Quantum Physics Research Papers

Protein measurement with the Folin phenol reagent

1951

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Collective dynamics of 'small-world' networks

1998, Nature

8 typically slower than ϳ1 km s −1 ) might differ significantly from what is assumed by current modelling efforts 27 . The expected equation-of-state differences among small bodies (ice versus rock, for instance) presents another... more

Figure 2 Characteristic path length L(p) and clustering coefficient C(p) for the family of randomly rewired graphs described in Fig. 1. Here L is defined as the number of edges in the shortest path between two vertices, averaged over all pairs of vertices. The clustering coefficient C(p) is defined as follows. Suppose that a vertex v has ky neighbours; then at most k,(k, — 1)/2 edges can exist between them (this occurs when every neighbour of v is connected to every other neighbour of v). Let C, denote the fraction of these allowable edges that actually exist. Define C as the average of C, over all v. For friendship networks, these statistics have intuitive meanings: L is the average number of friendships in the shortest chain connecting two people; C, reflects the extent to which friends ofv are also friends of each other; and thus C measures the cliquishness of a typical friendship circle. The data shown in the figure are averages over 20 random realizations of the rewiring process described in Fig. 1, and have been normalized by the values L (0), C(0) for a regular lattice. All the graphs haven = 1,000 vertices and an average degree of k = 10 edges per vertex. We note that a logarithmic horizontal scale has been used to resolve the rapid drop inL(p), corresponding to the onset of the small-world phenomenon. During this drop, C(o) remains almost constant at its value for the regular lattice, indicating that the transition to a small world is almost undetectable at the local level.

Table 1 shows that all three graphs are small-world networks. These examples were not hand-picked; they were chosen because of their inherent interest and because complete wiring diagrams were available. Thus the small-world phenomenon is not merely a curiosity of social networks'*"* nor an artefact of an idealized

Characteristic path length L and clustering coefficient C for three real networks, compared to random graphs with the same number of vertices (n) and average number of edges per vertex (k). (Actors:n = 225,226, k = 61. Power grid:n = 4,941,k = 2.67.C. elegans:n = 282, k = 14.) The graphs are defined as follows. Two actors are joined by an edge if they have acted in a film together. We restrict attention to the giant connected component" of this graph, which includes ~90% of all actors listed in the Internet Movie Database (available at http://us.imdb.com), as of April 1997. For the power grid, vertices represent generators, transformers and substations, and edges represent high-voltage transmission lines between them. For C. elegans, an edge joins two neurons if they are connected by either a synapse or a gap junction. We treat all edges as undirected and unweighted, and all vertices as identical, recognizing that these are crude approximations. All three networks show the small-world phenomenon: L 2 Ltandom DUt C > Crandom: Table 1 Empirical examples of small-world networks

Received 27 November 1997; accepted 6 April 1998.

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Quantum computation and quantum information

by KOCHU MOIDU NM

2000

The paper is intended to be a survey of all the important aspects and results that have shaped the field of quantum computation and quantum information. The reader is first familiarized with those features and principles of quantum... more

Figure 1. Young’s double-slit experiment.

Figure 2. The Bloch sphere representation of a qubit.

Figure 5. Quantum key distribution in the absence of eavesdropping.

In the final step of the computation, another Walsh—Hadamard gate acts on the first
qubits interfering the terms in the superposition:
Figure 6. Quantum circuit implementing the Deutsch—Jozsa algorithm.

Figure 7. Lattice of variable assignments.

Figure 8. Lattice of variable assignments in ket form.

Figure 9. Quantum Toffoli (controlled—controlled-NOT) gate.

Figure 10. Relationships between quantum and classical complexity classes.

Figure 11. A Mach—Zehnder interferometer (BS, beam splitter; M, mirror).

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Review of particle physics

by Uttaran Dutta

2004, Physics …

Written October 2003 by B.D. Fields (Univ. of Illinois) and S. Sarkar (Univ. of Oxford).

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Graphene-based composite materials

by ruggero volponi

2006, Nature

Graphene sheets-one-atom-thick two-dimensional layers of sp 2 -bonded carbon-are predicted to have a range of unusual properties. Their thermal conductivity and mechanical stiffness may rival the remarkable in-plane values for graphite... more

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A globally coherent fingerprint of climate change impacts across natural systems

by fadindra subedi

2003, Nature

Causal attribution of recent biological trends to climate change is complicated because non-climatic influences dominate local, short-term biological changes. Any underlying signal from climate change is likely to be revealed by analyses... more

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MicroRNA expression profiles classify human cancers

by Eric Miska

2005, Nature

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Inflationary universe: A possible solution to the horizon and flatness problems

by Alan Guth

1981, Physical Review D

The standard model of hot big bang cosmology requires initial conditions which are problematic in two ways: (1) the early universe is assumed to be highly homogeneous, in spite of the fact that separated regions were causally disconnected... more

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Reticular synthesis and the design of new materials

by Os Shekhah

2003, Nature

The long-standing challenge of designing and constructing new crystalline solid-state materials from molecular building blocks is just beginning to be addressed with success. A conceptual approach that requires the use of secondary... more

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Antimicrobial peptides of multicellular organisms

by Michael Zasloff

2002, Nature

Figure 1 Clustering of cationic and hydrophobic amino acids into distinct domains in several antimicrobial peptides of different structural classes. This ‘amphipathic’ design is evident in many, but not all, antimicrobial peptides. Red, basic (positively charged) amino acids; green, hydrophobic (‘oily’) amino acids. Other amino acids are not shown. Magainin is depicted in its o-helical configuration. The diversity of sequences is such that the same peptide sequence is rarely recovered from two different species of animal, even those closely related, be they insects, frogs or mammals (exceptions include peptides cleaved from highly conserved proteins, such as buforin II). However, both within the antimicrobial peptides from a single species, and even between certain classes of different peptides from diverse species (reviewed in ref. 4), significant conservation of amino-acid sequences can be recognized in the preproregion of the precursor molecules; the design suggests that constraints exist on the sequences involved in the translation, secretion or intracellular

Figure 2 The membrane target of antimicrobial peptides of multicellular organisms and the basis of specificity. (Modified from ref. 21.)

‘wormhole’ formation. Transient pores form at this stage. d, Transport of lipids and peptides into the inner leaflet. e, Diffusion of peptides onto intracellular targets (in some cases). f, Collapse of the membrane into fragments and physical disruption of the target cell’s membrane. Lipids with yellow headgroups are acidic, or negatively charged. Lipids with black headgroups have no net charge. Figure 3 The Shai—Matsuzaki—Huang model of the mechanism of action of an antimicrobial peptide. An «-helical peptide is depicted. a, Carpeting of the outer leaflet with peptides. b, Integration of the peptide into the membrane and thinning of the outer leaflet. The surface area of the outer leaflet expands relative to the inner leaflet, resulting in strain within the bilayer (jagged arrows). ¢, Phase transition and Why have microbes not been more successful in resisting the Unlike conventional antibiotics such as penicillin, which microbes readily circumvent, acquisition of resistance by a sensitive microbial strain against antimicrobial peptides is surprisingly improbable. Resistant species of genera such as Morganella and Serratia express an outer membrane that lacks the appropriate density of acidic

noted. The proteolytic system that results in the cleavage of pro-Spaetzle is not know The existence of a receptor in the Imd circuit is depicted, but remains speculative. Figure 4 Signalling cascades that activate antimicrobial peptide genes in the fat bod of Drosophila. The pathways have been deduced, by and large, through genetic analysis of immune function in Drosophila, and proteins encoded by genetic loci are

Cysteines paired in disulphide linkages are noted by common numerical subscripts. C-terminal amides are noted by a. In 6-defensin, the first and last residues are joined in a peptide bond. *BC, blood cell; H, haemolymph; E, epithelial tissue. leaflet of the bilayer, the surface exposed to the outer world, is heavily populated by lipids with negatively charged phospholipid headgroups. In contrast, the outer leaflet of the membranes of plants and animals is composed principally of lipids with no net charge; most of the lipids with negatively charged headgroups are segregated into the inner leaflet, facing the cytoplasm (Fig. 2) (reviewed in ref. 21). A model that explains the activity of most antimicrobial peptides is the Shai-Matsuzaki-Huang (SMH) model (refs 21-23; Fig. 3). The model proposes the interaction of

“BPI, bactericidal permeability increasing protein.

