LIN28B induced PCAT5 promotes endometrial cancer progression and glycolysis via IGF2BP3 deubiquitination.

Endometrial cancer (EC) cells exhibit abnormal glucose metabolism, characterized by increased aerobic glycolysis and decreased oxidative phosphorylation. Targeting cellular glucose metabolism in these cells could be an effective therapeutic approach for EC. This study aimed to assess the roles of LIN28B, PCAT5, and IGF2BP3 in the glucose metabolism, proliferation, migration, and invasion of EC cells. LIN28B highly expressed in EC, binds and stabilizes PCAT5. PCAT5, overexpressed in EC, and its 1485-2288nt region can bind to the KH1-2 domain of IGF2BP3 to prevent MKRN2 from binding to the K294 ubiquitination site of IGF2BP3, thus stabilizing IGF2BP3. Finally, IGF2BP3 promotes the aerobic glycolysis, proliferation, migration and invasion of EC cells by stabilizing the key enzymes of glucose metabolism HK2 and PKM2. Taken together, our data reveal that the LIN28B/PCAT5/IGF2BP3 axis is critical for glucose reprogramming and malignant biological behavior in EC cells. Therefore, targeting this axis may contribute to the development of a novel therapeutic strategy for EC metabolism.

Enhancing Pixel Charging Efficiency by Optimizing Thin-Film Transistor Dimensions in Gate Driver Circuits for Active-Matrix Liquid Crystal Displays.

Flat panel displays are electronic displays that are thin and lightweight, making them ideal for use in a wide range of applications, from televisions and computer monitors to mobile devices and digital signage. The Thin-Film Transistor (TFT) layer is responsible for controlling the amount of light that passes through each pixel and is located behind the liquid crystal layer, enabling precise image control and high-quality display. As one of the important parameters to evaluate the display performance, the faster response time provides more frames in a second, which benefits many high-end applications, such as applications for playing games and watching movies. To further improve the response time, the single-pixel charging efficiency is investigated in this paper by optimizing the TFT dimensions in gate driver circuits in active-matrix liquid crystal displays. The accurate circuit simulation model is developed to minimize the signal's fall time (Tf) by optimizing the TFT width-to-length ratio. Our results show that using a driving TFT width of 6790 µm and a reset TFT width of 640 µm resulted in a minimum Tf of 2.6572 µs, corresponding to a maximum pixel charging ratio of 90.61275%. These findings demonstrate the effectiveness of our optimization strategy in enhancing pixel charging efficiency and improving display performance.

Proteomic characterization of epithelial ovarian cancer delineates molecular signatures and therapeutic targets in distinct histological subtypes.

Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicates potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.

Development and validation of a prognostic nomogram model incorporating routine laboratory biomarkers for preoperative patients with endometrial cancer.

BACKGROUND: Some biomarkers collected from routine laboratory tests have shown important value in cancer prognosis. The study aimed to evaluate the prognostic significance of routine laboratory biomarkers in patients with endometrial cancer (EC) and to develop credible prognostic nomogram models for clinical application. METHODS: A total of 727 patients were randomly divided into a training set and a validation set. Cox proportional hazards models were used to evaluate each biomarker's prognostic value, and independent prognostic factors were used to generate overall survival (OS) and progression-free survival (PFS) nomgrams. The efficacy of the nomograms were evaluated by Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, X-tile analysis and Kaplan‒Meier curves. RESULTS: Ten significant biomarkers in multivariate Cox analysis were integrated to develop OS and PFS nomograms. The C-indices of the OS- nomogram in the training and validation sets were 0.885 (95% confidence interval (CI), 0.810-0.960) and 0.850 (95% CI, 0.761-0.939), respectively; those of the PFS- nomogram in the training and validation sets were 0.903 (95% CI, 0.866-0.940) and 0.825 (95% CI, 0.711-0.939), respectively. ROC, DCA and calibration curves showed better clinical application value for the nomograms incorporating routine laboratory biomarkers. X-tile analysis and Kaplan‒Meier curves showed that the nomograms were stable and credible in evaluating patients at different risks. CONCLUSIONS: Nomogram models incorporating routine laboratory biomarkers, including NLR, MLR, fibrinogen, albumin and AB blood type, were demonstrated to be simple, reliable and favourable in predicting the outcomes of patients with EC.

Analysis and experimental validation of fatty acid metabolism-related genes prostacyclin synthase (PTGIS) in endometrial cancer.

