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Article ; Online: scSemiGCN: boosting cell-type annotation from noise-resistant graph neural networks with extremely limited supervision.

Yang, Jue / Wang, Weiwen / Zhang, Xiwen

2024 Volume 40, Issue 2

Abstract: Motivation: Cell-type annotation is fundamental in revealing cell heterogeneity for single-cell data analysis. Although a host of works have been developed, the low signal-to-noise-ratio single-cell RNA-sequencing data that suffers from batch effects ... ...

Abstract	Motivation: Cell-type annotation is fundamental in revealing cell heterogeneity for single-cell data analysis. Although a host of works have been developed, the low signal-to-noise-ratio single-cell RNA-sequencing data that suffers from batch effects and dropout still poses obstacles in discovering grouped patterns for cell types by unsupervised learning and its alternative-semi-supervised learning that utilizes a few labeled cells as guidance for cell-type annotation. Results: We propose a robust cell-type annotation method scSemiGCN based on graph convolutional networks. Built upon a denoised network structure that characterizes reliable cell-to-cell connections, scSemiGCN generates pseudo labels for unannotated cells. Then supervised contrastive learning follows to refine the noisy single-cell data. Finally, message passing with the refined features over the denoised network structure is conducted for semi-supervised cell-type annotation. Comparison over several datasets with six methods under extremely limited supervision validates the effectiveness and efficiency of scSemiGCN for cell-type annotation. Availability and implementation: Implementation of scSemiGCN is available at https://github.com/Jane9898/scSemiGCN.
MeSH term(s)	Neural Networks, Computer ; Signal-To-Noise Ratio ; Single-Cell Analysis ; Supervised Machine Learning
Language	English
Publishing date	2024-02-17
Publishing country	England
Document type	Journal Article
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btae091
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Article ; Online: Dual effects on vegetation from urban expansion in the drylands of northern China: A multiscale investigation using the vegetation disturbance index.

Qi, Tao / Ren, Qiang / He, Chunyang / Zhang, Xiwen

The Science of the total environment

2024 Volume 928, Page(s) 172481

Abstract: Drylands contribute roughly 40 % of the global net primary productivity and are essential for achieving sustainable development. Investigating the effects on vegetation from urban expansion in drylands within the context of rapid urbanization could help ... ...

Abstract	Drylands contribute roughly 40 % of the global net primary productivity and are essential for achieving sustainable development. Investigating the effects on vegetation from urban expansion in drylands within the context of rapid urbanization could help enhance the sustainability of dryland cities. With the use of the drylands of northern China (DNC) as an example, we applied the vegetation disturbance index to investigate the negative and positive effects on vegetation from urban expansion in drylands. The results revealed that the DNC experienced massive and rapid urban expansion from 2000 to 2020. Urban land in the entire DNC increased by 19,646 km
MeSH term(s)	China ; Urbanization ; Conservation of Natural Resources ; Environmental Monitoring ; Ecosystem ; Desert Climate ; Plants ; Cities ; Sustainable Development
Language	English
Publishing date	2024-04-16
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2024.172481
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Zs.A 949: Show issues

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Article ; Online: Lightweight model-based sheep face recognition via face image recording channel.

Zhang, Xiwen / Xuan, Chuanzhong / Ma, Yanhua / Liu, Haiyang / Xue, Jing

Journal of animal science

2024 Volume 102

Abstract: The accurate identification of individual sheep is a crucial prerequisite for establishing digital sheep farms and precision livestock farming. Currently, deep learning technology provides an efficient and non-contact method for sheep identity ... ...