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Exploring complex networks

by atilla abila

2001, Nature

Figure 3 Schematic illustration of regular and random network architectures. a, Ring of ten nodes connected to their nearest neighbours. b, Fully connected network of ten nodes. ¢, Random graph constructed by placing nnodes on a plane, then joining pairs of them together at random until mlinks are used. Nodes may be chosen more than once, or not at all. The resulting wiring diagram (not shown) would be a snarl of criss- crossed lines; to clarify it, | have segregated the different connected components, coloured them, and eliminated as many spurious crossings as possible. The main topological features are the presence of a single giant component, as expected?" °° for arandom graph with m> n/2 (here n= 200, m= 193), and the absence of any dominant hubs. The degree, or number of neighbours, is Poisson distributed across the nodes; most nodes have between one and four neighbours, and all have between Zero and six. d, Scale-free graph, grown by attaching new nodes at random to previously existing nodes. The probability of attachment is proportional to the degree of the target node; thus richly connected nodes tend to get richer, leading to the formation of hubs and a skewed degree distribution with a heavy tail. Colours indicate the three nodes with the most links (red, k= 33 links; blue, k= 12; green, k= 11). Here n= 200 nodes, m= 199 links. Figure provided by D. Callaway. Network visualization was done using the Pajek program for large network analysis http://vlado.fmf.uni-lj.si/pub/networks/pajek/pajekman.htm). analogue of a phase transition“’. He proposed a mean-field model of nearly identical, weakly coupled limit-cycle oscillators and showed that when the coupling is small compared to the spread of natural frequencies, the system behaves incoherently, with each oscillator running at its natural frequency. As the coupling is increased, the

where K.=2y. In other words, the oscillators are desynchronized completely until the coupling strength K exceeds a critical value K.. After that, the population splits into a partially synchronized state Figure 4 Solvable model of a small-world network. The model starts with a ring lattice of nnodes, each connected to its neighbours out to some range k (here n= 24 and k=8). Shortcut links are added between random pairs of nodes, with probability @ per link on the underlying lattice. In the limit n > 1, the average path length between nodes can be approximated analytically. (Adapted from ref. 75.)

Figure 5 Average path length, normalized by system size, is plotted as a function of the average number of shortcuts. The circles are results from simulations of the model with range k= 1 and size up to n= 10’ nodes. The solid line is given by the formula in the text. (Adapted from ref. 75.)

contacts together influence the spread of infectious disease, with implications for vaccination strategies and the evolution of virulence®”’. Neurobiologists have wondered about the possible evolutionary significance of small-world neural architecture. They have argued that this kind of topology combines fast signal processing with coherent oscillations”, unlike either regular or random architectures, and that it may be selected by adaptation to rich sensory environments and motor demands™.

Figure 8 Structural properties of the Fortun hereby creating interlocked directorates. TI onsequences for business practices in the mber of boards per director. The probabi creases roughly exponentially with /. b, D oard. The probability q, that a board has k stributed, with a typical board size around rector’s total number of co-directors, sum rector sits. The probability r, of serving wi e 1,000 network of corporate directors for 999. The data shown here comprise 7,673 directors and 914 boards. Most directors serve on the board of only one company, but about 20% sit on two or more boards, his has potentially importan United States’’. a, Distribution of the ity p,that a director sits on exactly /boards istribution of the number of directors per members is approximately lognormally k=10 members. ¢, Distribution of each med over all the boards on which the h zother co-directors is a complicated => nction of z, with a long tail and a seconda rediction (solid line) agrees almost perfect! cles). (Adapted from ref. 91.) @). 4s) fa & ©, Si, [se , SB SG es y shoulder near z= 20, yet the theoretical ly with the actual distribution (green

US corporate directors: 7,673 company directors linked by joint membership on 914 boards of the Fortune 1,000 companies for 1999. Movie actors: 449,913 actors linked by mutual appearances in 151,261 feature films, as specified by the Internet Movie Database (www.imdb.com) as of 1 May 2000. Biomedical collaborations: 1,388,989 scientists linked by coauthorship of at least one of 2,156,769 biomedical journal articles published between 1995 and 1999 inclusive, as listed in the MEDLINE database. The clustering coefficient C is defined as the probability that a connected triple of nodes is actually a triangle; here nodes correspond to people, as in the unipartite representation shown in Fig. 7b. Intuitively, C measures the likelihood that two people who have a mutual collaborator are also collaborators of each other. The results show that the random model accurately predicts C for the corporate director network, given the network’s bipartite structure and its degree distributions; no additional social forces need to be invoked. For the networks of actors and scientists, the model accounts for about half of the observed clustering. The remaining portion depends on social mechanisms at work in these communities (see text). (Adapted from ref. 91.) Although regular networks and random graphs are both useful ideal- izations, many real networks lie somewhere between the extremes of order and randomness. Watts and Strogatz’**’ studied a simple model that can be tuned through this middle ground: a regular lattice

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Long-Range Corrected Hybrid Density Functionals with Damped Atom-Atom Dispersion Corrections

by Jeng-Da Chai

We report re-optimization of a recently proposed long-range corrected (LC) hybrid density functional [J.-D. Chai and M. Head-Gordon, J. Chem. Phys., 2008, 128, 084106] to include empirical atom-atom dispersion corrections. The resulting... more

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Stem cells, cancer, and cancer stem cells

by Narae Lee

2001, Nature

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Reciprocal developmental pathways for the generation of pathogenic effector TH17 and regulatory T cells

by Wenda Gao

2006, Nature

On activation, T cells undergo distinct developmental pathways, attaining specialized properties and effector functions. T-helper (T H ) cells are traditionally thought to differentiate into T H 1 and T H 2 cell subsets. T H 1 cells are... more

Figure 1| Inhibition of T,.. development by different cytokines. a—c, FACS- sorted CD4+GEP” (Foxp3_ ) cells from Foxp3—GEP knockin mice were stimulated with anti-CD3 and anti-CD28 antibodies for 3 days (a, b) or anti- CD3 plus antigen-presenting cells for 48 h in the presence of different cytokines (c). a, Percentage of GFP-expressing cells induced by various cytokines in the presence of TGF-6 (the percentage of GFP* cells induced in the presence of TGF-8 was kept at 100%). b, GFP expression in CD4* T cells. c, Amount of IL-17 produced in triplicate wells +s.d. MOG)-specific T-cell receptor (TCR) transgenic mouse (hereafter called 2D2)"*. In vitro activation of unsorted splenic T cells from the transgenic mice in the presence MOG35-—55 peptide and recombinant IL-23 resulted in the generation of 6.5% of IL-17-producing CD4* T cells (Fig. 2a). Because the IL-23 receptor is expressed only on activated/memory T cells’*’*, we wanted to investigate further whether IL-23 could guide differentiation of naive T cells into T};17 cells. To address this question, naive 2D2 transgenic T cells (CD4*CD62L")

Figure 2 | Cytokines required for the generation of T,,17 cells. a, Splenocytes from 2D2 TCR transgenic mice were stimulated with MOG35-55 peptide in neutral conditions or with IL-23. b, c, FACS-sorted naive CD4*CD62L"" T cells from 2D2 TCR transgenic mice were stimulatec with soluble anti-CD3, C57BL/6 irradiated spleen cells and the indicated cytokines plus neutralizing antibodies. Five days after the activation, cells were re-stimulated with PMA/ionomycin and subjected to intracellular cytokine staining. The contour plots represent IL-17 expression in CD4* cells.

Figure 3 | Reciprocal expression of Foxp3 and IL-17 in T cells during differentiation. FACS-sorted naive CD4*CD62L"'GFP~ T cells from 2D2 X Foxp3—GFP knockin mice were stimulated with soluble anti-CD3, antigen-presenting cells and the indicated cytokines. a, Foxp3 (GFP) and cytokine (IL-17 or IFN-y) intracellular expression in CD4* T cells after 5 days. b, Expression of IFN-y, Foxp3 and IL-17 mRNA relative to control actin (in triplicate wells +s.d.). ¢, Proliferation in triplicate wells (+s.d.) of CD4*CD25° cells and Tror-g+it-6 cells (T cells differentiated in the presence of TGF-8 and IL-6) in the presence of angen presenting cells, soluble anti-CD3 and different concentrations of CD4*CD25* T cells or Trep. g cells (T cells generated in the presence of TGF-8) measured by P H]thymidine incorporation.

Figure 4 | Enhanced IL-17 production by T cells and CNS autoimmunity in TGF-8 transgenic mice. a, b, Splenocytes from naive C57BL/6 wild-type (WT) mice (a, left panel), wild-type and TgTGF-8 mice immunized with MOG35-55 peptide (a, right panel), and 2D2 and 2D2 X TgTGF-8 mice immunized with MOG35-—55 peptide (b), were stimulated with lipopolysaccharide (for IL-6) or MOG35-55 peptide (for other cytokines). Data represent mean cytokine produced in each group (nm = 3) + s.d. c, Wild-type C57BL/6 (n = 13), 2D2 (n = 11) and 2D2 X TgTGF-B (n = 13) mice were immunized with MOG35-—55 in CFA and monitored for clinical signs of EAE (top panel). Linear regression analysis of the individual disease curves reveals a highly significant difference (P < 0.0001) between each of the EAE groups (bottom panel). d, Frequency of IL-17- and Foxp3-expressing CD4* T cells isolated from the CNS of 2D2 x TgTGF-6 or 2D2 mice at the peak of disease.

Table 1 | EAE in 2D2 and 2D2 x TgTGF-8 mice Mice were immunized with MOG35-55 peptide emulsified in complete Freund's adjuvant and monitored for the development of EAE. Statistical analysis was performed by comparing thre Zroups using one-way analysis of variance (ANOVA) followed by a Newman-Keuls multiple comparison as a post-hoc test. ‘P<0.05. +P < 0.05. tP < 0,001. $P < 0.01.

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Hydrogen-storage materials for mobile applications

by Andreas ZÜTTEL

2001, Nature

insight review articles NATURE | VOL 414 | 15 NOVEMBER 2001 | www.nature.com 353 E nergy can be stored in different forms: as mechanical energy (for example, potential energy or rotation energy of a flywheel); in an electric or magnetic... more

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Surfing the p53 network

by Agus Tinus

2000, Nature

Figure 1 The many ways in which p53 may malfunction in human cancers. able confusion and controversy. Here we sug- gest that signalling pathways involving p53 — like cellular signalling pathways in general — cannot be understood by looking at isolated components. Instead, it is essential to consid- er the tangled networks into which these sig- nalling components are integrated. many cases it even causes the programmed death (apoptosis) of the cells in a desperate attempt to contain the damage and protect the organism. The p53 protein therefore pro- vides a critical brake on tumour develop- ment, explaining why it is so often mutated (and thereby inactivated) in cancers.