The deregulation of fatty acid metabolism plays a pivotal role in cancer. Our objective is to construct a prognostic model for patients with endometrial carcinoma (EC) based on genes related to fatty acid metabolism-related genes (FAMGs). RNA sequencing and clinical data for EC were obtained from The Cancer Genome Atlas (TCGA). Lasso-Penalized Cox regression was employed to derive the risk formula for the model, the score = esum(corresponding coefficient × each gene's expression). Gene set enrichment analysis (GSEA) was utilized to examine the enrichment of KEGG and GO pathways within this model. Correlation analysis of immune function was conducted using Single-sample GSEA (ssGSEA). The "ESTIMATE" package in R was utilized to evaluate the tumor microenvironment. The support vector machine recursive feature elimination (SVM-RFE) and randomforest maps were employed to identify key genes. The effects of PTGIS on the malignant biological behavior of EC were assessed through CCK-8 assay, transwell invasion assay, cell cycle analysis, apoptosis assay, and tumor xenografts in nude mice. A novel prognostic signature comprising 10 FAMGs (INMT, ACACB, ACOT4, ACOXL, CYP4F3, FAAH, GPX1, HPGDS, PON3, PTGIS) was developed. This risk score serves as an independent prognostic marker validated for EC. According to ssGSEA analysis, the low- and high-risk groups exhibited distinct immune enrichments. The key gene PTGIS was screened by SVM-RFE and randomforest method. Furthermore, we validated the expression of PTGIS through qRT-PCR. In vitro and in vivo experiments also confirmed the effect of PTGIS on the malignant biological behavior of EC.

Ultrasound-Induced Gold Nanoparticle United with Acoustic Reprogramming of Macrophages for Enhanced Cancer Therapy.

Sonodynamic therapy (SDT) has considerable potential in cancer treatment and exhibits high tissue penetration with minimal damage to healthy tissues. The efficiency of SDT is constrained by the complex immunological environment and tumor treatment resistance. Herein, a specific acoustic-actuated tumor-targeted nanomachine is proposed to generate mechanical damage to lysosomes for cancer SDT. The hybrid nanomachine was assembled with gold nanoparticles (GNPs) as the core and encapsulated with macrophage exosomes modified by AS1411 aptamers (GNP@EXO-APs) to optimize the pharmacokinetics and tumor aggregation. GNP@EXO-APs could be specifically transferred to the lysosomes of tumor cells. After induction with ultrasound, GNP@EXO-APs generated strong mechanical stress to produce lysosomal-dependent cell death in cancer cells. Notably, tumor-associated macrophages were reprogrammed in the ultrasound environment to an antitumor phenotype. Enhanced mechanical destruction via GNP@EXO-APs and immunotherapy of cancer cells were verified both in vitro and in vivo under SDT. This study provides a new direction for inside-out killing effects on tumor cells for cancer treatment.

Immune regulation in gastric adenocarcinoma is linked with therapeutic efficacy and improved recovery.

Adenocarcinomas are one of the most common histological types of gastric cancer. It has been ranked fifth among common cancers and is the third among death causing cancers worldwide. The high mortality rate among patients with gastric cancer is because of its silent evolution, genetic heterogeneity, high resistance to chemotherapy as well as unavailability of highly effective therapeutic strategy. Until now a number of several treatment strategies have been developed and are being practiced such as surgery, chemotherapy, radio therapy, and immunotherapy, however, further developments are required to improve the treatment responses and reduce the side effects. Therefore, novel personal therapeutic strategies based on immunological responses should be developed by targeting different check points and key immune players. Targeting macrophages and related molecular elements can be useful to achieve these goals. In this minireview, we discuss the available treatment options, molecular underpinnings and immunological regulations associated with gastric adenocarcinoma. We further describe the possible check points and immunological targets that can be used to develop novel therapeutic options.

A novel predictive model based on inflammatory response-related genes for predicting endometrial cancer prognosis and its experimental validation.

