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Milk production traits play an important role in dairy cattle breeding, and single nucleotide polymorphisms can be used as effective molecular markers for milk production trait marker-assisted breeding in dairy cattle. Based on the results of the preliminary GWAS, candidate genes SPP1 and NCAPG associated with milk production traits were screened. In this study, the aim was to screen and characterize the SNPs of SPP1 and NCAPG genes about milk production traits. Two SNPs and one haplotype block of the SPP1 gene and four SNPs and one haplotype block of the NCAPG gene were obtained by amplification, sequencing and association analysis, and all six SNPs were located in the exon region. Association analysis showed that all six SNPs were significantly associated with milk protein percentage. Linkage disequilibrium analysis showed that 2 SNPs of SPP1 (g. 36,700,265 C > T and g. 36,693,596 C > A) constituted a haplotype that correlated with milk protein percentage, and the dominant haplotype was H2H2, which was CCTT. 4 SNPs of NCAPG (g. 37,342,705 C > A, g. 37,343,379 G > T, g. 37,374,314 C > A and g. 37,377,857 G > A) constituted a haplotype associated with milk protein percentage, 305-days milk protein yield and 305 days milk yield. Tissue expression profiling results revealed that SPP1 and NCAPG had the highest expression in mammary tissue. Interference with SPP1 and NCAPG inhibited the proliferation of Bovine mammary epithelial cells. (BMECs), down-regulated the expression of PCNA, CDK2 and CCND1, up-regulated the expression of BAX and BAD, and promoted apoptosis. Reduced triglyceride synthesis in BMECs, down-regulated the expression of DGAT1, DGAT2, LPIN1, and AGPAT6.SPP1 and NCAPG are involved in the synthesis of milk proteins, and interfering with SPP1 and NCAPG decreased the secretion of β-casein, κ-casein, and αs1-casein, as well as up-regulated the CSN2 and CSN3 expression. The above results indicate that the SNP loci of SPP1 and NCAPG can be used as potential molecular markers to improve milk production traits in dairy cows, laying the foundation for marker-assisted selection. It also proves that SPP1 and NCAPG can be used as candidate key genes for milk production traits in dairy cows, providing new insights into the physiological mechanisms of lactation regulation in dairy cows.

In Holstein cows, β-casein, one of the most critical proteins in milk, exists in two main genotypes, A1 and A2. Herein, 45 Holstein cows [categorized into three groups based on β-casein A1A1, A1A2, and A2A2 genotypes (N = 15)] with the same feeding management and litter size were enrolled to explore differences in rumen microflora and metabolites across various β-casein genotypes. Rumen fluids were collected for metagenomics and metabolomics analyses. Metabolomics and weighted gene co-expression network analysis (WGCNA) revealed that arachidonic acid (AA), adrenic acid (AdA), glycocholic acid (GCA), and taurocholic acid (TCA) were significantly and positively correlated with milk fat % in dairy cows (p

Abstract Background Cow milk fat is an essential indicator for evaluating and measuring milk quality and cow performance. Growing research has identified the molecular functions of circular RNAs (circRNAs) necessary for mammary gland development and lactation in mammals. Method The present study analyzed circRNA expression profiling data in mammary epithelial cells (MECs) from cows with highly variable milk fat percentage (MFP) using differential expression analysis and weighted gene co-expression network analysis (WGCNA). Results A total of 309 differentially expressed circRNAs (DE-circRNAs) were identified in the high and low MFP groups. WGCNA analysis revealed that the pink module was significantly associated with MFP (r = − 0.85, P = 0.007). Parental genes of circRNAs in this module were enriched mainly in lipid metabolism-related signaling pathways, such as focal adhesion, ECM-receptor interaction, adherens junction and AMPK. Finally, six DE-circRNAs were screened from the pink module: circ_0010571, circ_0007797, circ_0002746, circ_0003052, circ_0004319, and circ_0012840. Among them, circ_0002746, circ_0003052, circ_0004319, and circ_0012840 had circular structures and were highly expressed in mammary tissues. Subcellular localization revealed that these four DE-circRNAs may play a regulatory role in the mammary glands of dairy cows, mainly as competitive endogenous RNAs (ceRNAs). Seven hub target genes (GNB1, GNG2, PLCB1, PLCG1, ATP6V0C, NDUFS4, and PIGH) were obtained by constructing the regulatory network of their ceRNAs and then analyzed by CytoHubba and MCODE plugins in Cytoscape. Functional enrichment analysis revealed that these genes are crucial and most probable ceRNA regulators in milk fat metabolism. Conclusions Our study identified several vital circRNAs and ceRNAs affecting milk fat synthesis, providing new research ideas and a theoretical basis for cow lactation, milk quality, and breed improvement.

