Search

Abstract Aims Patients with high‐flow arteriovenous (AV) access are at risk of developing high‐output cardiac failure (HOCF) and subsequent hospitalization. However, diagnosing HOCF is challenging and often requires invasive procedures. The role of systemic vascular resistance (SVR) in diagnosing HOCF is underestimated, and its predictive value is limited. Our study aims to identify non‐invasive risk factors for HOCF to facilitate early diagnosis and timely surgical interventions. Methods and results We included 109 patients with high‐flow AV access who underwent serial echocardiography. The retrospective cohort was divided into two groups based on their hospitalization due to HOCF. The two groups were matched for age and gender. After a mean follow‐up of 25.1 months, 19 patients (17.4%) were hospitalized due to HOCF. The two groups had similar baseline characteristics. However, the HOCF group had a higher value of vascular access blood flow (Qa) (2168 ± 856 vs. 1828 ± 617 mL/min; P = 0.045). Echocardiographic analysis revealed that the HOCF group had more pronounced left ventricular diastolic dysfunction (E/e′: 21.1 ± 7.3 vs. 16.2 ± 5.9; P = 0.002), more severe pulmonary hypertension (right ventricular systolic pressure: 41.4 ± 16.7 vs. 32.2 ± 12.8; P = 0.009), a higher Doppler‐derived cardiac index (CI) (4.3 ± 0.8 vs. 3.7 ± 1.1; P = 0.031), and a lower Doppler‐derived estimated SVR (eSVR) value (5.5 ± 0.3 vs. 6.9 ± 0.2; P = 0.002) than the non‐HOCF group. Using multivariable Cox regression analysis, a low eSVR value (

Background: Hemodialysis (HD) patients are particularly vulnerable to severe coronavirus disease 2019 (COVID-19) due to their immunocompromised state and comorbid conditions. Timely vaccination could be the most effective strategy to reduce morbidity and mortality. However, data on the survival benefit of the COVID-19 vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and death among HD patients are limited, especially during the Omicron-dominant period. Methods: In this prospective hospital-based cohort study, we identified HD patients from July 1, 2021, to April 29, 2022. The patients were divided into fully vaccinated and partially vaccinated groups. We compared the humoral response, risk of developing SARS-CoV-2 infection, and all-cause mortality between the two groups. Results: Among the 440 HD patients included, 152 patients were fully vaccinated, and 288 patients were partially vaccinated. Patients in the fully vaccinated group exhibited higher anti-spike protein receptor-binding domain (S protein RBD) antibody levels and lower risks of all-cause mortality (adjusted hazard ratio, 0.35; 95% confidence interval, 0.17–0.73; p = 0.005) than the partially vaccinated group. However, the risk for SARS-CoV-2 infection did not significantly differ between the two groups. Irrespective of the number of vaccinations, the risk of all-cause mortality was lower in patients with anti-S protein RBD antibody levels in the higher tertile. Conclusion: A third dose of the COVID-19 vaccine was associated with a decreased risk of all-cause mortality among HD patients during the Omicron-dominant period. A higher post-vaccination anti-S protein RBD antibody level was also associated with a lower risk of mortality.

Abstract Objectives Type 2 diabetes mellitus (T2DM) imposes a great burden on healthcare systems, and these patients experience higher long-term risks for developing end-stage renal disease (ESRD). Managing diabetic nephropathy becomes more challenging when kidney function starts declining. Therefore, developing predictive models for the risk of developing ESRD in newly diagnosed T2DM patients may be helpful in clinical settings. Methods We established machine learning models constructed from a subset of clinical features collected from 53,477 newly diagnosed T2DM patients from January 2008 to December 2018 and then selected the best model. The cohort was divided, with 70% and 30% of patients randomly assigned to the training and testing sets, respectively. Results The discriminative ability of our machine learning models, including logistic regression, extra tree classifier, random forest, gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting machine were evaluated across the cohort. XGBoost yielded the highest area under the receiver operating characteristic curve (AUC) of 0.953, followed by extra tree and GBDT, with AUC values of 0.952 and 0.938 on the testing dataset. The SHapley Additive explanation summary plot in the XGBoost model illustrated that the top five important features included baseline serum creatinine, mean serum creatine within 1 year before the diagnosis of T2DM, high-sensitivity C-reactive protein, spot urine protein-to-creatinine ratio and female gender. Conclusions Because our machine learning prediction models were based on routinely collected clinical features, they can be used as risk assessment tools for developing ESRD. By identifying high-risk patients, intervention strategies may be provided at an early stage.

