Drug-drug interactions between propofol and ART drugs: inhibiting neuronal activity by affecting glucose metabolism

Li, Sijun; Zheng, Yanqing; Qian, Long; Nong, Jianhong; Shao, Honghua; Li, Gang; Wu, Feng‐Yao

doi:10.21037/atm-23-255

Cited by 1 publication

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“…VTE can cause ischemia and hypoxia of local blood vessels that can result in glucose and oxygen deficiency in VECs, which may lead to energy metabolism disorder. If these are not corrected, cell damage can occur ( 22 ). It has also been reported that in energy metabolism disorder, the accumulation of large amounts of LA serves a key role in cell function and structural damage ( 9 ).…”

Section: Discussionmentioning

confidence: 99%

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Association between lactate metabolism‑related molecules and venous thromboembolism: A study based on bioinformatics and an in vitro model

Qin,

Chen,

Zhang

et al. 2023

Exp Ther Med

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Venous thromboembolism (VTE) is characterized by a high recurrence rate and adverse consequences, including high mortality. Damage to vascular endothelial cells (VECs) serves a key role in VTE and lactate (LA) metabolism is associated with VEC damage. However, the pathogenesis of VTE and the role of lactate metabolism-related molecules (LMRMs) remain unclear. Based on the GSE48000 dataset, the present study identified differentially expressed (DE-)LMRMs between healthy individuals and those with VTE. Thereafter, LMRMs were used to establish four machine learning models, namely, the random forest, support vector machine and generalized linear model (GLM) and eXtreme gradient boosting. To verify disease prediction efficiency of the models, nomograms, calibration curves, decision curve analyses and external datasets were used. The optimal machine learning model was used to predict genes involved in disease and an in vitro oxygen-glucose deprivation (OGD) model was used to detect the survival rate, LA levels and LMRM expression levels of VECs. A total of four DE-LMRMs, solute carrier family 16 member 1 (SLC16A1), SLC16A7, SLC16A8 and SLC5A12 were obtained and GLM was identified as the best performing model based on its ability to predict differential expression of the embigin, lactate dehydrogenase B, SLC16A1, SLC5A12 and SLC16A8 genes. Additionally, SLC16A1, SLC16A7 and SLC16A8 served key roles in VTE and the OGD model demonstrated a significant decrease in VEC survival rate as well as a significant increase and decrease in intracellular LA and SLC16A1 expression levels in VECs, respectively. Thus, LMRMs may be involved in VTE pathogenesis and be used to build accurate VTE prediction models. Further, it was hypothesized that the observed increase in intracellular LA levels in VECS was associated with the decrease in SLC16A1 expression. Therefore, SLC16A1 expression may be an essential target for VTE treatment.

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Section: Discussionmentioning

confidence: 99%

“…MTT analysis of VEC survival rate. VEC survival was analyzed as described by Li et al (22) using the MTT kit (cat. no.…”

Section: Data Acquisition Preprocessing and Screening Of De-lmrmsmentioning

confidence: 99%

Association between lactate metabolism‑related molecules and venous thromboembolism: A study based on bioinformatics and an in vitro model

Qin,

Chen,

Zhang

et al. 2023

Exp Ther Med

View full text Add to dashboard Cite

show abstract

Drug-drug interactions between propofol and ART drugs: inhibiting neuronal activity by affecting glucose metabolism

Cited by 1 publication

References 0 publications

Association between lactate metabolism‑related molecules and venous thromboembolism: A study based on bioinformatics and an in vitro model

Association between lactate metabolism‑related molecules and venous thromboembolism: A study based on bioinformatics and an in vitro model

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