慢性伤口治疗中普遍存在的问题？

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糖尿病足

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蔡道章院长

Custom Mod Mega1

主任医师、教授、博导，南方医科大学第三附属医院（广东省骨科医院）院长

中德骨科伤口管理学校校长

广东省骨科研究院运动医学研究所所长

广东省内运动医学专业唯一的博士研究生导师

美国哈弗大学医学院骨科访问学者

专业特长处于省内领先、国内或国际先进水平以上

2018年获得“国之名医卓越建树”荣誉称号

2017年被评为全国卫生计生系统先进工作者、广东省医学领军人才

中国医师协会运动医师分会副会长

STCOT中国部运动医学分会副主任委员

广东省医学会关节外科分会主任委员

广东省医学会运动医学会分会名誉主任委员

独立承担过国家“863”课题，主持过10余项省、部级科研项目

多份专业杂志编委
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Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection 2025-08-20 00:00

Guadalupe Gutiérrez-Esparza 1,2,* ,†, Mireya Martínez-García 3,† , Manlio F. Márquez-Murillo 2 , Malinalli Brianza-Padilla 3 , Enrique Hernández-Lemus 4,5,* and Luis M. Amezcua-Guerra 3,*

1 “Researcher for Mexico” Program under SECIHTI, Secretariat of Sciences, Humanities, Technology, and Innovation, Mexico City 08400, Mexico

2 Division of Diagnostic and Treatment Services, National Institute of Cardiology Ignacio Chávez, Mexico City 04510, Mexico; 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。

3 Department of Immunology, National Institute of Cardiology Ignacio Chávez, Mexico City 04510, Mexico; 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (M.M.-G.); 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (M.B.-P.)

4 Computational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico

5 Center for Complexity Sciences, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico

*Correspondence: 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (G.G.-E.); 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (E.H.-L.); 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。 (L.M.A.-G.)

† These authors contributed equally to this work.

Academic Editor: Motoyuki Iemitsu Received: 11 February 2025 Revised: 3 March 2025 Accepted: 6 March 2025 Published: 17 March 2025

Citation: Gutiérrez-Esparza, G.; Martínez-García, M.; Márquez Murillo, M.F.; Brianza-Padilla, M.; Hernández-Lemus, E.; Amezcua Guerra, L.M. Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection. Nutrients 2025, 17, 1052. https://doi.org/ 10.3390/nu17061052

Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/)

Abstract: Background/Objectives: Uric acid is a key metabolic byproduct of purine degradation and plays a dual role in human health. At physiological levels, it acts as an antioxidant, protecting against oxidative stress. However, excessive uric acid can lead to hyperuricemia, contributing to conditions like gout, kidney stones, and cardiovascular diseases. Emerging evidence also links elevated uric acid levels with metabolic disorders, including hypertension and insulin resistance. Understanding its regulation is crucial for preventing associated health complications. Methods: This study, part of the Tlalpan 2020 project, aimed to predict uric acid levels using advanced machine learning algorithms. The dataset included clinical, anthropometric, lifestyle, and nutritional characteristics from a cohort in Mexico City. We applied Boosted Decision Trees (Boosted DTR), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Shapley Additive Explanations (SHAP) to identify the most relevant variables associated with hyperuricemia. Feature engineering techniques improved model performance, evaluated using Mean Squared Error (MSE), Root-Mean-Square Error (RMSE), and the coefficient of determination (R²). Results: Our study showed that XGBoost had the highest accuracy for anthropometric and clinical predictors, while CatBoost was the most effective at identifying nutritional risk factors. Distinct predictive profiles were observed between men and women. In men, uric acid levels were primarily influenced by renal function markers, lipid profiles, and hereditary predisposition to hyperuricemia, particularly paternal gout and diabetes. Diets rich in processed meats, high-fructose foods, and sugary drinks showed stronger associations with elevated uric acid levels. In women, metabolic and cardiovascular markers, family history of metabolic disorders, and lifestyle factors such as passive smoking and sleep quality were the main contributors. Additionally, while carbohydrate intake was more strongly associated with uric acid levels in women, fructose and sugary beverages had a greater impact in men. To enhance model robustness, a cross-feature selection approach was applied, integrating top features from multiple models, which further improved predictive accuracy, particularly in gender-specific analyses. Conclusions: These findings provide insights into the metabolic, nutritional characteristics, and lifestyle determinants of uric acid levels, supporting targeted public health strategies for hyperuricemia prevention.

