Giant Faraday rotation in single- and multilayer graphene

Optical Faraday rotation is one of the most direct and practically important manifestations of magnetically broken time-reversal symmetry. The rotation angle is proportional to the distance traveled by the light, and up to now sizeable effects were observed only in macroscopically thick samples and in two-dimensional electron gases with effective thicknesses of several nanometers. Here we demonstrate that a single atomic layer of carbon - graphene - turns the polarization by several degrees in modest magnetic fields. The rotation is found to be strongly enhanced by resonances originating from the cyclotron effect in the classical regime and the inter-Landau-level transitions in the quantum regime. Combined with the possibility of ambipolar doping, this opens pathways to use graphene in fast tunable ultrathin infrared magneto-optical devices

A study on the construct validity of the Parent-Child Conflict Tactics Scale (CTSPC) in an urban population in Northeast Brazil

The Parent-Child Conflict Tactics Scale (CTSPC) is one of the most widely used instruments in the world for investigating domestic violence against children, but targeted use has proven inadequate given the phenomenon's complexity. This study focused on the factor structure of CTSPC scales in an urban population in Northeast Brazil. We conducted a cross-sectional study in a cohort of 1,370 children in Salvador, Bahia State. Factor analysis with promax oblique rotation was performed, and the Kuder-Richardson coefficient was calculated. Factor analysis showed a different distribution of items in the factors as compared to the original instrument. Violence showed a gradual profile in each factor. The Kuder-Richardson coefficient was 0.63 for factor 1, 0.59 for factor 2, and 0.42 for factor 3. The items behaved differently from the original instrument, corroborating international studies. These findings support proposing a resizing of the CTSPC

Properties of Graphene: A Theoretical Perspective

In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic

‘ASMR’ Autobiographies and the (Life-)Writing of Digital Subjectivity

For years now, a growing online subculture has been exchanging videos designed to induce ‘autonomous sensory meridian response’ (ASMR), a mysterious, blissfully relaxing tingling sensation held to alleviate anxiety, pain, insomnia and depression. Emerging from online health forums, ASMR culture today centres on YouTube, where ‘ASMRtists’ have used the feedback mechanisms built into social media platforms to refine a repertoire of ‘trigger’ techniques. Exemplifying a wider trend for using ‘ambient media’ as mood modulators and task facilitators (Roquet, 2016), ASMR culture’s use of the word ‘trigger’ is telling, gesturing towards what Halberstam (2014) sees as a shift away from the Freudian notion of ‘memory as a palimpsest’ towards one of memory as ‘a live wire sitting in the psyche waiting for a spark’, whereby digital subjects become black-boxed nodes in a cybernetic circuit. This shift has serious implications for the humanities and is particularly resonant for scholars of life-writing. As McNeill (2012) argues, digital technologies ‘complicate[] definitions of the self and its boundaries, both dismantling and sustaining the humanist subject in practices of personal narrative’ (p. 65). The resulting friction is highlighted in ‘ASMR autobiographies’: texts narrating the author’s experiences of ASMR and their discovery of online ASMR communities. Echoing familiar auto/biographical forms, from medical case histories and coming out narratives to tales of religious conversion, these texts show that the models of subjectivity we have inherited from Enlightenment philosophy, religion, psychology and Romantic literature retain some cultural purchase. But they also suggest digital media are fostering new understandings of personhood informed by cybernetics, evolutionary psychology, behaviourism and neuroscience. Focusing on works by Andrew MacMuiris, Andrea Seigel and Jon Kersey while also addressing a range of other texts, this article asks what ASMR autobiographies can tell us about digital subjectivity

Physiochemical property space distribution among human metabolites, drugs and toxins

<p>Abstract</p> <p>Background</p> <p>The current approach to screen for drug-like molecules is to sieve for molecules with biochemical properties suitable for desirable pharmacokinetics and reduced toxicity, using predominantly biophysical properties of chemical compounds, based on empirical rules such as Lipinski's "rule of five" (Ro5). For over a decade, Ro5 has been applied to combinatorial compounds, drugs and ligands, in the search for suitable lead compounds. Unfortunately, till date, a clear distinction between drugs and non-drugs has not been achieved. The current trend is to seek out drugs which show metabolite-likeness. In identifying similar physicochemical characteristics, compounds have usually been clustered based on some characteristic, to reduce the search space presented by large molecular datasets. This paper examines the similarity of current drug molecules with human metabolites and toxins, using a range of computed molecular descriptors as well as the effect of comparison to clustered data compared to searches against complete datasets.</p> <p>Results</p> <p>We have carried out statistical and substructure functional group analyses of three datasets, namely human metabolites, drugs and toxin molecules. The distributions of various molecular descriptors were investigated. Our analyses show that, although the three groups are distinct, present-day drugs are closer to toxin molecules than to metabolites. Furthermore, these distributions are quite similar for both clustered data as well as complete or unclustered datasets.</p> <p>Conclusion</p> <p>The property space occupied by metabolites is dissimilar to that of drugs or toxin molecules, with current drugs showing greater similarity to toxins than to metabolites. Additionally, empirical rules like Ro5 can be refined to identify drugs or drug-like molecules that are clearly distinct from toxic compounds and more metabolite-like. The inclusion of human metabolites in this study provides a deeper insight into metabolite/drug/toxin-like properties and will also prove to be valuable in the prediction or optimization of small molecules as ligands for therapeutic applications.</p

Immunomodulation Targeting Abnormal Protein Conformation Reduces Pathology in a Mouse Model of Alzheimer's Disease

