The role of the signaling mediator Smad1 in BMP2-dependent osteo/chondrogenic development in mesenchymal progenitors (C3H10T1/2)

The aim of this research was to elucidate the functions of the three domains of the BMP2 signaling mediator-Smad1: the N-terminal domain, the C-terminal domain and the proline-rich linker domain, especially the function of the less conserved proline-rich linker region, in the mesenchymal differentiation processes, particularly in regard to osteo-/chondrogenic development was investigated by histological staining and also by RT-PCR analyses of the expression of several marker genes, which are specific or typical for osteogenic-, chondrogenic-, and adipogenic development. Smad1 and its biological active C domain initiated osteogenic development in the C3H10T1/2 cells and stimulated in C3H10T1/2BMP2 cells differentiation into osteogenic lineages. The N domain was sufficient to initiate transcription of some osteogenic marker genes in parental C3H10T1/2 cells. However, this domain blocked osteogenic development when recombinantly expressed in C3H10T1/2BMP2 cells. The P domain dominant-negatively inhibited the BMP2-dependent osteogenesis in C3H10T1/2 cells. The P domain of Smad1 inhibited Smad1 C domain dependent osteogenesis in a dose dependent manner. And the inhibitory effect of P domain on osteogenesis is not a common property of all Smads, but seems specific for Smad1. Smad1 and its domains do obviously not participate in the BMP2-dependent chondrogenic development. The trancriptional assays of promoter luciferase constructs for some BMP-responsive genes, substantiated the histological and genetic analyses of Smad1 by showing stimulation of the promoter luciferase activities by the Smad1 C domain. The analysis of effects of the Smad1 domains has important value in understanding the process of BMP2-dependent osteo-/chondrogenic development in mesenchymal progenitors (C3H10T1/2).Die vorliegende Forschung zielt darauf ab, die Funktionen der drei Domänen des BMP2-Signalmediators Smad1, insbesondere die Funktion der weniger konservierten Linkerdomäne in dem mesenchymalen Differentierungsprozeß zu ermitteln. Vor allem werden ihre Funktionen in bezug auf die osteo-/chondrogene Entwicklung mittels histologischer Färbung und genetischer Anaylse der Expression mehrerer Markergene, die spezifisch oder typisch für die osteogene, chondrogene und adipogene Entwicklung sind, untersucht. Smad1 und sein biologisch aktive C-Domäne führen osteogene Entwicklung in C3H10T1/2 -Zellen ein und stimulieren die Differenterung von C3H10T1/2BMP2-Zellen zur osteogenetischen Zellinie. Die N-Domäne ist in der Lage, die Transkription von manchen osteogenetischen Markergenen in der C3H10T1/2-Zellen zu induzieren, während sie die osteogenetische Entwicklung der rekombinanten C3H10T1/2BMP hindert. Die Linkerdomäne inhibiert die BMP2-abhängige Osteogenese auf dominant negative Weise. Die von Smad1 C-Domäne abhänige Osteogenese wird je nach der Dosis der Smad1 P-Domäne mehr oder weniger gehindert. Die Inhibierung der Osteogenese durch die P-Domäne ist aber nur auf Smad1 beschränkt. Smad1 und ihre Domäne zeigen keine Auswirkung auf die BMP2-abhänige chondrogene Entwicklung. Die Transkriptionsanalyse der Promotor-Luciferase-Konstrukte der BMP-reagierten Gene bestätigt die Ergebnisse der histologischen Färbung und genetischen Analyse. Die Analyse der Auswirkung der Smad1-Domäne hat eine große Bedeutung für das Verständnis des Prozesses der BMP-abhängigen osteog-/chondrogene Entwicklung in den mesenchymalen Vorläuferzellen (C3H10T1/2)

Incorporating longitudinal biomarkers for dynamic risk prediction in the era of big data: A pseudo‐observation approach

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163461/3/sim8687.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163461/2/sim8687-sup-0001-supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163461/1/sim8687_am.pd

Transcriptome Analysis of Proximal Tubular Cells (HK-2) Exposed to Urines of Type 1 Diabetes Patients at Risk of Early Progressive Renal Function Decline

