Agrin isoforms and their role in synaptogenesis

Agrin is thought to mediate the motor neuron-induced aggregation of synaptic proteins on the surface of muscle fibers at neuromuscular junctions. Recent experiments provide direct evidence in support of this hypothesis, reveal the nature of agrin immunoreactivity at sites other than neuromuscular junctions, and have resulted in findings that are consistent with the possibility that agrin plays a role in synaptogenesis throughout the nervous system

The agrin gene codes for a family of basal lamina proteins that differ in function and distribution

We isolated two cDNAs that encode isoforms of agrin, the basal lamina protein that mediates the motor neuron-induced aggregation of acetylcholine receptors on muscle fibers at the neuromuscular junction. Both proteins are the result of alternative splicing of the product of the agrin gene, but, unlike agrin, they are inactive in standard acetylcholine receptor aggregation assays. They lack one (agrin-related protein 1) or two (agrin-related protein 2) regions in agrin that are required for its activity. Expression studies provide evidence that both proteins are present in the nervous system and muscle and that, in muscle, myofibers and Schwann cells synthesize the agrin-related proteins while the axon terminals of motor neurons are the sole source of agrin

Similarities between the Hubbard and Periodic Anderson Models at Finite Temperatures

The single band Hubbard and the two band Periodic Anderson Hamiltonians have traditionally been applied to rather different physical problems - the Mott transition and itinerant magnetism, and Kondo singlet formation and scattering off localized magnetic states, respectively. In this paper, we compare the magnetic and charge correlations, and spectral functions, of the two systems. We show quantitatively that they exhibit remarkably similar behavior, including a nearly identical topology of the finite temperature phase diagrams at half-filling. We address potential implications of this for theories of the rare earth ``volume collapse'' transition.Comment: 4 pages (RevTeX) including 4 figures in 7 eps files; as to appear in Phys. Rev. Let

Hubbard-U calculations for Cu from first-principles Wannier functions

We present first-principles calculations of optimally localized Wannier functions for Cu and use these for an ab-initio determination of Hubbard (Coulomb) matrix elements. We use a standard linearized muffin-tin orbital calculation in the atomic-sphere approximation (LMTO-ASA) to calculate Bloch functions, and from these determine maximally localized Wannier functions using a method proposed by Marzari and Vanderbilt. The resulting functions were highly localized, with greater than 89% of the norm of the function within the central site for the occupied Wannier states. Two methods for calculating Coulomb matrix elements from Wannier functions are presented and applied to fcc Cu. For the unscreened on-site Hubbard $U$ for the Cu 3d-bands we have obtained about 25eV. These results are also compared with results obtained from a constrained local-density approximation (LDA) calculation.Comment: 13 pages, 8 figures, 5 table

Dynamical Mean-Field Theory and Its Applications to Real Materials

Dynamical mean-field theory (DMFT) is a non-perturbative technique for the investigation of correlated electron systems. Its combination with the local density approximation (LDA) has recently led to a material-specific computational scheme for the ab initio investigation of correlated electron materials. The set-up of this approach and its application to materials such as (Sr,Ca)VO_3, V_2O_3, and Cerium is discussed. The calculated spectra are compared with the spectroscopically measured electronic excitation spectra. The surprising similarity between the spectra of the single-impurity Anderson model and of correlated bulk materials is also addressed.Comment: 20 pages, 9 figures, invited paper for the JPSJ Special Issue "Kondo Effect - 40 Years after the Discovery"; final version, references adde

Quantum critical point in a periodic Anderson model

We investigate the symmetric Periodic Anderson Model (PAM) on a three-dimensional cubic lattice with nearest-neighbor hopping and hybridization matrix elements. Using Gutzwiller's variational method and the Hubbard-III approximation (which corresponds to the exact solution of an appropriate Falicov-Kimball model in infinite dimensions) we demonstrate the existence of a quantum critical point at zero temperature. Below a critical value $V_c$ of the hybridization (or above a critical interaction $U_c$) the system is an {\em insulator} in Gutzwiller's and a {\em semi-metal} in Hubbard's approach, whereas above $V_c$ (below $U_c$) it behaves like a metal in both approximations. These predictions are compared with the density of states of the $d$- and $f$-bands calculated from Quantum Monte Carlo and NRG calculations. Our conclusion is that the half-filled symmetric PAM contains a {\em metal-semimetal transition}, not a metal-insulator transition as has been suggested previously.Comment: ReVteX, 10 pages, 2 EPS figures. Minor corrections made in the text and in the figure captions from the first version. More references added. Accepted for publication in Physical Review

