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Article ; Online: Comparisons of gene coexpression network modules in breast cancer and ovarian cancer.

Zhang, Shuqin

BMC systems biology

2018 Volume 12, Issue Suppl 1, Page(s) 8

Abstract: Background: Breast cancer and ovarian cancer are hormone driven and are known to have some predisposition genes in common such as the two well known cancer genes BRCA1 and BRCA2. The objective of this study is to compare the coexpression network modules ...

Abstract	Background: Breast cancer and ovarian cancer are hormone driven and are known to have some predisposition genes in common such as the two well known cancer genes BRCA1 and BRCA2. The objective of this study is to compare the coexpression network modules of both cancers, so as to infer the potential cancer-related modules. Methods: We applied the eigen-decomposition to the matrix that integrates the gene coexpression networks of both breast cancer and ovarian cancer. With hierarchical clustering of the related eigenvectors, we obtained the network modules of both cancers simultaneously. Enrichment analysis on Gene Ontology (GO), KEGG pathway, Disease Ontology (DO), and Gene Set Enrichment Analysis (GSEA) in the identified modules was performed. Results: We identified 43 modules that are enriched by at least one of the four types of enrichments. 31, 25, and 18 modules are enriched by GO terms, KEGG pathways, and DO terms, respectively. The structure of 29 modules in both cancers is significantly different with p-values less than 0.05, of which 25 modules have larger densities in ovarian cancer. One module was found to be significantly enriched by the terms related to breast cancer from GO, KEGG and DO enrichment. One module was found to be significantly enriched by ovarian cancer related terms. Conclusion: Breast cancer and ovarian cancer share some common properties on the module level. Integration of both cancers helps identifying the potential cancer associated modules.
MeSH term(s)	Algorithms ; Breast Neoplasms/genetics ; Cluster Analysis ; Female ; Gene Expression Profiling ; Gene Ontology ; Gene Regulatory Networks ; Humans ; Ovarian Neoplasms/genetics
Language	English
Publishing date	2018-04-11
Publishing country	England
Document type	Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1752-0509
ISSN (online)	1752-0509
DOI	10.1186/s12918-018-0530-9
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Article ; Online: Automatic Cell Type Annotation Using Marker Genes for Single-Cell RNA Sequencing Data.

Chen, Yu / Zhang, Shuqin

Biomolecules

2022 Volume 12, Issue 10

Abstract: Recent advancement in single-cell RNA sequencing (scRNA-seq) technology is gaining more and more attention. Cell type annotation plays an essential role in scRNA-seq data analysis. Several computational methods have been proposed for automatic annotation. ...

Abstract	Recent advancement in single-cell RNA sequencing (scRNA-seq) technology is gaining more and more attention. Cell type annotation plays an essential role in scRNA-seq data analysis. Several computational methods have been proposed for automatic annotation. Traditional cell type annotation is to first cluster the cells using unsupervised learning methods based on the gene expression profiles, then to label the clusters using the aggregated cluster-level expression profiles and the marker genes' information. Such procedure relies heavily on the clustering results. As the purity of clusters cannot be guaranteed, false detection of cluster features may lead to wrong annotations. In this paper, we improve this procedure and propose an Automatic Cell type Annotation Method (ACAM). ACAM delineates a clear framework to conduct automatic cell annotation through representative cluster identification, representative cluster annotation using marker genes, and the remaining cells' classification. Experiments on seven real datasets show the better performance of ACAM compared to six well-known cell type annotation methods.
MeSH term(s)	Sequence Analysis, RNA/methods ; Single-Cell Analysis/methods ; Cluster Analysis ; Transcriptome ; Data Analysis ; Biomarkers ; Gene Expression Profiling/methods ; Algorithms ; RNA
Chemical Substances	Biomarkers ; RNA (63231-63-0)
Language	English
Publishing date	2022-10-21
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2701262-1
ISSN	2218-273X ; 2218-273X
ISSN (online)	2218-273X
ISSN	2218-273X
DOI	10.3390/biom12101539
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Article ; Online: Nickel-Catalyzed Suzuki Coupling of Phenols Enabled by SuFEx of Tosyl Fluoride.