Inflammatory response is an important feature of most tumors. Local inflammation promotes tumor cell immune evasion and chemotherapeutic drug resistance. We aimed to build a prognostic model for endometrial cancer patients based on inflammatory response-related genes (IRGs). RNA sequencing and clinical data for uterine corpus endometrial cancer were obtained from TCGA datasets. LASSO-penalized Cox regression was used to obtain the risk formula of the model: the score = esum(corresponding coefficient × each gene's expression). The "ESTIMATE" and "pRRophetic" packages in R were used to evaluate the tumor microenvironment and the sensitivity of patients to chemotherapy drugs. Data sets from IMvigor210 were used to evaluate the efficacy of immunotherapy in cancer patients. For experimental verification, 37 endometrial cancer and 43 normal endometrial tissues samples were collected. The mRNA expression of the IRGs was measured using qRT-PCR. The effects of IRGs on the malignant biological behaviors of endometrial cancer were detected using CCK-8, colony formation, Transwell invasion, and apoptosis assays. We developed a novel prognostic signature comprising 13 IRGs, which is an independent prognostic marker for endometrial cancer. A nomogram was developed to predict patient survival accurately. Three key IRGs (LAMP3, MEP1A, and ROS1) were identified in this model. Furthermore, we verified the expression of the three key IRGs using qRT-PCR. Functional experiments also confirmed the influence of the three key IRGs on the malignant biological behavior of endometrial cancer. Thus, a characteristic model constructed using IRGs can predict the survival, chemotherapeutic drug sensitivity, and immunotherapy response in patients with endometrial cancer.

K8sSim: A Simulation Tool for Kubernetes Schedulers and Its Applications in Scheduling Algorithm Optimization.

In recent years, Kubernetes (K8s) has become a dominant resource management and scheduling system in the cloud. In practical scenarios, short-running cloud workloads are usually scheduled through different scheduling algorithms provided by Kubernetes. For example, artificial intelligence (AI) workloads are scheduled through different Volcano scheduling algorithms, such as GANG_MRP, GANG_LRP, and GANG_BRA. One key challenge is that the selection of scheduling algorithms has considerable impacts on job performance results. However, it takes a prohibitively long time to select the optimal algorithm because applying one algorithm in one single job may take a few minutes to complete. This poses the urgent requirement of a simulator that can quickly evaluate the performance impacts of different algorithms, while also considering scheduling-related factors, such as cluster resources, job structures and scheduler configurations. In this paper, we design and implement a Kubernetes simulator called K8sSim, which incorporates typical Kubernetes and Volcano scheduling algorithms for both generic and AI workloads, and provides an accurate simulation of their scheduling process in real clusters. We use real cluster traces from Alibaba to evaluate the effectiveness of K8sSim, and the evaluation results show that (i) compared to the real cluster, K8sSim can accurately evaluate the performance of different scheduling algorithms with similar CloseRate (a novel metric we define to intuitively show the simulation accuracy), and (ii) it can also quickly obtain the scheduling results of different scheduling algorithms by accelerating the scheduling time by an average of 38.56×.

ImmuneScore of eight-gene signature predicts prognosis and survival in patients with endometrial cancer.

Background: Endometrial cancer (EC) is a common gynecological cancer worldwide and the sixth most common female malignant tumor. A large number of studies conducted through database mining have identified many biomarkers that may be related to survival and prognosis. However, the predictive ability of single-gene biomarkers is not sufficiently accurate. In recent years, tumors have been shown to interact closely with their microenvironment, and tumor-infiltrating immune cells in the tumor microenvironment were associated with therapeutic effects. Furthermore, sequencing technology has evolved and allowed the identification of genetic signatures that may improve prediction results. The purpose of this research was to discover the Cancer Genome Atlas (TCGA) data to evaluate new genetic features that can predict the prognosis of EC. Methods: mRNA expression profiling was analyzed in patients with EC identified in the TCGA database (n = 530). Differentially expressed genes at different stages of EC were screened using the immune cell enrichment score (ImmuneScore). Univariate and multivariate Cox regression analyses was applied to evaluate genes significantly related to overall survival and establish the prognostic risk parameter formula. Kaplan-Meier survival curves and the logarithmic rank method were applied to verify the importance of risk parameters for the prognostic forecast. The accuracy of survival prediction was confirmed using the nomogram and Receiver Operating Characteristic (ROC) curve analysis. The mRNA expression of eight genes were measured by qRT-PCR. According to COX and HR values, NBAT1, a representative gene among 8 genes, was selected for CCK-8 assay, colony formation assay and transwell invasion assay to verify the effect on survival. Results: Eight related genes (NBAT1, GFRA4, PTPRT, DLX4, RANBP3L, UNQ6494, KLRB1, and PRAC1) were discovered to be significantly associated with the overall survival rate. According to these eight-gene signatures, 530 patients with EC were assigned to high- and low-risk subgroups. The prognostic capability of the eight-gene signature was not influenced by other elements. Conclusions: Eight related gene markers were identified using ImmuneScore, which could predict prognosis and survival in patients with EC. These findings provide a basis for understanding the application of biological information in tumors and identifying the poor prognosis of EC.