Group activity recognition is a significant and challenging task in computer vision. The solution of group activity prediction can be classified with traditional hand-crafted features, RGB video features, and skeleton data-based deep learning architectures, such as Graph Convolutional Networks (GCNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTMs). However, they rarely explore pose information and rarely use relational networks to reason about group activity behavior. In this work, we leverage minimal prior knowledge about the skeleton information to reason about the interactions from group activity. The objective is to obtain discriminative representations and filter out some ambiguous actions to enhance the performance of group activity recognition. Our contribution is a proposed Attention Relation Network (ARN) that fuses the attention mechanisms and joint vector sequences into the relation network. The skeleton joints vector sequences are previously unexplored pose information and assign greater significance attributed to individuals who are more relevant for distinguishing the group activity behavior. First, our model focuses on the specified edge-level information (encompassing both edge and edge motion data) within the skeleton dataset, considering directionality, to analyze the spatiotemporal aspects of the action. Second, recognizing the inherent motion directionality, we establish diverse directions for skeleton edges and extract distinct motion features (including translation and rotation information) aligned with these various orientations, thereby augmenting the utilization of motion attributes related to the action. We also introduce a representation of human motion achieved by combining relational networks and examining their integrated characteristics. Extensive experiments were tested in the Hockey and UT-interaction datasets to evaluate our method, obtaining competitive performance to the state-of-the-art. Results demonstrate the modeling potential of a skeleton-based method for group activity recognition.

In the above article [1], the dataset mentioned as Hockey Penalty Dataset (HPD) is not what described in [2] and [3] and instead it is referred to as YMJA dataset. HPD was never made available to the public by the authors of [2] and [3], and the dataset that we accessed, while it was briefly available online, and used in [1] is different and is called YMJA. Therefore, the corresponding dataset description in [1] needs to be corrected. We now understand that the YMJA dataset was never officially released or supported by the authors of [2] and [3]. Note that [2] and [3] are references 21 and 49, respectively, in [1].

BackgroundApplication of stent-assisted coiling and FD in acute phase of ruptured wide-necked aneurysms is relatively contraindicated due to the potential risk of ischemic and hemorrhagic complications. Scheduled stenting after initial coiling has emerged as an alternative paradigm for ruptured wide-necked aneurysms. The objective of this study is to evaluate the safety and efficacy of a strategy of staged stent-assisted coiling in acutely ruptured saccular wide-necked intracranial aneurysms compared with conventional early stent-assisted coiling strategy via propensity score matching in a high-volume center.MethodsA retrospective review of patients with acutely ruptured saccular wide-necked intracranial aneurysms who underwent staged stent-assisted coiling or conventional stent-assisted coiling from November 2014 to November 2019 was performed. Perioperative procedure-related complications and clinical and angiographic follow-up outcomes were compared.ResultsA total of 69 patients with staged stent-assisted coiling and 138 patients with conventional stent-assisted coiling were enrolled after 1:2 propensity score matching. The median interval time between previous coiling and later stenting was 4.0 weeks (range 3.5–7.5 weeks). No rebleeding occurred during the intervals. The rate of immediate complete occlusion was lower with initial coiling before scheduled stenting than with conventional stent-assisted coiling (21.7 vs. 60.9%), whereas comparable results were observed at follow-up (82.5 vs. 72.9%; p = 0.357). The clinical follow-up outcomes, overall procedure-related complications and procedure-related mortality between the two groups demonstrated no significant differences (P = 0.232, P = 0.089, P = 0.537, respectively). Multivariate analysis showed that modified Fisher grades (OR = 2.120, P = 0.041) were independent predictors for overall procedure-related complications and no significant predictors for hemorrhagic and ischemic complications.ConclusionsStaged stent-assisted coiling is a safe and effective treatment strategy for acutely ruptured saccular wide-necked intracranial aneurysms, with comparable complete occlusion rates, recurrence rates at follow-up and overall procedure-related complication rates compared with conventional stent-assisted coiling strategy. Staged stent-assisted coiling could be an alternative treatment option for selected ruptured intracranial aneurysms in the future.

BackgroundMilk fat is one of the main reference elements for evaluating milk quality and is a primary objective trait in dairy cattle breeding. In recent years, circular RNAs (circRNAs) have been found to play crucial roles in many biological processes. However, the function and expression profiles of circRNAs in milk fat synthesis in cows are not completely understood. We performed RNA sequencing to analyze the genome-wide expression of circRNA transcripts in bovine mammary epithelial cells (BMECs) from cows with extreme differences in milk fat percentage. We identified candidate differential circRNAs associated with milk fat metabolism using functional enrichment analysis and constructed a lipid metabolism-related competing endogenous RNA (ceRNA) interactive regulatory network.ResultsA total of 290 circRNAs were significantly differentially expressed (DE-circRNAs) in high milk fat percentage (HMF) cows compared to that in low milk fat percentage (LMF) cows. Of the 290 circRNAs, 142 were significantly upregulated and 148 were significantly downregulated. Enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) identified four DE-circRNAs (circ_0001122, circ_0007367, circ_0018269, and circ_0015179) that potentially regulate milk fat metabolism. Among them, circ_0001122, circ_0007367, and circ_0015179 had relatively high expression levels in cow mammary gland tissue compared to other tissues (heart, liver, kidney, uterus, ovaries, and small intestine) of cows. The regulatory networks circ_0001122:miR-12043:LIPG, circ_0007367:miR-331-3p:CIDEA/PML, and circ_0018269:miR-11989:RORC/HPX are potential networks to explore the mechanism of milk fat regulation.ConclusionsThese results reveal the possible role of circRNAs in milk fat metabolism in dairy cows. Several important circRNAs and ceRNAs affecting milk fat synthesis were identified, providing insights into the complex biology of milk fat synthesis as well as a novel theoretical perspective for future research on lactation, milk quality, and breed improvement in dairy cows.