Wang, Huimin / Zhang, Shuqin / Xü, Minling / Zou, Gang

Molecules (Basel, Switzerland)

2023 Volume 28, Issue 2

Abstract: A practical and efficient Suzuki coupling of phenols has been developed by ... ...

Abstract	A practical and efficient Suzuki coupling of phenols has been developed by using
Language	English
Publishing date	2023-01-07
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules28020636
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Article ; Online: Age-level bias correction in brain age prediction.

Zhang, Biao / Zhang, Shuqin / Feng, Jianfeng / Zhang, Shihua

NeuroImage. Clinical

2023 Volume 37, Page(s) 103319

Abstract: The predicted age difference (PAD) between an individual's predicted brain age and chronological age has been commonly viewed as a meaningful phenotype relating to aging and brain diseases. However, the systematic bias appears in the PAD achieved using ... ...

Abstract	The predicted age difference (PAD) between an individual's predicted brain age and chronological age has been commonly viewed as a meaningful phenotype relating to aging and brain diseases. However, the systematic bias appears in the PAD achieved using machine learning methods. Recent studies have designed diverse bias correction methods to eliminate it for further downstream studies. Strikingly, here we demonstrate that bias still exists in the PAD of samples with the same age even after kind of correction. Therefore, current PAD may not be taken as a reliable phenotype and more investigations are needed to solve this fundamental defect. To this end, we propose an age-level bias correction method and demonstrate its efficacy in numerical experiments.
MeSH term(s)	Magnetic Resonance Imaging/methods ; Brain/diagnostic imaging ; Machine Learning
Language	English
Publishing date	2023-01-07
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2701571-3
ISSN	2213-1582 ; 2213-1582
ISSN (online)	2213-1582
ISSN	2213-1582
DOI	10.1016/j.nicl.2023.103319
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Article: Comparison of Proximal Anti-Rotation Intramedullary Nail and Femoral Head Replacement for the Treatment of Femoral Intertrochanteric Fractures in Elderly Patients.

Bi, Chunqiang / Zhao, Yan / Ma, Zilong / Zhang, Shuqin

Alternative therapies in health and medicine

2023 Volume 29, Issue 5, Page(s) 268–273

Abstract: Objective: To compare and analyze the effects of proximal femoral nail anti-rotation (PFNA) and femoral head replacement in treating elderly patients with femoral intertrochanteric fracture.: Methods: A retrospective analysis was performed on ... ...

Abstract	Objective: To compare and analyze the effects of proximal femoral nail anti-rotation (PFNA) and femoral head replacement in treating elderly patients with femoral intertrochanteric fracture. Methods: A retrospective analysis was performed on clinical data of elderly patients with femoral intertrochanteric fractures from February 2019 to February 2021 in the hospital. Patients were divided into a control group (PFNA) and a study group (femoral head replacement) based on surgical methods after propensity score matching. Perioperative indicators, hematocrit (HCT), hemoglobin (Hb), hip function, and complications one year after surgery were compared between the two groups after excluding confounding factors. Result: Both groups had complete follow-ups without any cases lost. The study group had longer surgical time, higher intraoperative blood loss, and greater postoperative drainage volume compared to the control group, while the hospital stay and weight-bearing starting time were shorter in the study group (P < .05). There were statistically significant differences in HCT and Hb after surgery between the two groups (P < .05). One year after surgery, the excellent and good rate of hip function was 90.28% in the study group and 76.39% in the control group (P < .05). The total incidence rate of postoperative early complications was higher in the study group, while the total incidence rate of late postoperative complications was lower in the study group compared to the control group (P < .05). Conclusion: PFNA and femoral head replacement have their respective advantages in treating elderly patients with femoral intertrochanteric fractures. PFNA causes less trauma to patients but has poorer postoperative hip function recovery, while femoral head replacement causes greater trauma to patients but has better postoperative hip function recovery. Therefore, the appropriate surgical method can be selected based on the patient's specific conditions.
MeSH term(s)	Humans ; Aged ; Retrospective Studies ; Femur Head ; Bone Nails ; Fracture Fixation, Intramedullary/methods ; Treatment Outcome ; Hip Fractures/surgery ; Femoral Fractures/surgery ; Postoperative Complications/epidemiology
Language	English
Publishing date	2023-04-22
Publishing country	United States
Document type	Journal Article
ZDB-ID	1225073-9
ISSN	1078-6791
ISSN	1078-6791
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Article ; Online: BLTSA: pseudotime prediction for single cells by branched local tangent space alignment.