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Error and attack tolerance of complex networks

by Vito Latora

2004, Physica A: Statistical …

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The Attention System of the Human Brain

by Siddheshvarananda Avt

1990, Annual Review of Neuroscience

Figure 1 The posterior attention system. The upper two drawings are the lateral (left) and medial (right) surfaces of the left hemisphere. The ower two drawings are the medial (left) and lateral (right) surfaces of the right hemisphere. The location of the posterior visual spatial altention system is shown on the lateral surface of each hemisphere as determined by blood flow studies (Petersen et al 1988a). The location of the visual word form area on the lateral surface of the left hemisphere is from Snyder et al (1989). BRENDAN Y AAR BALLARAT EL BO LEE MIE, LEE 1 OUTTIY VV IUI I, La) UI UI of lateralization found in nonliterate normals and patients differs fron that found in literate populations (Lecours et al 1988). The general anatomy of the attention system that we have been describ ing lies in the dorsal visual pathway that has its primary cortical projectiot area in V1 and extends into the parietal lobe. The black areas on th lateral surface of Figure | indicate the parietal projection of this posterio attention system as shown in PET studies (Petersen et al 1988a). Th parietal PET activation during visual orienting fits well with the lesion an single cell recording results discussed above. PET studies of blood flov so reveal prestriate areas related to visual word processing. For example n area of the left ventral occipital lobe (gray area in Figure 1) is activ during processing of visual words but not for letter-like forms (Snyder e a 1989). The posterior attention system is thought to operate upon th A. aL

Figure 2 The anterior attention system. The upper two drawings are the lateral (left) anc medial (right) surface of the left hemisphere. The /ower two drawings are the medial (/eft’ and lateral (right) surfaces of the right hemisphere. The semantic association area on the lateral aspect of the left hemisphere is determined by blood flow studies (Petersen et a! 1988b), The anterior attention area is also from blood flow studies (Petersen et al 1988b. Posner et al 1988).

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Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn's disease

by Curt Tysk and

2001, Nature

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Glioma stem cells promote radioresistance by preferential activation of the DNA damage response

by ROGER MCLENDON

2006, Nature

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Entanglement of formation of an arbitrary state of two rebits

by Carlton Caves

2001

We consider entanglement for quantum states defined in vector spaces over the real numbers. Such real entanglement is different from entanglement in standard quantum mechanics over the complex numbers. The differences provide insight into... more

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A fast quantum mechanical algorithm for database search

by Lov Grover

1996, Proceedings of the twenty-eighth annual ACM symposium on Theory of computing - STOC '96

Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic) will need to look at a... more

Figure 1. Inversion about average operation. amplitude in each state increases (decreases) so that after this operation it is as much below (above) © as it was above (below) & before the operation.

Figure 2. The inversion about average operation is applied to a distribution in which all but one of the com-

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The next generation of scenarios for climate change research and assessment

by Richard Moss and

2010, Nature

Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth's climate system and its likely response to human and natural influences. The implications of climate... more

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Involvement of chemokine receptors in breast cancer metastasis

by jose luis

2001, Nature

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Mitochondrial Dysfunction and Oxidative Stress in Insulin Resistance

by Antonio Hernandez-mijares and

2013, Current Pharmaceutical Design

Oxidative stress and low-grade inflammation are the hallmarks of the aging process and are even more enhanced in many age-related degenerative diseases. Mitochondrial dysfunction and oxidative stress can provoke and potentiate... more

Fig. 1 Mitochondrial dysfunction activates ROS production and secretion of mitochondrial DAMPs which activate NLRP3 inflam- masomes and subsequently enhance the appearance of the proinflammatory phenotype during the aging process and in age- related diseases. Loss of mitochondrial integrity triggers the release of mtDNA and synthesis of ceramides and formyl peptides. Autophagic clearance of damaged mitochondria maintains mitochondrial integrity and prevents the activation of NLRP3 inflammasomes

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Calcium signalling: dynamics, homeostasis and remodelling

by Llewelyn Roderick

2003, Nature Reviews Molecular …

-igure 1 | Calcium-signalling dynamics and homeostasis. During the ‘on’ reactions, stimuli induce both the entry of external Ca** and the formation of second messengers that lease internal Ca?* that is stored within the endoplasmic/ sarcoplasmic reticulum (ER/SR). Most of this Ca?* (shown as ‘ed circles) is bound to buffers, whereas a small proportion oinds to the effectors that activate various cellular processes that operate over a wide temporal spectrum. During the ‘off’ eactions, Ca** leaves the effectors and buffers and is removed rom the cell by various exchangers and pumps. The Na*/Ca?* exchanger (NCX) and the plasma-membrane Ca?*-ATPase PMCA) extrude Ca?* to the outside, whereas the sarco(endo)plasmic reticulum Ca?*-ATPase (GSERCA) pumps Ca?* back into the ER. Mitochondria also have an active junction during the recovery process in that they sequester Ca?" apidly through a uniporter, and this is then released more slowly oack into the cytosol to be dealt with by the SERCA and the MCA. Cell survival is dependent on Ca?+ homeostasis, whereby the Ca?* fluxes during the off reactions exactly match those during the on reactions. [Ca?*], Ca?* concentration; ns(1,4,5)P,R, inositol-1 ,4,5-trisphosphate receptor; RYR, ryanodine receptor.

Figure 2 | Calcium-mobilizing messengers and modulators. Various second messengers or modulators regulate the release of Ca?* from internal stores by the inositol-1 ,4,5-trisohosphate receptor (Ins(1,4,5)P,R) or the ryanodine receptor (RYR). These release channels are sensitive to factors that function from the cytosol and from within the lumen of the endoplasmic/sarcoplasmic reticulum (ER/SR). The Ins(1,4,5)P,R is regulated by inositol-1 ,4,5-trisphosphate (Ins(1,4,5)P.), which is generated by various signalling pathways using different isoforms of phospholipase C (PLC; , 5, €, yand ¢). The nucleotides cyclic ADP ribose (CADPR) and nicotinic acid adenine dinucleotide phosphate (NAADP) are generated by ADP ribosyl cyclase, which has both synthase (S) and hydrolase (H) activity. This dual-function enzyme might be sensitive to the cellular metabolism, as ATP and NADH inhibit the hydrolase. Just how cADPR and NAADP function is still unclear, but they seem to have an indirect action. cADPR might function by stimulating the sarco(endo)plasmic reticulum Ca?*-ATPase (SERCA) pump, which increases the luminal level of Ca?*, which results in sensitization of the RYR. NAADP functions through a channel that is located on alysosomal-like organelle to release Ca** that can either stimulate the Ins(1,4,5)P,R or the RYR directly, or might function indirectly, like cADPR, to increase the lumenal level of Ca?*. Ptdins(4,5)P,, phosphatidylinositol-4,5-bisphosphate.

and generate the rapid Ca** fluxes that control fast cellular processes such as muscle contraction or exo- cytosis at synaptic endings (BOx 2, part c). are sensitive to a diverse array of stimuli, such as the STORE-OPERATED CHANNELS (SOCs), thermosensors and stretch-activated channels. Many of these channels belong to the large transient receptor protein (TRP) ion-channel family*'™, which are encoded by up to 23 different genes. This family consists of three groups — the canonical TRPC family, the vanilloid TRPV family and the melastatin TRPM family (Box 1). TRP channels tend to have low conductances and therefore can oper- ate over much longer time scales without swamping the cell with too much Ca**. Members of the TRP family are particularly important in controlling slow cellular processes such as smooth-muscle contractility and cell proliferation.

Figure 3 | Cardiac calcium-signalling module. This self-contained module generates the localized Ca?* ‘sparks’ that are responsible for activating contraction and perhaps also gene transcription (Ca?* is shown as red circles). Signalling begins with an amplification step in the junctional zone, where the L-type channel on the T-tubule membrane responds to depolarization by introducing a small pulse of trigger Ca?*, which then diffuses across the narrow gap of the junctional zone to activate ryanodine receptor 2 (RYR2) (BOX 2, part a) to generate a spark. Ca?* from this spark diffuses out to activate contraction. Recovery occurs as Ca** is pumped out of the cell by the Na*/Ca?* exchanger (NCX) or is returned to the sarcoplasmic reticulum (SR) by sarco(endo)plasmic Ca?*-ATPase (GSERCA) pumps on the non-junctional region of the SR. A proportion of this Ca?* travels through the mitochondria, during which time it stimulates the metabolism to provide the ATP that is necessary to maintain contraction and transcription. The Ca?* that is returned to the SR ‘tunnels’ back to the junctional zone to be used again for subsequent heart beats. This circulation of Ca?* is modulated by second messengers such as cyclic AMP (cAMP), which removes the inhibitory action of phospholamban (PLN), or by cyclic ADP ribose (CADPR) that activates the pump to increase the amount of releasable Ca?* in the SR.