Mesenchymal stem cells (MSCs) possess the capacity for self-renewal and multipotency. The traditional approach to manipulating MSC's fate choice predominantly relies on biochemical stimulation. Accumulating evidence also suggests the role of physical input in MSCs differentiation. Therefore, investigating mechanotransduction at the molecular level and related to tissue-specific cell functions sheds light on the responses secondary to mechanical forces. In this review, a new frontier aiming to optimize the cultural parameters was illustrated, i.e. spatial boundary condition, which recapitulates in vivo physiology and facilitates the investigations of cellular behavior. The concept of mechanical memory was additionally addressed to appreciate how MSCs store imprints from previous culture niches. Besides, different types of forces as physical stimuli were of interest based on the association with the respective signaling pathways and the differentiation outcome. The downstream mechanoreceptors and their corresponding effects were further pinpointed. The cardiovascular system or immune system may share similar mechanisms of mechanosensing and mechanotransduction; for example, resident stem cells in a vascular wall and recruited MSCs in the bloodstream experience mechanical forces such as stretch and fluid shear stress. In addition, baroreceptors or mechanosensors of endothelial cells detect changes in blood flow, pass over signals induced by mechanical stimuli and eventually maintain arterial pressure at the physiological level. These mechanosensitive receptors transduce pressure variation and regulate endothelial barrier functions. The exact signal transduction is considered context dependent but still elusive. In this review, we summarized the current evidence of how mechanical stimuli impact MSCs commitment and the underlying mechanisms. Future perspectives are anticipated to focus on the application of cardiovascular bioengineering and regenerative medicine.

Elevated circulating low-density lipoprotein cholesterol (LDL-C) is a major risk factor of atherosclerotic cardiovascular disease (ASCVD). Early control of LDL-C to prevent ASCVD later in life is important. The Taiwan Society of Lipids and Atherosclerosis in association with the other seven societies developed this new lipid guideline focusing on subjects without clinically significant ASCVD. In this guideline for primary prevention, the recommended LDL-C target is based on risk stratification. A healthy lifestyle with recommendations for foods, dietary supplements and alcohol drinking are described. The pharmacological therapies for LDL-C reduction are recommended. The aim of this guideline is to decrease the risk of ASCVD through adequate control of dyslipidemia in Taiwan.

Introduction: The 2019 Kidney Disease Outcome Quality Initiative (K/DOQI) guideline recommended evaluating arteriovenous fistula (AVF) malfunction risks primarily based on clinical monitoring, which can be assisted with the value of vascular access flow (Qa). Nevertheless, Qa thresholds recommended by different guidelines vary, ranging from 300 to 500 ml/min. This study investigated the optimal Qa threshold to predict future functional patency in AVFs with Qa

