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Article ; Online: Construction and Signal Feature Processing of Gold Nanobiosensors Based on the Internet of Things.

Chen, Ling

2022 Volume 2022, Page(s) 1432266

Abstract: With the continuous development of signal amplification technology and nanotechnology, more and more electrochemical sensors combining nanotechnology and signal amplification technology are applied in the field of analysis. In this paper, combined with ... ...

Abstract	With the continuous development of signal amplification technology and nanotechnology, more and more electrochemical sensors combining nanotechnology and signal amplification technology are applied in the field of analysis. In this paper, combined with the Internet of Things technology, the construction of gold nanobiosensors and signal characteristic processing are carried out. In this paper, a T-rich DNA probe is used as the recognition element, modified on the electrode surface, combined with DNA-modified nanogold particle amplification technology, and the electroactive substance peg amine is used as the signal molecule to develop a highly sensitive electrochemical biosensor for the detection of melamine. The sensor has good specificity and sensitivity, and the detection limit is as low as 0.5 NM. In addition, by combining sensors with the Internet of Things technology, melamine monitoring and signal characteristic processing can be carried out in real time. This model can easily achieve the purpose of accurate and quantitative analysis of melamine toxins and can be effective for food safety.
MeSH term(s)	Biosensing Techniques ; Electrochemical Techniques ; Gold/chemistry ; Humans ; Internet of Things ; Limit of Detection ; Metal Nanoparticles/chemistry
Chemical Substances	Gold (7440-57-5)
Language	English
Publishing date	2022-01-10
Publishing country	England
Document type	Journal Article ; Retracted Publication
ZDB-ID	2545054-2
ISSN	2040-2309 ; 2040-2295
ISSN (online)	2040-2309
ISSN	2040-2295
DOI	10.1155/2022/1432266
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A Spectral Method for Identifiable Grade of Membership Analysis with Binary Responses.

Chen, Ling / Gu, Yuqi

Psychometrika

2024

Abstract: Grade of membership (GoM) models are popular individual-level mixture models for multivariate categorical data. GoM allows each subject to have mixed memberships in multiple extreme latent profiles. Therefore, GoM models have a richer modeling capacity ... ...

Abstract	Grade of membership (GoM) models are popular individual-level mixture models for multivariate categorical data. GoM allows each subject to have mixed memberships in multiple extreme latent profiles. Therefore, GoM models have a richer modeling capacity than latent class models that restrict each subject to belong to a single profile. The flexibility of GoM comes at the cost of more challenging identifiability and estimation problems. In this work, we propose a singular value decomposition (SVD)-based spectral approach to GoM analysis with multivariate binary responses. Our approach hinges on the observation that the expectation of the data matrix has a low-rank decomposition under a GoM model. For identifiability, we develop sufficient and almost necessary conditions for a notion of expectation identifiability. For estimation, we extract only a few leading singular vectors of the observed data matrix and exploit the simplex geometry of these vectors to estimate the mixed membership scores and other parameters. We also establish the consistency of our estimator in the double-asymptotic regime where both the number of subjects and the number of items grow to infinity. Our spectral method has a huge computational advantage over Bayesian or likelihood-based methods and is scalable to large-scale and high-dimensional data. Extensive simulation studies demonstrate the superior efficiency and accuracy of our method. We also illustrate our method by applying it to a personality test dataset.
Language	English
Publishing date	2024-02-15
Publishing country	United States
Document type	Journal Article
ZDB-ID	209479-4
ISSN	1860-0980 ; 0033-3123
ISSN (online)	1860-0980
ISSN	0033-3123
DOI	10.1007/s11336-024-09951-y
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Article ; Online: The Functional Circular RNA Screening via RfxCas13d/BSJ-gRNA System.

