A full body musculoskeletal model based on flexible multibody simulation approach utilised in bone strain analysis during human locomotion

Load-induced strains applied to bone can stimulate its development and adaptation. In order to quantify the incident strains within the skeleton, in vivo implementation of strain gauges on the surfaces of bone is typically used. However, in vivo strain measurements require invasive methodology that is challenging and limited to certain regions of superficial bones only such as the anterior surface of the tibia. Based on our previous study [Al Nazer et al. (2008) J Biomech. 41:1036–1043], an alternative numerical approach to analyse in vivo strains based on the flexible multibody simulation approach was proposed. The purpose of this study was to extend the idea of using the flexible multibody approach in the analysis of bone strains during physical activity through integrating the magnetic resonance imaging (MRI) technique within the framework. In order to investigate the reliability and validity of the proposed approach, a three-dimensional full body musculoskeletal model with a flexible tibia was used as a demonstration example. The model was used in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model was developed using the actual geometry of human tibia, which was obtained from three-dimensional reconstruction of MRI. Motion capture data obtained from walking at constant velocity were used to drive the model during the inverse dynamics simulation in order to teach the muscles to reproduce the motion in the forward dynamics simulation. Based on the agreement between the literature-based in vivo strain measurements and the simulated strain results, it can be concluded that the flexible multibody approach enables reasonable predictions of bone strain in response to dynamic loading. The information obtained from the present approach can be useful in clinical applications including devising exercises to prevent bone fragility or to accelerate fracture healing.     

Proteomic Differences Between Hepatocellular Carcinoma and Nontumorous Liver Tissue Investigated by a Combined Gel-based and Label-free Quantitative Proteomics Study

Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 × HCC versus 7 × nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n = 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies.Hepatocellular carcinoma (HCC)¹ currently is the fifth most common malignancy worldwide with an annual incidence up to 500 per 100,000 individuals depending on the geographic region investigated. Whereas 80% of new cases occur in developing countries, the incidence increases in industrialized nations including Western Europe, Japan, and the United States (1). To manage patients with HCC, tumor markers are very important tools for diagnosis, indicators of disease progression, outcome prediction, and evaluation of treatment efficacy. Several tumor markers have been reported for HCC, including α-fetoprotein (AFP) (2), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) (3), and des-γ-carboxyl prothrombin (DCP) (4). However, none of these tumor markers show 100% sensitivity or specificity, which calls for new and better biomarkers.To identify novel biomarkers of HCC, many clinical studies using “omics”-based methods have been reported over the past decade (5–6). In particular, the proteomics-based approach has turned out to be a promising one, offering several quantification techniques to reveal differences in protein expression that are caused by a particular disease. In most studies, the well-established 2D-DIGE technique has been applied for protein quantification followed by identification via mass spectrometry (7–15). Even if the quantification is very accurate and sensitive in this gel-based approach, the relatively high amount of protein sample necessary for protein identification is the major disadvantage of this technique. Several mass-spectrometry-based quantitative studies using labeling-techniques like SILAC (stable isotope labeling by amino acids in cell culture) or iTRAQ (isobaric tags for relative and absolute quantification) have also been carried out for biomarker discovery of HCC (16–18). Here, the concomitant protein quantification and identification in a mass spectrometer allows high-throughput analyses. However, such experiments imply additional labeling reactions (in case of iTRAQ) or are limited to tissue culture systems (in case of SILAC). In the latter case, one can overcome the limitation by using the isotope-labeled proteins obtained from tissue culture as an internal standard added to a corresponding tissue sample. This approach is known as CDIT (culture-derived isotope tags) and was applied in a HCC study, very recently (19). Label-free proteomics approaches based on quantification by ion-intensities or spectral counting offer another possibility for biomarker discovery. These approaches are relatively cheap compared with the labeling approaches, because they do not require any labeling reagents and furthermore they allow for high-throughput and sensitive analyses in a mass spectrometer. A quantitative study of HCC using spectral counting has been reported (20), whereas to our knowledge an ion-intensity-based study has not been performed yet. Apart from these quantification strategies, protein alterations in HCC have been studied by MALDI imaging, as well. Here, the authors could show that based on its proteomic signature, hepatocellular carcinoma can be discriminated with high accuracy from liver metastasis samples or other cancer types (21) as well as liver cirrhosis (22). Based on these results, it could be assumed that MALDI imaging might be a promising alternative to standard histological methods in the future.Here, we report a quantitative proteomic study that combines two different techniques, namely the well-established 2D-DIGE approach and a label-free ion-intensity-based quantification via mass spectrometry and liquid chromatography. To our knowledge this is the first time such a combined study was performed with regard to hepatocellular carcinoma. By comparing the results of both studies, we aim to identify high-confident biomarker candidates of HCC, as gel- and LC-MS-based techniques are complementary. To verify the differential protein expressions detected in our proteomic studies we performed additional immunological verifications for selected proteins within two different sample sets (Fig. 1).Open in a separate windowFig. 1.Schematic representation of the applied workflow.     