Background: Our aim was to characterize etiologic diagnoses obtained from bronchoalveolar lavage fluid (BALF) and blood specimens, and to identify risk factors for mortality in systemic lupus erythematosus (SLE) patients with pneumonia and respiratory failure. Methods: We conducted a retrospective analysis of SLE patients with pneumonia and respiratory failure. Clinical characteristics, laboratory profiles, and microbiology in BALF and blood samples were evaluated. We performed univariable analyses to identify mortality risk factors. Results: All 24 patients (F:M = 21:3, median age 46.5 years; disease duration 11 years) received mechanical ventilation (median duration: 11 days). Pathogens identified in BALF included Pneumocystis jiroveci (12 patients [50%]), cytomegalovirus (CMV, 7 patients [29.2%]), and bacteria (11 patients [45.8%]). Thirteen patients (54.2%) yielded pathogens in blood (CMV in 8 patients [33.3%] and Escherichia coli in 5 patients [20.8%]). Eight developed septic shock, and 9 died within 30 days. Univariable analysis identified thrombocytopenia (odds ratio [OR]: 8.0, 95% confidence interval [CI]: 1.23–52.25), bacteremia within 30 days before or after endotracheal intubation (OR: 8.0, 95% CI: 1.23–52.5), and P. jiroveci pneumonia (PJP, OR: 7.0, 95% CI: 1.04–46.95) as risk factors for 30-day mortality. Kaplan–Meier analysis confirmed an increased risk of 30-day mortality with thrombocytopenia and bacteremia. Conclusion: There are high prevalence rates of PJP and CMV infections as evidenced by BALF analyses in SLE patients with pneumonia and respiratory failure. BALF analysis can facilitate rescue therapy per pathogen. Thrombocytopenia, bacteremia, and PJP in SLE patients can increase their 30-day mortality, so warrant early and aggressive treatments.

BackgroundAnterior cruciate ligament (ACL) injuries are common in sports and are critical knee injuries that require prompt diagnosis. Magnetic resonance imaging (MRI) is a strong, noninvasive tool for detecting ACL tears, which requires training to read accurately. Clinicians with different experiences in reading MR images require different information for the diagnosis of ACL tears. Artificial intelligence (AI) image processing could be a promising approach in the diagnosis of ACL tears. ObjectiveThis study sought to use AI to (1) diagnose ACL tears from complete MR images, (2) identify torn-ACL images from complete MR images with a diagnosis of ACL tears, and (3) differentiate intact-ACL and torn-ACL MR images from the selected MR images. MethodsThe sagittal MR images of torn ACL (n=1205) and intact ACL (n=1018) from 800 cases and the complete knee MR images of 200 cases (100 torn ACL and 100 intact ACL) from patients aged 20-40 years were retrospectively collected. An AI approach using a convolutional neural network was applied to build models for the objective. The MR images of 200 independent cases (100 torn ACL and 100 intact ACL) were used as the test set for the models. The MR images of 40 randomly selected cases from the test set were used to compare the reading accuracy of ACL tears between the trained model and clinicians with different levels of experience. ResultsThe first model differentiated between torn-ACL, intact-ACL, and other images from complete MR images with an accuracy of 0.9946, and the sensitivity, specificity, precision, and F1-score were 0.9344, 0.9743, 0.8659, and 0.8980, respectively. The final accuracy for ACL-tear diagnosis was 0.96. The model showed a significantly higher reading accuracy than less experienced clinicians. The second model identified torn-ACL images from complete MR images with a diagnosis of ACL tear with an accuracy of 0.9943, and the sensitivity, specificity, precision, and F1-score were 0.9154, 0.9660, 0.8167, and 0.8632, respectively. The third model differentiated torn- and intact-ACL images with an accuracy of 0.9691, and the sensitivity, specificity, precision, and F1-score were 0.9827, 0.9519, 0.9632, and 0.9728, respectively. ConclusionsThis study demonstrates the feasibility of using an AI approach to provide information to clinicians who need different information from MRI to diagnose ACL tears.

