Isotope effects in the Hubbard-Holstein model within dynamical mean-field theory

We study the isotope effects arising from the coupling of correlated electrons with dispersionless phonons by considering the Hubbard-Holstein model at half-filling within the dynamical mean-field theory. In particular we calculate the isotope effects on the quasi-particle spectral weight $Z$, the renormalized phonon frequency, and the static charge and spin susceptibilities. In the weakly correlated regime $U/t \lesssim 1.5$, where $U$ is the Hubbard repulsion and $t$ is the bare electron half-bandwidth, the physical properties are qualitatively similar to those characterizing the Holstein model in the absence of Coulomb repulsion, where the bipolaronic binding takes place at large electron-phonon coupling, and it reflects in divergent isotope responses. On the contrary in the strongly correlated regime $U/t \gtrsim 1.5$, where the bipolaronic metal-insulator transition becomes of first order, the isotope effects are bounded, suggesting that the first order transition is likely driven by an electronic mechanism, rather then by a lattice instability. These results point out how the isotope responses are extremely sensitive to phase boundaries and they may be used to characterize the competition between the electron-phonon coupling and the Hubbard repulsion.Comment: 10 pages, 8 figures. The paper has been already accepted on Phys. Rev.

Polaronic and nonadiabatic phase diagram from anomalous isotope effects

Isotope effects (IEs) are powerful tool to probe directly the dependence of many physical properties on the lattice dynamics. In this paper we invenstigate the onset of anomalous IEs in the spinless Holstein model by employing the dynamical mean field theory. We show that the isotope coefficients of the electron effective mass and of the dressed phonon frequency are sizeable also far away from the strong coupling polaronic crossover and mark the importance of nonadiabatic lattice fluctuations in the weak to moderate coupling region. We characterize the polaronic regime by the appearence of huge IEs. We draw a nonadiabatic phase diagram in which we identify a novel crossover, not related to polaronic features, where the IEs attain their largest anomalies.Comment: 5 pages, 4 figure

Allyl sulfur compounds and cellular detoxification system: effects and perspectives in cancer therapy

Natural organosulfur compounds (OSCs) have been shown to have chemopreventive effects and to suppress the proliferation of tumor cells in vitro through the induction of apoptosis. The biochemical mechanisms underlying the antitumorigenic and anti-proliferative effects of garlic-derived OSCs are not fully understood. Several modes of action of these compounds have been proposed, and it seems likely that the rate of clearance of allyl sulfur groups from cells is a determinant of the overall response. The aim of this review is to focus attention on the effects of natural allyl sulfur compounds on the cell detoxification system in normal and tumor cells. It has been already reported that several natural allyl sulfur compounds induce chemopreventive effects by affecting xenobiotic metabolizing enzymes and inducing their down-activation. Moreover, different effects of water- and oil-soluble allyl sulfur compounds on enzymes involved in the detoxification system of rat tissues have been observed. A direct interaction of the garlic allyl sulfur compounds with proteins involved in the detoxification system was studied in order to support the hypothesis that proteins possessing reactive thiol groups and that are involved in the detoxification system and in the cellular redox homeostasis, are likely the preferential targets of these compounds. The biochemical transformation of the OSCs in the cell and their adducts with thiol functional groups of these proteins, could be considered relevant events to uncover the anticancer properties of the allyl sulfur compounds. Although additional studies, using proteomic approaches and transgenic models, are needed to identify the molecular targets and modes of action of these natural compounds, the allyl sulfur compounds can represent potential ideal agents in anticancer therapy, either alone or in association with other antitumor drugs

Stress evaluation in hares (Lepus europaeus Pallas) captured for traslocation

With the aim to evaluate the capturing techniques some haematic and physiological parameters were studied to discrim- inate stressed hares from non stressed hares. A total of 66 wild hares (experimental group) were sampled in 14 different non-hunting areas, where hares are usually captured for later release in low-density areas. In the same season a total of 30 hares (about 1 year old), reared in cages and thus showing a reduced fear of man, were sampled (control group). In each area the hares were captured by cours- ing with 3-4 dogs (greyhounds or lurches). The dogs were released by the different hunter teams to find and drive into trammel nets any hare that was seen running. After capture, the hares remained inside darkened, wooden capture-boxes for a variable period of time before blood drawing. For blood sample collection all the hares were physically restrained and their eyes immediately covered. Blood, always collected within 1-2 minutes, was drawn from the auricular vein. Blood samples (plasma) were analysed for glucose, AST, ALT, CPK and cortisol concentrations. Body temperature, heart and respiratory rate, sex, and age were evaluated in each hare. The effect of origin, sex and age on haematic and physiolog- ical parameters was analysed by ANOVA. Every measured parameter of the hares bearing to the capture group or the control group (reared) was then subjected to stepwise and to discriminant analysis, in order to select the groups of stressed (discriminated by the controls) and non-stressed hares. CPK, AST and glucose were found to be the best parameters for distinguishing stressed from non-stressed hares. The intensive exercise suffered by the wild hares induced a depletion of energetic reserves, so that most of the captured hares showed lower glucose and higher CPK activity in the plasma, probably due to muscle damage (P< 0.05). After reclassi- fying the hares in the two groups of stressed and non stressed hares, the reference values (means ± SE) resulted as fol- lows: estimated non-stressed hares, glucose 234 ± 9 .4 mg/dl, AST 112 ± 22.2 U/l, CPK 1334 ± 734 U/l; estimated stressed hares, glucose 128 ± 7 mg/dl, AST 164 ± 13 U/l, CPK 4658 ± 454 U/l. These three cheap and quickly analysable analytes can be useful to the game manager in detecting stressed and non stressed hares, in order to improve the capturing techniques by the evaluation of the following relationship: (number of stressed hares + number of the dead hares during the capture)/number of total captured hares