Effect of GA3 and 2,4-D foliar application on the anatomy of date palm (Phoenix dactylifera L.) seedling leaf

Two concentrations (10-5M and 10-3M) of both GA3 and 2,4-D were used as foliar spray to evaluate the response of date palm (Phoenix dactylifera L.) cv. Khedri seedlings. They affected some of the anatomical characteristics of the first leaf emerging after the beginning of the spray. The high concentration of GA3 increased the size of the midrib and its vascular bundle numbers. Both low and high concentrations of 2,4-D inhibited the formation of the midrib. 2,4-D in both low and high concentrations decreased the number of vessels in both protoxylem and metaxylem and also decreased their diameters, where as GA3 in low and high concentrations have less effect on the number of vessels and its diameters. GA3 in high concentration increased the number of vascular bundles in 1mm long of the leaf blade, while 2,4-D in low and high concentrations decreased their numbers. 10-3M of 2,4-D increased the size and layers of special hypodermal cells.     

TNFR1 determines progression of chronic liver injury in the IKKγ/Nemo genetic model

Death receptor-mediated hepatocyte apoptosis is implicated in a wide range of liver diseases including viral and alcoholic hepatitis, ischemia/reperfusion injury, fulminant hepatic failure, cholestatic liver injury, as well as cancer. Deletion of NF-κB essential modulator in hepatocytes (IKKγ/Nemo) causes spontaneous progression of TNF-mediated chronic hepatitis to hepatocellular carcinoma (HCC). Thus, we analyzed the role of death receptors including TNFR1 and TRAIL in the regulation of cell death and the progression of liver injury in IKKγ/Nemo-deleted livers. We crossed hepatocyte-specific IKKγ/Nemo knockout mice (Nemo^Δhepa) with constitutive TNFR1^−/− and TRAIL^−/− mice. Deletion of TNFR1, but not TRAIL, decreased apoptotic cell death, compensatory proliferation, liver fibrogenesis, infiltration of immune cells as well as pro-inflammatory cytokines, and indicators of tumor growth during the progression of chronic liver injury. These events were associated with diminished JNK activation. In contrast, deletion of TNFR1 in bone-marrow-derived cells promoted chronic liver injury. Our data demonstrate that TNF- and not TRAIL signaling determines the progression of IKKγ/Nemo-dependent chronic hepatitis. Additionally, we show that TNFR1 in hepatocytes and immune cells have different roles in chronic liver injury–a finding that has direct implications for treating chronic liver disease.     

Characterization of water and wildlife strains as a subgroup of Campylobacter jejuni using DNA microarrays

Campylobacter jejuni is the leading cause of human bacterial gastroenteritis worldwide, but source attribution of the organism is difficult. Previously, DNA microarrays were used to investigate isolate source, which suggested a non‐livestock source of infection. In this study we analysed the genome content of 162 clinical, livestock and water and wildlife (WW) associated isolates combined with the previous study. Isolates were grouped by genotypes into nine clusters (C1 to C9). Multilocus sequence typing (MLST) data demonstrated that livestock associated clonal complexes dominated clusters C1–C6. The majority of WW isolates were present in the C9 cluster. Analysis of previously reported genomic variable regions demonstrated that these regions were linked to specific clusters. Two novel variable regions were identified. A six gene multiplex PCR (mPCR) assay, designed to effectively differentiated strains into clusters, was validated with 30 isolates. A further five WW isolates were tested by mPCR and were assigned to the C7‐C9 group of clusters. The predictive mPCR test could be used to indicate if a clinical case has come from domesticated or WW sources. Our findings provide further evidence that WW C. jejuni subtypes show niche adaptation and may be important in causing human infection.     