ObjectiveSLC12A3 (solute carrier family 12 member 3) gene variants are associated with diabetic nephropathy; however, their association with hypertensive nephropathy remains unknown. We aimed to investigate the association between SLC12A3 gene polymorphisms and renal function in patients with hypertension.MethodsParticipants from three non-diabetic hypertensive cohorts, including young-onset hypertension (cohort 1, n = 882), treatment-naïve hypertension (cohort 2, n = 90), and follow-up cohort (cohort 3, n = 166), underwent genotyping for single nucleotide polymorphisms in SLC12A3. Renal events were defined as a >25 and >50% decline in estimated glomerular filtration rate (eGFR).ResultsIn cohort 1, SLC12A3 rs16963397 C/C or C/G (P = 0.005), rs13334864 C/C or C/T (P = 0.020), and rs7187932 A/A or A/G polymorphisms (P = 0.014) had higher eGFRs compared to their counterparts, with similar findings observed in cohort 2. In cohort 3, over a mean follow-up of 5.8 ± 1.7 years, participants with either SLC12A3 rs16963397 C/C or rs13334864 C/C polymorphisms had more >25 and >50% eGFR decline than their counterparts (log-rank test, P = 0.058 and P = 0.038, respectively). Cox regression analysis revealed that SLC12A3 rs16963397 C/C and rs13334864 C/C polymorphisms were significantly associated with an increased risk of >25% [hazard ratio (HR), 3.294; 95% confidence interval (CI), 1.158–9.368; P = 0.025] and >50% decline in eGFR (HR, 18.630; 95% CI, 1.529–227.005, P = 0.022) than their counterparts.ConclusionSLC12A3 polymorphisms are associated with renal function in Chinese patients with hypertension.

Background/Purpose: End-stage kidney disease (ESKD) is a global burden that reflects each country's unique condition. We used the National Health Insurance Research Database (NHIRD) of Taiwan to decipher changes in the mortality and international survival rates and to determine the effectiveness of the pre-end-stage renal disease care program (pre-ESRD care program) to guide future health policies for ESKD. Methods: We conducted a retrospective cohort analysis of the NHIRD data along with records from the catastrophic illness certificate program of ESKD patients from 2010 to 2018. Results: From 2010 to 2018, the annual dialysis-related mortality rate in Taiwan increased from 10.6 to 11.8 deaths per hundred patient-years. The mortality rate for patients below 40 years appears to be decreasing, reflecting the improved quality of care for ESKD patients. Patients above 75 years showed increasing mortality, indicating the prolonged survival and aging of the ESKD population. Patients undergoing dialysis who participated in the pre-ESRD care program had a higher post-dialysis initiation life expectancy than those who did not participate. Among the program enrollees, the post-dialysis initiation life expectancy was higher in patients who had participated for more than one year. Taiwan has one of the highest ESKD patient survival rates globally. Conclusion: From 2010 to 2018, the reduced mortality in young patients and aging of the ESKD population might indicate that the quality of care in Taiwan for ESKD has improved. Furthermore, a better survival rate after dialysis initiation was observed in the pre-ESRD care program participants.

BackgroundHemodialysis (HD) therapy is an indispensable tool used in critical care management. Patients undergoing HD are at risk for intradialytic adverse events, ranging from muscle cramps to cardiac arrest. So far, there is no effective HD device–integrated algorithm to assist medical staff in response to these adverse events a step earlier during HD. ObjectiveWe aimed to develop machine learning algorithms to predict intradialytic adverse events in an unbiased manner. MethodsThree-month dialysis and physiological time-series data were collected from all patients who underwent maintenance HD therapy at a tertiary care referral center. Dialysis data were collected automatically by HD devices, and physiological data were recorded by medical staff. Intradialytic adverse events were documented by medical staff according to patient complaints. Features extracted from the time series data sets by linear and differential analyses were used for machine learning to predict adverse events during HD. ResultsTime series dialysis data were collected during the 4-hour HD session in 108 patients who underwent maintenance HD therapy. There were a total of 4221 HD sessions, 406 of which involved at least one intradialytic adverse event. Models were built by classification algorithms and evaluated by four-fold cross-validation. The developed algorithm predicted overall intradialytic adverse events, with an area under the curve (AUC) of 0.83, sensitivity of 0.53, and specificity of 0.96. The algorithm also predicted muscle cramps, with an AUC of 0.85, and blood pressure elevation, with an AUC of 0.93. In addition, the model built based on ultrafiltration-unrelated features predicted all types of adverse events, with an AUC of 0.81, indicating that ultrafiltration-unrelated factors also contribute to the onset of adverse events. ConclusionsOur results demonstrated that algorithms combining linear and differential analyses with two-class classification machine learning can predict intradialytic adverse events in quasi-real time with high AUCs. Such a methodology implemented with local cloud computation and real-time optimization by personalized HD data could warn clinicians to take timely actions in advance.