Figure 4 | A calcium-induced calcium-signalling remodelling hypothesis. Cell-specific Ca?’ signalsomes that are created by selecting components from the Ca?*-signalling toolkit (BOX 1) generate Ca?* transients that are characteristic for each cell type. It is proposed that the Ca?* transient has two functions. In addition to activating cellular responses, it also functions as part of a feedback mechanism to regulate the transcriptional events that are responsible for maintaining the signalsome. This Ca?*-dependent transcriptional regulation might have a central role in the compensatory mechanisms that enable cells to adapt to any modifications of their Ca?*-signalling systems. It seems that Ca?* can adjust transcriptional activity both positively and negatively. Diseases such as manic depression, hypertension, diabetes and congestive heart failure might develop from a failure of this proposed phenotypic remodelling system.

Figure 5 | Signalling pathways that participate in the control of compensatory hypertrophy. A key element of this remodelling process is the Ca?* that is released by the cardiac signalling module (FIG. 3). This Ca?* signal is enhanced during hypertrophy by the adrenergic pathway that functions through adenylyl cyclase (AC) to increase cyclic AMP (CAMP), which enhances signalling by phosphorylating the entry channel (Ca,1.2), ryanodine receptor 2 (RYR2) and phospholamban (PLN). Ca’* functions through calcineurin (CN) to dephosphorylate the transcription factor NFATS, thereby enabling it to enter the nucleus to induce the transcription of genes, some of which are fetal genes. Hypertrophy can also be enhanced by angiotensin Il and endothelin that function through G, and phospholipase C-f (PLC) to generate inositol-1 ,4,5-trisohosphate (Ins(1,4,5)P,), which could enhance Ca**, and diacylglycerol (DAG), which seems to function by recruiting the mitogen-activated protein kinase (MAPk)-signalling pathway to stimulate cAMP response element-binding protein (CREB). The phosphatidylinositol 3-kinase (PI3K)-signalling pathway, which is activated by insulin-like growth factor (IGF-1), contributes to hypertrophy by inhibiting the glycogen synthase kinase 3 (GSK-3) that inactivates NFATS, by stimulating Bcl-associated death promoter (BAD) to inhibit apoptosis and by stimulating p705* (70-kD ribosomal S6 kinase) to stimulate the expression of the newly transcribed genes. Cav-3, caveolin-3; GATA4, zinc-finger transcription factor; HDAC, histone deacetylase; MEF2, myocyte enhancer factor 2; MEK, MAPK kinase; NFAT, nuclear factor of activated T cells; PDK, phosphoinositide-dependent protein kinase; PKB, protein kinase B; PKC, protein kinase C; Ptdins(4,5)P.,, phosphatidylinositol-4,5-bisphosphate; Ptdins(3,4,5)P.,, phosphatidylinositol-3,4,5-trisohosphate; SOS, Son of sevenless; TnC, troponin C.

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Systematic conservation planning

by Isabella Sarfo Mireku

2000, Nature

The realization of conservation goals requires strategies for managing whole landscapes including areas allocated to both production and protection. Reserves alone are not adequate for nature conservation but they are the cornerstone on... more

insight residual from intensive uses, giving them a political advantage over goals such as representativeness, which focus also on disturbed, economically productive landscapes (Fig. 1). planning will enhance the effectiveness with which science can dc these three things.

Systematic conservation planning can be seen as a process in six stages” (Box 1), each of which is discussed below with examples of the tasks and decisions required. The process is not unidirectional — there will be many feedbacks and reasons for revised decisions about priority areas. For example, it will be necessary to re-examine conser- vation goals as knowledge accumulates, and replacement candidate reserves will have to be identified when unforeseen difficulties arise inimplementation. Although our discussion focuses on reserves, the framework applies equally well to many problems in ‘off-reserve’ conservation, including habitat restoration®”°. Decisions about both on- and off-reserve conservation, if they are not to be ad hocand uncoordinated, should be guided by explicit goals, identification of priorities in regional or broader contexts, and clear choices between

Planning is essentially a matter of comparison so it is preferable to compare two or more areas with the same kind of information at the same level of detail. A map of vegetation types (communities or habi- tat types) and/or environmental classes provides spatial consistency across wide areas. On the other hand, museum and herbarium data on the locations of taxa are notoriously biased, having been collected for a different purpose (systematics), and often in an opportunistic manner, from the places that collectors expected to find what they were looking for or that were conveniently accessible”. Plots of the field records from many collections therefore map road networks. Various methods — empirical, statistical and computational — are now available for modelling wider spatial distribution patterns from the point records that field samples represent*’™, but their reliability is also at least partly a function of the degree of spatial bias. New systematic field surveys to fill gaps are the best solution but they can be expensive and time consuming.

Figure 5 Pattern of complementarity on part of the south coast of New South Wales. The map is based on the same data used in the C-Plan decision-support system’ in late 1999 to guide negotiations between interest groups over new forest reserves in the region. The eastern boundary is the coastline. Blue areas are reserves established before the negotiations. Grey areas are tenures not considered in the planning process. Other polygons are logging compartments (average area about 200 ha or 2 x 10° m’) used as the building blocks of the expanded reserve system. Colours of these indicate five intervals of ‘percent age contribution’, the measure used in this exercise to indicate complementarity with existing reserves. Highest values are red (81—-100%) and grade through pink, orange, dark yellow, pale yellow (>0—20%) and white (0%). Values of percentage contribution are based on reservation targets (in hectares) for each of 107 forest ecosystems in the region. Percentage contribution is calculated in two stages. In the first stage, aco T, where A,is the extent regional reservation target for the forest ecosystem, taking into account the contributions of existing reserve status, and C;is orest ecosystem to the highest values are large’ rom the large reserves contrast, the small coas of the adjacent compart higher values reflect the tribution value (in hectares) for each forest ecosystem in each compartment is calculated using two rules — if A, s7;then C= A; if A,> 7,then C;= x! of forest ecosystem /in the compartment, 7,is the remaining reserves and any compartments previously given notional the current contribution of the compartment’s sample of the arget. In the second stage, percentage contribution of the compartment is calculated as the sum of Cvalues across all the forest ecosystems it contains, expressed as a percentage of the compartment’s area. Compartments with y or fully occupied by forest ecosystems well below target. Compartments with zero values contain only forest ecosystems with targets already achieved. Complementarity values show a marked association with distance eastwards in the westerly escarpment and more rugged foothills. In al reserves have no apparent influence on the complementarity ments because they contain little forest. In the far northwest, occurrence of forest ecosystems of the tableland, which are poorly reserved in the nearby escarpment reserves. Because complementarity is dynamic, percentage co ntribution was recalculated and redisplayed during the negotiations whenever one or more compartments were notionally reserved. If reserves become remnants of natural habitat surrounded by alien habitat such as cropland or pasture, changes brought about by isolation and exposure have implications for the persistence of species within them (Fig. 4). Changes in fluxes of wind, water and solar radiation” can lead, in turn, to changes in vegetation structure, microclimate, ground cover and nutrient status’. These changes may favour some species, but they also lead to reduced population sizes and local extinction of others’*’’. Once isolated and exposed, habitat remnants may be placed ona trajectory of continued change. Deleterious effects can feed back on themselves to increase their magnitude”, they can simply accumulate with time”, or they can cascade, with a change in a species’ abundance or productivity leading to unforeseen changes in the populations of other species. In

Figure 6 Pattern of irreplaceability in part of he northeast forests of New South Wales. The map is based on the same data and calculations of irreplaceability used in the C- Plan decision-support system’ in 1998 to gui de negotiations between interest groups over new reserves in the region. Blue areas, grey areas and other polygons as in Fig. 5. The gradient from red to white indicates irrepl based on the mix of forest ecosystems within 198 forest ecosystems across the region, the hectares, and the extent to which each target Red areas are totally irreplaceable; if they are laceability values of logging compartments each compartment, the distributions of ir individual reservation targets in is already met in the existing reserves. not reserved, one or more targets will not be met. Progressively lower values (pink, oran ge, dark yellow, pale yellow and white) indicate logging compartments with progressively more replacements. With lower values, the options for achieving targets are less constrained if compartments are unavailable or prove unsuitable for reservation. Like complementarity, irreplaceability is a dynamic measure. In the 1998 negotiations , values were recalculated each time one or more compartments were notionally reserved.

