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Article: [Application of sulfylated calcium alginate composite hydrogel loaded with zinc-based zeolite imidazole for the treatment of periodontitis].

Ouyang, Ming / Wang, Guo-Hua

Shanghai kou qiang yi xue = Shanghai journal of stomatology

2023 Volume 31, Issue 4, Page(s) 379–383

Abstract: Purpose: To explore the feasibility of adhesive thiomer calcium alginate composite hydrogel (ZIF-8@CHA-SH) containing metal-organic framework for the treatment of periodontitis in rats.: Methods: Preparation and characterization of ZIF-8@CHA-SH were ... ...

Abstract	Purpose: To explore the feasibility of adhesive thiomer calcium alginate composite hydrogel (ZIF-8@CHA-SH) containing metal-organic framework for the treatment of periodontitis in rats. Methods: Preparation and characterization of ZIF-8@CHA-SH were performed, and the morphology and chemical composition were observed. The antibacterial properties were detected by plate coating method and scanning electron microscope. CCK-8 and live/dead cell fluorescence staining were used to evaluate the toxicity of ZIF-8@CHA-SH on gingival fibroblasts. The anti-inflammatory and tissue repair promoting effects of ZIF-8@CHA-SH were verified by animal experiments. GraphPad Prism 7.0 software was used for statistical analysis. Results: The successful synthesis of ZIF-8@CHA-SH was proved by scanning electron microscopy, energy spectrum analysis, Fourier transform infrared spectroscopy and X-ray diffraction. ZIF-8@CHA-SH had excellent antibacterial ability, and the antibacterial rates against Escherichia coli, Staphylococcus aureus and Streptococcus mutans were (99.88±0.12)%, (99.81±0.32)% and (95.53±3.08)%, respectively（P<0.001）. The cell viability rate of ZIF-8@CHA-SH was (91.64±3.66)% after 5 days of co-culture with human gingival fibroblasts (P=0.6). In vivo experiments showed that ZIF-8@CHA-SH could reduce the infiltration of inflammatory cells and the expression of pro-inflammatory factor IL-6 in rats with periodontitis. Conclusions: ZIF-8@CHA-SH has excellent biological performance, which can effectively treat periodontitis caused by bacteria, and provids a new strategy for the treatment of periodontal diseases in the future.
MeSH term(s)	Rats ; Animals ; Humans ; Zinc ; Zeolites/chemistry ; Hydrogels/chemistry ; Alginates ; Anti-Bacterial Agents/pharmacology ; Periodontitis/drug therapy ; Imidazoles/chemistry
Chemical Substances	Zinc (J41CSQ7QDS) ; Zeolites (1318-02-1) ; Hydrogels ; Alginates ; Anti-Bacterial Agents ; Imidazoles
Language	Chinese
Publishing date	2023-01-30
Publishing country	China
Document type	English Abstract ; Journal Article
ZDB-ID	2269714-7
ISSN	1006-7248
ISSN	1006-7248
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Article ; Online: Liquid Biopsy, a Potential New Detection Method in Heart Allograft Rejection.

Li, Chenghao / Wang, Guohua

Methods in molecular biology (Clifton, N.J.)

2023 Volume 2695, Page(s) 309–315

Abstract: Allografts rejection remains the most important reason causing allograft dysfunction in heart transplantation recipients. Currently, the golden standard for detecting graft rejection is endomyocardial biopsy (EMB). As a new noninvasive technique, liquid ... ...

Abstract	Allografts rejection remains the most important reason causing allograft dysfunction in heart transplantation recipients. Currently, the golden standard for detecting graft rejection is endomyocardial biopsy (EMB). As a new noninvasive technique, liquid biopsy emerges along with the great developments of droplet-based digital PCR and the various optimizations of next-generation sequencing technologies, which is also cheaper than EMB. This review introduces several types of liquid biopsy and its application in heart transplantation.
MeSH term(s)	Heart Transplantation/adverse effects ; Biopsy ; Liquid Biopsy ; Transplantation, Homologous ; Graft Rejection/diagnosis ; Graft Rejection/pathology ; Allografts ; Myocardium/pathology
Language	English
Publishing date	2023-07-14
Publishing country	United States
Document type	Review ; Journal Article
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-3346-5_21
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: [Characteristics of vegetation and soil in

Wang, Guo-Hua / Wang, Jia-Qi / Liu, Jing

Ying yong sheng tai xue bao = The journal of applied ecology

2024 Volume 35, Issue 1, Page(s) 62–72

Abstract: We investigated the changes of soil nutrients and plant communities in the artificial sand fixation forests ... ...