Abstract	The accurate identification of individual sheep is a crucial prerequisite for establishing digital sheep farms and precision livestock farming. Currently, deep learning technology provides an efficient and non-contact method for sheep identity recognition. In particular, convolutional neural networks can be used to learn features of sheep faces to determine their corresponding identities. However, the existing sheep face recognition models face problems such as large model size, and high computational costs, making it difficult to meet the requirements of practical applications. In response to these issues, we introduce a lightweight sheep face recognition model called YOLOv7-Sheep Face Recognition (YOLOv7-SFR). Considering the labor-intensive nature associated with manually capturing sheep face images, we developed a face image recording channel to streamline the process and improve efficiency. This study collected facial images of 50 Small-tailed Han sheep through a recording channel. The experimental sheep ranged in age from 1 to 3 yr, with an average weight of 63.1 kg. Employing data augmentation methods further enhanced the original images, resulting in a total of 22,000 sheep face images. Ultimately, a sheep face dataset was established. To achieve lightweight improvement and improve the performance of the recognition model, a variety of improvement strategies were adopted. Specifically, we introduced the shuffle attention module into the backbone and fused the Dyhead module with the model's detection head. By combining multiple attention mechanisms, we improved the model's ability to learn target features. Additionally, the traditional convolutions in the backbone and neck were replaced with depthwise separable convolutions. Finally, leveraging knowledge distillation, we enhanced its performance further by employing You Only Look Once version 7 (YOLOv7) as the teacher model and YOLOv7-SFR as the student model. The training results indicate that our proposed approach achieved the best performance on the sheep face dataset, with a mean average precision@0.5 of 96.9%. The model size and average recognition time were 11.3 MB and 3.6 ms, respectively. Compared to YOLOv7-tiny, YOLOv7-SFR showed a 2.1% improvement in mean average precision@0.5, along with a 5.8% reduction in model size and a 42.9% reduction in average recognition time. The research results are expected to drive the practical applications of sheep face recognition technology.
MeSH term(s)	Animals ; Sheep ; Pregnancy ; Female ; Facial Recognition ; Agriculture ; Farms ; Labor, Obstetric ; Livestock
Language	English
Publishing date	2024-03-12
Publishing country	United States
Document type	Journal Article
ZDB-ID	390959-1
ISSN	1525-3163 ; 0021-8812
ISSN (online)	1525-3163
ISSN	0021-8812
DOI	10.1093/jas/skae066
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Zs.A 1312: Show issues

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Article: A causal association between amyotrophic lateral sclerosis and atrial fibrillation: a two-sample Mendelian randomization study.

Yao, Yiren / Liu, Hongyang / Gu, Yang / Xu, Xiaojin / Zhang, Xiwen

Frontiers in cardiovascular medicine

2024 Volume 11, Page(s) 1351495

Abstract: Objectives: To look into the connection between amyotrophic lateral sclerosis (ALS) and atrial fibrillation (AF) using Mendelian randomization (MR).: Methods: Two-sample MR was performed using genetic information from genome-wide association studies ( ...

Abstract	Objectives: To look into the connection between amyotrophic lateral sclerosis (ALS) and atrial fibrillation (AF) using Mendelian randomization (MR). Methods: Two-sample MR was performed using genetic information from genome-wide association studies (GWAS). Genetic variants robustly associated with ALS and AF were used as instrumental variables. GWAS genetic data for ALS ( Results: The IVW method demonstrated that ALS positively affected AF [OR: 1.062, 95% CI (1.004-1.122); Conclusions: This MR study proves a positive causal connection between ALS and atrial fibrillation. Further studies are warranted to elucidate the mechanisms linking ALS and AF.
Language	English
Publishing date	2024-04-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2781496-8
ISSN	2297-055X
ISSN	2297-055X
DOI	10.3389/fcvm.2024.1351495
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Article ; Online: Reinforcement of Aminopropyl-Terminated Siloxane-Treated Carbon Nanotubes in Epoxy Thermosets: Mechanical and Thermal Properties.

Sun, Yuxin / Zhang, Xiwen / Zhao, Dongyu

Polymers

2023 Volume 15, Issue 15

Abstract: The synthesis and characterization of aminopropyl-terminated polydimethylsiloxane- treated carbon nanotube (AFCNT)-reinforced epoxy nanocomposites are reported in the current study. The amine functionalization of the CNTs was performed with a reaction to ...

Abstract	The synthesis and characterization of aminopropyl-terminated polydimethylsiloxane- treated carbon nanotube (AFCNT)-reinforced epoxy nanocomposites are reported in the current study. The amine functionalization of the CNTs was performed with a reaction to PDMS-NH
Language	English
Publishing date	2023-07-27
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym15153184
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Article: Transcriptome-based network analysis of cell cycle-related genes in response to blue and red light in maize.

Liu, Tiedong / Zhang, Xiwen / Liu, Shengqun

AoB PLANTS

2023 Volume 15, Issue 6, Page(s) plad079

Abstract: In maize, blue and red light are key environmental factors regulating cell-cycle progression. We used transcriptomics to investigate and compare differential gene expression under the four light conditions: red light, blue light, red converted to blue ... ...

Abstract	In maize, blue and red light are key environmental factors regulating cell-cycle progression. We used transcriptomics to investigate and compare differential gene expression under the four light conditions: red light, blue light, red converted to blue and blue converted to red. A total of 23 differentially expressed genes were identified. The gene-gene interaction analysis indicated a significant interaction between four unidentified genes,
Language	English
Publishing date	2023-12-11
Publishing country	England
Document type	Journal Article
ZDB-ID	2555823-7
ISSN	2041-2851
ISSN	2041-2851
DOI	10.1093/aobpla/plad079
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Article ; Online: Fully Electrically Controlled van der Waals Multiferroic Tunnel Junctions.