unidirectional. New data on patterns and processes within a reserve might call for revised goals. More generally, ongoing management should be complemented by periodic monitoring (back to stage 3) to assess the effectiveness of management actions in achieving nomi- nated goals, with subsequent adjustment of goals and activities as appropriate. Adaptive management”, coupled with a genuine com- mitment to monitoring, is increasingly recognized as crucial, not only to follow the status of selected elements of biodiversity, but also to assess the adequacy of resources for management, the capability of the responsible institutions, and the accountability with which funds are being used’™. PIQUE OPV IGITOWUIRA TUL IUCHULYT TY PIULILY UUTOGIVAUUT alGdo HI UNIO ail ovduu, ions to environments or other land types” or to potential conservation areas‘**°, The graph shows hypothetical data for 100 potential applicable within regi conservation areas, each with agricultural potential) replacements. Selected areas proportion increases scales", Quadra Protection is urgent i apply (private tenure values for irreplaceability and vulnerability (for example, . Red points are a subset of areas that are notionally selected to achieve targets but not yet given reservation status. Blue points are possible with high with off-reserve management. Qu replacements, either targets or because tai are necessary to avoi 1. Options for protec reserves in quadrant rocky ranges in a mai of agriculture). Protection is less because feal dl loss of son occur in all parts of the graph, although the selected er irreplaceability. If not all selected areas can be protected immediately (a common situation ime. Some of the more vulnerable areas are likely to be converted to agriculture. As this happens, the irreplaceability of some of the remaining areas will increase as they become more important for achieving targets for features that are now less extensive and/or less frequent elsewhere. Conversely, as areas are progressively reserved, the irreplaceability of others will decrease as the features they contain approach or reach heir conservation targets. The vulnerability of areas will also change, most likely upwards as land-use pressures intensify. Appropriate responses by conservation planners can be related to the different quadrants, as in previous studies at broade nt 1: areas most likely to be lost and with fewest replacements. targets are not to be compromised. Some will probably be ragments of previously extensive vegetation types where strict reservation is difficult to or impractical (management liabilities) and must be supplemented , the positions of areas in the graph will change over = adrant 2: areas vulnerable to loss but with more ures are relatively common and extensive relative to rgets have been partly met in existing reserves. Holding measures e areas causing others to move upwards into quadrant ion include reservation where appropriate (and without pre-empting 1) complemented with off-reserve management. Quadrant 3: areas with lower present risk of agricult ral conversion but high irreplaceability (for example, rix of agricu ural land or rare land types outside the climatic limits rgent and acquisition for reservation more feasible than for quadrants 1 and 2 because of slower rates of transformation and (likely) lower land prices. Quadran least intervention. alt! 4: the positi ons of areas here are likely to be stable and require hough monitoring of land use is advisable.

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Identification of stem cells in small intestine and colon by marker gene Lgr5

by Miranda Miranda

2007, Nature

The intestinal epithelium is the most rapidly self-renewing tissue in adult mammals. It is currently believed that four to six crypt stem cells reside at the 14 position immediately above the Paneth cells in the small intestine; colon... more

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Recent advances in magnetic structure determination by neutron powder diffraction

by Juan Rodríguez-Carvajal

1993, Physica B: Condensed Matter

Abstract In spite of intrinsic limitations, neutron powder diffraction is, and will still be in the future, the primary and most straightforward technique for magnetic structure determination. In this paper some recent improvements in the... more

$Fig. 1. Plot of the profile matching result, refinement without structural model, obtained for the oxide Co, TeOQ,. The satellites (second row of reflection markers) are broadened and have a lorentzian shape with a propagation vector [0 08] with 5 ~ 0.08 (see ext). J. Rodriguez-Carvajal ! On magnetic structure determination by neutron powder diffraction$

Fig. 3. Variation of the average R-factor and the percentage of accepted jumps for model 2 of panel II (see appendix) for Er,Cu,Q, as a function of temperature. J. Rodriguez-Carvajal | On magnetic structure determination by neutron powder diffraction

Fig. 4. Average values of 8 angular parameters as a function of temperature. Note that large fluctuations dominate at high temperature and the parameters change slowly in the ‘refinement region’ (model 2 of panel II).

$Fig. 5. Comparison between the low-angle portions of the neutron diffraction patterns, at 1.5K on D1B, of two different samples of CsMnF,. Two symmetry-unrelated propagation vectors, k, = [0065] and k, = (00 4], are present in both cases. course of analysis from the point of view of the involved physics [29]. Here we shall be inter- ested only in the problem of magnetic structure refinement. The compound was described as a planar ferromagnet [30] and belongs to the space group P4/n. The crystal structure is very simple 29,30] and has MnF, octahedra forming perov- skite layers (of composition MnF,) separated by Cs” ions. There is no Mn—F—Mn superexchange path between layers. Due to the Jahn-Teller effect of Mn*~ and the antiferrodistorsive orbital ordering within the perovskite layers, the in- plane Mn-F—Mn exchange is ferromagnetic and much more intense than the interaction between adjacent layers. The weakness of this later inter- action and, probably, the existence of structural defects perturbs the ferromagnetic ground state causing a more complex magnetic structure. Two different prepared samples [29] have been studied. In fig. 5 a comparison between the low angle portions of their neutron diffraction pat- ferns, at 1.5K on D1B, is presented. One can observe that two symmetry-unrelated propaga- ion vectors, k,=[006] and k,=[004], are present in both cases. From the figure it is deduced that (k,, —k,) and k, are correlated. In fig. 6 is presented the low-angle part of the profile refinement using the above models. The resulting magnetic structure corresponds to a perturbed helix described by the formula given$

Fig. 6. Plots (a and b) of the observed and calculated patterns of the low-angle part for the two samples (A and B) of CsMnF The fit is performed with the model discussed in the text and detailed in panel [I of the appendix. J. Rodriguez-Carvajal | On magnetic structure determination by neutron powder diffraction

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Quantum phase transition from a superfluid to a Mott insulator in an ultracold gas of atoms

by A. Altmeyer and

2003, Physica B: Condensed Matter

A quantum phase transition from a superfluid to a Mott insulating ground state was observed in a Bose-Einstein condensate stored in a three-dimensional optical lattice potential. With this experiment a new field of physics with ultracold... more

Fig. 1. Time of flight absorption images of multiple matter wave interference pattern 15 ms after releasing the atoms from an optical lattice potential: (a) Superfluid state for a 7E, deep lattice; (b) Mott insulator with no phase coherence for a 20E, lattice; (c) After ramping the potential down to 7£, again the phase coherence is restored.

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Mdm2 promotes the rapid degradation of p53

by Ygal Haupt

1997, Nature

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Self-organized criticality

by C Tang

1988, Physical Review A

We show that certain extended dissipative dynamical systems naturally evolve into a critical state, with no characteristic time or length scales. The temporal "fingerprint" of the self-organized critical state is the presence of flicker... more

FIG. 1. One-dimensional “sand-pile automaton.” The state of the system is specified by an array of integers representing the height difference between neighboring plateaus. (a) There is a wall at the left and sand can exit only at the right; (b) there are walls at both ends. Equation (2.2) is a nonlinear discretized diffusion equa- tion (nonlinear because of the threshold condition). The process continues until all the z, are below threshold, at which point another grain of sand is added (at a random site) via Eq. (2.1). The model is a cellular automaton where the state of the discrete variable z, at time t +1 de-

FIG. 2. Typical domain structures resulted from several local perturbations for a 100 100 array. Each cluster is triggered by a single perturbation. Once relaxed, the properties of the state are probed by locally perturbing the system. Specifically, we randomly select a minimally stable site [i-e., with z(x,y)=z,] and enforce Eq. (3.2). This corresponds to pushing two units of sand downward in the diagonal direction; we thus in- duce a “sand slide.” This, in general, will cause further slidings as the perturbation spreads. We then measure the total number of slidings s induced by the single per- turbation. Note that this operationally defines a domain over which a given perturbation is communicated. After each perturbation, the original static state is restored, and another site is perturbed, and so on. Figure 2 shows a typical domain structure obtained from a number of single-site-induced perturbations. The dark sites are domains affected by perturbing a single interior site. One sees that domains of a variety of sizes exist, from a single site up to one that is comparable to the system size itself. (Note that tickling the interior of a single domain at different individual sites need not result in precisely the same domain boundary.) In a sense, we are measuring the linear response of the system under infinitesimal per- turbations. The quantity being measured is the distribu- tion function D(s) of slide sizes. In the simulation, we

FIG. 3. Distribution of cluster sizes at criticality in two and three dimensions computed as described in the text. The data have been coarse grained. (a) 5050 array, averaged over 200 samples. The dashed line is a straight line with slope — 1.0; (b) 20 20X20 array, averaged over 200 samples. The dashed straight line has a slope — 1.37. The fact that the distributions in Fig. 3 begin to deviate from a power law at large cluster sizes is a finite-size effect. For example, in the 50 x 50 array the deviation be- gins around s ~200, whereas simulations on a 20 20 ar- ray (not shown) deviate at s=70. To verify that this is really a finite-size effect, we borrowed a page from the analysis of equilibrium statistical physics and performed

We now give the “‘sliding” a new meaning, namely a point of energy dissipation: When a sliding event occurs, a unit of energy is dissipated. Let us introduce the quan- tity f(x,t) representing dissipation of energy at site x at time t. The process (3.2) represents dissipation of one

FIG. 5. Cluster size distribution for system built up from scratch according to rules (3.2) and (3.8) for a 50X50 array. The curve is indistinguishable from that in Fig. 3(a). For this system the system is in a stationary critical state and it is self- averaging. Rule (3.8) has been applied 100000 times to the sta- tionary critical state to obtain this curve.

FIG. 7. Power spectrum of the function F(t) depicted in Fig. 6. The spectrum is 1/f, varying as f—°°8. The crossover to white noise at very low frequencies is a finite-size effect. The scaling laws simulation. We found that removing at random as many at 25% of the bonds still led to power-law distributions. Figure 8 shows the cluster size distribution for a situation with 10% of the bonds removed. No change in the ex- ponent was detected. Whether this is due to true univer- sality of the exponent, or due to our inability to detect a small change numerically is not known. Quantitatively, the presence of this kind of randomness increases the mean value of the pressure z since fewer nearest neigh- bors are available to communicate the noise. In the sand picture, the introduction of impedements causes a build-

FIG. 6. F(t) generated by superimposing randomly the response represented by the individual clusters for a 20 x 20 x 20 array. Note the fluctuations on a wide range of time scales.