Title translation	晋西北丘陵风沙区柠条锦鸡儿人工林植被和土壤随林龄变化特征.
Abstract	We investigated the changes of soil nutrients and plant communities in the artificial sand fixation forests of
MeSH term(s)	Soil ; Sand ; Caragana ; Carbon/analysis ; China ; Nitrogen
Chemical Substances	Soil ; Sand ; Carbon (7440-44-0) ; Nitrogen (N762921K75)
Language	Chinese
Publishing date	2024-03-21
Publishing country	China
Document type	English Abstract ; Journal Article
ZDB-ID	2881809-X
ISSN	1001-9332
ISSN	1001-9332
DOI	10.13287/j.1001-9332.202401.004
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Article: Coronary Artery Fistula and Severe Coronary Artery Stenosis: A Case Report and an Insight for Potential Pathogenesis of Coronary Artery Atherosclerosis.

Liu, Jinchun / Yu, Zhijun / Wang, Guohua

International medical case reports journal

2024 Volume 17, Page(s) 227–233

Abstract: Coronary artery fistulae (CAF) are a rare anomaly characterized by abnormal connections between a coronary artery and a cardiac chamber or a great vessel, with most patients remaining asymptomatic. Despite being predisposed to severe complications like ... ...

Abstract	Coronary artery fistulae (CAF) are a rare anomaly characterized by abnormal connections between a coronary artery and a cardiac chamber or a great vessel, with most patients remaining asymptomatic. Despite being predisposed to severe complications like heart failure, patients with CAF infrequently experience severe stenosis in the coronary artery. This study delineates a case involving a 46-year-old male presenting with a fistula bridging the right coronary artery (RCA) and right atrium (RA), manifesting a pronounced 99% stenosis at the right extremity of the coronary artery proximal to the fistula. Concurrently, the individual exhibits six conventional risk factors: age over 40, male gender, hypertension, diabetes, smoking, and hypertriglyceridemia. Following pharmaceutical intervention, the patient was discharged and subjected to extended follow-up. This case highlights the dual processes of "accelerating damage" and "retarding renewal" in the progression of atherosclerosis. Factors such as shear stress, smoking, and hypertension are posited to expedite endothelial cell damage, while aging and diabetes may impede the renewal and repair of these cells. Together with the concept of secondary atherosclerotic plaque healing, this case prompts the introduction of a "Double Endothelial Healings" hypothesis, proposing a potential pathogenetic mechanism for coronary artery atherosclerosis.
Language	English
Publishing date	2024-03-26
Publishing country	New Zealand
Document type	Case Reports
ZDB-ID	2495077-4
ISSN	1179-142X
ISSN	1179-142X
DOI	10.2147/IMCRJ.S442878
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Article ; Online: GSL-DTI: Graph structure learning network for Drug-Target interaction prediction.

E, Zixuan / Qiao, Guanyu / Wang, Guohua / Li, Yang

Methods (San Diego, Calif.)

2024 Volume 223, Page(s) 136–145

Abstract: Motivation: Drug-target interaction prediction is an important area of research to predict whether there is an interaction between a drug molecule and its target protein. It plays a critical role in drug discovery and development by facilitating the ... ...

Abstract	Motivation: Drug-target interaction prediction is an important area of research to predict whether there is an interaction between a drug molecule and its target protein. It plays a critical role in drug discovery and development by facilitating the identification of potential drug candidates and expediting the overall process. Given the time-consuming, expensive, and high-risk nature of traditional drug discovery methods, the prediction of drug-target interactions has become an indispensable tool. Using machine learning and deep learning to tackle this class of problems has become a mainstream approach, and graph-based models have recently received much attention in this field. However, many current graph-based Drug-Target Interaction (DTI) prediction methods rely on manually defined rules to construct the Drug-Protein Pair (DPP) network during the DPP representation learning process. However, these methods fail to capture the true underlying relationships between drug molecules and target proteins. Results: We propose GSL-DTI, an automatic graph structure learning model used for predicting drug-target interactions (DTIs). Initially, we integrate large-scale heterogeneous networks using a graph convolution network based on meta-paths, effectively learning the representations of drugs and target proteins. Subsequently, we construct drug-protein pairs based on these representations. In contrast to previous studies that construct DPP networks based on manual rules, our method introduces an automatic graph structure learning approach. This approach utilizes a filter gate on the affinity scores of DPPs and relies on the classification loss of downstream tasks to guide the learning of the underlying DPP network structure. Based on the learned DPP network, we transform the prediction of drug-target interactions into a node classification problem. The comprehensive experiments conducted on three public datasets have shown the superiority of GSL-DTI in the tasks of DTI prediction. Additionally, GSL-DTI provides a fresh perspective for advancing research in graph structure learning for DTI prediction.
MeSH term(s)	Drug Discovery ; Drug Delivery Systems ; Machine Learning
Language	English
Publishing date	2024-02-14
Publishing country	United States
Document type	Journal Article
ZDB-ID	1066584-5
ISSN	1095-9130 ; 1046-2023
ISSN (online)	1095-9130
ISSN	1046-2023
DOI	10.1016/j.ymeth.2024.01.018
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Article ; Online: An analog circuit fault diagnosis method using improved sparrow search algorithm and support vector machine.