The purpose of this study is to explore the impact of pollution control on industrial production efficiency in 31 provinces and cities in the Yellow River and Non-Yellow River basins in China from 2013 to 2017, using the methods of the directional distance function (hereinafter referred to as DDF) and the technology gap ratio (hereinafter referred to as TGR) in parallel, while taking the industrial production sector (labor force, total capital formation, energy consumption and industrial water consumption) and the pollution control sector (wastewater treatment funds and waste gas treatment funds) as input variables. Undesirable outputs (total wastewater discharge, lead, SO2 and smoke and dust in wastewater) and an ideal output variable (industrial output value) are taken as output variables. It is found that the total efficiency of DDF in the Non-Yellow River Basin is 0.9793, which is slightly better than 0.9688 in the Yellow River Basin. Among the 17 provinces and cities with a total efficiency of 1, only Shandong and Sichuan are located in the Yellow River Basin. The TGR values of 31 provinces, cities and administrative regions are less than 1, and the average TGR value of the Yellow River Basin is 0.3825, which is lower than the average TGR value of the Non-Yellow River Basin of 0.5234. We can start by improving the allocation of manpower and capital, implementing the use of pollution prevention and control funds, improving the technical level of industrial production, improving pollutant emission, and increasing output value to improve overall efficiency performance. This study uses the parallel method, taking the industrial production department and the pollution control department as inputs, to objectively evaluate the changes in industrial production efficiency and technology gap in the Yellow River and Non-Yellow River basins, which is conducive to mastering the situation of pollution control and industrial production efficiency, and provides the reference for SDG-6- and SDG-9-related policy making.

Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of nitric oxide synthase and plays a significant role in the pathogenesis of arteriovenous fistula (AVF) dysfunction. The aim of this study is to evaluate the effect of far-infrared (FIR) therapy on the maturation and patency of newly-created AVFs in patients with advanced diabetic kidney disease (DKD) as well as the concurrent change in plasma ADMA. The study enrolled 144 participants with advanced DKD where 101 patients were randomly allocated to the FIR therapy group (N = 50) and control group (N = 51). Patients receiving FIR therapy had a decreased AVF failure rate within 12 months (16% versus 35.3%; p = 0.027); decreased incremental change of ADMA concentration at the 3rd and 12th month; increased AVF blood flow at the 1st, 3rd, and 12th month; increased 3-month physiologic maturation rate (88% versus 68.6%; p = 0.034); increased 1-year unassisted AVF patency rate (84% versus 64.7%; p = 0.017); and increased clinical AVF maturation rate within 12 months (84% versus 62.7%; p = 0.029) compared to the control group. The study demonstrates that FIR therapy can reduce the incremental changes in plasma ADMA concentration, which may be associated with the improvement of AVF prognosis in patients with advanced DKD.

Background and Objectives: Osteoporosis and anemia are prevalent among chronic kidney disease stage 5D (CKD stage 5D) patients. Osteoblasts are known as the niche cells of hematopoietic stem cells (HSCs) and stimulate HSCs to form blood-cell lineages within bone marrow microenvironments. We hypothesized that an inverse correlation may exist between mean corpuscular volume (MCV), a surrogate for ineffective hematopoiesis, and bone mineral density (BMD) in the CKD stage 5D population. Materials and Methods: This is a cross-sectional designed cohort study evaluating CKD stage 5D patients who have received dialysis therapy for over three months. Baseline clinical characteristics and laboratory data were prospectively collected. The dual-energy X-ray absorptiometry (DXA) method was used to measure BMD at five sites, which were bilateral femoral neck, total hip, and lumbar spine 1–4. The Pearson correlation test was initially adopted, and a multivariate linear regression model was further applied for potential confounder adjustments. Results: From September 2020 to January 2021, a total of 123 CKD stage 5D patients were enrolled. The Pearson correlation test revealed a significant inverse association between MCV and BMD at bilateral femoral neck and lumbar spine. The lowest T-score of the five body sites was determined as the recorded T-score. After adjustments for several potential confounding factors, the multivariate linear regression model found consistent negative associations between T-score and MCV. Conclusions: The present study found significant inverse correlations between MCV and BMD at specific body locations in patients on dialysis. A decreased T-score was also found to be associated with macrocytosis after adjustments for confounding variables. However, direct evidence for the causative etiology was lacking.

