Publications by authors named "Kyemyung Park"

4 Publications

  • Page 1 of 1

Predictive models for chronic kidney disease after radical or partial nephrectomy in renal cell cancer using early postoperative serum creatinine levels.

J Transl Med 2021 Jul 16;19(1):307. Epub 2021 Jul 16.

Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.

Background: Several predictive factors for chronic kidney disease (CKD) following radical nephrectomy (RN) or partial nephrectomy (PN) have been identified. However, early postoperative laboratory values were infrequently considered as potential predictors. Therefore, this study aimed to develop predictive models for CKD 1 year after RN or PN using early postoperative laboratory values, including serum creatinine (SCr) levels, in addition to preoperative and intraoperative factors. Moreover, the optimal SCr sampling time point for the best prediction of CKD was determined.

Methods: Data were retrospectively collected from patients with renal cell cancer who underwent laparoscopic or robotic RN (n = 557) or PN (n = 999). Preoperative, intraoperative, and postoperative factors, including laboratory values, were incorporated during model development. We developed 8 final models using information collected at different time points (preoperative, postoperative day [POD] 0 to 5, and postoperative 1 month). Lastly, we combined all possible subsets of the developed models to generate 120 meta-models. Furthermore, we built a web application to facilitate the implementation of the model.

Results: The magnitude of postoperative elevation of SCr and history of CKD were the most important predictors for CKD at 1 year, followed by RN (compared to PN) and older age. Among the final models, the model using features of POD 4 showed the best performance for correctly predicting the stages of CKD at 1 year compared to other models (accuracy: 79% of POD 4 model versus 75% of POD 0 model, 76% of POD 1 model, 77% of POD 2 model, 78% of POD 3 model, 76% of POD 5 model, and 73% in postoperative 1 month model). Therefore, POD 4 may be the optimal sampling time point for postoperative SCr. A web application is hosted at https://dongy.shinyapps.io/aki_ckd .

Conclusions: Our predictive model, which incorporated postoperative laboratory values, especially SCr levels, in addition to preoperative and intraoperative factors, effectively predicted the occurrence of CKD 1 year after RN or PN and may be helpful for comprehensive management planning.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12967-021-02976-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8283951PMC
July 2021

A local regulatory T cell feedback circuit maintains immune homeostasis by pruning self-activated T cells.

Cell 2021 Jul 21;184(15):3981-3997.e22. Epub 2021 Jun 21.

Lymphocyte Biology Section, Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892-1892, USA. Electronic address:

A fraction of mature T cells can be activated by peripheral self-antigens, potentially eliciting host autoimmunity. We investigated homeostatic control of self-activated T cells within unperturbed tissue environments by combining high-resolution multiplexed and volumetric imaging with computational modeling. In lymph nodes, self-activated T cells produced interleukin (IL)-2, which enhanced local regulatory T cell (Treg) proliferation and inhibitory functionality. The resulting micro-domains reciprocally constrained inputs required for damaging effector responses, including CD28 co-stimulation and IL-2 signaling, constituting a negative feedback circuit. Due to these local constraints, self-activated T cells underwent transient clonal expansion, followed by rapid death ("pruning"). Computational simulations and experimental manipulations revealed the feedback machinery's quantitative limits: modest reductions in Treg micro-domain density or functionality produced non-linear breakdowns in control, enabling self-activated T cells to subvert pruning. This fine-tuned, paracrine feedback process not only enforces immune homeostasis but also establishes a sharp boundary between autoimmune and host-protective T cell responses.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cell.2021.05.028DOI Listing
July 2021

Environment Tunes Propagation of Cell-to-Cell Variation in the Human Macrophage Gene Network.

Cell Syst 2017 04 29;4(4):379-392.e12. Epub 2017 Mar 29.

Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institutes of Health, Bethesda, MD 20892, USA; Trans-NIH Center for Human Immunology (CHI), National Institutes of Health, Bethesda, MD 20892, USA. Electronic address:

Cell-to-cell variation in gene expression and the propagation of such variation (PoV or "noise propagation") from one gene to another in the gene network, as reflected by gene-gene correlation across single cells, are commonly observed in single-cell transcriptomic studies and can shape the phenotypic diversity of cell populations. While gene network "rewiring" is known to accompany cellular adaptation to different environments, how PoV changes between environments and its underlying regulatory mechanisms are less understood. Here, we systematically explored context-dependent PoV among genes in human macrophages, utilizing different cytokines as natural perturbations of multiple molecular parameters that may influence PoV. Our single-cell, epigenomic, computational, and stochastic simulation analyses reveal that environmental adaptation can tune PoV to potentially shape cellular heterogeneity by changing parameters such as the degree of phosphorylation and transcription factor-chromatin interactions. This quantitative tuning of PoV may be a widespread, yet underexplored, property of cellular adaptation to distinct environments.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.cels.2017.03.002DOI Listing
April 2017

Effect of fluvastatin, lovastatin, nifedipine and verapamil on the systemic exposure of nateglinide in rabbits.

Biopharm Drug Dispos 2010 Nov;31(8-9):443-9

Daewon Foreign Language High School, Seoul, 143-713 Korea.

A diabetic patient may suffer simultaneously from cardiovascular disease; thus, lipid-lowering or anti-hypertensive agents could be given together with nateglinide. The pharmacokinetics of nateglinide were investigated in the presence and absence of HMG-CoA reductase inhibitors (fluvastatin, lovastatin) and calcium channel blockers (verapamil, nifedipine) in rabbits. A pharmacokinetic modeling approach was used to quantify the effects of the drugs that significantly influenced the pharmacokinetics of nateglinide. Fluvastatin and nifedipine shifted the time course of serum nateglinide concentrations upwards; there was no significant change with verapamil or lovastatin. The C(max) and AUC(inf) increased 1.5- (p<0.05) and 1.3-fold in the presence of fluvastatin and 1.8- (p<0.01) and 2.4-fold (p<0.01) in the presence of nifedipine, respectively. In a simultaneous nonlinear regression, fluvastatin and nifedipine decreased the elimination rate constant, by 76% and 32%, respectively. Fluvastatin and nifedipine increased the systemic exposure of nateglinide in rabbits, probably due to their inhibitory action on the metabolism of nateglinide by CYP2C5 (human CYP2C9). The concomitant use of fluvastatin and/or nifedipine with nateglinide is quite likely; therefore, the clinical consequences of long-term treatments must be considered.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/bdd.724DOI Listing
November 2010
-->