Endoscopic treatment and management of rectal neuroendocrine tumors less than 10 mm in diameter.

Rectal neuroendocrine tumors (rNETs) measuring less than 10 mm in diameter are defined as small rNETs. Due to the low risk of distant invasion and metastasis, endoscopic treatments, including modified endoscopic mucosal resection, endoscopic submucosal dissection, and other transanal surgical procedures, are effective. This review article proposes a follow-up plan according to the size and histopathology of the tumor after operation.

PVT1/miR-136/Sox2/UPF1 axis regulates the malignant phenotypes of endometrial cancer stem cells.

Tumor stem cells (TSCs) are thought to contribute to the progression and maintenance of cancer. Previous studies have suggested that plasmacytoma variant translocation 1 (PVT1) has a tumor-promoting effect on endometrial cancer; however, its mechanism of action in endometrial cancer stem cells (ECSCs) is unknown. Here, we found that PVT1 was highly expressed in endometrial cancers and ECSCs, correlated with poor patient prognosis, promoted the malignant behavior and the stemness of endometrial cancer cells (ECCs) and ECSCs. In contrast, miR-136, which was lowly expressed in endometrial cancer and ECSCs, had the opposite effect, and knockdown miR-136 inhibited the anticancer effects of down-regulated PVT1. PVT1 affected miR-136 specifically binding the 3' UTR region of Sox2 by competitively "sponging" miR-136, thus positively saving Sox2. Sox2 promoted the malignant behavior and the stemness of ECCs and ECSCs, and overexpression Sox2 inhibited the anticancer effects of up-regulated miR-136. Sox2 can act as a transcription factor to positively regulate Up-frameshift protein 1 (UPF1) expression, thereby exerting a tumor-promoting effect on endometrial cancer. In nude mice, simultaneously downregulating PVT1 and upregulating miR-136 exerted the strongest antitumor effect. We demonstrate that the PVT1/miR-136/Sox2/UPF1 axis plays an important role in the progression and maintenance of endometrial cancer. The results suggest a novel target for endometrial cancer therapies.

Three RNA-binding protein signature as a novel biomarker to predict endometrial cancer prognosis.

The aim of this study was to build a prognostic model for endometrial cancer (EC) patients based on RNA-binding proteins (RBPs). RNA sequencing and clinical data for uterine corpus EC (UCEC) were obtained from The Cancer Genome Atlas (TCGA). Univariate and multivariate Cox regression analysis were used to obtain the following risk formula: score = sum (corresponding coefficient × expression of each gene). A nomogram was developed to accurately predict patient survival based on risk score, age, stage, and grade. Immunohistochemistry (IHC) was used to verify the expression of RBPs in EC. The mRNA expression of RBPs was measured by qRT-PCR. The effects of RBPs on the malignant biologic behavior of EC were detected using CCK-8, colony formation, and transwell invasion assays. A novel prognostic signature was constructed, comprising three RBPs (CD3EAP, SBDS, and TDRKH). The risk score was: Risk score = (0.860 × CD3EAP expression) + (0.622 × 6SBDS expression) + (0.427 × 4TDRKH expression). The area under the receiver operating characteristic curves (AUCs) of risk score for 1-, 3-, and 5-year overall survival (OS) was 0.75, 0.68, and 0.65, respectively. The AUCs of the nomogram for 1-, 3-, and 5-year OS were 0.811, 0.793, and 0.814, respectively. In our independent cohort, the IHC results revealed that CD3EAP (P < 0.001) and TDRKH (P < 0.001) were upregulated and SBDS (P < 0.001) was downregulated in EC. Immunostaining showed the expression levels of CD3EAP, SBDS and TDRKH for each patient and these were multiplied by their respective coefficients of 0.860, 0.622 and 0.427 to obtain the risk scores. The AUCs of risk score for 1-, 3-, and 5-year OS were 0.888, 0.793, and 0.780 respectively. The AUCs of the nomogram for 1-, 3-, and 5-year OS were 0.790, 0.826, and 0.906, respectively. Cell functional experiments also confirmed the influence of the key RBPs on the malignant biologic behavior of EC. In summary, a characteristic model based on our three RBPs accurately predicted the prognosis of EC. Our in-depth analysis of these RBPs may inform the development of novel strategies for the diagnosis and treatment of EC.