Acute kidney injury (AKI) causes a lot of harm to human health but is treated by only supportive therapy in most cases. Recent evidence shows that mesenchymal stem cells (MSCs) benefit kidney regeneration through releasing paracrine factors and extracellular vesicles (EVs) to the recipient kidney cells and are considered to be promising cellular therapy for AKI. To develop more efficient, precise therapies for AKI, we review the therapeutic mechanism of MSCs and MSC-derived EVs in AKI and look for a better understanding of molecular signaling and cellular communication between donor MSCs and recipient kidney cells. We also review recent clinical trials of MSC-EVs in AKI. This review summarizes the molecular mechanisms of MSCs’ therapeutic effects on kidney regeneration, expecting to comprehensively facilitate future clinical application for treating AKI.

Polyacrylonitrile (AN69) filter membranes adsorb cytokines during continuous venovenous hemofiltration (CVVH). Although high-volume hemofiltration has shown limited benefits, the dose-effect relationship in CVVH with AN69 membranes on severe sepsis remains undetermined. This multi-centered study enrolled 266 patients with sepsis-induced multiorgan dysfunction syndrome (MODS) who underwent CVVH with AN69 membranes between 2014 and 2015. We investigated the effects of ultrafiltration rates (UFR) on mortality. We categorized patients that were treated with UFR of 20–25 mL/kg/h as the standard UFR group (n = 124) and those that were treated with a UFR >25 mL/kg/h as the high UFR group (n = 142). Among the patient characteristics, the baseline estimated glomerular filtration rates (eGFR) 2, hemoglobin levels p = 0.005). We concluded that in patients with sepsis-induced MODS, SOFA scores ≥15 predicted a poor rate of survival. High UFR setting >25 mL/kg/h in CVVH with AN69 membranes may reduce the mortality risk in these high-risk patients.

The purpose of this study is to analyze whether there are differences in the impact of corporate social responsibility on its financial performance and stock performance in different industries. The research period is from 2016 to 2018. The samples are selected from the corporate social responsibility awardwinning companies selected by Commonwealth Magazine and Vision Magazine, and the financial information comes from Taiwan Economic News (TEJ). The empirical results show that traditional heavy industries have been established for a long time and the equipment is relatively old, so it needs to pay a relatively high cost to improve. Therefore, in this type of industry, corporate social responsibility has a negative impact on its financial impact, and even if it is a reputation, it has won the evaluation of the public, but its stock characteristics are not easy to fluctuate, so the impact on its stock performance is not significant. On the contrary, in the other two industries, corporate social responsibility will not burden its financial performance, but will positively help its stock performance. Among them, in the electronics industry, corporate social responsibility will positively help its financial performance. It may be that this type of industry has a relatively high bargaining power for products and relatively advanced technology, so it can transfer the cost of corporate responsibility invested to the selling price of the product. [ABSTRACT FROM AUTHOR]