Does the presence of grassy strips and landscape grain affect the spatial distribution of aphids and their carabid predators?

• 1 We investigated, over the course of 2 years, the spatial distribution and abundance of two species of aphid, Metopolophium dirhodum and Sitobion avenae, and predatory species of carabid. This was undertaken in 24 wheat fields in ‘coarse‐grain’ and ‘fine‐grain’ landscapes in western France. A greater percentage of the latter landscape was covered by hedgerows and grassland and the total area covered by fields and the average size of the fields were smaller.
• 2 The effects on aphid abundance of the distance from field margins, the presence of grassy strips and carabid abundance were determined in both landscapes.
• 3 Both aphid species were more abundant in the ‘fine‐grain’ landscape, which may have been a result of the higher density of semi‐natural elements. In both types of landscape, the total numbers of aphids were negatively correlated with the distance from the field margin. This may have been because aphids were dispersing from overwintering sites in field margins. The abundance of M. dirhodum was strongly negatively correlated with the presence of grassy strips in the ‘coarse‐grain’ landscape, although there were no such significant correlations for either of the aphid species in the ‘fine‐grain’ landscape.
• 4 Aphid and carabid abundances were negatively correlated in the ‘fine‐grain’ and positively in ‘coarse‐grain’ landscape.
• 5 The results obtained in the present study emphasize the importance of semi‐natural areas in agricultural landscapes in shaping the spatial distribution of aphids and carabid beetles, their natural enemies, at different spatial scales.

     

Reconstructing Coherent Networks from Electroencephalography and Magnetoencephalography with Reduced Contamination from Volume Conduction or Magnetic Field Spread

Volume conduction (VC) and magnetic field spread (MFS) induce spurious correlations between EEG/MEG sensors, such that the estimation of functional networks from scalp recordings is inaccurate. Imaginary coherency [1] reduces VC/MFS artefacts between sensors by assuming that instantaneous interactions are caused predominantly by VC/MFS and do not contribute to the imaginary part of the cross-spectral densities (CSDs). We propose an adaptation of the dynamic imaging of coherent sources (DICS) [2] - a method for reconstructing the CSDs between sources, and subsequently inferring functional connectivity based on coherences between those sources. Firstly, we reformulate the principle of imaginary coherency by performing an eigenvector decomposition of the imaginary part of the CSD to estimate the power that only contributes to the non-zero phase-lagged (NZPL) interactions. Secondly, we construct an NZPL-optimised spatial filter with two a priori assumptions: (1) that only NZPL interactions exist at the source level and (2) the NZPL CSD at the sensor level is a good approximation of the projected source NZPL CSDs. We compare the performance of the NZPL method to the standard method by reconstructing a coherent network from simulated EEG/MEG recordings. We demonstrate that, as long as there are phase differences between the sources, the NZPL method reliably detects the underlying networks from EEG and MEG. We show that the method is also robust to very small phase lags, noise from phase jitter, and is less sensitive to regularisation parameters. The method is applied to a human dataset to infer parts of a coherent network underpinning face recognition.     

