The complex hexaploid oil‐Camellia genome traces back its phylogenomic history and multi‐omics analysis of Camellia oil biosynthesis

Summary: Oil‐Camellia (Camellia oleifera), belonging to the Theaceae family Camellia, is an important woody edible oil tree species. The Camellia oil in its mature seed kernels, mainly consists of more than 90% unsaturated fatty acids, tea polyphenols, flavonoids, squalene and other active substances, which is one of the best quality edible vegetable oils in the world. However, genetic research and molecular breeding on oil‐Camellia are challenging due to its complex genetic background. Here, we successfully report a chromosome‐scale genome assembly for a hexaploid oil‐Camellia cultivar Changlin40. This assembly contains 8.80 Gb genomic sequences with scaffold N50 of 180.0 Mb and 45 pseudochromosomes comprising 15 homologous groups with three members each, which contain 135 868 genes with an average length of 3936 bp. Referring to the diploid genome, intragenomic and intergenomic comparisons of synteny indicate homologous chromosomal similarity and changes. Moreover, comparative and evolutionary analyses reveal three rounds of whole‐genome duplication (WGD) events, as well as the possible diversification of hexaploid Changlin40 with diploid occurred approximately 9.06 million years ago (MYA). Furthermore, through the combination of genomics, transcriptomics and metabolomics approaches, a complex regulatory network was constructed and allows to identify potential key structural genes (SAD, FAD2 and FAD3) and transcription factors (AP2 and C2H2) that regulate the metabolism of Camellia oil, especially for unsaturated fatty acids biosynthesis. Overall, the genomic resource generated from this study has great potential to accelerate the research for the molecular biology and genetic improvement of hexaploid oil‐Camellia, as well as to understand polyploid genome evolution

HECT, UBA and WWE domain containing 1 represses cholesterol efflux during CD4+ T cell activation in Sjögren’s syndrome

Introduction: Sjögren’s syndrome (SS) is a chronic autoimmune disorder characterized by exocrine gland dysfunction, leading to loss of salivary function. Histological analysis of salivary glands from SS patients reveals a high infiltration of immune cells, particularly activated CD4+ T cells. Thus, interventions targeting abnormal activation of CD4+ T cells may provide promising therapeutic strategies for SS. Here, we demonstrate that Hect, uba, and wwe domain containing 1 (HUWE1), a member of the eukaryotic Hect E3 ubiquitin ligase family, plays a critical role in CD4+ T-cell activation and SS pathophysiology.Methods: In the context of HUWE1 inhibition, we investigated the impact of the HUWE1 inhibitor BI8626 and sh-Huwe1 on CD4+ T cells in mice, focusing on the assessment of activation levels, proliferation capacity, and cholesterol abundance. Furthermore, we examined the therapeutic potential of BI8626 in NOD/ShiLtj mice and evaluated its efficacy as a treatment strategy.Results: Inhibition of HUWE1 reduces ABCA1 ubiquitination and promotes cholesterol efflux, decreasing intracellular cholesterol and reducing the expression of phosphorylated ZAP-70, CD25, and other activation markers, culminating in the suppressed proliferation of CD4+ T cells. Moreover, pharmacological inhibition of HUWE1 significantly reduces CD4+ T-cell infiltration in the submandibular glands and improves salivary flow rate in NOD/ShiLtj mice.Conclusion: These findings suggest that HUWE1 may regulate CD4+ T-cell activation and SS development by modulating ABCA1-mediated cholesterol efflux and presents a promising target for SS treatment

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Study on the Virtual Care System for the Elderly

The virtual care system for the elderly is designed to make them healthier and safer under the increasingly serious aging situation. By using the image processing, speech recognition and relative sensors based on the intelligent terminals, the system accomplishes six functions: sports statistics, heart rate measurement, drug manager, intelligent navigation home and reminder, SOS voice for help and kitchen reminder. Experiments show that it can provide health analysis and safe tutelage for the elderly comprehensively and accurately

Phenytoin regulates osteogenic differentiation of human bone marrow stem cells by PI3K/Akt pathway

Background: We mainly studied the mechanism by which phenytoin promotes osteogenic differentiation of human jawbone marrow stem cells. Methods: Bone marrow stem cells were extracted from jaw bone tissue debris obtained from 5 subjects undergoing implant restoration. Osteogenic and adipogenic experiments proved cells stemness, and the expression of ALP, RUNX2, and OSX were detected by qPCR and Western blot. High-throughput sequencing was used to extract differentially expressed genes, the network database predicted phenytoin drug targets, GO and KEGG enrichment combined with PPI network diagram to analyze the osteogenesis mechanism. Results: Calcium nodules and lipid droplet formation were observed in osteogenic and adipogenic experiments. The concentration of phenytoin within 100 mg/L does not produce cytotoxicity. The results of PCR and WB indicated that 50 mg/L phenytoin significantly promoted the expression of ALP and RUNX2, and 25 mg/L phenytoin significantly promoted the expression of OSX. The results of network pharmacology suggest that phenytoin promotes bone formation by up-regulating FGFR2, S1PR1, TGFB3, VCAN core proteins and activating PI3K/Akt pathway. Conclusions: Phenytoin activated the PI3K/Akt pathway to regulate the osteogenic differentiation of human jawbone marrow stem cells. https://data.mendeley.com/datasets/t3xstktt93/1

Study on the Virtual Care System for the Elderly

The virtual care system for the elderly is designed to make them healthier and safer under the increasingly serious aging situation. By using the image processing, speech recognition and relative sensors based on the intelligent terminals, the system accomplishes six functions: sports statistics, heart rate measurement, drug manager, intelligent navigation home and reminder, SOS voice for help and kitchen reminder. Experiments show that it can provide health analysis and safe tutelage for the elderly comprehensively and accurately

Study on the Virtual Care System for the Elderly

The virtual care system for the elderly is designed to make them healthier and safer under the increasingly serious aging situation. By using the image processing, speech recognition and relative sensors based on the intelligent terminals, the system accomplishes six functions: sports statistics, heart rate measurement, drug manager, intelligent navigation home and reminder, SOS voice for help and kitchen reminder. Experiments show that it can provide health analysis and safe tutelage for the elderly comprehensively and accurately

Nighttime Foreground Pedestrian Detection Based on Three-Dimensional Voxel Surface Model

Pedestrian detection is among the most frequently-used preprocessing tasks in many surveillance application fields, from low-level people counting to high-level scene understanding. Even though many approaches perform well in the daytime with sufficient illumination, pedestrian detection at night is still a critical and challenging problem for video surveillance systems. To respond to this need, in this paper, we provide an affordable solution with a near-infrared stereo network camera, as well as a novel three-dimensional foreground pedestrian detection model. Specifically, instead of using an expensive thermal camera, we build a near-infrared stereo vision system with two calibrated network cameras and near-infrared lamps. The core of the system is a novel voxel surface model, which is able to estimate the dynamic changes of three-dimensional geometric information of the surveillance scene and to segment and locate foreground pedestrians in real time. A free update policy for unknown points is designed for model updating, and the extracted shadow of the pedestrian is adopted to remove foreground false alarms. To evaluate the performance of the proposed model, the system is deployed in several nighttime surveillance scenes. Experimental results demonstrate that our method is capable of nighttime pedestrian segmentation and detection in real time under heavy occlusion. In addition, the qualitative and quantitative comparison results show that our work outperforms classical background subtraction approaches and a recent RGB-D method, as well as achieving comparable performance with the state-of-the-art deep learning pedestrian detection method even with a much lower hardware cost