imprinted genes (GNG11, BET1, COL1A2, CASD1, and PON1) and four secondary DMRs at the SGCE/PEG10 locus.

A novel imprinted locus on bovine chromosome 18 homologous with human chromosome 16q24.1

Genomic imprinting is an epigenetic regulation mechanism in mammals resulting in the parentally dependent monoallelic expression of genes. Imprinting disorders in humans are associated with several congenital syndromes and cancers and remain the focus of many medical studies. Cattle is a better model organism for investigating human embryo development than mice. Imprinted genes usually cluster on chromosomes and are regulated by different methylation regions (DMRs) located in imprinting control regions that control gene expression in cis. There is an imprinted locus on human chromosome 16q24.1 associated with congenital lethal developmental lung disease in newborns. However, genomic imprinting on bovine chromosome 18, which is homologous with human chromosome 16 has not been systematically studied. The aim of this study was to analyze the allelic expressions of eight genes (CDH13, ATP2C2, TLDC1, COTL1, CRISPLD2, ZDHHC7, KIAA0513, and GSE1) on bovine chromosome 18 and to search the DMRs associated gene allelic expression. Three transcript variants of the ZDHHC7 gene (X1, X2, and X5) showed maternal imprinting in bovine placentas. In addition, the monoallelic expression of X2 and X5 was tissue-specific. Five transcripts of the KIAA0513 gene showed tissue- and isoform-specific monoallelic expression. The CDH13, ATP2C2, and TLDC1 genes exhibited tissue-specific imprinting, however, COTL1, CRISLPLD2, and GSE1 escaped imprinting. Four DMRs, established after fertilization, were found in this region. Two DMRs were located between the ZDHHC7 and KIAA0513 genes, and two were in exon 1 of the CDH13 and ATP2C2 genes, respectively. The results from this study support future studies on the molecular mechanism to regulate the imprinting of candidate genes on bovine chromosome 18.

Assessing wind field characteristics along the airport runway glide slope: an explainable boosting machine-assisted wind tunnel study

Aircraft landings are especially perilous when the wind is gusty near airport runways. For this reason, an aircraft may deviate from its glide slope, miss its approach, or even crash in the worst cases. In the study, we used the state-of-the-art glass-box model, the Explainable Boosting Machine (EBM), to estimate the variation in headwind speed and turbulence intensity along the airport runway glide slope and to interpret the various contributing factors. To begin, the wind field characteristics were examined by developing a scaled-down model of Hong Kong International Airport (HKIA) runway as well as and the surrounding buildings and complex terrain in the TJ-3 atmospheric boundary layer wind tunnel. The placement of probes along the glide slope of the model runway aided in the measurement of wind field characteristics at different locations in the presence and absence of surrounding buildings. Next, the experimental data was used to train the EBM model in conjunction with Bayesian optimization approach. The counterpart black box models (extreme gradient boosting, random forest, extra tree and adaptive boosting) as well as other glass box models (linear regression and decision tree) were compared with the outcomes of the EBM model. Based on the holdout testing data, the EBM model revealed superior performance for both variation in headwind speed and turbulence intensity in terms of mean absolute error, mean squared error, root mean squared error and R-square values. To further evaluate the impact of different factors on the wind field characteristics along the airport runway glide slope, the EBM model allows for a full interpretation of the contribution of individual and pairwise interactions of factors to the prediction results from both a global and a local perspective.

KHGCN: Knowledge-Enhanced Recommendation with Hierarchical Graph Capsule Network

Knowledge graphs as external information has become one of the mainstream directions of current recommendation systems. Various knowledge-graph-representation methods have been proposed to promote the development of knowledge graphs in related fields. Knowledge-graph-embedding methods can learn entity information and complex relationships between the entities in knowledge graphs. Furthermore, recently proposed graph neural networks can learn higher-order representations of entities and relationships in knowledge graphs. Therefore, the complete presentation in the knowledge graph enriches the item information and alleviates the cold start of the recommendation process and too-sparse data. However, the knowledge graph's entire entity and relation representation in personalized recommendation tasks will introduce unnecessary noise information for different users. To learn the entity-relationship presentation in the knowledge graph while effectively removing noise information, we innovatively propose a model named knowledge-enhanced hierarchical graph capsule network (KHGCN), which can extract node embeddings in graphs while learning the hierarchical structure of graphs. Our model eliminates noisy entities and relationship representations in the knowledge graph by the entity disentangling for the recommendation and introduces the attentive mechanism to strengthen the knowledge-graph aggregation. Our model learns the presentation of entity relationships by an original graph capsule network. The capsule neural networks represent the structured information between the entities more completely. We validate the proposed model on real-world datasets, and the validation results demonstrate the model's effectiveness.

Fermiology of Chiral Cadmium Diarsenide CdAs2, a Candidate for Hosting Kramers-Weyl Fermions

Nonmagnetic chiral crystals are a new class of systems hosting Kramers-Weyl Fermions, arising from the combination of structural chirality, spin-orbit coupling (SOC), and time-reversal symmetry. These materials exhibit nontrivial Fermi surfaces with SOC-induced Chern gaps over a wide energy range, leading to exotic transport and optical properties. In this study, we investigate the electronic structure and transport properties of CdAs₂, a newly reported chiral material. We use synchrotron-based angle-resolved photoelectron spectroscopy (ARPES) and density functional theory (DFT) to determine the Fermiology of the (110)-terminated CdAs₂ crystal. Our results, together with complementary magnetotransport measurements, suggest that CdAs₂ is a promising candidate for novel topological properties protected by the structural chirality of the system. Our work sheds light on the details of the Fermi surface and topology for this chiral quantum material, providing useful information for engineering novel spintronic and optical devices based on quantized chiral charges, negative longitudinal magnetoresistance, and nontrivial Chern numbers.