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1. The Relationship Between Computerized Face and Tongue Image Segmentation and Metabolic Parameters in Patients with Type 2 Diabetes Based on Machine Learning.

Author

Wen, Song, Li, Yanyan, Xu, Chenglin, Jin, Jianlan, Xu, Zhimin, Yuan, Yue, Chen, Lijiao, Ren, Yishu, Gong, Min, Wang, Congcong, Dong, Meiyuan, Zhou, Yingfan, Yuan, Xinlu, Li, Fufeng, and Zhou, Ligang

Subjects
BLOOD cell count, RECEIVER operating characteristic curves, LEUKOCYTES, TYPE 2 diabetes, GLYCOSYLATED hemoglobin
Abstract

We aim to examine and reestablish the correlational and linear regression relationships, as well as the predictive value, between the significant facial and tongue features and the metabolic parameters in type 2 diabetes mellitus (T2DM). Materials and Methods: From March to May 2024, we studied 269 patients with T2DM in the endocrinology department of Shanghai Pudong Hospital. The patients' facial and tongue characteristics were sampling by a tongue imaging device equipped with artificial intelligence (AI) (XiMaLife, Sinology, China) of automated and advanced machine learning algorithms. Then, the imaging features were examined in relation to the blood examination. Results: Multiple facial and tongue features, as well as dimensional facial and tongue color parameters, were significantly correlated with glycated hemoglobin A1c (HbA1c) (r < 0.3, p < 0.05), glycated albumin (GA) (− 0.20 < 0.30, p < 0.05), C-peptide (− 0.20.20, p < 0.05), plasma insulin (r < 0.30, p < 0.05), fasting plasma glucose (FPG) (r < 0.3, p < 0.05), significant hepatic and renal function indicators (− 0.30 < r < 0.20, p< 0.05), cardiac injury markers (− 0.30 < r < 0.30, p < 0.05), tumor markers (− 0.5 < r < 0.5, p < 0.05), thyroid function (− 0.15 < r < 0.55, p < 0.05), and blood cell count, including white blood cells (r < 0.2, p < 0.05), and hemoglobin (Hb) (− 0.30 < r < 0.3, 0.0001. The correlational results demonstrated that the tongue's characteristics and signs may be linked with the dynamic of the metabolic status of T2DM. In order to examine the causal relationships, we performed linear regression analyses, which revealed that various facial and tongue imaging parameters partially determined the metabolic indicators. The predictive value of imaging features was evaluated by receiver operating characteristic curve (ROC) to assess metabolic status in T2DM. Conclusion: This study demonstrated that metabolic status, renal and hepatic, cardiac, and thyroid function, the proportion of blood cells, and Hb in T2DM were intimately associated with facial and tongue features. The precise analysis of facial and tongue features through AI and advanced machine learning could be used to predict T2DM's conditions and progression. [ABSTRACT FROM AUTHOR]

Published
2024
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2. The Relationship Between Computerized Face and Tongue Image Segmentation and Metabolic Parameters in Patients with Type 2 Diabetes Based on Machine Learning

Author

Wen,Song, Li,Yanyan, Xu,Chenglin, Jin,Jianlan, Xu,Zhimin, Yuan,Yue, Chen,Lijiao, Ren,Yishu, Gong,Min, Wang,Congcong, Dong,Meiyuan, Zhou,Yingfan, Yuan,Xinlu, Li,Fufeng, Zhou,Ligang, Wen,Song, Li,Yanyan, Xu,Chenglin, Jin,Jianlan, Xu,Zhimin, Yuan,Yue, Chen,Lijiao, Ren,Yishu, Gong,Min, Wang,Congcong, Dong,Meiyuan, Zhou,Yingfan, Yuan,Xinlu, Li,Fufeng, and Zhou,Ligang

Abstract

Song Wen,1,2 Yanyan Li,1 Chenglin Xu,1 Jianlan Jin,1 Zhimin Xu,1 Yue Yuan,1 Lijiao Chen,1 Yishu Ren,1 Min Gong,1 Congcong Wang,1 Meiyuan Dong,1 Yingfan Zhou,3 Xinlu Yuan,1 Fufeng Li,4 Ligang Zhou1,2,5 1Department of Endocrinology, Shanghai Pudong Hospital, Fudan University, Pudong Medical Center, Shanghai, 201399, People’s Republic of China; 2Fudan Zhangjiang Institute, Fudan University, Shanghai, 201203, People’s Republic of China; 3Medical School of Tianjin University, Tianjin, 300072, People’s Republic of China; 4Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China; 5Shanghai Key Laboratory of Vascular Lesions Regulation and Remodeling, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, People’s Republic of ChinaCorrespondence: Ligang Zhou, Department of Endocrinology, Shanghai Pudong Hospital, Fudan University, Pudong Medical Center, Shanghai, 201399, People’s Republic of China, Tel +8613611927616, Email zhouligang1n1@163.com Fufeng Li, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China, Email li_fufeng@aliyun.comObjective: We aim to examine and reestablish the correlational and linear regression relationships, as well as the predictive value, between the significant facial and tongue features and the metabolic parameters in type 2 diabetes mellitus (T2DM).Materials and Methods: From March to May 2024, we studied 269 patients with T2DM in the endocrinology department of Shanghai Pudong Hospital. The patients’ facial and tongue characteristics were sampling by a tongue imaging device equipped with artificial intelligence (AI) (XiMaLife, Sinology, China) of automated and advanced machine learning algorithms. Then, the imaging features were examined in relation to the blood examination.Results: Multiple facial and tongue features, as well as dimensional facial and tongue color parameters, were significantly correlated with glycated he