Stability of metallic stripes in the extended one-band Hubbard model

Based on an unrestricted Gutzwiller approximation (GA) we investigate the stripe orientation and periodicity in an extended one-band Hubbard model. A negative ratio between next-nearest and nearest neighbor hopping t'/t, as appropriate for cuprates, favors partially filled (metallic) stripes for both vertical and diagonal configurations. At around optimal doping diagonal stripes, site centered (SC) and bond centered (BC) vertical stripes become degenerate suggesting strong lateral and orientational fluctuations. We find that within the GA the resulting phase diagram is in agreement with experiment whereas it is not in the Hartree-Fock approximation due to a strong overestimation of the stripe filling. Results are in agreement with previous calculations within the three-band Hubbard model but with the role of SC and BC stripes interchanged.Comment: 10 pages, 8 figure

Should Research Ethics Encourage the Production of Cost-Effective Interventions?

This project considers whether and how research ethics can contribute to the provision of cost-effective medical interventions. Clinical research ethics represents an underexplored context for the promotion of cost-effectiveness. In particular, although scholars have recently argued that research on less-expensive, less-effective interventions can be ethical, there has been little or no discussion of whether ethical considerations justify curtailing research on more expensive, more effective interventions. Yet considering cost-effectiveness at the research stage can help ensure that scarce resources such as tissue samples or limited subject popula- tions are employed where they do the most good; can support parallel efforts by providers and insurers to promote cost-effectiveness; and can ensure that research has social value and benefits subjects. I discuss and rebut potential objections to the consideration of cost-effectiveness in research, including the difficulty of predicting effectiveness and cost at the research stage, concerns about limitations in cost-effectiveness analysis, and worries about overly limiting researchers’ freedom. I then consider the advantages and disadvantages of having certain participants in the research enterprise, including IRBs, advisory committees, sponsors, investigators, and subjects, consider cost-effectiveness. The project concludes by qualifiedly endorsing the consideration of cost-effectiveness at the research stage. While incorporating cost-effectiveness considerations into the ethical evaluation of human subjects research will not on its own ensure that the health care system realizes cost-effectiveness goals, doing so nonetheless represents an important part of a broader effort to control rising medical costs

Efficiently Learning Structured Distributions from Untrusted Batches

We study the problem, introduced by Qiao and Valiant, of learning from untrusted batches. Here, we assume $m$ users, all of whom have samples from some underlying distribution $p$ over $1, \ldots, n$. Each user sends a batch of $k$ i.i.d. samples from this distribution; however an $\epsilon$-fraction of users are untrustworthy and can send adversarially chosen responses. The goal is then to learn $p$ in total variation distance. When $k = 1$ this is the standard robust univariate density estimation setting and it is well-understood that $\Omega (\epsilon)$ error is unavoidable. Suprisingly, Qiao and Valiant gave an estimator which improves upon this rate when $k$ is large. Unfortunately, their algorithms run in time exponential in either $n$ or $k$. We first give a sequence of polynomial time algorithms whose estimation error approaches the information-theoretically optimal bound for this problem. Our approach is based on recent algorithms derived from the sum-of-squares hierarchy, in the context of high-dimensional robust estimation. We show that algorithms for learning from untrusted batches can also be cast in this framework, but by working with a more complicated set of test functions. It turns out this abstraction is quite powerful and can be generalized to incorporate additional problem specific constraints. Our second and main result is to show that this technology can be leveraged to build in prior knowledge about the shape of the distribution. Crucially, this allows us to reduce the sample complexity of learning from untrusted batches to polylogarithmic in $n$ for most natural classes of distributions, which is important in many applications. To do so, we demonstrate that these sum-of-squares algorithms for robust mean estimation can be made to handle complex combinatorial constraints (e.g. those arising from VC theory), which may be of independent technical interest.Comment: 46 page