Do Twin Boundaries Always Strengthen Metal Nanowires?

It has been widely reported that twin boundaries strengthen nanowires regardless of their morphology—that is, the strength of nanowires goes up as twin spacing goes down. This article shows that twin boundaries do not always strengthen nanowires. Using classical molecular dynamics simulations, the authors show that whether twin boundaries strengthen nanowires depends on the necessary stress for dislocation nucleation, which in turn depends on surface morphologies. When nanowires are circular cylindrical, the necessary stress of dislocation nucleation is high and the presence of twin boundaries lowers this stress; twin boundaries soften nanowires. In contrast, when nanowires are square cylindrical, the necessary stress of dislocation nucleation is low, and a higher stress is required for dislocations to penetrate twin boundaries; they strengthen nanowires

ErbB2, EphrinB1, Src Kinase and PTPN13 Signaling Complex Regulates MAP Kinase Signaling in Human Cancers

In non-cancerous cells, phosphorylated proteins exist transiently, becoming de-phosphorylated by specific phosphatases that terminate propagation of signaling pathways. In cancers, compromised phosphatase activity and/or expression occur and contribute to tumor phenotype. The non-receptor phosphatase, PTPN13, has recently been dubbed a putative tumor suppressor. It decreased expression in breast cancer correlates with decreased overall survival. Here we show that PTPN13 regulates a new signaling complex in breast cancer consisting of ErbB2, Src, and EphrinB1. To our knowledge, this signaling complex has not been previously described. Co-immunoprecipitation and localization studies demonstrate that EphrinB1, a PTPN13 substrate, interacts with ErbB2. In addition, the oncogenic V660E ErbB2 mutation enhances this interaction, while Src kinase mediates EphrinB1 phosphorylation and subsequent MAP Kinase signaling. Decreased PTPN13 function further enhances signaling. The association of oncogene kinases (ErbB2, Src), a signaling transmembrane ligand (EphrinB1) and a phosphatase tumor suppressor (PTPN13) suggest that EphrinB1 may be a relevant therapeutic target in breast cancers harboring ErbB2-activating mutations and decreased PTPN13 expression

Detection of Functional Modes in Protein Dynamics

Proteins frequently accomplish their biological function by collective atomic motions. Yet the identification of collective motions related to a specific protein function from, e.g., a molecular dynamics trajectory is often non-trivial. Here, we propose a novel technique termed “functional mode analysis” that aims to detect the collective motion that is directly related to a particular protein function. Based on an ensemble of structures, together with an arbitrary “functional quantity” that quantifies the functional state of the protein, the technique detects the collective motion that is maximally correlated to the functional quantity. The functional quantity could, e.g., correspond to a geometric, electrostatic, or chemical observable, or any other variable that is relevant to the function of the protein. In addition, the motion that displays the largest likelihood to induce a substantial change in the functional quantity is estimated from the given protein ensemble. Two different correlation measures are applied: first, the Pearson correlation coefficient that measures linear correlation only; and second, the mutual information that can assess any kind of interdependence. Detecting the maximally correlated motion allows one to derive a model for the functional state in terms of a single collective coordinate. The new approach is illustrated using a number of biomolecules, including a polyalanine-helix, T4 lysozyme, Trp-cage, and leucine-binding protein

Mechanical Failure Mode of Metal Nanowires: Global Deformation versus Local Deformation

It is believed that the failure mode of metal nanowires under tensile loading is the result of the nucleation and propagation of dislocations. Such failure modes can be slip, partial slip or twinning and therefore they are regarded as local deformation. Here we provide numerical and theoretical evidences to show that global deformation is another predominant failure mode of nanowires under tensile loading. At the global deformation mode, nanowires fail with a large contraction along a lateral direction and a large expansion along the other lateral direction. In addition, there is a competition between global and local deformations. Nanowires loaded at low temperature exhibit global failure mode first and then local deformation follows later. We show that the global deformation originates from the intrinsic instability of the nanowires and that temperature is a main parameter that decides the global or local deformation as the failure mode of nanowires.close10

Anti-relapse neurons in the infralimbic cortex of rats drive relapse-suppression by drug omission cues

Drug addiction is a chronic relapsing disorder of compulsive drug use. Studies of the neurobehavioral factors that promote drug relapse have yet to produce an effective treatment. Here we take a different approach and examine the factors that suppress – rather than promote – relapse. Adapting Pavlovian procedures to suppress operant drug response, we determined the anti-relapse action of environmental cues that signal drug omission (unavailability) in rats. Under laboratory conditions linked to compulsive drug use and heightened relapse risk, drug omission cues suppressed three major modes of relapse-promotion (drug-predictive cues, stress, and drug exposure) for cocaine and alcohol. This relapse-suppression is partially driven by omission cue-reactive neurons, which constitute small subsets of glutamatergic and GABAergic cells, in the infralimbic cortex. Future studies of such neural activity-based cellular units (neuronal ensembles/memory engram cells) for relapse-suppression can be used to identify alternate targets for addiction medicine through functional characterization of anti-relapse mechanisms