Many neurodegenerative diseases are characterized by the conformational change of normal self-proteins into amyloidogenic, pathological conformers, which share structural properties such as high β-sheet content and resistance to degradation. The most common is Alzheimer's disease (AD) where the normal soluble amyloid β (sAβ) peptide is converted into highly toxic oligomeric Aβ and fibrillar Aβ that deposits as neuritic plaques and congophilic angiopathy. Currently, there is no highly effective treatment for AD, but immunotherapy is emerging as a potential disease modifying intervention. A major problem with most active and passive immunization approaches for AD is that both the normal sAβ and pathogenic forms are equally targeted with the potential of autoimmune inflammation. In order to avoid this pitfall, we have developed a novel immunomodulatory method that specifically targets the pathological conformations, by immunizing with polymerized British amyloidosis (pABri) related peptide which has no sequence homology to Aβ or other human proteins. We show that the pABri peptide through conformational mimicry induces a humoral immune response not only to the toxic Aβ in APP/PS1 AD transgenic mice but also to paired helical filaments as shown on AD human tissue samples. Treated APP/PS1 mice had a cognitive benefit compared to controls (p<0.0001), associated with a reduction in the amyloid burden (p = 0.0001) and Aβ40/42 levels, as well as reduced Aβ oligomer levels. This type of immunomodulation has the potential to be a universal β-sheet disrupter, which could be useful for the prevention or treatment of a wide range of neurodegenerative diseases

Does Diabetes Accelerate the Progression of Aortic Stenosis through Enhanced Inflammatory Response within Aortic valves?

Diabetes predisposes to aortic stenosis (AS). We aimed to investigate if diabetes affects the expression of selected coagulation proteins and inflammatory markers in AS valves. Twenty patients with severe AS and concomitant type 2 diabetes mellitus (DM) and 40 well-matched patients without DM scheduled for valve replacement were recruited. Valvular tissue factor (TF), TF pathway inhibitor (TFPI), prothrombin, C-reactive protein (CRP) expression were evaluated by immunostaining and TF, prothrombin, and CRP transcripts were analyzed by real-time PCR. DM patients had elevated plasma CRP (9.2 [0.74–51.9] mg/l vs. 4.7 [0.59–23.14] mg/l, p = 0.009) and TF (293.06 [192.32–386.12] pg/ml vs. 140 [104.17–177.76] pg/ml, p = 0.003) compared to non-DM patients. In DM group, TF−, TFPI−, and prothrombin expression within valves was not related to demographics, body mass index, and concomitant diseases, whereas increased expression related to DM was found for CRP on both protein (2.87 [0.5–9]% vs. 0.94 [0–4]%, p = 0.01) and transcript levels (1.3 ± 0.61 vs. 0.22 ± 0.43, p = 0.009). CRP-positive areas were positively correlated with mRNA TF (r = 0.84, p = 0.036). Diabetes mellitus is associated with enhanced inflammation within AS valves, measured by CRP expression, which may contribute to faster AS progression

Development and validation of an improved algorithm for overlaying flexible molecules

A program for overlaying multiple flexible molecules has been developed. Candidate overlays are generated by a novel fingerprint algorithm, scored on three objective functions (union volume, hydrogen-bond match, and hydrophobic match), and ranked by constrained Pareto ranking. A diverse subset of the best ranked solutions is chosen using an overlay-dissimilarity metric. If necessary, the solutions can be optimised. A multi-objective genetic algorithm can be used to find additional overlays with a given mapping of chemical features but different ligand conformations. The fingerprint algorithm may also be used to produce constrained overlays, in which user-specified chemical groups are forced to be superimposed. The program has been tested on several sets of ligands, for each of which the true overlay is known from protein–ligand crystal structures. Both objective and subjective success criteria indicate that good results are obtained on the majority of these sets

PubChem3D: a new resource for scientists

<p>Abstract</p> <p>Background</p> <p>PubChem is an open repository for small molecules and their experimental biological activity. PubChem integrates and provides search, retrieval, visualization, analysis, and programmatic access tools in an effort to maximize the utility of contributed information. There are many diverse chemical structures with similar biological efficacies against targets available in PubChem that are difficult to interrelate using traditional 2-D similarity methods. A new layer called PubChem3D is added to PubChem to assist in this analysis.</p> <p>Description</p> <p>PubChem generates a 3-D conformer model description for 92.3% of all records in the PubChem Compound database (when considering the parent compound of salts). Each of these conformer models is sampled to remove redundancy, guaranteeing a minimum (non-hydrogen atom pair-wise) RMSD between conformers. A diverse conformer ordering gives a maximal description of the conformational diversity of a molecule when only a subset of available conformers is used. A pre-computed search per compound record gives immediate access to a set of 3-D similar compounds (called "Similar Conformers") in PubChem and their respective superpositions. Systematic augmentation of PubChem resources to include a 3-D layer provides users with new capabilities to search, subset, visualize, analyze, and download data.</p> <p>A series of retrospective studies help to demonstrate important connections between chemical structures and their biological function that are not obvious using 2-D similarity but are readily apparent by 3-D similarity.</p> <p>Conclusions</p> <p>The addition of PubChem3D to the existing contents of PubChem is a considerable achievement, given the scope, scale, and the fact that the resource is publicly accessible and free. With the ability to uncover latent structure-activity relationships of chemical structures, while complementing 2-D similarity analysis approaches, PubChem3D represents a new resource for scientists to exploit when exploring the biological annotations in PubChem.</p