FIG. 8. Cluster size distribution for 20x20 array with 10% of the bonds removed, averaged over 1000 samples. The slope is — 1.0, same as for the pure system.

FIG. 10. Lifetime distribution of the sand flow for a system of size 7575. The straight line has a slope — 1.05.

FIG. 9. The critical sand pile for a 2D system with open edge perpendicular to flow. - To test the assertion that the lifetime distribution is scaling, with cutoff due only to the finite size, we applied a technique familiar from the study of critical phenomena

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Dynamics of Dark Energy

by Muhammad Sami

2006, International Journal of Modern Physics D

In this paper we review in detail a number of approaches that have been adopted to try and explain the remarkable observation of our accelerating Universe. In particular we discuss the arguments for and recent progress made towards... more

FIG. 1: Luminosity distance dz in the units of Hy! for a two component flat universe with a non-relativistic fluid (wm = 0) and a cosmological constant (wa = —1). We plot Hodz for various values of af.

FIG. 3: The age of the universe (in units of Hy") is plotted against Q\) for (i) a flat model with QO) +4 2 = 1 (solid curve) and (ii) a open model (dashed curve). We also show the border to = 11 Gyr coming from the bound of the old- est stellar ages. The region above this border is allowed for consistency. This constraint strongly supports the evidence of dark energy.

FIG. 4: The 2? of confidence regions constrained from the observations of SN Ia, CMB and galaxy clustering. We also show the expected confidence region from a SNAP satel- lite for a flat universe with Q = 0.28. From Ref. [06).

In the flat Friedmann background we obtain the energy density and pressure density of the scalar field:

Hence this induces a Lagrangian with noncanonical ki- netic terms:

We note that this procedure is analogous to the recon- struction methods we adopted for the quintessence and tachyon potentials. Since the Hubble expansion rate is given by H = (8rp/3m2,)'/?, we can rewrite Eq. (152) in terms of the derivative of a:

FIG. 5: The phase plane for 1 = 2 and y = 1. The scalar field dominated solution (c) is a saddle point at a = (2/3)'/? and y = (1/3)'/*. Since the point (d) is a stable spiral in this case, the late-time attractor is the scaling solution with a = y = (3/8)'/?. From Ref. [14].

In what follows we clarify the properties of the five fixed points given in TABLE I. Basically we are interested in a fluid with 0 < y < 2. The point (a) corresponds to a fluid dominated solution and is a saddle point since fy <0 and pe > 0. The points (b1) and (b2) are either an unstable node or a saddle point depending upon the value of \. The point (c) is a stable node for \? < 3y, whereas it is a saddle point for 3y < A? < 6. Since the effective equation of state is weg = we = —1+ d2/3 from Eqs. (179) and ([8I), the universe accelerates for d? < 2 in this case. The point (d) corresponds to a scaling solution in which the energy density of the field @ decreases proportionally to that of the barotropic fluid (Ys = 7). Since both jz; and pig are negative for \? > 3y from Eq. (18%), the point (d) is stable in this case. Meanwhile it is a saddle point for A? < 3y, but this case is not realistic because the condition, Qg, < 1, is not satisfied. We note that the point (d) becomes a stable spiral for \? > 24y7/(9y — 2). TABLE I: The properties of the critical points for the quintessence model (I70) with « by Eq. (182).

Let us define the following dimensionless quantities: The energy density and the pressure density of a tachyon field are given by Eqs. (28) and (129), with the tachyon satisfying the equation of motion ([3]). In the presence of a barotropic fluid whose equation of state is y= 1+wm =1+Pm/Pm, Equations (15%) and (58) give

FIG. 6: Evolution of the parameters x and y together with the critical points x- and ye for tachyon with potential V(¢) = M°¢~' and a barotropic fluid with y = 1. We choose initial conditions x; = 0.8, yi = 5.0 x 1074 and \; = 1.0. The so- lution approaches instantaneous critical points whose asymp- totic values are x_ = 0 and ye = 1. From Ref. [179]. JO) in the case of tachyon. y; is defined in Eq. GOD

TABLE III: The critical points for the inverse square potential (200) 1. In the limit 4 — 0 one has « — 0 and y — 1 for the point (c), which means that slow-roll approximations can be used at late-times. The slow-roll parameter for the tachyon is given by {170}.

FIG. 7: Evolution of Q4, Qm, we, x and y" forc=1, wm =0 and A = 0.1 with initial conditions x; = 0.0085 and y; = 0.0085. The solution approaches the scalar-field dominated fixed point (c) with a? ~ 1.834, y? = 3.561 and Y ~ 0.515, Q¢ =1 and Q,» = 0. The equation of state in the attractor regime is given by wg = —0.889. From Ref. [9].

the above equations can written in an autonomous form The equation of state and the fraction of the energy den- sity for the field can now be written as

TABLE IV: The critical points for the dilatonic ghost condensate model given by (45). Here Y and f+(A) are defined Eqs. @17) and (20).

FIG. 8: Evolution of the energy density pg for 4 = 20 and pu = 0.5. The background energy density Pmatter + Pradiation is plotted as a dotted line. Even when pg is larger than Pmatter + Pradiation at the initial stage, the solutions approach the scaling regime in which the scalar field energy density is subdominant and tracks the background fluid. We thank Nelson J. Nunes for providing us this figure.

TABLE V: The critical points for the ordinary (phantom) scalar field with an exponential potential in the presence of the coupling @. The points (b1) and (b2) do not exist for the phantom field.

FIG. 10: Top panel shows the evolution of QR (dashed), Qu (dotted) and Q4 (solid) with \ = 30 in the case where the coupling Q changes rapidly from Qi = 0 to Q2 = 57.15. Bottom panel shows the evolution of the effective equation of state Yer = Wer + 1. It first equals 1/3, then goes down to 1, and approaches —0.7 with an accelerated expansion. From Ref.

FIG. 9: Evolution of QR, Qu and Q¢g in a coupled quintessence scenario for (i) \ = 0.1, Q = 0 and (ii) A = 0.1, Q = 0.245. In these cases the late-time attractor is the scalar-field dominated fixed point (d) in Table [YI] In the case (ii) there exists a transient fixed point (a) characterized by Q4 = 2Q?/3 ~ 0.04 during the matter dominated era, whereas this behavior is absent in the case (i).

FIG. 11: Evolution of Aa/a for a coupled quintessence model with contributions Qm,- = 0.05 and Qg = 0.7 today. The solid and dashed curves correspond to A = 100 and A = 10, respectively. We also show observational data with error bars. We thank Nelson J. Nunes for providing us this figure.

FIG. 12: Contour plot of the index n+ in terms of the func- tions of Qg and wer. The numbers which we show in the figure correspond to the values n+. In the non-phantom region char- acterized by 24+ Wer > 0, n+ are always positive. Meanwhile in the phantom region (Q4 + wee < 0) with weg > —1, n+ take complex values with negative real parts. The real parts of n+ are plotted in the phantom region. The box (blue in the color version) represents schematically the observational constraints on Weg, Q¢ coming from the SN Ia data.

FIG. 13: Evolution of w(z) versus redshift z for QW = 0.3 with the parametrization given by (426). Here the thick solid line corresponds to the best-fit, the light grey contour rep- resents the lo confidence level, and the dark grey contour represents the 20 confidence. The dashed line corresponds to the ACDM model. From Ref. [8Q}. higher-order derivatives of H called “state finder” [57], and see where the authors have proposed a new non- parametric method of smoothing supernova data over redshift using a Gaussian kernel, the aim being to recon- struct H(z) and w(z) in a model independent manner.

FIG. 14: Reconstruction of generalized ghost condensate model for the parametrization (426) with the best-fit param- eters Aj = —4.16 and Az = 1.67. We show u, w and z in terms of the function of ¢. This model allows a possibility to cross the cosmological-constant boundary (w = —1).

Case (i) includes the ACDM model. Case (ii) was in- troduced_by Huterer and Turner (391) & Weller and Al- brecht |392] with n < 1, ie., won = wo + wiz. In this case Eq. (433) gives the Hubble parameter where several expansion functions have been considered

FIG. 16: Evolution of the equation of state of dark energy for the best-fit Kink parametrization. The maximized limits on w(z) are shown for (a) redshift (red dashed line), (b) scale- factor (green dash-dotted), (c) logarithmic (blue-dotted), and (d) Kink (solid black lines) parametrizations. From Ref. |389].

FIG. 15: Schemtic illustration of the equation of state of dark energy for the kink parametrization (442). TABLE VIII: Best fits values of wo and wi for several different Taylor expansions at linear order. Error bars correspond to the lo confidence level. From Ref. sg}.

FIG. 17: The shift of the power spectrum for the equation of state w = —0.5, 1.0, —2.0, —4.0 with h = 0.69, AY, = 0.252 and af = 0.046. The spectrum shifts toward larger | for smaller w. From Ref. [405].

FIG. 18: CMB angular power spectra for three different models without dark energy perturbations. The solid line, dotted line and dashed line correspond to (a) w = —1, QW = 0.3, 2 = 0.05, Ho = 65kms~'Mpc™!, (b) w = —0.6, QW = 0.44, 2 = 0.073, Ho = 54kms~!Mpc™!, and (c) w = —2.0, © = 0.17, 2 = 0.027, Ho = 84kms~!Mpc"!, respectively. When w = —2 there is a large contribution to low multipoles from the ISW effect. From Ref. [410].

