Ultra-strong Adhesion of Graphene Membranes

As mechanical structures enter the nanoscale regime, the influence of van der Waals forces increases. Graphene is attractive for nanomechanical systems because its Young's modulus and strength are both intrinsically high, but the mechanical behavior of graphene is also strongly influenced by the van der Waals force. For example, this force clamps graphene samples to substrates, and also holds together the individual graphene sheets in multilayer samples. Here we use a pressurized blister test to directly measure the adhesion energy of graphene sheets with a silicon oxide substrate. We find an adhesion energy of 0.45 \pm 0.02 J/m2 for monolayer graphene and 0.31 \pm 0.03 J/m2 for samples containing 2-5 graphene sheets. These values are larger than the adhesion energies measured in typical micromechanical structures and are comparable to solid/liquid adhesion energies. We attribute this to the extreme flexibility of graphene, which allows it to conform to the topography of even the smoothest substrates, thus making its interaction with the substrate more liquid-like than solid-like.Comment: to appear in Nature Nanotechnolog

STM Spectroscopy of ultra-flat graphene on hexagonal boron nitride

Graphene has demonstrated great promise for future electronics technology as well as fundamental physics applications because of its linear energy-momentum dispersion relations which cross at the Dirac point. However, accessing the physics of the low density region at the Dirac point has been difficult because of the presence of disorder which leaves the graphene with local microscopic electron and hole puddles, resulting in a finite density of carriers even at the charge neutrality point. Efforts have been made to reduce the disorder by suspending graphene, leading to fabrication challenges and delicate devices which make local spectroscopic measurements difficult. Recently, it has been shown that placing graphene on hexagonal boron nitride (hBN) yields improved device performance. In this letter, we use scanning tunneling microscopy to show that graphene conforms to hBN, as evidenced by the presence of Moire patterns in the topographic images. However, contrary to recent predictions, this conformation does not lead to a sizable band gap due to the misalignment of the lattices. Moreover, local spectroscopy measurements demonstrate that the electron-hole charge fluctuations are reduced by two orders of magnitude as compared to those on silicon oxide. This leads to charge fluctuations which are as small as in suspended graphene, opening up Dirac point physics to more diverse experiments than are possible on freestanding devices.Comment: Nature Materials advance online publication 13/02/201

What Does Brain Response to Neutral Faces Tell Us about Major Depression? Evidence from Machine Learning and fMRI

Introduction: A considerable number of previous studies have shown abnormalities in the processing of emotional faces in major depression. Fewer studies, however, have focused specifically on abnormal processing of neutral faces despite evidence that depressed patients are slow and less accurate at recognizing neutral expressions in comparison with healthy controls. The current study aimed to investigate whether this misclassification described behaviourally for neutral faces also occurred when classifying patterns of brain activation to neutral faces for these patients. Methods: Two independent depressed samples: (1) Nineteen medication-free patients with depression and 19 healthy volunteers and (2) Eighteen depressed individuals and 18 age and gender-ratio-matched healthy volunteers viewed emotional faces (sad/neutral; happy/neutral) during an fMRI experiment. We used a new pattern recognition framework: first, we trained the classifier to discriminate between two brain states (e.g. viewing happy faces vs. viewing neutral faces) using data only from healthy controls (HC). Second, we tested the classifier using patterns of brain activation of a patient and a healthy control for the same stimuli. Finally, we tested if the classifier's predictions (predictive probabilities) for emotional and neutral face classification were different for healthy controls and depressed patients. Results: Predictive probabilities to patterns of brain activation to neutral faces in both groups of patients were significantly lower in comparison to the healthy controls. This difference was specific to neutral faces. There were no significant differences in predictive probabilities to patterns of brain activation to sad faces (sample 1) and happy faces (samples 2) between depressed patients and healthy controls. Conclusions: Our results suggest that the pattern of brain activation to neutral faces in depressed patients is not consistent with the pattern observed in healthy controls subject to the same stimuli. This difference in brain activation might underlie the behavioural misinterpretation of the neutral faces content by the depressed patients. © 2013 Oliveira et al

Transient peak-strain matching partially recovers the age-impaired mechanoadaptive cortical bone response

Mechanoadaptation maintains bone mass and architecture; its failure underlies age-related decline in bone strength. It is unclear whether this is due to failure of osteocytes to sense strain, osteoblasts to form bone or insufficient mechanical stimulus. Mechanoadaptation can be restored to aged bone by surgical neurectomy, suggesting that changes in loading history can rescue mechanoadaptation. We use non-biased, whole-bone tibial analyses, along with characterisation of surface strains and ensuing mechanoadaptive responses in mice at a range of ages, to explore whether sufficient load magnitude can activate mechanoadaptation in aged bone. We find that younger mice adapt when imposed strains are lower than in mature and aged bone. Intriguingly, imposition of short-term, high magnitude loading effectively primes cortical but not trabecular bone of aged mice to respond. This response was regionally-matched to highest strains measured by digital image correlation and to osteocytic mechanoactivation. These data indicate that aged bone’s loading response can be partially recovered, non-invasively by transient, focal high strain regions. Our results indicate that old murine bone does respond to load when the loading is of sufficient magnitude, and bones’ age-related adaptation failure may be due to insufficient mechanical stimulus to trigger mechanoadaptation