T-Cell Mineralocorticoid Receptor Deficiency Attenuates Pathologic Ventricular Remodelling After Myocardial Infarction.

BACKGROUND: Mineralocorticoid receptor (MR) antagonists have been widely used to treat heart failure (HF). Studies have shown that MR in T cells plays important roles in hypertension and myocardial hypertrophy. However, the function of T-cell MR in myocardial infarction (MI) has not been elucidated. METHODS: In this study, we used T-cell MR knockout (TMRKO) mouse to investigate the effects of T-cell MR deficiency on MI and to explore the underlying mechanisms. Echocardiography and tissue staining were used to assess cardiac function, fibrosis, and myocardial apoptosis after MI. Flow cytometry and quantitative real-time polymerase chain reaction (qRT-PCR) were used to detect immune cell infiltration and inflammation. RESULTS: T-cell MR deficiency significantly improved cardiac function, promoted myocardial repair, and inhibited myocardial apoptosis, fibrosis, and inflammation after MI. Luminex assays revealed that TMRKO mice had significantly lower levels of interferon-gamma (IFN-γ) and interleukin-6 (IL-6) in serum and infarcted myocardium than littermate control mice. In cultured splenic T cells, MR deficiency suppressed IL-6 expression, whereas MR overexpression enhanced IL-6 expression. Chromatin immunoprecipitation (ChIP) assay demonstrated that MR bound to the MR response element on the promoter of IL-6 gene. Finally, T-cell MR deficiency significantly suppressed accumulation of macrophages in infarcted myocardium and differentiation of proinflammatory macrophages, thereby alleviating the consequences of MI. CONCLUSIONS: T-cell MR deficiency improved pathologic ventricular remodelling after MI, likely through inhibition of accumulation and differentiation of proinflammatory macrophages. At the molecular level, MR may work through IFN-γ and IL-6 in T cells to exert functions in MI.

Mitochondrial Transfer Regulates Cell Fate Through Metabolic Remodeling in Osteoporosis.

Mitochondria are the powerhouse of eukaryotic cells, which regulate cell metabolism and differentiation. Recently, mitochondrial transfer between cells has been shown to direct recipient cell fate. However, it is unclear whether mitochondria can translocate to stem cells and whether this transfer alters stem cell fate. Here, mesenchymal stem cell (MSC) regulation is examined by macrophages in the bone marrow environment. It is found that macrophages promote osteogenic differentiation of MSCs by delivering mitochondria to MSCs. However, under osteoporotic conditions, macrophages with altered phenotypes, and metabolic statuses release oxidatively damaged mitochondria. Increased mitochondrial transfer of M1-like macrophages to MSCs triggers a reactive oxygen species burst, which leads to metabolic remodeling. It is showed that abnormal metabolism in MSCs is caused by the abnormal succinate accumulation, which is a key factor in abnormal osteogenic differentiation. These results reveal that mitochondrial transfer from macrophages to MSCs allows metabolic crosstalk to regulate bone homeostasis. This mechanism identifies a potential target for the treatment of osteoporosis.

Using Metal-Organic Frameworks to Confine Liquid Samples for Nanoscale NV-NMR.

Atomic-scale magnetic field sensors based on nitrogen vacancy (NV) defects in diamonds are an exciting platform for nanoscale nuclear magnetic resonance (NMR) spectroscopy. The detection of NMR signals from a few zeptoliters to single molecules or even single nuclear spins has been demonstrated using NV centers close to the diamond surface. However, fast molecular diffusion of sample molecules in and out of the nanoscale detection volumes impedes their detection and limits current experiments to solid-state or highly viscous samples. Here, we show that restricting diffusion by confinement enables nanoscale NMR spectroscopy of liquid samples. Our approach uses metal-organic frameworks (MOF) with angstrom-sized pores on a diamond chip to trap sample molecules near the NV centers. This enables the detection of NMR signals from a liquid sample, which would not be detectable without confinement. These results set the route for nanoscale liquid-phase NMR with high spectral resolution.

Nomograms Based on Fibrinogen, Albumin, Neutrophil-Lymphocyte Ratio, and Carbohydrate Antigen 125 for Predicting Endometrial Cancer Prognosis.

