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Article ; Online: A Study on Fucosyltransferase 2 Gene Polymorphism and Secretion Status Related to Neonatal Necrotizing Enterocolitis

Qing Ye / Jialin Yu

Journal of Healthcare Engineering, Vol

2021 Volume 2021

Abstract: Objective. To detect the single nucleotide polymorphism (SNP) of alpha-(1,2) fucosyltransferase 2 gene (FUT2) and the secretion status in the newborns of Chongqing China and explore the relationship between genotype or phenotype of FUT2 and neonatal ... ...

Abstract	Objective. To detect the single nucleotide polymorphism (SNP) of alpha-(1,2) fucosyltransferase 2 gene (FUT2) and the secretion status in the newborns of Chongqing China and explore the relationship between genotype or phenotype of FUT2 and neonatal necrotizing enterocolitis (NEC). Methods. Newborns who were hospitalized in Children’s Hospital of Chongqing Medical University from August 2014 to December 2015 and in line with the inclusion criteria were chosen as the research subjects; 34 cases of them in accordance with the diagnostic criteria of NEC stage II or III were NEC group, and 36 other cases of them were the control group. Total DNA was extracted from oral epithelial cells of patients which were collected with cotton buds. FUT2 SNP genotype was detected by gene sequencing. H antigen was detected with saliva samples by saliva agglutination inhibition test. Related clinical data were collected for analysis. Results. There are three genotypes on the rs1047781 (A385T) allele of the FUT2 encoding sequence: AA, AT, and TT. The number of genotypes AA, AT, and TT in the NEC group was 9 (26.47%), 12 (35.29%), and 13 (38.24%), respectively. In the control group, the number of genotypes AA, AT, and TT was 12 (33.33%), 17 (47.23%), and 7 (19.44%). There were no differences in genotypes between the two groups according to the chi-square test (P>0.05). There were 22 cases of secretors (64.7%) and 12 cases of nonsecretors (35.3%) in the NEC group. The number of secretors and nonsecretors in the control group was 31 (88.89%) and 5 (11.11%). Statistical difference was found in the phenotype between two groups through the chi-square test (P<0.05). In addition, no G428A homozygous mutation, which causes nonsecretor phenotype in Caucasians, was seen in all the subjects of this study. Conclusions. These findings indicate that secretion status (nonsecretor) was significantly associated with NEC in Chongqing, China.
Keywords	Medicine (General) ; R5-920 ; Medical technology ; R855-855.5
Subject code	690
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Hindawi Limited
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Detection of Weeds Growing in Alfalfa Using Convolutional Neural Networks

Jie Yang / Yundi Wang / Yong Chen / Jialin Yu

Agronomy, Vol 12, Iss 1459, p

2022 Volume 1459

Abstract: Alfalfa ( Medicago sativa L.) is used as a high-nutrient feed for animals. Weeds are a significant challenge that affects alfalfa production. Although weeds are unevenly distributed, herbicides are broadcast-applied in alfalfa fields. In this research, ... ...

Abstract	Alfalfa ( Medicago sativa L.) is used as a high-nutrient feed for animals. Weeds are a significant challenge that affects alfalfa production. Although weeds are unevenly distributed, herbicides are broadcast-applied in alfalfa fields. In this research, object detection convolutional neural networks, including Faster R-CNN, VarifocalNet (VFNet), and You Only Look Once Version 3 (YOLOv3), were used to indiscriminately detect all weed species (1-class) and discriminately detect between broadleaves and grasses (2-class). YOLOv3 outperformed other object detection networks in detecting grass weeds. The performances of using image classification networks (GoogLeNet and VGGNet) and object detection networks (Faster R-CNN and YOLOv3) for detecting broadleaves and grasses were compared. GoogLeNet and VGGNet (F 1 scores ≥ 0.98) outperformed Faster R-CNN and YOLOv3 (F 1 scores ≤ 0.92). Classifying and training various broadleaf and grass weeds did not improve the performance of the neural networks for weed detection. VGGNet was the most effective neural network (F 1 scores ≥ 0.99) tested to detect broadleaf and grass weeds growing in alfalfa. Future research will integrate the VGGNet into the machine vision subsystem of smart sprayers for site-specific herbicide applications.
Keywords	alfalfa ; deep convolutional neural networks ; object detection ; image classification ; precision herbicide application ; Agriculture ; S
Subject code	630
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Effects of Chemical Oxidation and High-Temperature Reduction on Surface Functional Groups and the Adsorption Performance of Biochar for Sulfamethoxazole Adsorption

Jifei Hou / Jialin Yu / Wenxuan Li / Xiudan He / Xuede Li

Agronomy, Vol 12, Iss 510, p

2022 Volume 510

Abstract: Biochar is a beneficial adsorbent for the treatment of organic pollutants in the environment. The association of oxygen functional groups and adsorption behaviors has not been well investigated. In this paper, the oxidation-modified biochar (O-BC) and ... ...