Yu, Xing / Zhang, Xiwen / Wang, Jinlan

ACS nano

2023 Volume 17, Issue 24, Page(s) 25348–25356

Abstract: The fully electrical control of the magnetic states in magnetic tunnel junctions is highly pursued for the development of the next generation of low-power and high-density information technology. However, achieving this functionality remains a formidable ...

Abstract	The fully electrical control of the magnetic states in magnetic tunnel junctions is highly pursued for the development of the next generation of low-power and high-density information technology. However, achieving this functionality remains a formidable challenge at present. Here we propose an effective strategy by constructing a trilayer van der Waals multiferroic structure, consisting of CrI
Language	English
Publishing date	2023-12-11
Publishing country	United States
Document type	Journal Article
ISSN	1936-086X
ISSN (online)	1936-086X
DOI	10.1021/acsnano.3c08747
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Article ; Online: A high-precision facial recognition method for small-tailed Han sheep based on an optimised Vision Transformer.

Zhang, Xiwen / Xuan, Chuanzhong / Ma, Yanhua / Su, He

Animal : an international journal of animal bioscience

2023 Volume 17, Issue 8, Page(s) 100886

Abstract: Accurate identification of individual animals plays a pivotal role in enhancing animal welfare and optimising farm production. Although Radio Frequency Identification technology has been widely applied in animal identification, this method still exhibits ...

Abstract	Accurate identification of individual animals plays a pivotal role in enhancing animal welfare and optimising farm production. Although Radio Frequency Identification technology has been widely applied in animal identification, this method still exhibits several limitations that make it difficult to meet current practical application requirements. In this study, we proposed ViT-Sheep, a sheep face recognition model based on the Vision Transformer (ViT) architecture, to facilitate precise animal management and enhance livestock welfare. Compared to Convolutional Neural Network (CNN), ViT is renowned for its competitive performance. The experimental procedure of this study consisted of three main steps. Firstly, we collected face images of 160 experimental sheep to construct the sheep face image dataset. Secondly, we developed two sets of sheep face recognition models based on CNN and ViT, respectively. To enhance the ability to learn sheep face biological features, we proposed targeted improvement strategies for the sheep face recognition model. Specifically, we introduced the LayerScale module into the encoder of the ViT-Base-16 model and employed transfer learning to improve recognition accuracy. Finally, we compared the training results of different recognition models and the ViT-Sheep model. The results demonstrated that our proposed method achieved the highest performance on the sheep face image dataset, with a recognition accuracy of 97.9%. This study demonstrates that ViT can successfully achieve sheep face recognition tasks with good robustness. Furthermore, the findings of this research will promote the practical application of artificial intelligence animal recognition technology in sheep production.
MeSH term(s)	Animals ; Sheep ; Artificial Intelligence ; Facial Recognition ; Animal Welfare ; Farms ; Livestock
Language	English
Publishing date	2023-06-15
Publishing country	England
Document type	Journal Article
ZDB-ID	2257920-5
ISSN	1751-732X ; 1751-7311
ISSN (online)	1751-732X
ISSN	1751-7311
DOI	10.1016/j.animal.2023.100886
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Article ; Online: Genotype and clinical phenotype analysis of a case of Stankiewicz-Isidor syndrome and literature review

ZHANG Xuelei / HE Qinyu / ZHANG Xiwen / CHEN Lifen / DONG Zhiya

Zhenduanxue lilun yu shijian, Vol 22, Iss 01, Pp 58-

2023 Volume 63

Abstract: Objective: To analyze the clinical characteristics and examination results of a child with Stankiewicz-Isidor syndrome (STISS), and to provide reference for the diagnosis and treatment of special types of short stature. Methods: A 4-year-old boy with “4 ... ...