Wang, Guohua / Tu, Yiwei / Nie, Jing

The Review of scientific instruments

2024 Volume 95, Issue 5

Abstract: In analog circuits, component tolerances and circuit nonlinearity pose obstacles to fault diagnosis. To solve this problem, a soft fault diagnosis method based on Sparrow Search Algorithm (SSA) and Support Vector Machine (SVM) is used. In this study, ... ...

Abstract	In analog circuits, component tolerances and circuit nonlinearity pose obstacles to fault diagnosis. To solve this problem, a soft fault diagnosis method based on Sparrow Search Algorithm (SSA) and Support Vector Machine (SVM) is used. In this study, ISSA is obtained by optimization using four strategies for SSA deficiency. Twenty-three benchmark functions are used for optimization experiments, and ISSA converges faster, more accurately, and with better robustness than other swarm intelligence algorithms. Finally, ISSA is used to optimize the SVM parameters and establish the ISSA-SVM fault diagnosis model. In the Sallen-key test circuit diagnosis experiments, the correct fault diagnosis rates of SSA-SVM and ISSA-SVM are 97.41% and 98.15%, respectively. The results show that the optimized ISSA-SVM model has a good analog circuit fault diagnosis with an increase in diagnostic accuracy.
Language	English
Publishing date	2024-05-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	209865-9
ISSN	1089-7623 ; 0034-6748
ISSN (online)	1089-7623
ISSN	0034-6748
DOI	10.1063/5.0210515
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Article ; Online: The impact of environmental risk and platform trust on satisfaction with health qr code use.

Shi, Guoliang / Wang, Guohua

Frontiers in public health

2022 Volume 10, Page(s) 923974

Abstract: In response to the economic and social hazards posed by the COVID-19 global pandemic, many countries have adopted various information technologies to rapidly track and control the spread of the epidemic. Health Quick Response (QR) codes are emergency ... ...

Abstract	In response to the economic and social hazards posed by the COVID-19 global pandemic, many countries have adopted various information technologies to rapidly track and control the spread of the epidemic. Health Quick Response (QR) codes are emergency measures implemented by the Chinese government in the epidemic environment to balance epidemic prevention and control with recovery of economic and social development, and facilitate public mobility across regions and access to various public spaces. The use of health codes by the public is a practical necessity, but the satisfaction of their use is influenced by multiple factors such as environment, technology, and organization. In this paper, we collected data through a questionnaire to analyze the basic situation of public satisfaction with the use of health QR codes in China and its influencing factors. The results show that perceived quality and platform trust directly affect the satisfaction of health code usage, while environmental risk and platform trust indirectly affect the satisfaction of health code usage through the mediating effect of perceived quality.
MeSH term(s)	COVID-19/epidemiology ; COVID-19/prevention & control ; Government ; Humans ; Personal Satisfaction ; Surveys and Questionnaires ; Trust
Language	English
Publishing date	2022-07-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2711781-9
ISSN	2296-2565 ; 2296-2565
ISSN (online)	2296-2565
ISSN	2296-2565
DOI	10.3389/fpubh.2022.923974
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: OGG1 prevents atherosclerosis-induced vascular endothelial cell injury through mediating DNA damage repair.

Zhang, Yi-Ming / Wang, Guo-Hua / Xu, Miao-Jun / Jin, Gan

Clinical hemorheology and microcirculation

2024

Abstract: Objective: This study was designed to investigate the role of 8-oxoguanine DNA glycosylase 1 (OGG1) in preventing atherosclerosis-induced vascular EC injury, thereby providing a theoretical basis for the exploration of drug targets and treatment methods ...

Abstract	Objective: This study was designed to investigate the role of 8-oxoguanine DNA glycosylase 1 (OGG1) in preventing atherosclerosis-induced vascular EC injury, thereby providing a theoretical basis for the exploration of drug targets and treatment methods for atherosclerosis. Methods: Human umbilical vein cell line (EA.hy926) was treated with ox-LDL to construct an in vitro atherosclerotic cell model. pcDNA3.1-OGG1 was transfected into EA.hy926 cells to overexpress OGG1. qRT-PCR, CCK-8 assay, flow cytometry, oil red O staining, ELISA, comet assay and western blot were used to evaluate the OGG1 expression, viability, apoptosis level, lipid droplet content, 8-OHdG level and DNA damage of cells in each group. Results: Compared with the Control group, ox-LDL stimulation of endothelial cells significantly decreased cell viability, promoted apoptosis and DNA damage, and increased intracellular levels of 8-OHdG and γH2AX, while decreasing protein levels of PPARγ, FASN, FABP4, RAD51 and POLB. However, overexpression of OGG1 can significantly inhibit ox-LDL damage to endothelial cells, promote lipid metabolism, decrease lipid droplet content, and improve DNA repair function. Conclusion: Over-expression of OGG1 improves DNA repair. Briefly, OGG1 over-expression enhances the DNA damage repair of ECs by regulating the expression levels of γH2AX, RAD51 and POLB, thereby enhancing cell viability and reducing apoptosis.
Language	English
Publishing date	2024-02-14
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1381750-4
ISSN	1875-8622 ; 1386-0291
ISSN (online)	1875-8622
ISSN	1386-0291
DOI	10.3233/CH-232082
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Article ; Online: Emerging Neuroprotective Strategies: Unraveling the Potential of HDAC Inhibitors in Traumatic Brain Injury Management.