Background: In patients with Type 1 Diabetes (T1D) who develop microalbuminuria, progressive decline in glomerular filtration rate (GFR) may be initiated by leakage into the urine of toxic proteins (txUPs). This study tested this hypothesis. Methods: After archiving baseline urine, we followed T1D patients with microalbuminuria for 8–12 years to distinguish those in whom GFR declined (Decliners) and those in whom it remained stable (Non-decliners). Human proximal tubular cells (HK-2 cells) were grown in serum-free medium enriched with pooled urines from Decliners or Non-decliners. We determined genome-wide expression profiles in extracted mRNA. Results: The two pooled urines induced differential expression of 312 genes. In terms of gene ontology, molecular functions of the 119 up-regulated genes were enriched for protein binding and peptidase inhibitor activities. Their biologic processes were enriched for defense response, responses to other organisms, regulation of cellular processes, or response to stress or stimulus, and programmed cell death. The 195 down-regulated genes were disproportionately represented in molecular functions of cation binding, hydrolase activity, and DNA binding. They were disproportionately represented in biological processes for regulation of metabolic processes, nucleic acid metabolic processes, cellular response to stress and macromolecule biosynthesis. The set of up-regulated genes in HK-2 cells overlaps significantly with sets of over-expressed genes in tubular and interstitial compartments of kidney biopsies from patients with advanced DN (33 genes in one study and 25 in the other compared with 10.3 expected by chance, p<$10^{−9}$ and p<$10^{−4}$, respectively). The overlap included genes encoding chemokines and cytokines. Overlap of down-regulated genes was no more than expected by chance. Conclusions: Molecular processes in tubules and interstitium seen in advanced diabetic nephropathy can be induced in vitro by exposure to urine from patients with minimal microalbuminuria who subsequently developed progressive renal function decline, presumably due to putative txUPs

Turning a native or corroded Mg alloy surface into an anti-corrosion coating in excited CO2

Despite their energy-efficient merits as promising light-weight structural materials, magnesium (Mg) based alloys suffer from inadequate corrosion resistance. One primary reason is that the native surface film on Mg formed in air mainly consists of Mg(OH)2 and MgO, which is porous and unprotective, especially in humid environments. Here, we demonstrate an environmentally benign method to grow a protective film on the surface of Mg/Mg alloy samples at room temperature, via a direct reaction of already-existing surface film with excited CO2. Moreover, for samples that have been corroded obviously on surface, the corrosion products can be converted directly to create a new protective surface. Mechanical tests show that compared with untreated samples, the protective layer can elevate the yield stress, suppress plastic instability and prolong compressive strains without peeling off from the metal surface. This environmentally friendly surface treatment method is promising to protect Mg alloys, including those already-corroded on the surface.China. Ministry of Science and Technology. National Key Research and Development Program (No. 2017YFB0702001)National Natural Science Foundation of China (51621063)National Natural Science Foundation of China (51601141)National Natural Science Foundation of China ( 51401239)Shaanxi Sheng (China). Science and Technology Department (2016KTZDGY-04-03)Shaanxi Sheng (China). Science and Technology Department (2016KTZDGY-04-04)China Postdoctoral Science Foundation (2016M600788)China University of Petroleum. Science Foundation (No. 2462018BJC005)China University of Petroleum. Science Foundation (C201603)National Science Foundation (U.S.) (ECCS-1610806

Urinary Epidermal Growth Factor/Creatinine Ratio and Graft Failure in Renal Transplant Recipients:A Prospective Cohort Study

Graft failure (GF) remains a significant limitation to improve long-term outcomes in renal transplant recipients (RTR). Urinary epidermal growth factor (uEGF) is involved in kidney tissue integrity, with a reduction of its urinary excretion being associated with fibrotic processes and a wide range of renal pathologies. We aimed to investigate whether, in RTR, uEGF is prospectively associated with GF. In this prospective cohort study, RTR with a functioning allograft >= 1-year were recruited and followed-up for three years. uEGF was measured in 24-hours urine samples and normalized by urinary creatinine (Cr). Its association with risk of GF was assessed by Cox-regression analyses and its predictive ability by C-statistic. In 706 patients, uEGF/Cr at enrollment was 6.43 [IQR 4.07-10.77] ng/mg. During follow-up, 41(6%) RTR developed GF. uEGF/Cr was inversely associated with the risk of GF (HR 0.68 [95% CI 0.59-0.78]; P <0.001), which remained significant after adjustment for immunosuppressive therapy, estimated Glomerular Filtration Rate, and proteinuria. C-statistic of uEGF/Cr for GF was 0.81 (P <0.001). We concluded that uEGF/Cr is independently and inversely associated with the risk of GF and depicts strong prediction ability for this outcome. Further studies seem warranted to elucidate whether uEGF might be a promising marker for use in clinical practice