Cosmological birefringence constraints from CMB and astrophysical polarization data

Cosmological birefringence is a rotation of the polarization plane of photons coming from sources of astrophysical and cosmological origin. The rotation can also depend on the energy of the photons and not only on the distance of the source and on the cosmological evolution of the underlying theoretical model. In this work, we constrain few selected models for cosmological birefringence, combining CMB and astrophysical data at radio, optical, X and gamma wavelengths, taking into account the specific energy and distance dependences.Comment: 12 pages, 2 figure

Feature transforms for image data augmentation

A problem with convolutional neural networks (CNNs) is that they require large datasets to obtain adequate robustness; on small datasets, they are prone to overfitting. Many methods have been proposed to overcome this shortcoming with CNNs. In cases where additional samples cannot easily be collected, a common approach is to generate more data points from existing data using an augmentation technique. In image classification, many augmentation approaches utilize simple image manipulation algorithms. In this work, we propose some new methods for data augmentation based on several image transformations: the Fourier transform (FT), the Radon transform (RT), and the discrete cosine transform (DCT). These and other data augmentation methods are considered in order to quantify their effectiveness in creating ensembles of neural networks. The novelty of this research is to consider different strategies for data augmentation to generate training sets from which to train several classifiers which are combined into an ensemble. Specifically, the idea is to create an ensemble based on a kind of bagging of the training set, where each model is trained on a different training set obtained by augmenting the original training set with different approaches. We build ensembles on the data level by adding images generated by combining fourteen augmentation approaches, with three based on FT, RT, and DCT, proposed here for the first time. Pretrained ResNet50 networks are finetuned on training sets that include images derived from each augmentation method. These networks and several fusions are evaluated and compared across eleven benchmarks. Results show that building ensembles on the data level by combining different data augmentation methods produce classifiers that not only compete competitively against the state-of-the-art but often surpass the best approaches reported in the literature

Myosin tails and single α-helical domains

The human genome contains 39 myosin genes, divided up into 12 different classes. The structure, cellular function and biochemical properties of many of these isoforms remain poorly characterized and there is still some controversy as to whether some myosin isoforms are monomers or dimers. Myosin isoforms 6 and 10 contain a stable single α-helical (SAH) domain, situated just after the canonical lever. The SAH domain is stiff enough to be able to lengthen the lever allowing the myosin to take a larger step. In addition, atomic force microscopy and atomistic simulations show that SAH domains unfold at relatively low forces and have a high propensity to refold. These properties are likely to be important for protein function, enabling motors to carry cargo in dense actin networks, and other proteins to remain attached to binding partners in the crowded cell

Recognition mechanism of p63 by the E3 ligase Itch Novel strategy in the study and inhibition of this interaction.

The HECT-containing E3 ubiquitin ligase Itch mediates the degradation of several proteins, including p63 and p73, involved in cell specification and fate. Itch contains four WW domains, which are essential for recognition on the target substrate, which contains a short proline-rich sequence. Several signaling complexes containing these domains have been associated with human diseases such as muscular dystrophy, Alzheimer’s or Huntington’s diseases. To gain further insight into the structural determinants of the Itch-WW2 domain, we investigated its interaction with p63. We assigned, by 3D heteronuclear NMR experiments, the backbone and side chains of the uniformly 13C-15N-labeled Itch-WW2. In vitro interaction of Itch-WW2 domain with p63 was studied using its interactive p63 peptide, pep63. Pep63 is an 18-mer peptide corresponding to the region from 534–551 residue of p63, encompassing the PP xY motif that interacts with the Itch-WW domains, and we identified the residues involved in this molecular recognition. Moreover, here, a strategy of stabilization of the conformation of the PP xY peptide has been adopted, increasing the WW-ligand binding. We demonstrated that cyclization of pep63 leads to an increase of both the biological stability of the peptide and of the WW-ligand complex. Stable metal-binding complexes of the pep63 have been also obtained, and localized oxidative damage on Itch-WW2 domain has been induced, demonstrating the possibility of use of metal-pep63 complexes as models for the design of metal drugs to inhibit the Itch-WW-p63 recognition in vivo. Thus, our data suggest a novel strategy to study and inhibit the recognition mechanism of Itch E3-ligase

Protein mechanics probed using simple molecular models

Background: Single-molecule experimental techniques such as optical tweezers or atomic force microscopy are a direct probe of the mechanical unfolding/folding of individual proteins. They are also a means to investigate free energy landscapes. Protein force spectroscopy alone provides limited information; theoretical models relate measurements to thermodynamic and kinetic properties of the protein, but do not reveal atomic level information. By building a molecular model of the protein and probing its properties through numerical simulation, one can gauge the response to an external force for individual interatomic interactions and determine structures along the unfolding pathway. In combination, single-molecule force probes and molecular simulations contribute to uncover the rich behavior of proteins when subjected to mechanical force. Scope of review: We focus on how simplified protein models have been instrumental in showing how general properties of the free energy landscape of a protein relate to its response to mechanical perturbations. We discuss the role of simple protein models to explore the complexity of free energy landscapes and highlight important conceptual issues that more chemically accurate models with all-atom representations of proteins and solvent cannot easily address. Major conclusions: Native-centric, coarse-grained models, despite simplifications in chemical detail compared to all-atom models, can reproduce and interpret experimental results. They also highlight instances where the theoretical framework used to interpret single-molecule data is too simple. However, these simple models are not able to reproduce experimental findings where non-native contacts are involved. General significance: Mechanical forces are ubiquitous in the cell and it is increasingly clear that the way a protein responds to mechanical perturbation is important