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Articles by Xinxing Li
Traceable Organization of Food Quality- and Safety-Related Postharvest Evidence in Fresh Tomato Literature
Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Supporting Information Filename Description jfs70089-sup-0001-FigureS1-S2.docxWord 2007 document , 459.5 KB Figure S1: Illustration of evidence preview and human review.
Uncovering ectopic GC-like niches for tumor reactive lymphocyte priming in lung adenocarcinoma using Stereo-XCR-seq
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Abstract T/B cell receptors (T/BCR), coordinating antigen-targeting immune response, play crucial roles in anti-tumor immune response. Tracking T and B cell clonal evolution in situ at single-cell resolution is essential for understanding the adaptive immune responses.
By Xiaojuan Zhan, Yang Zhang, Zhong Liu, Chengwu Liu, Yanying Guo, Yi Liu, Wenwen Zhou, Yixin Yan, Hui Zeng, Xuan Dong, Xiaoyu Chen, Rong Ma, Fan Zhu, Xubin Zheng, Xinxing Li, Sen Hou, Zhidong Gao, Jinwen Yin, Francis Chan, Qin Wu, Senyi Deng, Yin Yao, Shengbao Suo, Chuanyu Liu, Longqi Liu, Xun Xu, Yong Hou, HaoRan Tao, Yuliang Dong, Tao Zeng, Hanyong Sun, Li Zuo, Hua Wang, Xin Zhe Liu, Zhifang Wu, Jingying Zhou, Zexian Zeng, Yu Feng, Mengye Huang, Yingqi Dong, Haohang Yang, Xinlei Ai
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Nature
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Dietary yacon concentrate reshapes microbial-metabolite crosstalk to inhibit colorectal cancer
Abstract Yacon concentrate, which is rich in fructan, phenolic compounds, and flavonoids, exhibits notable nutritional and antioxidant properties. This study explored the potential of New Zealand yacon concentrate to modulate the gut microbiota and host metabolism, alleviate inflammation, and enhance antitumor immunity. The anti-inflammatory and antitumor effects of yacon concentrate were evaluated in mouse models of dextran sulfate sodium (DSS)-induced colitis and colorectal cancer (CRC).
Decision-Centric Expert Systems for Quality Assurance and Food-Safety-Related Risk Management in Protected Tomato Production: Architectures, Data Fusion, and Validation Insights
X., S.Yuan, R.Yu, J.Li, L.Xue, and Y.Ma. 2026. “Decision-Centric Expert Systems for Quality Assurance and Food-Safety-Related Risk Management in Protected Tomato Production: Architectures, Data Fusion, and Validation Insights.” Journal of Food Safety46, no. 3: e70077. Li, https://doi.org/10.1111/jfs.70077. Data Availability Statement Data sharing not applicable to this article as no datasets were generated or analysed during the current study. References 2020.
A sequential deep learning model for predicting people with obesity in adults aged 18–64 using physical fitness variables
Abstract Health of people with obesity is a global concern. We developed an explainable sequential deep learning model using nationally representative physical fitness data to predict people with obesity and to identify the most influential predictors. We analyzed data from 204,334 adults collected between 2010 and 2023. A sequential neural network model was trained and evaluated using stratified 5-fold cross-validation.
Copy number alteration fingerprint predicts the clinical response of oxaliplatin-based chemotherapy in metastatic colorectal cancer
Abstract Oxaliplatin-based chemotherapy is a standard treatment for metastatic colorectal cancer (mCRC), yet accurate biomarkers to identify responders remain lacking. In this study, we developed and validated a genomic copy number alteration (CNA)-based biomarker to predict clinical response to oxaliplatin-based chemotherapy. A total of 297 samples were collected, and shallow sequencing was employed to extract CNA features.
An Adsorption Principle‐Based Meat Freshness Detection Method Using Gas Sensors
Disclosure This study did not involve any live animals or experimental animal procedures. All golden pomfret samples were commercially purchased as pre-slaughtered products from a licensed seafood supplier. The experimental work consisted solely of handling postharvest fish tissues, which falls outside the scope of institutional animal welfare regulations. According to the institutional guidelines of China Agricultural University, such studies fall outside the scope of animal ethics review.
A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry
1. Introduction Mutton is a nutritious food source, and the per capita consumption of mutton in China has risen to 1.5 kg over the past few years, exceeding the world average. The rapidly growing demand for mutton not only stimulates the development of the meat and sheep industry, but also raises the quality and safety standards for mutton. Live sheep transportation is an essential step in the meat production market.
Experimental Study on Fire Resistance of Geopolymer High-Performance Concrete Prefabricated Stairs
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Near‐Infrared Spectroscopy‐Based Chilled Fresh Lamb Quality Detection Using Machine Learning Algorithms
Conflicts of Interest The authors declare no conflicts of interest. References , , , , and . 2013. “Detection of Minced Beef Adulteration With Turkey Meat by UV–Vis, NIR and MIR Spectroscopy.” Food Science and Technology 53, no. 1: 225–232. https://doi.org/10.1016/j.lwt.2013.01.027. , , , et al. 2008. “Freshness Monitoring of Sea Bream (Sparus aurata) With a Potentiometric Sensor.” Food Chemistry 108, no. 2: 681–688. https://doi.org/10.1016/j.foodchem.2007.10.034. , , , and . 2013.