Ye, Lisha / Li, Wenfeng / Tang, Xiaoyan / Xu, Ting / Wang, Guohua

Current neuropharmacology

2024

Abstract: Traumatic brain injury (TBI) is a significant global health problem, leading to high rates of mortality and disability. It occurs when an external force damages the brain, causing immediate harm and triggering further pathological processes that ... ...

Abstract	Traumatic brain injury (TBI) is a significant global health problem, leading to high rates of mortality and disability. It occurs when an external force damages the brain, causing immediate harm and triggering further pathological processes that exacerbate the condition. Despite its widespread impact, the underlying mechanisms of TBI remain poorly understood, and there are no specific pharmacological treatments available. This creates an urgent need for new, effective neuroprotective drugs and strategies tailored to the diverse needs of TBI patients. In the realm of gene expression regulation, chromatin acetylation plays a pivotal role. This process is controlled by two classes of enzymes: histone acetyltransferase (HAT) and histone deacetylase (HDAC). These enzymes modify lysine residues on histone proteins, thereby determining the acetylation status of chromatin. HDACs, in particular, are involved in the epigenetic regulation of gene expression in TBI. Recent research has highlighted the potential of HDAC inhibitors (HDACIs) as promising neuroprotective agents. These compounds have shown encouraging results in animal models of various neurodegenerative diseases. HDACIs offer multiple avenues for TBI management: they mitigate the neuroinflammatory response, alleviate oxidative stress, inhibit neuronal apoptosis, and promote neurogenesis and axonal regeneration. Additionally, they reduce glial activation, which is associated with TBI-induced neuroinflammation. This review aims to provide a comprehensive overview of the roles and mechanisms of HDACs in TBI and to evaluate the therapeutic potential of HDACIs. By summarizing current knowledge and emphasizing the neuroregenerative capabilities of HDACIs, this review seeks to advance TBI management and contribute to the development of targeted treatments.
Language	English
Publishing date	2024-01-29
Publishing country	United Arab Emirates
Document type	Journal Article
ZDB-ID	2192352-8
ISSN	1875-6190 ; 1570-159X
ISSN (online)	1875-6190
ISSN	1570-159X
DOI	10.2174/1570159X22666240128002056
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Book ; Online: Practical Network Acceleration with Tiny Sets

Wang, Guo-Hua / Wu, Jianxin

Hypothesis, Theory, and Algorithm

2023

Abstract: Due to data privacy issues, accelerating networks with tiny training sets has become a critical need in practice. Previous methods achieved promising results empirically by filter-level pruning. In this paper, we both study this problem theoretically and ...

Abstract	Due to data privacy issues, accelerating networks with tiny training sets has become a critical need in practice. Previous methods achieved promising results empirically by filter-level pruning. In this paper, we both study this problem theoretically and propose an effective algorithm aligning well with our theoretical results. First, we propose the finetune convexity hypothesis to explain why recent few-shot compression algorithms do not suffer from overfitting problems. Based on it, a theory is further established to explain these methods for the first time. Compared to naively finetuning a pruned network, feature mimicking is proved to achieve a lower variance of parameters and hence enjoys easier optimization. With our theoretical conclusions, we claim dropping blocks is a fundamentally superior few-shot compression scheme in terms of more convex optimization and a higher acceleration ratio. To choose which blocks to drop, we propose a new metric, recoverability, to effectively measure the difficulty of recovering the compressed network. Finally, we propose an algorithm named PRACTISE to accelerate networks using only tiny training sets. PRACTISE outperforms previous methods by a significant margin. For 22% latency reduction, it surpasses previous methods by on average 7 percentage points on ImageNet-1k. It also works well under data-free or out-of-domain data settings. Our code is at https://github.com/DoctorKey/Practise Comment: under review for TPAMI. arXiv admin note: substantial text overlap with arXiv:2202.07861
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning ; Statistics - Machine Learning
Subject code	006
Publishing date	2023-03-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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