BackgroundFlow diverters (FDs) for the treatment of basilar artery (BA) aneurysms remain controversial. In this study, we report our initial experience of flow diversion for treatment of this pathology.MethodsConsecutive patients with an aneurysm of the BA that was treated by implantation of the FD were included in our retrospective study. Procedural complications, aneurysm occlusion, and a functional outcome were evaluated. FD placement in BA for aneurysm treatment reported in the literature was also reviewed and summarized.ResultsSixteen patients with 16 BA aneurysms were treated by FD implantation with (n = 8) or without (n = 8) adjunctive coiling. The Tubridge was used in 13 (81.3%) and Pipeline in 3 (18.8%) procedures. Average aneurysm size was 15.7 mm. Four aneurysms were located at the basilar apex, six at the basilar trunk, and six at the vertebrobasilar junction. Three patients experienced procedural complications (18.8%), including two ischemic strokes and one hydrocephalus, with resultant mortality in one case (6.3%). Median follow-up was 7.7 months and available for 15 aneurysms. Complete/near-complete occlusion was seen in 13 (86.7%) aneurysms.ConclusionIn our initial experience, flow diversion is feasible and safe in the treatment of BA aneurysms with promising occlusion rates at mid-term follow-up. Larger cohort studies are required to validate these results.

Background and PurposePhenotypic modulation of vascular smooth muscle cells (VSMCs) plays an important role in the development of intracranial aneurysms (IAs). Growing evidence has demonstrated that circular RNAs (circRNAs) may serve as a potential modulator of VSMC phenotype in various vascular diseases. This study aimed to assess the potential function of circRNAs in the rupture of IAs and VSMC phenotypic modulation.MethodsUsing surgically dissected human ruptured (n = 8) and unruptured (n = 8) IA lesions, differentially expressed circRNAs were screened by transcriptomic sequencing and verified using qRT-PCR. Based on the screened circRNA, we predicted and screened the combined miRNA and downstream mRNAs to construct circRNA-miRNA-mRNA networks. Further in vitro experiments were performed to investigate the relationship between the validated circRNA and the phenotypic switching of VSMCs.ResultsWe found 1,373 differentially expressed genes in ruptured versus unruptured aneurysms. The top five dysregulated circRNAs were selected for qRT-PCR validation. We found hsa_circ_0031608 was both highly expressed in ruptured IAs and pro-inflammatory transformation of VSMCs. Then, a regulatory circRNA-miRNA-mRNA with one circRNA node, six miRNA nodes, and 84 mRNA nodes was constructed. GO analysis and KEGG pathway enrichment analysis were performed on mRNAs in the network. Then, a PPI network was built based on these mRNAs and five hub genes were identified (FOXO3, DICER1, CCND2, IGF1R, and TNRC6B) by the cytoHubba plugin in Cytoscape software. In vitro, overexpression of hsa_circ_0031608 influenced the expression of VSMC phenotypic markers validated by qPCR and Western blotting. Furthermore, hsa_circ_0031608 promoted the migration and proliferation capacity of VSMCs.Conclusionhsa_circ_0031608 regulated the phenotypic modulation of VSMCs and played an important role in the rupture of IAs. The specific mechanism should be further studied and confirmed.

The flowers of Elaeagnus angustifolia L. have been used as a homologous variety in China, whose quality seriously relies on the compositions during the flowering period. Unfortunately, studies on the variations of volatile compounds during the flowering season are rarely reported. Herein, a gas chromatography-mass spectrometry-based untargeted metabolomic methodology was proposed for the comprehensive analysis of volatile compounds in E. angustifolia flowers to classify various flowering stages. Samples from four flowering stages were collected, including the initial bloom stage, pre-full bloom stage (70–80% of flowers), full bloom stage, and ending of the bloom stage. Simultaneous distillation extraction was used for the extraction of volatile compounds in the flowers, which was then analyzed by a newly developed chemometric data analysis tool, autoGCMSDataAnal. An advantage of the developed methodology is that compounds can be accurately screened and identified. Finally, 59 compounds that showed significant difference among four flowering stages were screened and 31 compounds were identified. Sample clustering results from principal component analysis and hierarchical clustering analysis suggested that flowers from the pre-full bloom stage and full bloom stage may be more suitable when used as raw materials for industrial products.