Deep neural network for estimating low density lipoprotein cholesterol

Lee, Taesic; Kim, Juwon; Uh, Young; Lee, Hyunju

doi:10.1016/j.cca.2018.11.022

Cited by 26 publications

(36 citation statements)

References 12 publications

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“…The total cholesterol, HDL-cholesterol, and LDL-cholesterol dataset were analyzed using the modular DPE system (Roche Diagnostics, Basel, Switzerland). 54 …”

Section: Methodsmentioning

confidence: 99%

COVID-19-activated SREBP2 disturbs cholesterol biosynthesis and leads to cytokine storm

Lee

Ahn

Park

et al. 2020

Sig Transduct Target Ther

119

106

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Sterol regulatory element binding protein-2 (SREBP-2) is activated by cytokines or pathogen, such as virus or bacteria, but its association with diminished cholesterol levels in COVID-19 patients is unknown. Here, we evaluated SREBP-2 activation in peripheral blood mononuclear cells of COVID-19 patients and verified the function of SREBP-2 in COVID-19. Intriguingly, we report the first observation of SREBP-2 C-terminal fragment in COVID-19 patients’ blood and propose SREBP-2 C-terminal fragment as an indicator for determining severity. We confirmed that SREBP-2-induced cholesterol biosynthesis was suppressed by Sestrin-1 and PCSK9 expression, while the SREBP-2-induced inflammatory responses was upregulated in COVID-19 ICU patients. Using an infectious disease mouse model, inhibitors of SREBP-2 and NF-κB suppressed cytokine storms caused by viral infection and prevented pulmonary damages. These results collectively suggest that SREBP-2 can serve as an indicator for severity diagnosis and therapeutic target for preventing cytokine storm and lung damage in severe COVID-19 patients.

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“…The total cholesterol, HDL-cholesterol, and LDL-cholesterol dataset were analyzed using the modular DPE system (Roche Diagnostics, Basel, Switzerland). 54 …”

Section: Methodsmentioning

confidence: 99%

COVID-19-activated SREBP2 disturbs cholesterol biosynthesis and leads to cytokine storm

Lee

Ahn

Park

et al. 2020

Sig Transduct Target Ther

119

106

View full text Add to dashboard Cite

show abstract

“…If a patient record contained multiple test results of the collection during the study period, only the first result was chosen in the dataset. The total cholesterol, triglyceride, HDL-C, and LDL-C for the Korea hospital dataset were analyzed using the modular DPE system (Roche Diagnostics, Basel, Switzerland) [1] . The lipoprotein subfraction test was performed by using the Lipoprint LDL System (Quantimetrix, Redondo Beach, CA, USA) [1] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…The total cholesterol, triglyceride, HDL-C, and LDL-C for the Korea hospital dataset were analyzed using the modular DPE system (Roche Diagnostics, Basel, Switzerland) [1] . The lipoprotein subfraction test was performed by using the Lipoprint LDL System (Quantimetrix, Redondo Beach, CA, USA) [1] . The Lipoprint system utilizes polyacrylamide gel electrophoresis to separate the various lipoprotein subfractions on the basis of particle size as VLDL band, three mid-bands [MID-C = VLDL remnants, MID-B = large intermediate density lipoprotein (IDL), and MID-A = small IDL], and seven LDL bands and an HDL band.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…The Lipoprint system utilizes polyacrylamide gel electrophoresis to separate the various lipoprotein subfractions on the basis of particle size as VLDL band, three mid-bands [MID-C = VLDL remnants, MID-B = large intermediate density lipoprotein (IDL), and MID-A = small IDL], and seven LDL bands and an HDL band. LDL-1 and -2 are defined as large LDL subfractions whereas LDL-3, 4, 5, 6, and -7 are defined as small LDL subfractions [1] , [3] , [4] .…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

“…Medians of total cholesterol, HDL cholesterol, and triglyceride in Korea hospital data were 165, 37, 103, respectively. Data source location KNHANES (Seoul, South Korea) WSCH (Wonju, South Korea) Data accessibilityThe KNHANES data is publicly available at https://knhanes.cdc.go.kr/knhanes/eng/index.do.Related research articleTaesic Lee, Juwon Kim, Young Uh, Hyunju Lee, Deep neural network for estimating low density lipoprotein cholesterol (Clin Chim Acta; in press) [1].…”

mentioning

confidence: 99%

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Korean public and hospital data for estimating LDL-cholesterol

Lee

Kim

et al. 2019

Data in Brief

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The data is composed of 14,812 subjects, and was obtained from the Korean National Health and Nutritional Examination Survey (KNHANES) from 2009 to 2015. The KNHANES data is publicly available at https://knhanes.cdc.go.kr/knhanes/eng/index.do. By using random annotated ID, all subjects can be anonymous.The dataset consisting of 4520 participants was obtained from Wonju Severance Christian Hospital (WSCH) in South Korea. To protect the patient׳s personal information, we removed ID and gender of patients. Detail information of the data presented in the present article is available in the research article “Deep neural network for estimating low density lipoprotein cholesterol” (Lee et al., 2018).

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