Frondoside A Suppressive Effects on Lung Cancer Survival,Tumor Growth,Angiogenesis, Invasion,and Metastasis

A major challenge for oncologists and pharmacologists is to develop less toxic drugs that will improve the survival of lung cancer patients. Frondoside A is a triterpenoid glycoside isolated from the sea cucumber, Cucumaria frondosa and was shown to be a highly safe compound. We investigated the impact of Frondoside A on survival, migration and invasion in vitro, and on tumor growth, metastasis and angiogenesis in vivo alone and in combination with cisplatin. Frondoside A caused concentration-dependent reduction in viability of LNM35, A549, NCI-H460-Luc2, MDA-MB-435, MCF-7, and HepG2 over 24 hours through a caspase 3/7-dependent cell death pathway. The IC50 concentrations (producing half-maximal inhibition) at 24 h were between 1.7 and 2.5 µM of Frondoside A. In addition, Frondoside A induced a time- and concentration-dependent inhibition of cell migration, invasion and angiogenesis in vitro. Frondoside A (0.01 and 1 mg/kg/day i.p. for 25 days) significantly decreased the growth, the angiogenesis and lymph node metastasis of LNM35 tumor xenografts in athymic mice, without obvious toxic side-effects. Frondoside A (0.1–0.5 µM) also significantly prevented basal and bFGF induced angiogenesis in the CAM angiogenesis assay. Moreover, Frondoside A enhanced the inhibition of lung tumor growth induced by the chemotherapeutic agent cisplatin. These findings identify Frondoside A as a promising novel therapeutic agent for lung cancer.     

Association between Gestational Weight Gain and Postpartum Diabetes: Evidence from a Community Based Large Cohort Study

We have investigated the prospective association between excess gestational weight gain (GWG) and development of diabetes by 21 years post-partum using a community-based large prospective cohort study in Brisbane, Australia. There were 3386 mothers for whom complete data were available on GWG, pre-pregnancy BMI and self-reported diabetes 21 years post-partum. We used The Institute of Medicine (IOM) definition to categorize GWG as inadequate, adequate and excessive. We found 839 (25.78%) mothers gained inadequate weight, 1,353 (39.96%) had adequate weight gain and 1,194 (35.26%) had gained excessive weight during pregnancy. At 21 years post-partum, 8.40% of mothers self-reported a diagnosis of diabetes made by their doctor. In the age adjusted model, we found mothers who gained excess weight during pregnancy were 1.47(1.11,1.94) times more likely to experience diabetes at 21 years post-partum compared to the mothers who gained adequate weight. This association was not explained by the potential confounders including maternal age, parity, education, race, smoking, TV watching and exercise. However, this association was mediated by the current BMI. There was no association for the women who had normal BMI before pregnancy and gained excess weight during pregnancy. The findings of this study suggest that women who gain excess weight during pregnancy are at greater risk of being diagnosed with diabetes in later life. This relationship is likely mediated through the pathway of post-partum weight-retention and obesity. This study adds evidence to the argument that excessive GWG during pregnancy for overweight mothers has long term maternal health implications.     

Virulence of infecting Helicobacter pyloristrains and intensity of mononuclear cell infiltration are associated with levels of DNA hypermethylation in gastric mucosae

DNA methylation changes are known to occur in gastric cancers and in premalignant lesions of the gastric mucosae. In order to examine variables associated with methylation levels, we quantitatively evaluated DNA methylation in tumors, non-tumor gastric mucosae, and in gastric biopsies at promoters of 5 genes with methylation alterations that discriminate gastric cancers from non-tumor epithelia (EN1, PCDH10, RSPO2, ZIC1, and ZNF610). Among Colombian subjects at high and low risk for gastric cancer, biopsies from subjects from the high-risk region had significantly higher levels of methylation at these 5 genes than samples from subjects in the low risk region (p ≤ 0.003). When results were stratified by Helicobacter pylori infection status, infection with a cagA positive, vacA s1m1 strain was significantly associated with highest methylation levels, compared with other strains (p = 0.024 to 0.001). More severe gastric inflammation and more advanced precancerous lesions were also associated with higher levels of DNA methylation (p ≤ 0.001). In a multivariate model, location of residence of the subject and the presence of cagA and vacA s1m1 in the H. pylori strain were independent variables associated with higher methylation in all 5 genes. High levels of mononuclear cell infiltration were significantly related to methylation in PCDH10, RSPO2, and ZIC1 genes. These results indicate that for these genes, levels of methylation in precancerous lesions are related to H. pylori virulence, geographic region and measures of chronic inflammation. These genes seem predisposed to sustain significant quantitative changes in DNA methylation at early stages of the gastric precancerous process.