Abstract	Objective: To analyze the clinical characteristics and examination results of a child with Stankiewicz-Isidor syndrome (STISS), and to provide reference for the diagnosis and treatment of special types of short stature. Methods: A 4-year-old boy with “4 years of developmental delay with craniofacial abnomality and ophthalmological malformation” was recruited,and detailed medical history were collected. Physical examination, laboratory detection [growth hormone stimulation test, insulin-like growth factor 1( IGF-1), thyroid function and other tests] and imaging examinations were performed. Whole-exome sequencing(WES) was used to detect suspicious mutation sites in children and their parents with se-cond-generation target region capture high-throughput sequencing technology, and the findings were verified by Sanger sequencing. The phenotypes and genotype of the STISS children were analyzed in combination with cases reported in literature reported in PubMed, China National Knowledge Internet(CNKI) and WANFANG DATA. Results: The child presented growth retardation, visual impairment, low ear position, mandibular recession, and special facial features of micrognathia. WES revealed a novel heterozygous frameshift variant c.1118delinsCC:p.Ile373ThrfsTer15 in the PSMD12 gene. According to ACMG guidelines, this was a pathogenic variant, which led to STISS.A total of 46 patients with STISS reported pre-viously,and thus there were 47 cases to be analyzed. It indicated that 89.4%(42/47) had growth and development disorders, 85.1%（40/47） had facial deformities, 70.2%（33/47） had intellectual disabilities, while brain imaging abnormalities and skin manifestations were rare.In 47 patients, 13 cases had PSMD12 gene deletion and 34 cases carried single base site mutations in PSMD12 gene. Conclusions: The STISS reported in this article is caused by a novel variation in PSMD12 gene. The child has common clinical phenotypes such as growth and development disorders and facial deformities, but the clinical phenotypes in patients with ...
Keywords	\|stankiewicz-isidor syndrome\|psmd12 gene\|genotype\|clinical phenotype ; Medicine ; R
Subject code	610
Language	Chinese
Publishing date	2023-02-01T00:00:00Z
Publisher	Editorial Office of Journal of Diagnostics Concepts & Practice
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Comparative transcriptome and metabolome analysis reveal glutathione metabolic network and functional genes underlying blue and red-light mediation in maize seedling leaf.

Liu, Tiedong / Zhang, Xiwen

BMC plant biology

2021 Volume 21, Issue 1, Page(s) 593

Abstract: Background: Light quality severely affects biosynthesis and metabolism-associated process of glutathione. However, the role of specific light is still unclear on the glutathione metabolism. In this article, comparatively transcriptome and metabolome ... ...

Abstract	Background: Light quality severely affects biosynthesis and metabolism-associated process of glutathione. However, the role of specific light is still unclear on the glutathione metabolism. In this article, comparatively transcriptome and metabolome methods are used to fully understand the blue and red-light conditions working on the glutathione metabolism in maize seedling leaf. Results: There are 20 differently expressed genes and 4 differently expressed metabolites in KEGG pathway of glutathione metabolism. Among them, 12 genes belong to the glutathione S-transferase family, 3 genes belong to the ascorbate peroxidase gene family and 2 genes belong to the ribonucleoside-diphosphate reductase gene family. Three genes, G6PD, SPDS1, and GPX1 belong to the gene family of glucose 6-phosphate dehydrogenase, spermidine synthase, and glutathione peroxidase, respectively. Four differently expressed metabolites are identified. Three of them, Glutathione disulfide, Glutathione, and l-γ-Glutamyl-L-amino acid are decreased while L-Glutamate is increased. In addition, Through PPI analysis, two annotated genes gst16 and DAAT, and 3 unidentified genes 100381533, pco105094 and umc2770, identified as RPP13-like3, BCAT-like1and GMPS, were obtained. By the analysis of protein sequence and PPI network, we predict that pco105094 and umc2770 were involved in the GSSG-GSH and AsA-GSH cycle in the network of glutathione metabolism. Conclusions: Compared to red light, blue light remarkably changed the transcription signal transduction and metabolism of glutathione metabolism. Differently expressed genes and metabolic mapped to the glutathione metabolism signaling pathways. In total, we obtained three unidentified genes, and two of them were predicted in current glutathione metabolism network. This result will contribute to the research of glutathione metabolism of maize.
MeSH term(s)	Gene Expression Regulation, Plant ; Genes, Plant ; Glutathione/metabolism ; Light ; Metabolic Networks and Pathways/genetics ; Metabolome ; Plant Leaves/enzymology ; Plant Leaves/metabolism ; Plant Leaves/radiation effects ; Plant Proteins/chemistry ; Plant Proteins/genetics ; Plant Proteins/metabolism ; Protein Conformation ; Seedlings/metabolism ; Seedlings/radiation effects ; Transcriptome ; Zea mays/enzymology ; Zea mays/genetics ; Zea mays/metabolism ; Zea mays/radiation effects
Chemical Substances	Plant Proteins ; Glutathione (GAN16C9B8O)
Language	English
Publishing date	2021-12-14
Publishing country	England
Document type	Comparative Study ; Journal Article
ISSN	1471-2229
ISSN (online)	1471-2229
DOI	10.1186/s12870-021-03376-w
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