Li, Limin / Zhao, Yameng / Li, Huiran / Zhang, Shuqin

Bioinformatics (Oxford, England)

2023 Volume 39, Issue 2

Abstract: Motivation: The development of single-cell RNA sequencing (scRNA-seq) technology makes it possible to study the cellular dynamic processes such as cell cycle and cell differentiation. Due to the difficulties in generating genuine time-series scRNA-seq ... ...

Abstract	Motivation: The development of single-cell RNA sequencing (scRNA-seq) technology makes it possible to study the cellular dynamic processes such as cell cycle and cell differentiation. Due to the difficulties in generating genuine time-series scRNA-seq data, it is of great importance to computationally infer the pseudotime of the cells along differentiation trajectory based on their gene expression patterns. The existing pseudotime prediction methods often suffer from the high level noise of single-cell data, thus it is still necessary to study the single-cell trajectory inference methods. Results: In this study, we propose a branched local tangent space alignment (BLTSA) method to infer single-cell pseudotime for multi-furcation trajectories. By assuming that single cells are sampled from a low-dimensional self-intersecting manifold, BLTSA first identifies the tip and branching cells in the trajectory based on cells' local Euclidean neighborhoods. Local coordinates within the tangent spaces are then determined by each cell's local neighborhood after clustering all the cells to different branches iteratively. The global coordinates for all the single cells are finally obtained by aligning the local coordinates based on the tangent spaces. We evaluate the performance of BLTSA on four simulation datasets and five real datasets. The experimental results show that BLTSA has obvious advantages over other comparison methods. Availability and implementation: R codes are available at https://github.com/LiminLi-xjtu/BLTSA. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Software ; Gene Expression Profiling/methods ; Single-Cell Analysis/methods ; Computer Simulation ; Cell Differentiation ; Sequence Analysis, RNA/methods
Language	English
Publishing date	2023-01-24
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btad054
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Article ; Online: CALLR: a semi-supervised cell-type annotation method for single-cell RNA sequencing data.

Wei, Ziyang / Zhang, Shuqin

Bioinformatics (Oxford, England)

2021 Volume 37, Issue Suppl_1, Page(s) i51–i58

Abstract: Motivation: Single-cell RNA sequencing (scRNA-seq) technology has been widely applied to capture the heterogeneity of different cell types within complex tissues. An essential step in scRNA-seq data analysis is the annotation of cell types. Traditional ... ...

Abstract	Motivation: Single-cell RNA sequencing (scRNA-seq) technology has been widely applied to capture the heterogeneity of different cell types within complex tissues. An essential step in scRNA-seq data analysis is the annotation of cell types. Traditional cell-type annotation is mainly clustering the cells first, and then using the aggregated cluster-level expression profiles and the marker genes to label each cluster. Such methods are greatly dependent on the clustering results, which are insufficient for accurate annotation. Results: In this article, we propose a semi-supervised learning method for cell-type annotation called CALLR. It combines unsupervised learning represented by the graph Laplacian matrix constructed from all the cells and supervised learning using sparse logistic regression. By alternately updating the cell clusters and annotation labels, high annotation accuracy can be achieved. The model is formulated as an optimization problem, and a computationally efficient algorithm is developed to solve it. Experiments on 10 real datasets show that CALLR outperforms the compared (semi-)supervised learning methods, and the popular clustering methods. Availability and implementation: The implementation of CALLR is available at https://github.com/MathSZhang/CALLR. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Cluster Analysis ; Gene Expression Profiling ; RNA ; Sequence Analysis, RNA ; Single-Cell Analysis
Chemical Substances	RNA (63231-63-0)
Language	English
Publishing date	2021-07-12
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btab286
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Article: Effects of electroacupuncture on repairing neurological damage following ischemic stroke based on miR-381-mediated SDF-1/CXCR4 signaling pathway.