A theoretical approach to spot active regions in antimicrobial proteins

Background: Much effort goes into identifying new antimicrobial compounds able to evade the increasing resistance of microorganisms to antibiotics. One strategy relies on antimicrobial peptides, either derived from fragments released by proteolytic cleavage of proteins or designed from known antimicrobial protein regions. Results: To identify these antimicrobial determinants, we developed a theoretical approach that predicts antimicrobial proteins from their amino acid sequence in addition to determining their antimicrobial regions. A bactericidal propensity index has been calculated for each amino acid, using the experimental data reported from a high-throughput screening assay as reference. Scanning profiles were performed for protein sequences and potentially active stretches were identified by the best selected threshold parameters. The method was corroborated against positive and negative datasets. This successful approach means that we can spot active sequences previously reported in the literature from experimental data for most of the antimicrobial proteins examined. Conclusion: The method presented can correctly identify antimicrobial proteins with an accuracy of 85% and a sensitivity of 90%. The method can also predict their key active regions, making this a tool for the design of new antimicrobial drugs

IGF-1, IGFBP-1, and IGFBP-3 Polymorphisms Predict Circulating IGF Levels but Not Breast Cancer Risk: Findings from the Breast and Prostate Cancer Cohort Consortium (BPC3)

IGF-1 has been shown to promote proliferation of normal epithelial breast cells, and the IGF pathway has also been linked to mammary carcinogenesis in animal models. We comprehensively examined the association between common genetic variation in the IGF1, IGFBP1, and IGFBP3 genes in relation to circulating IGF-I and IGFBP-3 levels and breast cancer risk within the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). This analysis included 6,912 breast cancer cases and 8,891 matched controls (n = 6,410 for circulating IGF-I and 6,275 for circulating IGFBP-3 analyses) comprised primarily of Caucasian women drawn from six large cohorts. Linkage disequilibrium and haplotype patterns were characterized in the regions surrounding IGF1 and the genes coding for two of its binding proteins, IGFBP1 and IGFBP3. In total, thirty haplotype-tagging single nucleotide polymorphisms (htSNP) were selected to provide high coverage of common haplotypes; the haplotype structure was defined across four haplotype blocks for IGF1 and three for IGFBP1 and IGFBP3. Specific IGF1 SNPs individually accounted for up to 5% change in circulating IGF-I levels and individual IGFBP3 SNPs were associated up to 12% change in circulating IGFBP-3 levels, but no associations were observed between these polymorphisms and breast cancer risk. Logistic regression analyses found no associations between breast cancer and any htSNPs or haplotypes in IGF1, IGFBP1, or IGFBP3. No effect modification was observed in analyses stratified by menopausal status, family history of breast cancer, body mass index, or postmenopausal hormone therapy, or for analyses stratified by stage at diagnosis or hormone receptor status. In summary, the impact of genetic variation in IGF1 and IGFBP3 on circulating IGF levels does not appear to substantially influence breast cancer risk substantially among primarily Caucasian postmenopausal women

Astrocyte pathology in the prefrontal cortex impairs the cognitive function of rats

Interest in astroglial cells is rising due to recent findings supporting dynamic neuron-astrocyte interactions. There is increasing evidence of astrocytic dysfunction in several brain disorders such as depression, schizophrenia or bipolar disorder; importantly these pathologies are characterized by the involvement of the prefrontal cortex and by significant cognitive impairments. Here, to model astrocyte pathology, we injected animals with the astrocyte specific toxin L-a-aminoadipate (L-AA) in the medial prefrontal cortex (mPFC); a behavioral and structural characterization two and six days after the injection was performed. Behavioral data shows that the astrocyte pathology in the mPFC affects the attentional set-shifting, the working memory and the reversal learning functions. Histological analysis of brain sections of the L-AA-injected animals revealed a pronounced loss of astrocytes in the targeted region. Interestingly, analysis of neurons in the lesion sites showed a progressive neuronal loss that was accompanied with dendritic atrophy in the surviving neurons. These results suggest that the L-AA-induced astrocytic loss in the mPFC triggers subsequent neuronal damage leading to cognitive impairment in tasks depending on the integrity of this brain region. These findings are of relevance to better understand the pathophysiological mechanisms underlying disorders that involve astrocytic loss/dysfunction in the PFC.This work was supported by the Marie Curie Fellowship FP7-PEOPLE-2010-IEF 273936, BIAL Foundation Grants 138/2008 and 61/2010, FEDER funds through Operational program for competitiveness factors-COMPETE -, ON2 Programa Operacional Regional do Norte (ON.2-O Novo Norte), QREN/FEDER, and by national funds through FCT-Foundation for Science and Technology-project (PTDC/SAU-NSC/118194/2010) and fellowships (SFRH/BPD/66151/2009 and SFRH/BD/89714/2012)

Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium.

BACKGROUND: Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions. METHODS: Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions. RESULTS: Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth. CONCLUSIONS: Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors

School Effects on the Wellbeing of Children and Adolescents

Well-being is a multidimensional construct, with psychological, physical and social components. As theoretical basis to help understand this concept and how it relates to school, we propose the Self-Determination Theory, which contends that self-determined motivation and personality integration, growth and well-being are dependent on a healthy balance of three innate psychological needs of autonomy, relatedness and competence. Thus, current indicators involve school effects on children’s well-being, in many diverse modalities which have been explored. Some are described in this chapter, mainly: the importance of peer relationships; the benefits of friendship; the effects of schools in conjunction with some forms of family influence; the school climate in terms of safety and physical ecology; the relevance of the teacher input; the school goal structure and the implementation of cooperative learning. All these parameters have an influence in promoting optimal functioning among children and increasing their well-being by meeting the above mentioned needs. The empirical support for the importance of schools indicates significant small effects, which often translate into important real-life effects as it is admitted at present. The conclusion is that schools do make a difference in children’s peer relationships and well-being