Keywords: uric acid; regression-based machine learning; feature selection; feature engineering; Mexico City; Tlalpan 2020 cohort

CB-MNCs@ CS/HEC/GP promote wound healing in aged murine pressure ulcer model 2025-08-19 00:00

Zhi‑cheng Yang1,3, He Lin1 , Guo‑jun Liu2 , Hui Pan1 , Jun‑lu Zhu3 , Xiao‑hong Zhang3 , Feng Gao2 , Zhong Wang2 and Zhi‑hao Wang

*Correspondence: Zhi‑hao Wang 该Email地址已收到反垃圾邮件插件保护。要显示它您需要在浏览器中启用JavaScript。

1 Department of Geriatric Medicine & Laboratory of Gerontology and Anti‑Aging Research, Qilu Hospital of Shandong University, Jinan 250012, Shandong, China

2 Shandong Qilu Stem Cell Engineering Co., Ltd, Jinan 250012, Shandong, China

3 School of Nursing and Rehabilitation, Shandong University, Jinan 250012, Shandong, China

© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Abstract

Background Non-healing pressure ulcers impose heavy burdens on patients and clinicians. Cord blood mononu‑ clear cells (CB-MNCs) are a novel type of tissue repair seed cells. However, their clinical application is restricted by low retention and survival rates post-transplantation. This study aims to investigate the role of thermo-sensitive chitosan/ hydroxyethyl cellulose/glycerophosphate (CS/HEC/GP) hydrogel encapsulated CB-MNCs in pressure ulcer wound

Methods Pressure ulcers were induced on the backs of aged mice. After construction and validation of the charac‑ terization of thermo-sensitive CS/HEC/GP hydrogel, CB-MNCs are encapsulated in the hydrogel, called CB-MNCs@ CS/HEC/GP which was locally applied to the mouse wounds. Mouse skin tissues were harvested for histological and molecular biology analyses.

Results CB-MNCs@CS/HEC/GP therapy accelerated pressure ulcer wound healing, attenuated inflammatory responses, promoted cell proliferation, angiogenesis, and collagen synthesis. Further investigation revealed that CB MNCs@CS/HEC/GP exerted therapeutic effects by promoting changes in cell types, including fibroblasts, endothelial cells, keratinocytes, and smooth muscle cells.

Conclusion CB-MNCs@CS/HEC/GP enhanced the delivery efficiency of CB-MNCs, preserved the cell viability, and contributed to pressure ulcer wound healing. Thus, CB-MNCs@CS/HEC/GP represents a novel therapeutic approach for skin regeneration of chronic wounds.

Keywords Wound healing, Aged, Pressure ulcers, Cord blood mononuclear cells, Thermo-sensitive hydrogel
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慢性伤口治疗中普遍存在的问题？

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12 10月 2019

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Author : 伤口世界

慢性伤口治疗中普遍存在的问题？

原创：卢魁

慢性伤口治疗中普遍是什么问题困扰着患者呢？

问题一：悲观思想，认为患了不治之症
事实上，精神压力和疾病之间，存在着一条明显的纽带。对疾病切勿忧虑恐惧，悲观失望，郁郁寡欢，闷闷不乐，要学会自我克制、自我调节，要心胸宽广，豁达大度，树立战胜疾病的信念，要有毅力和勇气。
问题二:
轻信广告和传言，相信“神药”
慢性伤口是一种长期慢性疾病，其中很多疾病都是没有办法完全根治的，因此必须要有长期和疾病做斗争的思想认识。切勿相信广告所说的秘方、神药，以免上当受骗，耽误病情。
问题三：
为什么症状控制后仍需要长期观察预防复发？
到目前为止，慢性伤口大部分尚不能根治，需要长期治疗让伤口愈合。症状减轻仅意味着病情得到控制，并未完全治愈。体内的病变可能并没有真正停止，停药后或受到外界刺激仍会复发。只有改变生活习惯、合理功能锻炼、合理使用控制病情的药物(慢作用药物)，才能减缓或阻止上述过程的进展。

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2019广东省医疗行业协会伤口管理分会年会

扫一扫了解详情:

2019年6月15日中国广州
主办单位：广东省医疗行业协会伤口管理分会

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