In Vivo Mechanical Loading Modulates Insulin-Like Growth Factor Binding Protein-2 Gene Expression in Rat Osteocytes

Mechanical stimulation is essential for maintaining skeletal integrity. Mechanosensitive osteocytes are important during the osteogenic response. The growth hormone-insulin-like growth factor (GH-IGF) axis plays a key role during regulation of bone formation and remodeling. Insulin-like growth factor binding proteins (IGFBPs) are able to modulate IGF activity. The aim of this study was to characterize the role of IGFBP-2 in the translation of mechanical stimuli into bone formation locally in rat tibiae. Female Wistar rats were assigned to three groups (n = 5): load, sham, and control. The four-point bending model was used to induce a single period of mechanical loading on the tibial shaft. The effect on IGFBP-2 mRNA expression 6 hours after stimulation was determined with nonradioactive in situ hybridization on decalcified tibial sections. Endogenous IGFBP-2 mRNA was expressed in trabecular and cortical osteoblasts, some trabecular and subendocortical osteocytes, intracortical endothelial cells of blood vessels, and periosteum. Megakaryocytes, macrophages, and myeloid cells also expressed IGFBP-2 mRNA. Loading and sham loading did not affect IGFBP-2 mRNA expression in osteoblasts, bone marrow cells, and chondrocytes. An increase of IGFBP-2 mRNA-positive osteocytes was shown in loaded (1.68-fold) and sham-loaded (1.35-fold) endocortical tibial shaft. In conclusion, 6 hours after a single loading session, the number of IGFBP-2 mRNA-expressing osteocytes at the endosteal side of the shaft and inner lamellae was increased in squeezed and bended tibiae. Mechanical stimulation modulates IGFBP-2 mRNA expression in endocortical osteocytes. We suggest that IGFBP-2 plays a role in the lamellar bone formation process

Pharmacogenetic prediction of clinical outcome in advanced colorectal cancer patients receiving oxaliplatin/5-fluorouracil as first-line chemotherapy

To determine whether molecular parameters could be partly responsible for resistance or sensitivity to oxaliplatin (OX)-based chemotherapy used as first-line treatment in advanced colorectal cancer (CRC). We studied the usefulness of the excision repair cross-complementing 1 (ERCC1), xeroderma pigmentosum group D (XPD), XRCC1 and GSTP1 polymorphisms as predictors of clinical outcome in these patients. We treated 126 CRC patients with a first-line OX/5-fluorouracil chemotherapeutic regimen. Genetic polymorphisms were determined by real-time PCR on an ABI PRISM 7000, using DNA from peripheral blood. Clinical response (CR), progression-free survival (PFS) and overall survival (OS) were evaluated according to each genotype. In the univariate analysis for CR, ERCC1-118 and XPD 751 polymorphisms were significant (P=0.02 and P=0.05, respectively). After adjustment for the most relevant clinical variables, only ERCC1-118 retained significance (P=0.008). In the univariate analysis for PFS, ERCC1-118 and XPD 751 were significant (P=0.003 and P=0.009, respectively). In the multivariant analysis, only the XPD 751 was significant for PFS (P=0.02). Finally, ERCC1-118 and XPD 751 polymorphisms were significant in the univariate analysis for OS (P=0.006 and P=0.015, respectively). Both genetic variables remained significant in the multivariate Cox survival analysis (P=0.022 and P=0.03). Our data support the hypothesis that enhanced DNA repair diminishes the benefit of platinum-based treatments

Long term hemodialysis aggravates lipolytic activity reduction and very low density, low density lipoproteins composition in chronic renal failure patients