Song, Xuemei / Qin, Hewei / Li, Yanjie / Niu, Yuqing / Guo, Ning / Zhang, Shuqin

Zhongguo zhen jiu = Chinese acupuncture & moxibustion

2024 Volume 44, Issue 2, Page(s) 175–181

Abstract: Objectives: To investigate the effects of electroacupuncture (EA) on the miR-381, leucine-rich repeat C4 protein (LRRC4), and downstream stromal cell-derived factor-1 (SDF-1)/CXC chemokine receptor 4 (CXCR4) signaling pathway in rat model of ischemic ... ...

Title translation	基于miR-381调控SDF-1/CXCR4信号通路探讨电针对缺血性脑卒中后神经损伤修复的影响.
Abstract	Objectives: To investigate the effects of electroacupuncture (EA) on the miR-381, leucine-rich repeat C4 protein (LRRC4), and downstream stromal cell-derived factor-1 (SDF-1)/CXC chemokine receptor 4 (CXCR4) signaling pathway in rat model of ischemic stroke, and to explore the mechanism by which EA improves neurological damage following ischemic stroke. Methods: Among 50 SPF male SD rats, 10 rats were randomly selected into a sham surgery group, and the remaining rats were used to establish the middle cerebral artery occlusion (MCAO) model. The 30 successfully modeled rats were randomly divided into a model group, an EA group, and an agonist group, with 10 rats in each group. The rats in the EA group received EA at "Baihui" (GV 20) and "Dazhui" (GV 14), with disperse-dense wave, a frequency of 2 Hz/10 Hz, and a current intensity of 1 mA, 30 min per session, once daily for a total of 14 days. The rats in the agonist group received miR-381 agonist injections into the lateral ventricle, with 10 μL per injection, every 7 days for a total of 2 injections. After intervention, ZeaLonga neurobehavioral deficit score was observed in each group. HE staining was performed to observe the morphological changes in the ischemic brain tissue of rats in each group. ELISA was used to measure the levels of tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), and nerve growth factor (NGF) in serum. Western blot was employed to detect the protein expression of LRRC4, SDF-1, CXCR4, and extracellular regulated protein kinase 1 (ERK1) in the ischemic brain tissue. Real-time PCR was utilized to assess the expression of miR-381 and LRRC4, SDF-1, CXCR4, ERK1 mRNA in the ischemic brain tissue. Results: After intervention, the brain tissue showed disordered cell arrangement, reduced quantity, and significant interstitial edema, with numerous vacuoles in the model group. The pathological changes mentioned above were alleviated in the brain tissue of rats in the EA group and the agonist group. Compared with the sham surgery group, the rats in the model group exhibited increased ZeaLonga neurobehavioral deficit scores, elevated levels of serum TNF-α and IL-6 ( Conclusions: EA at "Baihui" (GV 20) and "Dazhui" (GV 14) may promote the repair of neurological damage following ischemic stroke by up-regulating miR-381 to selectively inhibit LRRC4 expression, thereby activating the SDF-1/CXCR4 signaling pathway.
MeSH term(s)	Rats ; Male ; Animals ; Ischemic Stroke ; Brain Ischemia/genetics ; Brain Ischemia/therapy ; Brain Ischemia/metabolism ; Rats, Sprague-Dawley ; Receptors, CXCR4/genetics ; Receptors, CXCR4/metabolism ; Electroacupuncture ; Tumor Necrosis Factor-alpha/genetics ; Interleukin-6 ; Nerve Growth Factor ; Signal Transduction ; MicroRNAs/genetics ; RNA, Messenger
Chemical Substances	Receptors, CXCR4 ; Tumor Necrosis Factor-alpha ; Interleukin-6 ; Nerve Growth Factor (9061-61-4) ; MicroRNAs ; RNA, Messenger
Language	Chinese
Publishing date	2024-02-12
Publishing country	China
Document type	Journal Article
ISSN	0255-2930
ISSN	0255-2930
DOI	10.13703/j.0255-2930.20220818-k0008
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Article ; Online: Microbiomic signatures of anal fistula and putative sources of microbes.