FIG. 19: CMB angular power spectra for three different mod- els with dark energy perturbations. Each line corresponds to the same model parameters as in Fig. [[8] From Ref. (410).

FIG. 20: Likelihood contours for w and Q')) in the case of con- stant equation of state of dark energy at the 68% and 95% con- fidence levels. This is a combined analysis of CMB (WMAP1), 2dF, SN iy HST and BBN data sets. The solid line corre- sponds toe = 1, we the dashed line to marginalizing over c2. From Ref.

FIG. 21: The variation of dark energy density is shown as a function of redshift for the parameterisation (4) with p = 1. This is the combined constraints from WMAP1 and SNLS data. The green/hatched region is excluded at 68% confidence limit, red/cross-hatched region at 95% confidence level and the blue/solid region at 99% confidence limit. The white region shows the allowed range of variation of dark en- ergy at 68% confidence limit. The phantom like models have pon(z)/ppr(z = 0) < 1. The allowed values of wo at 95% confidence limit for this parameterisation are —1.89 < wo < —0.61 (with SNLS data), —1.64 < wo < —0.42 (with WMAP1 data) and —1.46 < wo < —0.81 when we combine the SNLS and WMAPI1 data. The values for w 1 for these data sets are constrained to lie in the range —4.82 < wi < 3.3 (SNLS), —3.09 < wi < 1.32 (WMAP1) and —0.99 < wi < 1.04 (com- bined). This clearly shows that the WMAP1 data is more effective in constraining the equation of state parameters are compared to the supernova data. From Ref.

FIG. 22: Large-scale redshift-space correlation function (mul- tiplied by the square of the separation s) from the SDSS sur- vey. From top to bottom the models are QO pn? =0. 12, 0.13, 0.14 and 0.105 with QO 7? = = 0.024. The bottom one cor- responds to a pure cold dark matter model, which does not have an acoustic peak. Meanwhile there exist acoustic peaks around 100h~' Mpc in other models. From Ref. [427].

Let us consider the case in which a phantom fluid (w < —1) is present together with the modulus string corrections. Equation (502) shows that the condition for the existence of the low-curvature solution (499) is not satisfied for Q = 0 and w < —1. However the presence of the coupling Q can fulfill this condition. This suggests that the Big Rip singularity may be avoided when the modulus field ¢ is coupled to dark energy. FIG. 23: Evolution of H and p with & = —2, w = —-1.1 for (a) Q = 0 and (b) Q@ = —5. We choose initial conditions as H; = 0.2, d; = 2.0 and p; = 0.1. The curves (al) and (b1) represent the evolution of H for Q = 0 and Q = —5, respectively, while the curves (a2) and (b2) show the evolution of p for corresponding Q.

FIG. 24: The lo, 20 and 30 contours drawn using the compi- lation of data sets from SN Ia, CMB, baryon oscillations and LSS observations. The ACDM model (a = —4.38, 3 = 0) is marked with the cross. The grey part represents the region which is excluded observationally. From Ref. [479]. and LSS data sets, the best fit values of the model pa- rameters were found to be (a, 3) = (—3.6,0.09). As is clearly seen in Fig. 24] the 6 = —1 case is ruled out ob- servationally. The allowed values of 3 exist in the narrow range: |G| < 0.2. Hence f(R) gravity models do not ex- hibit any significant observational preference compared to the GR case ((G = 0).

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Identification and expansion of human colon-cancer-initiating cells

by cesar p

2007, Nature

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The diameter of the world wide web

by Anderson Dorregaray Linares

1999, Computing Research Repository

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STRESS AND THE BRAIN: FROM ADAPTATION TO DISEASE

by Marian Florian

| In response to stress, the brain activates several neuropeptide-secreting systems. This eventually leads to the release of adrenal corticosteroid hormones, which subsequently feed back on the brain and bind to two types of nuclear... more

Box 2 | Diversity of mineralocorticoid and glucocorticoid receptor signalling in limbic neurons

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Consequences of changing biodiversity

by Erika Diaz

2000, Nature

Human alteration of the global environment has triggered the sixth major extinction event in the history of life and caused widespread changes in the global distribution of organisms. These changes in biodiversity alter ecosystem... more

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Ecological responses to recent climate change

by Durga Sharan Dubey

2002, Nature

There is now ample evidence of the ecological impacts of recent climate change, from polar terrestrial to tropical marine environments. The responses of both¯ora and fauna span an array of ecosystems and organizational hierarchies, from... more

Figure 1 Spatial variability of annual trends in temperature and precipitation since 1976 relative to 1961 to 1990 normals (ref. 1, modified). a, Temperature (°C per decade) b, precipitation (% per decade).

appear to profit from milder winter conditions, indicated here by the decreasing number of days with frost per year (the smoothed curve gives five year averages for the number of frost days per year)"’. Figure 3 Vegetation shift from indigenous deciduous to exotic evergreen broad-leav vegetation in southern Switzerland. The shrub layer is dominated by the growing number of spreading exotic evergreen broad-leaved species (see illustration) that Substantial impacts on community structure have been observed in coral reefs during periods of warmer than normal sea tempera- tures. Poised near their upper thermal limits, coral reefs have undergone global mass bleaching events whenever sea temperatures have exceeded long-term summer averages by more than 1.0°C for several weeks*!’, Six periods of mass coral bleaching have occurred The combination of rising temperatures and ENSO variability has generated contrasting impacts in Antarctic terrestrial versus tropical marine ecosystems. Increasing temperatures have reduced the likelihood that Antarctic organisms will be exposed to thei lower thermal limits, thereby allowing increases in both numbers and extent of populations previously at the edge of their range while also, in a few instances, increasing the risk of exposure to uppet

radiation) by using different Perspex types, VE and OX, between 1998 and 2000. These led within 2 years to an increased diversity in soil nematode communities (colours indicate the proportional contribution of major genera), comparable to that found naturally in more developed microhabitats (c). However the increased occurrence of bleaching events on coral reefs (d) is likely to decrease abundance if not diversity. Figure 4 Different environments and their responses to warming. Biodiversity is low in terrestrial communities in Antarctica (a), but very high in nearshore marine communities in tropical oceans (b). The response of these communities to warming seems to differ. Manipulations of Antarctic soils by using Perspex cloches provided realistic simulations of climate change (temperature increase and exposure to different wavelengths of UV

*Where possible, numbers of species which showed a response to climate change are given.

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Toll-like receptors and innate immunity

by Himanshu Kumar

2009, Biochemical and Biophysical Research Communications

The innate immune system is an evolutionally conserved host defense mechanism against pathogens.

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Vascular-specific growth factors and blood vessel formation

by Stanley C Atueyi

2000, Nature

A recent explosion in newly discovered vascular growth factors has coincided with exploitation of powerful new genetic approaches for studying vascular development. An emerging rule is that all of these factors must be used in perfect... more

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Chiral perturbation theory: Expansions in the mass of the strange quark

by Heinrich Leutwyler

1985, Nuclear Physics B

In a previous paper, we have shown how to systematically determine the low-energy structure of the Green functions in QCD. The present article extends this framework to expansions in the mass of the strange quark. We construct the... more

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Cosmological parameters from SDSS and WMAP

by Timothy McKay

2004, Physical Review …

We measure cosmological parameters using the three-dimensional power spectrum P (k) from over 200,000 galaxies in the Sloan Digital Sky Survey (SDSS) in combination with WMAP and other data. Our results are consistent with a "vanilla"... more

FIG. 4: 95% constraints in the (wg,wp) plane. Shaded dark red/grey region is ruled out by WMAP alone for 6-parameter “vanilla” models. The shaded light red/grey region is ruled out when adding SDSS information. The hatched band is required by Big Bang Nucleosynthesis (BBN). FIG. 3: 95% constraints in the (ns,w») plane. The shaded dark red/grey region is ruled out by WMAP alone for 6-parameter “vanilla” models, leaving the long degeneracy banana discussed in the text. The shaded light red/grey region is ruled out when adding SDSS information. The hatched band is required by Big Bang Nucleosynthesis (BBN). From right to left, the three vertical bands correspond to a scale-invariant Harrison-Zel’dovich spectrum and to the common inflationary predictions ns = 1— 2/N ~ 0.96 and ns = 1—3/N ~ 0.94 (Table 6), assuming that the number of e-foldings between horizon exit of the observed fluctuations and the end of inflation is 50 < N < 60.

FIG. 6: 95% constraints in the (Qm,os) plane. Shaded dark red/grey region is ruled out by WMAP alone for 6-parameter “vanilla” models. The shaded light red/grey region is ruled out when adding SDSS information. The 95% confidence regions are hatched for various recent cluster (black) and lensing (green/grey) analyses as discussed in the text. The vertical lines indicate the constraints described in [8] from mass-to-light ratios in galaxies and clusters (0.06 S Qm < 0.22) and from cluster baryon fractions (0.22 S Qm S 0.37). ~N FIG. 5: 95% constraints in the (Qm,h) plane. Shaded dark red/grey region is ruled out by WMAP alone for 6-parameter “vanilla” models, leaving the long degeneracy banana discussed in the text. The shaded light red/grey region is ruled out when adding SDSS information, which can be understood as SDSS accu- rately measuring the P(k) “shape parameter” hQm = 0.21 + 0.03 at 2c (sloping hatched band). The horizontal hatched band is re- quired by the HST key project [49]. The dotted line shows the fit h = 0.7(Qm/0.3)—°:3°, explaining the origin of the accurate con- straint h(Qm/0.3)°>> = 0.70 + 0.01 (10).