<p>Abstract</p> <p>Background</p> <p>Dyslipidemia, particularly hypertriglyceridemia is common in uremia, and represents an independent risk factor for atherosclerosis.</p> <p>Methods</p> <p>To investigate the effects of hemodialysis (HD) duration on very low density lipoprotein (VLDL) and low density lipoprotein (LDL) compositions and lipopolytic activities, 20 patients on 5 to 7 years hemodialysis were followed-up during 9 years. Blood samples were drawn at T0 (beginning of the study), T1 (3 years after initiating study), T2 (6 years after initiating study) and T3 (9 years after initiating study). T0 was taken as reference.</p> <p>Results</p> <p>Triacylglycerols (TG) values were correlated with HD duration (r = 0.70, P < 0.05). An increase of total cholesterol was noted at T2 and T3. Lowered activity was observed for lipoprotein lipase (LPL) (-44%) at T3 and hepatic lipase (HL) (-29%) at T1, (-64%) at T2 and (-73%) at T3. Inverse relationships were found between HD duration and LPL activity (r = -0.63, P < 0.05), and HL activity (r = -0.71, P < 0.01). At T1, T2 and T3, high VLDL-amounts and VLDL-TG and decreased VLDL-phospholipids values were noted. Increased LDL-cholesteryl esters values were noted at T1 and T2 and in LDL-unesterified cholesterol at T2 and T3.</p> <p>Conclusion</p> <p>Despite hemodialysis duration, VLDL-LDL metabolism alterations are aggravated submitting patients to a greater risk of atherosclerosis.</p

Time-course of exercise and its association with 12-month bone changes

<p>Abstract</p> <p>Background</p> <p>Exercise has been shown to have positive effects on bone density and strength. However, knowledge of the time-course of exercise and bone changes is scarce due to lack of methods to quantify and qualify daily physical activity in long-term. The aim was to evaluate the association between exercise intensity at 3, 6 and 12 month intervals and 12-month changes in upper femur areal bone mineral density (aBMD) and mid-femur geometry in healthy premenopausal women.</p> <p>Methods</p> <p>Physical activity was continuously assessed with a waist-worn accelerometer in 35 healthy women (35-40 years) participating in progressive high-impact training. To describe exercise intensity, individual average daily numbers of impacts were calculated at five acceleration levels (range 0.3-9.2 <it>g</it>) during time intervals of 0-3, 0-6, and 0-12 months. Proximal femur aBMD was measured with dual x-ray absorptiometry and mid-femur geometry was evaluated with quantitative computed tomography at the baseline and after 12 months. Physical activity data were correlated with yearly changes in bone density and geometry, and adjusted for confounding factors and impacts at later months of the trial using multivariate analysis.</p> <p>Results</p> <p>Femoral neck aBMD changes were significantly correlated with 6 and 12 months' impact activity at high intensity levels (> 3.9 <it>g</it>, <it>r </it>being up to 0.42). Trochanteric aBMD changes were associated even with first three months of exercise exceeding 1.1 <it>g </it>(<it>r </it>= 0.39-0.59, <it>p </it>< 0.05). Similarly, mid-femoral cortical bone geometry changes were related to even first three months' activity (<it>r </it>= 0.38-0.52, <it>p </it>< 0.05). In multivariate analysis, 0-3 months' activity did not correlate with bone change at any site after adjusting for impacts at later months. Instead, 0-6 months' impacts were significant correlates of 12-month changes in femoral neck and trochanter aBMD, mid-femur bone circumference and cortical bone attenuation even after adjustment. No significant correlations were found at the proximal or distal tibia.</p> <p>Conclusion</p> <p>The number of high acceleration impacts during 6 months of training was positively associated with 12-month bone changes at the femoral neck, trochanter and mid-femur. These results can be utilized when designing feasible training programs to prevent bone loss in premenopausal women.</p> <p>Trial registration</p> <p>Clinical trials.gov NCT00697957</p

White dwarf cooling and large extra dimensions

Theories of fundamental interactions with large extra dimensions have recently become very popular. Astrophysical bounds from the Sun, red-giants and SN1987a have already been derived by other authors for the theory proposed by Arkani-Hamed, Dimopoulos and Dvali. In this paper we consider G117-B15A pulsating white dwarf (ZZ Ceti star) for which the secular rate at which the period of its fundamental mode increases has been accurately measured and claimed that this mode of G117-B15A is perhaps the most stable oscillation ever recorded in the optical band. Because an additional channel of energy loss (Kaluza-Klein gravitons) would speed up the cooling rate, one is able to use the aforementioned stability to derive a bound on theories with large extra dimensions. Within the framework of the theory with large extra dimensions proposed by Arkani-Hamed, Dimopoulos and Dvali we find the lower bound on string comapctification scale which is more stringent than solar or red-giant bounds.Comment: 9 pages,LaTeX, new references added. Phys. Rev. D in pres

Inferring the role of transcription factors in regulatory networks

<p>Abstract</p> <p>Background</p> <p>Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays.</p> <p>Results</p> <p>We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of <it>E. coli </it>extracted from the literature (1529 nodes and 3802 edges), and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to <it>S. cerevisiae </it>transcriptional network (2419 nodes and 4344 interactions), by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions). In addition, we report predictions for 14.5% of all interactions.</p> <p>Conclusion</p> <p>Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine a significant portion of regulatory effects. This is a key practical asset compared to statistical methods for network reconstruction. We demonstrate that our approach is able to provide accurate predictions, even when the network is incomplete and the data is noisy.</p