Wu, Hao / Chen, Ling-Ling

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

2024 Volume 2765, Page(s) 173–191

Abstract: Although discovered decades ago, functions of circular RNAs (circRNAs) produced from exon(s) back-splicing of pre-mRNAs have only been unveiled recently. As circRNAs share overlapping sequences with their cognate linear RNAs, except for the back-splicing ...

Abstract	Although discovered decades ago, functions of circular RNAs (circRNAs) produced from exon(s) back-splicing of pre-mRNAs have only been unveiled recently. As circRNAs share overlapping sequences with their cognate linear RNAs, except for the back-splicing junction sites, it is difficult to distinguish circRNAs from cognate mRNAs in functional studies. In this chapter, we describe a programmable method for the large-scale functional circRNA screening based on the RNA-guided, RNA-targeting CRISPR-Cas13 (RfxCas13d) system. This method can be applied both in vivo and in cell to explore highly expressed circRNAs that may influence cell growth, either under natural conditions or in response to environmental stimulation, without disturbing cognate linear mRNAs.
MeSH term(s)	RNA, Circular ; RNA, Guide, CRISPR-Cas Systems ; RNA, Untranslated ; RNA/genetics ; Cell Cycle ; RNA, Messenger
Chemical Substances	RNA, Circular ; RNA, Guide, CRISPR-Cas Systems ; RNA, Untranslated ; RNA (63231-63-0) ; RNA, Messenger
Language	English
Publishing date	2024-02-21
Publishing country	United States
Document type	Journal Article
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-0716-3678-7_10
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Article ; Online: Is it caffeine? Coffee consumption and future risk of type 2 diabetes among women with a history of gestational diabetes.

Chen, Ling-Wei

The American journal of clinical nutrition

2022 Volume 116, Issue 6, Page(s) 1468–1469

MeSH term(s)	Pregnancy ; Female ; Humans ; Coffee ; Caffeine/pharmacology ; Diabetes, Gestational ; Prospective Studies ; Diabetes Mellitus, Type 2/epidemiology ; Diabetes Mellitus, Type 2/etiology ; Risk Factors
Chemical Substances	Coffee ; Caffeine (3G6A5W338E)
Language	English
Publishing date	2022-11-15
Publishing country	United States
Document type	Editorial ; Research Support, Non-U.S. Gov't ; Comment
ZDB-ID	280048-2
ISSN	1938-3207 ; 0002-9165
ISSN (online)	1938-3207
ISSN	0002-9165
DOI	10.1093/ajcn/nqac275
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Article ; Online: Towards higher-resolution and in vivo understanding of lncRNA biogenesis and function.

Chen, Ling-Ling

Nature methods

2022 Volume 19, Issue 10, Page(s) 1152–1155

MeSH term(s)	Cell Proliferation ; Gene Expression Regulation, Neoplastic ; RNA, Long Noncoding/genetics ; Signal Transduction
Chemical Substances	RNA, Long Noncoding
Language	English
Publishing date	2022-09-25
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2169522-2
ISSN	1548-7105 ; 1548-7091
ISSN (online)	1548-7105
ISSN	1548-7091
DOI	10.1038/s41592-022-01626-9
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Article ; Online: Identification of Senescence-Related Biomarkers and Regulatory Networks in Intracerebral Hemorrhage.

Wang, Yan / Chen, Ling

The neurologist

2024

Abstract: Objectives: Intracerebral hemorrhage (ICH) is a severe neurological disorder with substantial societal implications. Cellular senescence plays a critical role in ICH pathogenesis. This study aims to identify senescence-related biomarkers in ICH for ... ...

