Analysis of the Release Characteristics of Cu-Treated Antimicrobial Implant Surfaces Using Atomic Absorption Spectrometry

New developments of antimicrobial implant surfaces doped with copper (Cu) ions may minimize the risk of implant-associated infections. However, experimental evaluation of the Cu release is influenced by various test parameters. The aim of our study was to evaluate the Cu release characteristics in vitro according to the storage fluid and surface roughness. Plasma immersion ion implantation of Cu (Cu-PIII) and pulsed magnetron sputtering process of a titanium copper film (Ti-Cu) were applied to titanium alloy (Ti6Al4V) samples with different surface finishing of the implant material (polished, hydroxyapatite and corundum blasted). The samples were submersed into either double-distilled water, human serum, or cell culture medium. Subsequently, the Cu concentration in the supernatant was measured using atomic absorption spectrometry. The test fluid as well as the surface roughness can alter the Cu release significantly, whereby the highest Cu release was determined for samples with corundum-blasted surfaces stored in cell medium

Alterations of mTOR signaling impact metabolic stress resistance in colorectal carcinomas with BRAF and KRAS mutations

Metabolic reprogramming is as a hallmark of cancer, and several studies have reported that BRAF and KRAS tumors may be accompanied by a deregulation of cellular metabolism. We investigated how BRAF(V600E) and KRAS(G12V) affect cell metabolism, stress resistance and signaling in colorectal carcinoma cells driven by these mutations. KRAS(G12V) expressing cells are characterized by the induction of glycolysis, accumulation of lactic acid and sensitivity to glycolytic inhibition. Notably mathematical modelling confirmed the critical role of MCT1 designating the survival of KRAS(G12V) cells. Carcinoma cells harboring BRAF(V600E) remain resistant towards alterations of glucose supply or application of signaling or metabolic inhibitors. Altogether these data demonstrate that an oncogene-specific decoupling of mTOR from AMPK or AKT signaling accounts for alterations of resistance mechanisms and metabolic phenotypes. Indeed the inhibition of mTOR in BRAF(V600E) cells counteracts the metabolic predisposition and demonstrates mTOR as a potential target in BRAF(V600E)-driven colorectal carcinomas

Chemical and electronic characterization of methyl-terminated Si(111) surfaces by high-resolution synchrotron photoelectron spectroscopy

The chemical state, electronic properties, and geometric structure of methyl-terminated Si(111) surfaces prepared using a two-step chlorination/alkylation process were investigated using high-resolution synchrotron photoelectron spectroscopy and low-energy electron diffraction methods. The electron diffraction data indicated that the methylated Si surfaces maintained a (1×1) structure, where the dangling bonds of the silicon surface atoms were terminated by methyl groups. The surfaces were stable to annealing at 720 K. The high degree of ordering was reflected in a well-resolved vibrational fine structure of the carbon 1s photoelectron emission, with the fine structure arising from the excitation of C-H stretching vibrations having hnu=0.38±0.01 eV. The carbon-bonded surface Si atoms exhibited a well-defined x-ray photoelectron signal having a core level shift of 0.30±0.01 eV relative to bulk Si. Electronically, the Si surface was close to the flat-band condition. The methyl termination produced a surface dipole of –0.4 eV. Surface states related to piCH3 and sigmaSi-C bonding orbitals were identified at binding energies of 7.7 and 5.4 eV, respectively. Nearly ideal passivation of Si(111) surfaces can thus be achieved by methyl termination using the two-step chlorination/alkylation process

Finite Element Analysis of Osteosynthesis Screw Fixation in the Bone Stock: An Appropriate Method for Automatic Screw Modelling

The use of finite element analysis (FEA) has grown to a more and more important method in the field of biomedical engineering and biomechanics. Although increased computational performance allows new ways to generate more complex biomechanical models, in the area of orthopaedic surgery, solid modelling of screws and drill holes represent a limitation of their use for individual cases and an increase of computational costs. To cope with these requirements, different methods for numerical screw modelling have therefore been investigated to improve its application diversity. Exemplarily, fixation was performed for stabilization of a large segmental femoral bone defect by an osteosynthesis plate. Three different numerical modelling techniques for implant fixation were used in this study, i.e. without screw modelling, screws as solid elements as well as screws as structural elements. The latter one offers the possibility to implement automatically generated screws with variable geometry on arbitrary FE models. Structural screws were parametrically generated by a Python script for the automatic generation in the FE-software Abaqus/CAE on both a tetrahedral and a hexahedral meshed femur. Accuracy of the FE models was confirmed by experimental testing using a composite femur with a segmental defect and an identical osteosynthesis plate for primary stabilisation with titanium screws. Both deflection of the femoral head and the gap alteration were measured with an optical measuring system with an accuracy of approximately 3 µm. For both screw modelling techniques a sufficient correlation of approximately 95% between numerical and experimental analysis was found. Furthermore, using structural elements for screw modelling the computational time could be reduced by 85% using hexahedral elements instead of tetrahedral elements for femur meshing. The automatically generated screw modelling offers a realistic simulation of the osteosynthesis fixation with screws in the adjacent bone stock and can be used for further investigations