Published
2024

3. Lived experiences of online harm amongst marginalized and vulnerable individuals in support-seeking communities on Reddit

Author

Zhou, Yingfan, Squicciarini, Anna, Rajtmajer, Sarah, Zhou, Yingfan, Squicciarini, Anna, and Rajtmajer, Sarah

Abstract

Online communities can serve as meaningful sources of social support, particularly for marginalized and vulnerable groups. Disclosure of personal information facilitates integration into online communities but may also expose individuals to harm, including cyberbullying and manipulation. To better understand negative user experiences resulting from self-disclosure in online conversations, we interviewed 25 participants from target populations on Reddit. Through thematic analysis, we outline the harm they experience, including damage to self- and group identities. We find that encountering online harm can worsen offline adversity. We discuss how users protect themselves and recover from harm in the context of current platform affordances, highlighting ongoing challenges. Finally, we explore design implications for a community-driven, bottom-up approach to enhance user well-being and safety.

Published
2023

4. Proteína 3 contendo um domínio NACHT, porção C-terminal rica em repetições de leucina e de domínio pirina e LL-37: valor prognóstico de novos biomarcadores em pneumonia adquirida na comunidade

Author

Zhu, Chuanan, Zhou, Yingfan, Zhu, Jiabin, Liu, Ye, and Sun, Mengyi

Subjects
Male, Time Factors, Community-acquired pneumonia, Prognóstico, Kaplan-Meier Estimate, Leucine-Rich Repeat Proteins, Risk Assessment, Predictive Value of Tests, Reference Values, Risk Factors, Cathelicidins, Natriuretic Peptide, Brain, NLR Family, Pyrin Domain-Containing 3 Protein, Humans, Prospective Studies, Prospective study, Aged, integumentary system, Pneumonia adquirida na comunidade, Proteins, Pneumonia, Middle Aged, Pyrin, Prognosis, Estudo prospectivo, Peptide Fragments, Community-Acquired Infections, Biomarcadores, Logistic Models, Editorial, Case-Control Studies, Multivariate Analysis, Original Article, Female, Biomarkers, Antimicrobial Cationic Peptides
Abstract

RESUMO Objetivo Este estudo teve como objetivo determinar os níveis séricos de proteína 3 contendo um domínio NACHT, porção C-terminal rica em repetições de leucina e de domínio pirina (NLRP3) e catelicidina LL-37, bem como investigar sua importância prognóstica em pneumonia adquirida na comunidade (PAC). Métodos Este estudo prospectivo incluiu 76 pacientes com PAC. Foram obtidos dados demográficos e características clínicas. Os níveis séricos de NLRP3 e LL-37 foram determinados por meio do teste ELISA. A correlação entre NLRP3 e LL-37 foi estimada por intermédio da análise de Spearman. A associação entre NLRP3 e LL-37 com 30 dias de taxa de sobrevida e de mortalidade foi avaliada pela curva de Kaplan-Meier e análise de regressão logística. Resultados Os níveis séricos de NLRP3 estavam elevados, enquanto os níveis de LL-37 apresentaram redução significativa em pacientes com PAC grave. Observou-se correlação significativa entre os níveis séricos de NLRP3 e LL-37 em pacientes com PAC. Pacientes com níveis elevados de NLRP3 e níveis reduzidos de LL-37 exibiram maior taxa de sobrevida em 30 dias e de mortalidade quando comparados com aqueles com níveis inferiores de NLRP3 e LL-37. Conclusões Pacientes com PAC grave tendem a apresentar níveis séricos elevados de NLRP3 e níveis reduzidos de LL-37, o que pode ser utilizado como um potencial biomarcador prognóstico. ABSTRACT Objective This study aimed to determine the serum levels of NACHT, Leucine-rich repeat (LRR), and Pyrin (PYD) domains-containing Protein 3 (NLRP3) and cathelicidin LL-37, and investigate their prognostic significance in community-acquired pneumonia (CAP). Methods The sample of this prospective study was composed of 76 consecutive patients with CAP. Demographic data and clinical characteristics were collected. Serum levels of NLRP3 and LL-37 were determined by ELISA. Spearman’s analysis was used to evaluate the correlation between NLRP3 and LL-37. Association of NLRP3 and LL-37 with 30-day survival and mortality rates was assessed using the Kaplan-Meier curve and logistic regression analysis. Results Serum NLRP3 significantly increased whereas serum LL-37 significantly decreased in patients with severe CAP. Significant correlation was observed between serum NLRP3 and LL-37 in CAP patients. Patients with higher levels of NLRP3 and lower levels of LL-37 showed lower 30-day survival rate and higher mortality compared with those with lower NLRP3 and higher LL-37 levels. Conclusion Severe CAP patients tend to present higher serum NLRP3 and lower serum LL-37, which might serve as potential biomarkers for CAP prognosis.

Published
2019

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