Abstract	Objectives: Intracerebral hemorrhage (ICH) is a severe neurological disorder with substantial societal implications. Cellular senescence plays a critical role in ICH pathogenesis. This study aims to identify senescence-related biomarkers in ICH for diagnostic and therapeutic purposes. Methods: Raw data from GSE24265 in Gene Expression Omnibus was downloaded. Senescence-related genes were acquired from CellAge. Differential gene analysis was done between patients with ICH and controls. The intersection of ICH differentially expressed genes and senescence-related genes for senescence-related ICH genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed. Protein-protein interaction network was constructed through the Search Tool for the Retrieval of Interacting Genes. Single sample gene set enrichment analysis was done for immune cell infiltration and function evaluation in control and ICH groups. miRWalk2.0 database was used for microRNA predictions targeting ICH biomarkers. Transcriptional regulatory relationships unraveled by sentence-based text mining database was employed to predict transcription factors regulating identified biomarkers. Results: Thirteen senescence-related ICH genes were identified. They were primarily enriched in the positive regulation of angiogenesis and the Advanced Glycation End Product -Receptor for AGE signaling pathway in diabetic complications. Validation in the GSE149317 data set and receiver operating characteristic analysis highlighted Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 as potential ICH biomarkers. Single sample gene set enrichment analysis revealed increased Type 2 T helper cell 2_cells, Treg cells, and immune functions like Antigen-presenting cells_co_stimulation in patients with ICH. Fourteen microRNA, including has-miR-6728-3p, were predicted to regulate these biomarkers. transcription factors such as PPARG, RARA, HMGA1, and NFKB1 were identified as potential regulators of the ICH biomarkers. Conclusion: Caveolin 1, C-X-C Motif Chemokine Ligand 1, ETS proto-oncogene 1, transcription factor, and Serpin Family E Member 1 may serve as valuable biomarkers in ICH. Targeting these genes could contribute to ICH prevention and treatment.
Language	English
Publishing date	2024-01-22
Publishing country	United States
Document type	Journal Article
ZDB-ID	1361380-7
ISSN	2331-2637 ; 1074-7931
ISSN (online)	2331-2637
ISSN	1074-7931
DOI	10.1097/NRL.0000000000000548
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Article ; Online: The analyticity of double complex variables functions

GENG Yongcai / CHEN Ling

Journal of Shanghai Normal University (Natural Sciences), Vol 52, Iss 3, Pp 323-

2023 Volume 326

Abstract: Due to the complexity of complex functions， many textbooks focus on the nature of univariate variable complex functions， but just simply mention multi-complex variables functions. However， there is no specific derivation for the analyticity of ... ...

Abstract	Due to the complexity of complex functions， many textbooks focus on the nature of univariate variable complex functions， but just simply mention multi-complex variables functions. However， there is no specific derivation for the analyticity of multivariate functions， such as the Cauchy Riemann condition. We will consider the analyticity of the double complex variables function. The methods of mathematical analysis and univariate variable complex functions will be applied to study the aforementioned question.
Keywords	double complex variables function ; analytic function ; cauchy-riemann condition ; Science (General) ; Q1-390
Language	English
Publishing date	2023-06-01T00:00:00Z
Publisher	Academic Journals Center of Shanghai Normal University
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Utilization of Traditional Chinese Medicine Analgesic and Delivery-Aiding Patch in Doula-Assisted Deliveries: Impact on Reducing Cesarean Section Rates.

Zhou, Jinmei / Chen, Ling

Alternative therapies in health and medicine

2023

Abstract: Objective: This study aimed to evaluate the impact of traditional Chinese medicine analgesic-assisted delivery patches on doula-assisted childbirth.: Methods: We conducted a comparative analysis of two groups of puerperae. The control group consisted ...