Abstract	Biochar is a beneficial adsorbent for the treatment of organic pollutants in the environment. The association of oxygen functional groups and adsorption behaviors has not been well investigated. In this paper, the oxidation-modified biochar (O-BC) and the reduction-modified biochar (R-BCX) were prepared by Co 2+ /peroxymonosulfate chemical oxidation and high-temperature reduction, respectively. The modified biochars were used to remove sulfamethoxazole (SMX) from water, and the adsorption amounts of biochar followed the order of R-BC700 (14.66 mg·L −1 ) > O-BC (4.91 mg·L −1 ) > BC (0.16 mg·L −1 ). Additionally, the effects of water chemical conditions (i.e., ionic strength, solution pH and humic acid (HA) concentration) on the adsorption of SMX on biochar, were further investigated. Combining physical adsorption, X-ray electron spectroscopy, and zeta potentiometer characterization techniques, the effect of functional groups on the adsorption mechanism was further explored, revealing the importance of various oxygen functional groups for SMX adsorption. The results showed that C=O and C=C, resulting in π–π interaction, were in favor of the adsorption of SMX, while C-O was not conducive to the adsorption of SMX, due to the steric hindrance and the negative surface charge. Additionally, the hydrophobic effect of the biochar was also one of the adsorption mechanisms.
Keywords	oxidized biochar ; reduced biochar ; oxygen functional groups ; adsorption ; sulfamethoxazole ; Agriculture ; S
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Deep learning for detecting herbicide weed control spectrum in turfgrass

Xiaojun Jin / Muthukumar Bagavathiannan / Aniruddha Maity / Yong Chen / Jialin Yu

Plant Methods, Vol 18, Iss 1, Pp 1-

2022 Volume 11

Abstract: Abstract Background Precision spraying of postemergence herbicides according to the herbicide weed control spectrum can substantially reduce herbicide input. The objective of this research was to evaluate the effectiveness of using deep convolutional ... ...

Abstract	Abstract Background Precision spraying of postemergence herbicides according to the herbicide weed control spectrum can substantially reduce herbicide input. The objective of this research was to evaluate the effectiveness of using deep convolutional neural networks (DCNNs) for detecting and discriminating weeds growing in turfgrass based on their susceptibility to ACCase-inhibiting and synthetic auxin herbicides. Results GoogLeNet, MobileNet-v3, ShuffleNet-v2, and VGGNet were trained to discriminate the vegetation into three categories based on the herbicide weed control spectrum: weeds susceptible to ACCase-inhibiting herbicides, weeds susceptible to synthetic auxin herbicides, and turfgrass without weed infestation (no herbicide). ShuffleNet-v2 and VGGNet showed high overall accuracy (≥ 0.999) and F1 scores (≥ 0.998) in the validation and testing datasets to detect and discriminate weeds susceptible to ACCase-inhibiting and synthetic auxin herbicides. The inference time of ShuffleNet-v2 was similar to MobileNet-v3, but noticeably faster than GoogLeNet and VGGNet. ShuffleNet-v2 was the most efficient and reliable model among the neural networks evaluated. Conclusion These results demonstrated that the DCNNs trained based on the herbicide weed control spectrum could detect and discriminate weeds based on their susceptibility to selective herbicides, allowing the precision spraying of particular herbicides to susceptible weeds and thereby saving more herbicides. The proposed method can be used in a machine vision-based autonomous spot-spraying system of smart sprayers.
Keywords	Deep learning ; Herbicide weed control spectrum ; Precision herbicide application ; Weed detection ; Plant culture ; SB1-1110 ; Biology (General) ; QH301-705.5
Subject code	571
Language	English
Publishing date	2022-07-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: LncRNA NR_003508 Suppresses Mycobacterium tuberculosis -Induced Programmed Necrosis via Sponging miR-346-3p to Regulate RIPK1

Li Liu / Zhirui Yu / Qinmei Ma / Jialin Yu / Zhaoqian Gong / Guangcun Deng / Xiaoling Wu

International Journal of Molecular Sciences, Vol 24, Iss 8016, p

2023 Volume 8016

Abstract: Emerging evidence suggests that long non-coding RNAs (LncRNAs) are involved in Mtb-induced programmed necrosis. Among these LncRNAs, LncRNA NR_003508 is associated with LPS-induced acute respiratory distress syndrome. However, whether LncRNA NR_003508 ... ...