Metabonomic fingerprints of fasting plasma and spot urine reveal human pre-diabetic metabolic traits

Impaired glucose tolerance (IGT) which precedes overt type 2 diabetes (T2DM) for decades is associated with multiple metabolic alterations in insulin sensitive tissues. In an UPLC-qTOF-mass spectrometry-driven non-targeted metabonomics approach we investigated plasma as well as spot urine of 51 non-diabetic, overnight fasted individuals aiming to separate subjects with IGT from controls thereby identify pathways affected by the pre-diabetic metabolic state. We could clearly demonstrate that normal glucose tolerant (NGT) and IGT subjects clustered in two distinct groups independent of the investigated metabonome. These findings reflect considerable differences in individual metabolite fingerprints, both in plasma and urine. Pre-diabetes associated alterations in fatty acid-, tryptophan-, uric acid-, bile acid-, and lysophosphatidylcholine-metabolism, as well as the TCA cycle were identified. Of note, individuals with IGT also showed decreased levels of gut flora-associated metabolites namely hippuric acid, methylxanthine, methyluric acid, and 3-hydroxyhippuric acid. The findings of our non-targeted UPLC-qTOF-MS metabonomics analysis in plasma and spot urine of individuals with IGT vs NGT offers novel insights into the metabolic alterations occurring in the long, asymptomatic period preceding the manifestation of T2DM thereby giving prospects for new intervention targets

Insulin Sensitivity Is Reflected by Characteristic Metabolic Fingerprints - A Fourier Transform Mass Spectrometric Non-Targeted Metabolomics Approach

BACKGROUND: A decline in body insulin sensitivity in apparently healthy individuals indicates a high risk to develop type 2 diabetes. Investigating the metabolic fingerprints of individuals with different whole body insulin sensitivity according to the formula of Matsuda, et al. (ISI(Matsuda)) by a non-targeted metabolomics approach we aimed a) to figure out an unsuspicious and altered metabolic pattern, b) to estimate a threshold related to these changes based on the ISI, and c) to identify the metabolic pathways responsible for the discrimination of the two patterns. METHODOLOGY AND PRINCIPAL FINDINGS: By applying infusion ion cyclotron resonance Fourier transform mass spectrometry, we analyzed plasma of 46 non-diabetic subjects exhibiting high to low insulin sensitivities. The orthogonal partial least square model revealed a cluster of 28 individuals with alterations in their metabolic fingerprints associated with a decline in insulin sensitivity. This group could be separated from 18 subjects with an unsuspicious metabolite pattern. The orthogonal signal correction score scatter plot suggests a threshold of an ISI(Matsuda) of 15 for the discrimination of these two groups. Of note, a potential subgroup represented by eight individuals (ISI(Matsuda) value between 8.5 and 15) was identified in different models. This subgroup may indicate a metabolic transition state, since it is already located within the cluster of individuals with declined insulin sensitivity but the metabolic fingerprints still show some similarities with unaffected individuals (ISI >15). Moreover, the highest number of metabolite intensity differences between unsuspicious and altered metabolic fingerprints was detected in lipid metabolic pathways (arachidonic acid metabolism, metabolism of essential fatty acids and biosynthesis of unsaturated fatty acids), steroid hormone biosyntheses and bile acid metabolism, based on data evaluation using the metabolic annotation interface MassTRIX. CONCLUSIONS: Our results suggest that altered metabolite patterns that reflect changes in insulin sensitivity respectively the ISI(Matsuda) are dominated by lipid-related pathways. Furthermore, a metabolic transition state reflected by heterogeneous metabolite fingerprints may precede severe alterations of metabolism. Our findings offer future prospects for novel insights in the pathogenesis of the pre-diabetic phase

Medium Chain Acylcarnitines Dominate the Metabolite Pattern in Humans under Moderate Intensity Exercise and Support Lipid Oxidation

Background: Exercise is an extreme physiological challenge for skeletal muscle energy metabolism and has notable health benefits. We aimed to identify and characterize metabolites, which are components of the regulatory network mediating the beneficial metabolic adaptation to exercise

Genome-Wide Association Study and Functional Characterization Identifies Candidate Genes for Insulin-Stimulated Glucose Uptake

Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in \u3e55,000 participants from three ancestry groups. We identified ten new loci (P \u3c 5 × 10-8) not previously associated with postchallenge insulin resistance, eight of which were shown to share their genetic architecture with type 2 diabetes in colocalization analyses. We investigated candidate genes at a subset of associated loci in cultured cells and identified nine candidate genes newly implicated in the expression or trafficking of GLUT4, the key glucose transporter in postprandial glucose uptake in muscle and fat. By focusing on postprandial insulin resistance, we highlighted the mechanisms of action at type 2 diabetes loci that are not adequately captured by studies of fasting glycemic traits