Abstract	Objective: This study aimed to evaluate the impact of traditional Chinese medicine analgesic-assisted delivery patches on doula-assisted childbirth. Methods: We conducted a comparative analysis of two groups of puerperae. The control group consisted of 120 individuals who underwent routine delivery at Haian Hospital of Traditional Chinese Medicine between May 2019 and May 2020. The observation group included 120 puerperae who gave birth between June 2020 and June 2021, and they utilized Chinese medicine analgesic and childbirth-assisting patches in combination with doula-assisted childbirth. We compared both groups concerning childbirth outcomes, duration of labor, pain intensity, and postpartum hemorrhage. Results: In the observation group, the cesarean section rate was 12.50%, significantly lower than the 25.83% rate in the control group (P < .05). Additionally, the observation group exhibited shorter first and second labor times and total labor time compared to the control group (P < .05). Moreover, the NRS scores in the observation group were lower during both the latent and active phases of labor (P < .05). Furthermore, the observation group experienced reduced postpartum bleeding at 2 hours and 24 hours after delivery compared to the control group (P < .05). Conclusions: The application of traditional Chinese medicine analgesics and delivery-aiding patches in doula-assisted childbirth significantly reduces the cesarean section rate. It contributes to improved childbirth outcomes, shortened labor durations, alleviation of labor pain, and reduced postpartum hemorrhage.
Language	English
Publishing date	2023-11-17
Publishing country	United States
Document type	Journal Article
ZDB-ID	1225073-9
ISSN	1078-6791
ISSN	1078-6791
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Article ; Online: Reply - Letter to the editor: Longitudinal trajectories of dietary quality and cognitive performance in older adults: Results from a 6-year cohort study.

Chen, Ling-Wei / Chen, Yen-Ching

Clinical nutrition (Edinburgh, Scotland)

2023 Volume 42, Issue 8, Page(s) 1535–1536

MeSH term(s)	Humans ; Aged ; Cohort Studies ; Diet ; Longitudinal Studies ; Cognition
Language	English
Publishing date	2023-06-07
Publishing country	England
Document type	Letter ; Comment
ZDB-ID	604812-2
ISSN	1532-1983 ; 0261-5614
ISSN (online)	1532-1983
ISSN	0261-5614
DOI	10.1016/j.clnu.2023.06.006
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Article ; Online: Affinity Uncertainty-Based Hard Negative Mining in Graph Contrastive Learning.

Niu, Chaoxi / Pang, Guansong / Chen, Ling

IEEE transactions on neural networks and learning systems

2024 Volume PP

Abstract: Hard negative mining has shown effective in enhancing self-supervised contrastive learning (CL) on diverse data types, including graph CL (GCL). The existing hardness-aware CL methods typically treat negative instances that are most similar to the anchor ...

Abstract	Hard negative mining has shown effective in enhancing self-supervised contrastive learning (CL) on diverse data types, including graph CL (GCL). The existing hardness-aware CL methods typically treat negative instances that are most similar to the anchor instance as hard negatives, which helps improve the CL performance, especially on image data. However, this approach often fails to identify the hard negatives but leads to many false negatives on graph data. This is mainly due to that the learned graph representations are not sufficiently discriminative due to oversmooth representations and/or non-independent and identically distributed (non-i.i.d.) issues in graph data. To tackle this problem, this article proposes a novel approach that builds a discriminative model on collective affinity information (i.e., two sets of pairwise affinities between the negative instances and the anchor instance) to mine hard negatives in GCL. In particular, the proposed approach evaluates how confident/uncertain the discriminative model is about the affinity of each negative instance to an anchor instance to determine its hardness weight relative to the anchor instance. This uncertainty information is then incorporated into the existing GCL loss functions via a weighting term to enhance their performance. The enhanced GCL is theoretically grounded that the resulting GCL loss is equivalent to a triplet loss with an adaptive margin being exponentially proportional to the learned uncertainty of each negative instance. Extensive experiments on ten graph datasets show that our approach does the following: 1) consistently enhances different state-of-the-art (SOTA) GCL methods in both graph and node classification tasks and 2) significantly improves their robustness against adversarial attacks. Code is available at https://github.com/mala-lab/AUGCL.
Language	English
Publishing date	2024-01-08
Publishing country	United States
Document type	Journal Article
ISSN	2162-2388
ISSN (online)	2162-2388
DOI	10.1109/TNNLS.2023.3339770
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