Machine Learning based Early Prediction of End-stage Renal Disease in Patients with Diabetic Kidney Disease using Clinical Trials Data

AimTo predict end‐stage renal disease (ESRD) in patients with type 2 diabetes by using machine‐learning models with multiple baseline demographic and clinical characteristics.Materials and methodsIn total, 11 789 patients with type 2 diabetes and nephropathy from three clinical trials, RENAAL (n = 1513), IDNT (n = 1715) and ALTITUDE (n = 8561), were used in this study. Eighteen baseline demographic and clinical characteristics were used as predictors to train machine‐learning models to predict ESRD (doubling of serum creatinine and/or ESRD). We used the area under the receiver operator curve (AUC) to assess the prediction performance of models and compared this with traditional Cox proportional hazard regression and kidney failure risk equation models.ResultsThe feed forward neural network model predicted ESRD with an AUC of 0.82 (0.76‐0.87), 0.81 (0.75‐0.86) and 0.84 (0.79‐0.90) in the RENAAL, IDNT and ALTITUDE trials, respectively. The feed forward neural network model selected urinary albumin to creatinine ratio, serum albumin, uric acid and serum creatinine as important predictors and obtained a state‐of‐the‐art performance for predicting long‐term ESRD.ConclusionsDespite large inter‐patient variability, non‐linear machine‐learning models can be used to predict long‐term ESRD in patients with type 2 diabetes and nephropathy using baseline demographic and clinical characteristics. The proposed method has the potential to create accurate and multiple outcome prediction automated models to identify high‐risk patients who could benefit from therapy in clinical practice.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163629/2/dom14178.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163629/1/dom14178_am.pd

A metabolomics based molecular pathway analysis for how the SGLT2-inhibitor dapagliflozin may slow kidney function decline in patients with diabetes

Aim: To investigate which metabolic pathways are targeted by the sodium-glucose co-transporter-2 inhibitor dapagliflozin to explore the molecular processes involved in its renal protective effects. Methods: An unbiased mass spectrometry plasma metabolomics assay was performed on baseline and follow-up (week 12) samples from the EFFECT II trial in patients with type 2 diabetes with non-alcoholic fatty liver disease receiving dapagliflozin 10 mg/day (n = 19) or placebo (n = 6). Transcriptomic signatures from tubular compartments were identified from kidney biopsies collected from patients with diabetic kidney disease (DKD) (n = 17) and healthy controls (n = 30) from the European Renal cDNA Biobank. Serum metabolites that significantly changed after 12 weeks of dapagliflozin were mapped to a metabolite-protein interaction network. These proteins were then linked with intra-renal transcripts that were associated with DKD or estimated glomerular filtration rate (eGFR). The impacted metabolites and their protein-coding transcripts were analysed for enriched pathways. Results: Of all measured (n = 812) metabolites, 108 changed (P &lt; 0.05) during dapagliflozin treatment and 74 could be linked to 367 unique proteins/genes. Intra-renal mRNA expression analysis of the genes encoding the metabolite-associated proteins using kidney biopsies resulted in 105 genes that were significantly associated with eGFR in patients with DKD, and 135 genes that were differentially expressed between patients with DKD and controls. The combination of metabolites and transcripts identified four enriched pathways that were affected by dapagliflozin and associated with eGFR: glycine degradation (mitochondrial function), TCA cycle II (energy metabolism), L-carnitine biosynthesis (energy metabolism) and superpathway of citrulline metabolism (nitric oxide synthase and endothelial function). Conclusion: The observed molecular pathways targeted by dapagliflozin and associated with DKD suggest that modifying molecular processes related to energy metabolism, mitochondrial function and endothelial function may contribute to its renal protective effect.</p