Yang, Jun / Li, Ling / Su, Wenya / Zhang, Shuqin / Xu, Hai / Wang, Mingyu / Shen, Wenlong

Frontiers in cellular and infection microbiology

2024 Volume 14, Page(s) 1332490

Abstract: Anal fistula is a common perianal disease that typically develops from an abscess caused by in-flammation in the area. It has long been believed that intestinal microbes play a significant role in its development, considering its close relation to the ... ...

Abstract	Anal fistula is a common perianal disease that typically develops from an abscess caused by in-flammation in the area. It has long been believed that intestinal microbes play a significant role in its development, considering its close relation to the intestinal environment. This work attempts to identify the microbiomic signatures of anal fistula, and putative sources of microbes by analyzing microbiomes of 7 anal fistula-associated sites in 12 patients. This study found that microbes in anal fistulas may originate from the skin surface in addition to the intestinal tract. This finding was further validated by NMDS analysis, which also indicated that the microbial communities in the inner and outer openings of the fistula were more similar to their surrounding environments. Using MaAslin2, the characteristics of the microbiome were examined, demonstrating a higher similarity between the abundant bacteria in the anal fistula samples and those found on the skin surface. Moreover, pin-to-pair analysis conducted on all subjects consistently showed a higher abundance of skin-sourced bacteria in anal fistulas. This study identifies the microbiomic signatures of anal fistula, and provides novel insights into the origin of microorganisms in anal fistulas.
MeSH term(s)	Humans ; Rectal Fistula ; Skin ; Microbiota ; Treatment Outcome
Language	English
Publishing date	2024-01-19
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2619676-1
ISSN	2235-2988 ; 2235-2988
ISSN (online)	2235-2988
ISSN	2235-2988
DOI	10.3389/fcimb.2024.1332490
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Article ; Online: Ecological and health risk assessments of heavy metals and their accumulation in a peanut-soil system.

Zhang, Xiaoqing / Liu, Huanhuan / Li, Xin / Zhang, Zhaowei / Chen, Zhihua / Ren, Dajun / Zhang, Shuqin

Environmental research

2024 Volume 252, Issue Pt 2, Page(s) 118946

Abstract: Heavy metals pollution is a notable threat to environment and human health. This study evaluated the potential ecological and health risks of heavy metals (Cu, Cr, Cd, Pb, Zn, Ni, and As) and their accumulation in a peanut-soil system based on 34 soil ... ...

Abstract	Heavy metals pollution is a notable threat to environment and human health. This study evaluated the potential ecological and health risks of heavy metals (Cu, Cr, Cd, Pb, Zn, Ni, and As) and their accumulation in a peanut-soil system based on 34 soil and peanut kernel paired samples across China. Soil As and Cd posed the greatest pollution risk with 47.1% and 17.6% of soil samples exceeding the risk screen levels, respectively, with 26.5% and 20.6% of the soil sites at relatively strong potential ecological risk level, respectively, and with the geo-accumulation levels at several soil sites in the uncontaminated to moderately contaminated categories. About 35.29% and 2.94% of soil sites were moderately and severely polluted based on Nemerow comprehensive pollution index, respectively, and a total of 32.4% of samples were at moderate ecological hazard level based on comprehensive potential ecological risk index values. The Cd, Cr, Ni, and Cu contents exceeded the standard in 11.76, 8.82, 11.76 and 5.88% of the peanut kernel samples, respectively. Soil metals posed more health risks to children than adults in the order As > Ni > Cr > Cu > Pb > Zn > Cd for non-carcinogenic health risks and Ni > Cr ≫ Cd > As > Pb for carcinogenic health risks. The soil As non-cancer risk index for children was greater than the permitted limits at 14 sites, and soil Ni and Cr posed the greatest carcinogenic risk to adults and children at many soil sites. The metals in peanut did not pose a non-carcinogenic risk according to standard. Peanut kernels had strong enrichment ability for Cd with an average bio-concentration factor (BCF) of 1.62. Soil metals contents and significant soil properties accounted for 35-74% of the variation in the BCF values of metals based on empirical prediction models.
Language	English
Publishing date	2024-04-15
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	205699-9
ISSN	1096-0953 ; 0013-9351
ISSN (online)	1096-0953
ISSN	0013-9351
DOI	10.1016/j.envres.2024.118946
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