Neural network model for prediction of possible sarcopenic obesity using Korean national fitness award data (2010–2023) - Scientific Reports
Abstract Sarcopenic obesity (SO) is characterized by concomitant sarcopenia and obesity and presents a high risk of disability, morbidity, and mortality among older adults. However, predictions based on sequential neural network SO studies and the relationship between physical fitness factors and SO are lacking. This study aimed to develop a predictive model for SO in older adults by focusing on physical fitness factors.
MXene Synthesis and Carbon Capture Applications: Mini‐Review
MXenes, a class of two-dimensional transition metal carbides, nitrides, and carbonitrides, have garnered significant attention due to their remarkable potential for energy storage, electrocatalysis, and gas separation applications. The fabrication processes of MXene involve building up the MXene structure from constituent elements and the selective elimination of M−A bonds from the precursor MAX.
Application of artificial intelligence techniques in meat processing: A review
CONFLICT OF INTEREST STATEMENT The authors declare no conflicts of interest. REFERENCES , & (2014). Safe meat-handling knowledge, attitudes and practices of private and government meat processing plants' workers: Implications for future policy. Journal of Preventive Medicine and Hygiene, 55, 10–16. , & (2020). A machine learning approach for lamb meat quality assessment using FTIR spectra. IEEE Access, 8, 52385–52394. https://doi.org/10.1109/ACCESS.2020.2974623 , , , , , , & (2021).
Stacking ensemble learning for gas sensor‐based detection of salmon freshness and shelf life
CONFLICT OF INTEREST STATEMENT The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Supporting Information Filename Description jfpe14593-sup-0001-data.csvCSV document, 11.6 KB DATA S1: Data. REFERENCES (1996). Bagging predictors. Machine Learning, 24(2), 123–140. https://doi.org/10.1007/BF00058655 , , , , & (2006).
How Does Physical Activity Enhance the Subjective Well-Being of University Students? A Chain Mediation of Cognitive Reappraisal and Resilience
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Revolutionizing solar greenhouses: A lighting environment control system for renewable vegetable cultivation, empowered by roller shutter control
CONFLICT OF INTEREST STATEMENT The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. REFERENCES , , , , , , & (2019). Sustainable agriculture options for production, greenhouse gasses and pollution alleviation, and nutrient recycling in emerging and transitional nations—an overview. Journal of Cleaner Production, 242, 118319.
Physical Activity, Sedentary Behavior, Fruit and Vegetable Consumption, and Sarcopenia in Older Chinese Adults: A Cross-Sectional Study
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De‐noising method of aquatic product image with foreign matters based on improved wavelet transform and bilateral filter
Abstract Aiming at the strong spot noise caused by the reflection of meat slices in fish image with foreign matters that collected by ordinary camera or Single Lens Reflex (SLR) camera, we proposed an improved wavelet transform and bilateral filtering algorithm to reduce the noise of image.
Isomerization-induced fluorescence enhancement of two new viologen derivatives: mechanism insight and DFT calculations
Isomerization-induced fluorescence enhancement of two new viologen derivatives: mechanism insight and DFT calculations† Xiuping Yin,a Xinxing Li,ab Xuyi Li,a Malgorzata Biczysko, *ab Shourong Zhu, a Jiaqiang Xu a and Yue-Ling Bai *a Abstract The dark-colored viologen radical cations are unstable in air and easily fade, thus greatly limiting their applications.
Deciphering tissue heterogeneity from spatially resolved transcriptomics by the autoencoder-assisted graph convolutional neural network
Xinxing Li, Wendong Huang, Xuan Xu, Hong-Yu Zhang and Qianqian Shi* Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China Spatially resolved transcriptomics (SRT) provides an unprecedented opportunity to investigate the complex and heterogeneous tissue organization. However, it is challenging for a single model to learn an effective representation within and across spatial contexts.
Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification
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Single-Electron Transport and Detection of Graphene Quantum Dots
Open AccessArticle by Xinxing Li 1,2,†, Jinggao Sui 3,† and Jingyue Fang 1,* 1 School of Physics and Electronics, Central South University, Changsha 410083, China 2 Key Laboratory of Nanodevices, Suzhou Institute of Nano-Tech and Nano-Bionics, CAS, Suzhou 215213, China 3 National Innovation Institute of Defense Technology, Academy of Military Sciences PLA China, Beijing 100071, China * Author to whom correspondence should be addressed. † These authors contributed equally to this work.
LANTSA: Landmark-based transferable subspace analysis for single-cell and spatial transcriptomics
New Results Chuanchao Zhang, Lequn Wang, Xinxing Li, Wei-Feng Guo, Qianqian Shi, Luonan Chen doi: https://doi.org/10.1101/2022.03.13.484116 Abstract Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies provide new insights to understand tissue organization and biological function. Accurately capturing the relationships of samples (e.g., sequenced cells, spatial locations) will result in reliable and consistent outcomes in downstream analyses.
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