High-normal serum carcinoembryonic antigen levels and increased risk of diabetic peripheral neuropathy in type 2 diabetes

Wang, Chunhua; Yu, Chao; Zhuang, Lei; Xu, Feng; Zhao, Lihua; Wang, Xiaohua; Ning, Li-yan; Zhang, Xiulin; Zhang, Dongmei; Wang, Xueqin; Su, Jianbin

doi:10.1186/s13098-022-00909-7

Cited by 3 publications

(1 citation statement)

References 47 publications

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“…TRAF6‐deficient mice develop severe osteopetrosis. [ 18 ] Conversely, microRNA‐125b negatively regulates TRAF6, leading to postmenopausal osteoporosis, [ 19 ] suggesting the complexity of well‐known downstream targets of PELLINO‐1 in bone metabolism.…”

Section: Discussionmentioning

confidence: 99%

Age‐Related Decrease in Pellino‐1 Expression Contributes to Osteoclast‐Mediated Bone Loss

Yoon,

Oh,

Lee

et al. 2024

Advanced Biology

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Aging‐related bone loss is driven by various biological factors, such as imbalanced bone metabolism from decreased osteoblast and increased osteoclast activities. Various transcriptional and post‐transcriptional factors increase osteoclast activity with aging; however, studies regarding the post‐translational regulators of osteoclast activity are still limited. The ubiquitin E3 ligase Pellino‐1 is a well‐known post‐translational regulator of inflammation. However, how Pellino‐1 expression regulation affects osteoclast differentiation remains unclear. This study determined that Pellino‐1 levels are reduced in bone marrow monocytes (BMMs) from 40‐week‐old mice compared to 4‐week‐old mice. Interestingly, conditional Knockout (cKO) of Pellino‐1 in 6‐week‐old mice resulted in decreased bone mass, reduced body size, and lower weight than in Pellino‐1 floxed mice; however, these differences are not observed in 20‐week‐old mice. The increased number of tartrate‐resistant acid phosphatase (TRAP)‐positive cells and serum levels of C‐terminal telopeptides of type I collagen, a marker of bone resorption, in 6‐week‐old Pellino‐1 cKO mice implied a connection between Pellino‐1 and the osteoclast population. Enhanced TRAP activity and upregulation of osteoclast genes in BMMs from the cKO mice indicate that Pellino‐1 deletion affects osteoclast differentiation, leading to decreased bone mass and heightened osteoclast activity. Thus, targeting Pellino‐1 could be a potential gene therapy for managing and preventing osteoporosis.

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Section: Discussionmentioning

confidence: 99%

Age‐Related Decrease in Pellino‐1 Expression Contributes to Osteoclast‐Mediated Bone Loss

Yoon,

Oh,

Lee

et al. 2024

Advanced Biology

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The Effect of Diabetic Ketoacidosis and Hyperosmolar Hyperglycemic on the Metabolic Tumor Markers: A Real-World Retrospective Study

Wen,

Xu,

Yuan

et al. 2024

DMSO

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Objective Serum tumor markers have been discovered to be elevated in individuals with diabetes mellitus (DM); however, their significance in diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemia (HHS) is unknown. We evaluated these indicators in the patients with DKA and HHS. Materials and Methods We retrospectively collected the laboratory data of 565 diabetic patients from Shanghai Pudong Hospital between Jan, 2019 and May, 2023, including 300 patients with type 2 diabetes mellitus (T2DM), 206 with DKA, and 59 with HHS. Serum tumor biomarkers and further clinical laboratory tests were compared among the three groups. Patients with conspicuous tumor evidence were excluded from the study. Results We found significantly higher levels of carbohydrate antigen 199 (CA199) in DKA (p<0.01), carcinoembryonic antigen (CEA), complex prostate specific antigen (CPSA) (p<0.01), prostate specific antigen (PSA) (p<0.05) in HHS, as well as the plasma lipid profile, iron, and electrolytes, in addition to decreased thyroid function, hepatic and renal function, and cardiac function (p<0.05). A Spearman correlational study revealed that osmolar levels were significantly positively correlated with myoglobin (MYO) and cardiac troponin I (cTNI), whereas serum iron concentration (r=0.520) was positively correlated with CEA levels in HHS. pH was negatively correlated with CA199 (r=−0.195), while HbA1c (r=0.22), globin (r=0.341), and total cholesterol (TC) (r=0.191) were positively correlated with elevated CA199 levels. Moreover, the multilinear regression investigation identified osmolarity as a significant determinant for CEA, as well as other parameters, and all proved to be proper predictors for CEA in HHS via ROC curve establishment. Conclusion Elevated CA199 levels in DKA were associated with acidosis, whereas HHS with elevated CEA levels may be related to iron homeostasis and could be predicted via the osmolar degree and other predictors.

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An ensemble model for predicting dyslipidemia using 3-years continuous physical examination data

Zhang,

Guo,

et al. 2024

Front. Physiol.

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BackgroundDyslipidemia has emerged as a significant clinical risk, with its associated complications, including atherosclerosis and ischemic cerebrovascular disease, presenting a grave threat to human well-being. Hence, it holds paramount importance to precisely predict the onset of dyslipidemia. This study aims to use ensemble technology to establish a machine learning model for the prediction of dyslipidemia.MethodsThis study included three consecutive years of physical examination data of 2,479 participants, and used the physical examination data of the first two years to predict whether the participants would develop dyslipidemia in the third year. Feature selection was conducted through statistical methods and the analysis of mutual information between features. Five machine learning models, including support vector machine (SVM), logistic regression (LR), random forest (RF), K nearest neighbor (KNN) and extreme gradient boosting (XGBoost), were utilized as base learners to construct the ensemble model. Area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate the model.ResultsExperimental results show that the ensemble model achieves superior performance across several metrics, achieving an AUC of 0.88 ± 0.01 (P < 0.001), surpassing the base learners by margins of 0.04 to 0.20. Calibration curves and DCA exhibited good predictive performance as well. Furthermore, this study explores the minimal necessary feature set for accurate prediction, finding that just the top 12 features were required for dependable outcomes. Among them, HbA1c and CEA are key indicators for model construction.ConclusionsOur results suggest that the proposed ensemble model has good predictive performance and has the potential to become an effective tool for personal health management.

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High-normal serum carcinoembryonic antigen levels and increased risk of diabetic peripheral neuropathy in type 2 diabetes

Cited by 3 publications

References 47 publications

Age‐Related Decrease in Pellino‐1 Expression Contributes to Osteoclast‐Mediated Bone Loss

Age‐Related Decrease in Pellino‐1 Expression Contributes to Osteoclast‐Mediated Bone Loss

The Effect of Diabetic Ketoacidosis and Hyperosmolar Hyperglycemic on the Metabolic Tumor Markers: A Real-World Retrospective Study

An ensemble model for predicting dyslipidemia using 3-years continuous physical examination data

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