Background: This study aimed to determine the prognostic value of the preoperative levels of fibrinogen, albumin (ALB), neutrophil−lymphocyte ratio (NLR), and carbohydrate antigen 125 (CA125) in endometrial cancer and to establish nomograms for predicting patient survival. Methods: Patients with endometrial cancer (n = 1483) who underwent surgery were included in this study, and their preoperative fibrinogen, ALB, NLR, and CA125 levels and clinicopathological characteristics were collected. Patients were randomized into a training cohort (70%, n = 1038) and an external validation cohort (30%, n = 445). The Cox regression analysis was performed using the data for the patients in the training cohort to identify independent prognostic factors; nomograms for predicting prognosis were established and validated. Results: High fibrinogen (≥3.185 g/L), NLR (≥2.521 g/L), and CA125 (≥35 U/mL) levels and low ALB (<4.185 g/L) levels were independently associated with poor progression-free survival (PFS) and poor overall survival (OS) in patients with endometrial cancer. Prognostic prediction model nomograms were developed and validated based on these results. Calibration curves and C-indexes underscored the good predictive power of the nomograms, and both the net reclassification index (NRI) and integrated discrimination improvement (IDI) values of the prognostic prediction model nomograms were improved. Conclusions: Nomograms that are developed based on preoperative fibrinogen, ALB, NLR, and CA125 levels accurately predict PFS and OS in patients with endometrial cancer.

Postmenopausal giant ovarian tumor: a rare case report and literature review.

OBJECTIVE: A giant ovarian tumor weighing 62 kg and containing 51 L cyst fluid is rare among postmenopausal women, and an early diagnosis contributes to a good prognosis. METHODS: We report a case of a 62-kg giant ovarian tumor, the largest ovarian tumor ever reported in China. A 64-year-old woman with a giant pelvic abdominal mass underwent surgery. Because of the occurrence of serious perioperative and postoperative complications, we then conducted a literature review to investigate possible risk factors for severe complications. RESULTS: During the operation, 51 L of intratumoral fluid was drained, and a giant ovarian tumor of approximately 62 kg was removed. The pathological examination showed that the tumor was a mucinous borderline one. The patient had perioperative hypotension and postoperative respiratory failure. After a comprehensive literature review, we found that the occurrence of serious complications may not be related to tumor volume and weight but age and the amount of fluid in the tumor. CONCLUSIONS: The high incidence of severe complications should be carefully considered when huge ovarian tumors or tumors containing a large amount of tumor fluid in postmenopausal women are removed.

Relationship between chronic periodontitis and inflammatory cytokines in patients undergoing maintenance hemodialysis.

OBJECTIVES: To investigate the correlation between serum and gingival crevicular fluid (GCF) levels of inflammatory cytokines and the association with periodontal parameters in patients with maintenance hemodialysis (MHD) and healthy control. MATERIALS AND METHODS: Patients who were undergoing MHD were enrolled as the MHD group. Healthy individuals who underwent oral examination were selected as the control group after matching for the MHD group. All participants underwent a full-mouth periodontal evaluation, and the levels of eight inflammatory cytokines, including IL-1ß, IL-17, IL-6, IL-8, and tumor necrosis factor-α (TNF-α), monocyte chemoattractant protein-1 (MCP-1), matrix metalloproteinase-8 (MMP-8), and C-reactive protein (CRP), in the GCF and serum were measured. RESULTS: A total of 63 MHD patients and 75 healthy persons were included. The prevalence of moderate/severe periodontitis was significantly higher in the MHD group than in the control group (88.9 vs. 66.7%, P < 0.05). The GCF levels of CRP, TNF-α, MCP-1, and MMP-8 were higher in patients in the MHD group with moderate/severe periodontitis than in the control group (P < 0.05). Serum CRP, MCP-1, TNF-α, and MMP-8 levels were positively correlated with the GCF CRP levels (P < 0.05). The GCF and serum CRP levels were positively correlated with the periodontal clinical parameters (P < 0.05). CONCLUSIONS: Serum CRP, MCP-1, TNF-α, and MMP-8 may relate with the GCF CRP levels. The GCF and serum CRP levels correlated positively with the periodontal clinical parameters, including the VPI, PPD, and CAL, indicating that CRP may play an important role between periodontitis and ESRD. CLINICAL RELEVANCE: The present study indicated that GCF and serum CRP levels correlated positively with the periodontal clinical parameters, and the CRP levels may be selected as an indicator to evaluate the severity of inflammation and the effectiveness, prognosis of periodontal treatment in ESRD patients.