Abstract	Emerging evidence suggests that long non-coding RNAs (LncRNAs) are involved in Mtb-induced programmed necrosis. Among these LncRNAs, LncRNA NR_003508 is associated with LPS-induced acute respiratory distress syndrome. However, whether LncRNA NR_003508 contributes to Mtb-induced programmed necrosis remains undocumented. Firstly, the expression of LncRNA NR_003508 was determined using RT-qPCR and FISH. The protein expression of RIPK1, p-RIPK1, RIPK3, p-RIPK3, MLKL, and p-MLKL was measured by Western blot in RAW264.7 and mouse lung tissues. Furthermore, luciferase reporter assays and bioinformatics were used to predict specific miRNA (miR-346-3p) and mRNA (RIPK1) regulated by LncRNA NR_003508. In addition, RT-qPCR was used to detect the RIPK1 expression in TB patients and healthy peripheral blood. The flow cytometry assay was performed to detect cell necrosis rates. Here we show that BCG infection-induced cell necrosis and increased LncRNA NR_003508 expression. si-NR_003508 inhibited BCG/H37Rv-induced programmed necrosis in vitro or in vivo. Functionally, LncRNA NR_003508 has been verified as a ceRNA for absorbing miR-346-3p, which targets RIPK1. Moreover, RIPK1 expression was elevated in the peripheral blood of TB patients compared with healthy people. Knockdown of LncRNA NR_003508 or miR-346-3p overexpression suppresses cell necrosis rate and ROS accumulation in RAW264.7 cells. In conclusion, LncRNA NR_003508 functions as a positive regulator of Mtb-induced programmed necrosis via sponging miR-346-3p to regulate RIPK1. Our findings may provide a promising therapeutic target for tuberculosis.
Keywords	LncRNA NR_003508 ; programmed necrosis ; Mycobacterium tuberculosis ; miR-346-3p ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
Subject code	616
Language	English
Publishing date	2023-04-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Polymeric Drug Delivery System Based on Pluronics for Cancer Treatment

Jialin Yu / Huayu Qiu / Shouchun Yin / Hebin Wang / Yang Li

Molecules, Vol 26, Iss 3610, p

2021 Volume 3610

Abstract: Pluronic polymers (pluronics) are a unique class of synthetic triblock copolymers containing hydrophobic polypropylene oxide (PPO) and hydrophilic polyethylene oxide (PEO) arranged in the PEO-PPO-PEO manner. Due to their excellent biocompatibility and ... ...

Abstract	Pluronic polymers (pluronics) are a unique class of synthetic triblock copolymers containing hydrophobic polypropylene oxide (PPO) and hydrophilic polyethylene oxide (PEO) arranged in the PEO-PPO-PEO manner. Due to their excellent biocompatibility and amphiphilic properties, pluronics are an ideal and promising biological material, which is widely used in drug delivery, disease diagnosis, and treatment, among other applications. Through self-assembly or in combination with other materials, pluronics can form nano carriers with different morphologies, representing a kind of multifunctional pharmaceutical excipients. In recent years, the utilization of pluronic-based multi-functional drug carriers in tumor treatment has become widespread, and various responsive drug carriers are designed according to the characteristics of the tumor microenvironment, resulting in major progress in tumor therapy. This review introduces the specific role of pluronic-based polymer drug delivery systems in tumor therapy, focusing on their physical and chemical properties as well as the design aspects of pluronic polymers. Finally, using newer literature reports, this review provides insights into the future potential and challenges posed by different pluronic-based polymer drug delivery systems in tumor therapy.
Keywords	pluronic ; hydrophilic-lipophilic balance ; cancer therapy ; drug delivery system ; stimulus-responsive polymer ; Organic chemistry ; QD241-441
Subject code	540
Language	English
Publishing date	2021-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Language as a latent sequence

Jialin Yu / Alexandra I. Cristea / Anoushka Harit / Zhongtian Sun / Olanrewaju Tahir Aduragba / Lei Shi / Noura Al Moubayed

AI Open, Vol 4, Iss , Pp 19-

Deep latent variable models for semi-supervised paraphrase generation

2023 Volume 32

Abstract: This paper explores deep latent variable models for semi-supervised paraphrase generation, where the missing target pair for unlabelled data is modelled as a latent paraphrase sequence. We present a novel unsupervised model named variational sequence ... ...

Abstract	This paper explores deep latent variable models for semi-supervised paraphrase generation, where the missing target pair for unlabelled data is modelled as a latent paraphrase sequence. We present a novel unsupervised model named variational sequence auto-encoding reconstruction (VSAR), which performs latent sequence inference given an observed text. To leverage information from text pairs, we additionally introduce a novel supervised model we call dual directional learning (DDL), which is designed to integrate with our proposed VSAR model. Combining VSAR with DDL (DDL+VSAR) enables us to conduct semi-supervised learning. Still, the combined model suffers from a cold-start problem. To further combat this issue, we propose an improved weight initialisation solution, leading to a novel two-stage training scheme we call knowledge-reinforced-learning (KRL). Our empirical evaluations suggest that the combined model yields competitive performance against the state-of-the-art supervised baselines on complete data. Furthermore, in scenarios where only a fraction of the labelled pairs are available, our combined model consistently outperforms the strong supervised model baseline (DDL) by a significant margin (p<.05; Wilcoxon test). Our code is publicly available at https://github.com/jialin-yu/latent-sequence-paraphrase.
Keywords	Deep latent variable models ; Paraphrase generation ; Semi-supervised learning ; Natural language processing ; Deep learning ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	006 ; 004
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	KeAi Communications Co. Ltd.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing

Siyuan Fan / Xiangyan He / Zhongyi Zhu / Lu Chen / Yijun Zou / Zhonglin Chen / Jialin Yu / Weijun Chen / Hongzhi Guan / Jinmin Ma

Cell & Bioscience, Vol 13, Iss 1, Pp 1-

2023 Volume 15

Abstract: Abstract Background The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are different. This study aims to discover some specific and sensitive biomarkers to ... ...

Abstract	Abstract Background The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are different. This study aims to discover some specific and sensitive biomarkers to distinguish AE from IE at early stage to give specific treatments for good outcomes. Results We compared the host gene expression profiles and microbial diversities of cerebrospinal fluid (CSF) from 41 patients with IE and 18 patients with AE through meta-transcriptomic sequencing. Significant differences were found in host gene expression profiles and microbial diversities in CSF between patients with AE and patients with IE. The most significantly upregulated genes in patients with IE were enriched in pathways related with immune response such as neutrophil degranulation, antigen processing and presentation and adaptive immune system. In contrast, those upregulated genes in patients with AE were mainly involved in sensory organ development such as olfactory transduction, as well as synaptic transmission and signaling. Based on the differentially expressed genes, a classifier consisting of 5 host genes showed outstanding performance with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95. Conclusions This study provides a promising classifier and is the first to investigate transcriptomic signatures for differentiating AE from IE by using meta-transcriptomic next-generation sequencing technology.
Keywords	Infectious encephalitis ; Autoimmune encephalitis ; Transcriptomic signatures ; Cerebrospinal fluid ; Next-generation sequencing (NGS) ; Biotechnology ; TP248.13-248.65 ; Biology (General) ; QH301-705.5 ; Biochemistry ; QD415-436
Subject code	616
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Poly(ionic liquid)-Modified Metal Organic Framework for Carbon Dioxide Adsorption

Guangyuan Yang / Jialin Yu / Sanwen Peng / Kuang Sheng / Haining Zhang

Polymers, Vol 12, Iss 2, p

2020 Volume 370

Abstract: The design and synthesis of solid sorbents for effective carbon dioxide adsorption are essential for practical applications regarding carbon emissions. Herein, we report the synthesis of composite materials consisting of amine-functionalized imidazolium- ... ...

Abstract	The design and synthesis of solid sorbents for effective carbon dioxide adsorption are essential for practical applications regarding carbon emissions. Herein, we report the synthesis of composite materials consisting of amine-functionalized imidazolium-type poly(ionic liquid) (PIL) and metal organic frameworks (MOFs) through complexation of amino groups and metal ions. The carbon dioxide adsorption behavior of the synthesized composite materials was evaluated using the temperature-programmed desorption (TPD) technique. Benefiting from the large surface area of metal organic frameworks and high carbon dioxide diffusivity in ionic liquid moieties, the carbon dioxide adsorption capacity of the synthesized composite material reached 19.5 cm 3 ·g −1 , which is much higher than that of pristine metal organic frameworks (3.1 cm 3 ·g −1 ) under carbon dioxide partial pressure of 0.2 bar at 25 °C. The results demonstrate that the combination of functionalized poly(ionic liquid) with metal organic frameworks can be a promising solid sorbent for carbon dioxide adsorption.
Keywords	metal organic framework ; poly(ionic liquid) ; carbon dioxide ; adsorption ; imidazolium ; temperature-programmed desorption ; Organic chemistry ; QD241-441
Language	English
Publishing date	2020-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Catheter allotopia with totally implantable access port

Jialin Gu / Guoli Wei / Lingchang Li / Yi Ji / Jialin Yu / Canhong Hu / Jiege Huo

Clinical Case Reports, Vol 9, Iss 1, Pp 128-

A report of three cases and literature review

2021 Volume 132

Abstract: Abstract Early detection and treatment are critical for preventing catheter allotopia in the totally implantable access ports and whenever possible, the right internal jugular vein should be selected as the first puncture point. ...

Abstract	Abstract Early detection and treatment are critical for preventing catheter allotopia in the totally implantable access ports and whenever possible, the right internal jugular vein should be selected as the first puncture point.
Keywords	catheter allotopia ; left internal jugular vein ; totally implantable access port ; X‐ray radiography ; Medicine ; R ; Medicine (General) ; R5-920
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Wiley
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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