This paper examines the protection against systemic risks of the financial and stock performance of firms in receipt of 'corporate social responsibility' (CSR) awards. The data we obtained from the Taiwan Economic Journal (TEJ) in 2016-2018, comprised of CSR-award-recipient firms (CSR firms) voted for by the Common Wealth and Global Views magazines, for a sample period running from the third quarter of 2017 to the third quarter of 2018. Our empirical results reveal that in terms of their financial performance, as compared to non-CSR-award-recipient (non-CSR) firms, CSR firms failed to demonstrate any better protection against systemic risks (such as the US-China trade war). However, the stock performance of CSR firms clearly provided better protection than that of non-CSR firms; the reason for this observation is assumed to be the higher operational costs faced by CSR firms seeking to continue to pursue their CSR goals when encountering systemic risks. Nevertheless, participation in CSR is found to have an insurance-like effect on firm value, which clearly helps to increase the confidence of investors and reduce stock volatility. [ABSTRACT FROM AUTHOR]

Arteriovenous fistula (AVF) is the vascular access of choice for renal replacement therapy. However, AVF is susceptible to calcification with a high prevalence of 40%-65% in chronic hemodialysis patients. Repeated needle puncture for hemodialysis cannulation results in intimal denudation of AVF. We hypothesized that exposure to blood shear stress in the medial layer promotes venous smooth muscle cell (SMC) osteogenesis. While previous studies of shear stress focused on arterial-type SMCs, SMCs isolated from the vein had not been investigated. This study established a venous cell model of AVF using the fluid shear device, combined with a high phosphate medium to mimic the uremic milieu. Osteogenic gene expression of venous SMCs upon mechanical and chemical cues was analyzed in addition to the activated cell signaling pathways. Our findings indicated that upon shear stress and high phosphate environment, mechanical stimulation (shear stress) had an additive effect in up-regulation of an early osteogenic marker, Runx2. We further identified that the integrin ß1-ERK1/2 signaling pathway was responsible for the molecular basis of venous SMC osteogenesis upon shear stress exposure. Mitochondrial biogenesis also took part in the early stage of this venopathy pathogenesis, evident by the up-regulated mitochondrial transcription factor A and mitochondrial DNA polymerase γ in venous SMCs. In conclusion, synergistic effects of fluid shear stress and high phosphate induce venous SMC osteogenesis via the ERK1/2 pathway through activating the mechanosensing integrin ß1 signaling. The present study identified a promising druggable target for reducing AVF calcification, which deserves further in vivo investigations. [ABSTRACT FROM AUTHOR]

* Context.--Galectin-9 reduces tissue damage in certain immune-mediated glomerular diseases. However, its role in structural and functional renal changes in patients with varying types of chronic kidney disease (CKD) is less clear. Objective.--To investigate the association between plasma galectin-9 levels, proteinuria, tubulointerstitial lesions, and renal function in different CKD stages. Design.--We measured plasma galectin-9 levels in 243 patients undergoing renal biopsy for determining the CKD etiology. mRNA and protein expression levels of intrarenal galectin-9 were assessed by quantitative real-time polymerase chain reaction and immunostaining. Relationships between plasma galectin-9, clinical characteristics, and tubulointerstitial damage were analyzed with logistic regression. We investigated galectin-9 expression patterns in vitro in murine J774 macrophages treated with differing stimuli. Results.--To analyze the relationship between galectin-9 and clinical features, we divided the patients into 2 groups according to median plasma galectin-9 levels. The high galectin-9 group tended to be older and to have decreased renal function, higher proteinuria, and greater interstitial fibrosis. After multivariable adjustment, elevated plasma galectin-9 levels were independently associated with stage 3b or higher CKD. An analysis of gene expression in the tubulointerstitial compartment in the biopsy samples showed a significant positive correlation between intrarenal galectin-9 mRNA expression and plasma galectin-9 levels. Immunohistochemistry confirmed increased galectin-9 expression in the renal interstitium of patients with advanced CKD, and most galectin-9--positive cells were macrophages, as determined by double-immunofluorescence staining. In vitro experiments showed that galectin-9 expression in macrophages was significantly increased after interferon-c stimulation. Conclusions.--Our findings suggest that plasma galectin- 9 is a good biomarker for diagnosing advanced CKD. [ABSTRACT FROM AUTHOR]