FIG. 9: 95% constraints in the (Qm,2,) plane. Shaded dark red/grey region is ruled out by WMAP alone for 7-parameter curved models, illustrating the well-known geometric degeneracy between models that all have the same acoustic peak locations. The shaded light red/grey region is ruled out when adding SDSS information. Continuing inwards, the next two regions are ruled out when adding the 7 < 0.3 assumption and when including SN Ia information as well. Models on the diagonal dotted line are flat, those below are open and those above are closed. The constraints in this plot agrees well with those in Figure 13 from [6] when taking the 7 prior into account.

FIG. 10: 95% constraints in the (ns,r) plane. Shaded dark red/grey region is ruled out by WMAP alone for 7-parameter mod- els (the vanilla models plus r). The shaded light red/grey region is ruled out when adding SDSS information. The two dotted lines delimit the three classes of inflation models known as small-field, large-field and hybrid models. Some single-field inflation models make highly specific predictions in this plane as indicated. From top to bottom, the figure shows the predictions for V(¢) « ¢ (line segment; ruled out by CMB alone), V(¢) « 4 (star; a text- book inflation model; on verge of exclusion) and V(¢) « ¢? (line segment; the eternal stochastic inflation model; still allowed), and V(¢) x 1— (¢/¢«)? (horizontal line segment with r ~ 0; still al- lowed). These predictions assume that the number of e-foldings between horizon exit of the observed fluctuations and the end of inflation is 64 for the ¢* model and between 50 and 60 for the others as per [86].

FIG. 11: 95% constraints in the (wg, fv) plane. Shaded dark red/grey region is ruled out by WMAP alone when neutrino mass is added to the 6 “vanilla” models. The shaded light red/grey region is ruled out when adding SDSS information. The five curves correspond to M,, the sum of the neutrino masses, equaling 1, 2, 3, 4 and 5 eV, respectively — barring sterile neutrinos, no neutrino can have a mass exceeding ~ M,/3.

FIG. 13: 95% constraints in the (Qm,w) plane. Shaded dark red/grey region is ruled out by WMAP alone when equation of state w is added to the 6 “vanilla” parameters. The shaded light red/grey region is ruled out when adding SDSS information, and the yellow/very light grey region is excluded when including SN Ia information as well.

FIG. 14: Effect of increasing the amount of SDSS data used, given by the maximum k-value used. Top panel shows how the relative errors on various parameters shrink as more data is included. For the neutrino density Q, = fy Qg, the absolute rather than relative error is shown. Bottom panel shows the ratio of systematic errors to statistical errors (from top panel) grows as smaller scales are included. This is for the extreme case where nonlinear corrections are present but completely ignored, which we view as a worst-case scenario.

FIG. 15: The reionization parameter Z as a function of the MCMC step. This example is for chain 6 from Table 8.

FIG. 16: The autocorrelation function (solid curve) for the exam- ple in Figure 15 is seen to be approximately fit by an exponential (dashed curve), dropping to 50% at a correlation length of 45 steps as indicated by the dotted lines.

FIG. 17: CMB data used. Error bars show do not include the calibration and beam uncertainties that we include as described ir the text. Solid curve corresponds to the “vanilla lite” model o: equation (2).

Table 1: Cosmological parameters used. Parameters 14-28 are determined by the first 13. Our Monte-Carlo Markov Chain assigns a uniform prior to the parameters labeled “MCMC”. The last six and those labeled “Fits” are closely related to observable power spectrur features [24—26] and are helpful for understanding the physical origin of the constraints. dom by 19 — 1 = 18 (since this requires the addition of the bias parameter b), yet raises the best-fit y? by only 15.7. Indeed, Figure 1 shows that even the model best fitting WMAP alone does a fine job at fitting the SDSS data with no further parameter tuning.

Table 2: lo constraints on cosmological parameters using WMAP information alone. The columns compare different theoretical priors indicated by numbers in italics. The penultimate column has only the six “vanilla” parameters (7,0Q),,wg,wp, As,ns) free and therefore gives the smallest error bars. The last column uses WMAP temperature data alone, all others also include WMAP polarization information. Figure 5 shows that the banana is well fit by h = 0.7(Qm/0.3)~°:3°, so even from WMAP+SDSS alone, we obtain the useful precision constraint h(Q»,/0.3)°?? = 0.6977) O17 (68%). 7 < 0.3), which cuts off much of the banana. Indeed, Fig- ure 2 shows that the distribution for several parameters (notably the reionization redshift zion) are bimodal, sc this prior eliminates the rightmost of the two bumps. In the present paper, we wish to keep assumptions to a min- imum and therefore break the degeneracy using the SDSS measurements instead. Figure 5 illustrates the physical reason that this works so well: SDSS accurately measures the P(k) “shape parameter” T = hQ,, = 0.21 + 0.03 at 20 [20], which crudely speaking determines the horizonta position of P(k) and this allowed region in the (Qm, h)- plane intersects the CMB banana at an angle. Once E- polarization results from WMAP become available, they should provide another powerful way of breaking this de- generacy from WMAP alone, by directly constraining 7 — from our WMAP+SDSS analysis, we make the predic- tion rT < 0.29 at 95% confidence for what this measure- ment should find. (Unless otherwise specified, we quote lo limits in text and tables, whereas the 2-dimensional figures show 2c limits.)

Table 3: lo constraints on cosmological parameters combining CMB and SDSS information. The columns compare different theoretical priors indicated by italics. The second last column drops the polarized WMAP information and the last column drops all WMAP information, replacing it by pree WMAP CMB experiments. The 6par+w column includes SN Ia information.

Table 4: 1o constraints on cosmological parameters as progressively more information/assumptions are added. First column uses WMAP data alone and treats the 9 parameters (7, Q,%, QA, wWa,wp, As,Ns,a@,7) as unknown, so the only assumptions are fy, = 0, w = —1. Moving to the right in the table, we add the assumptions r = a = 0, then add SDSS information, then add SN Ia information, then add the assumption that 7 < 0.3. The next two columns are for 6-parameter vanilla models (Q, = r = a = 0), first using WMAP+SDSS data alone, then adding small-scale non- WMAP CMB data. The last two columns use WMAP-+SDSS alone for 5-parameter models assuming ns = 1 (“vanilla lite”) and ns = 0.96, r = 0.15 (V « ¢? stochastic eternal inflation), respectively.

Table 5: Recent constraints in the (Om, ¢g)-plane.

strongly favors the inflationary model. Note that it did not have to come out this way: observing Qtot = 0.90 + 0.02 would have given 99.99% posterior probability for the anthropic model. from distributions Qtot = 1+0.02 and OQro¢ = 1 +1, respectively. If we approximate these distributions by Gaussians f(Qtot) = eUMtot-D/o]?/2 Jy 2no with o = 0.02 and o = 1, respectively, we find that the observed value is about 22 times more likely given inflation. In other words, if we view both models as equally likely from the outset, the standard Bayesian calculation

[able 6: Sample inflation model predictions. N is the number of e-folds between horizon exit of the observed fluctuations and the end inflation. therefore drop our priors on 2; and r when constraining Q.

Table 7: Robustness to data and method details.

Table 8: Monte Carlo Markov chains used in the chain. The figure of merit for a chain is the effective length (the actual length divided by the correlation length). Here we have chosen to tabulate correlation lengths for the 7-parameter, since it is typically the largest (together with that for n; and wz, because of the banana degeneracy of Section III A). The success rate is the percentage of steps accepted. “Vanilla” denotes the six parameters (7, wp, wa, a, As,ns). In the data column, T denotes the unpolarized power spectrum, X denotes the temperature/E-polarization cross power spectrum, and 7 denotes the prior 7 < 0.3.

FIG. 2: Constraints on individual cosmological quantities using WMAP alone (shaded yellow/light grey distributions) and including SDSS information (narrower red/dark grey distributions). Each distribution shown has been marginalized over all other quantities in the class of 6-parameter (7,0Q,,wg,wp,As,ns) “vanilla” models as well as over a galaxy bias parameter b for the SDSS case. The a-distributions are also marginalized over r and Q;. The parameter measurements and error bars quoted in the tables correspond to the median and the central 68% of the distributions, indicated by three vertical lines for the WMAP+SDSS case above. When the distribution peaks near zero (like for r), we instead quote an upper limit at the 95th percentile (single vertical line). The horizontal dashed lines indicate e-2*/2 for x = 1 and 2, respectively, so if the distribution were Gaussian, its intersections with these lines would correspond to lo and 2a limits, respectively.

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The complete genome sequence of the gastric pathogen Helicobacter pylori

by William Hayes

1997, Nature

Helicobacter pylori, strain 26695, has a circular genome of 1,667,867 base pairs and 1,590 predicted coding sequences. Sequence analysis indicates that H. pylori has well-developed systems for motility, for scavenging iron, and for DNA... more

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Small molecule activators of sirtuins extend Saccharomyces cerevisiae lifespan

by Dudley Lamming

2003, Nature

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Electric-Magnetic Duality, Monopole Condensation, And Confinement In N = 2 Supersymmetric Yang-Mills Theory

by Nathan Seiberg

We study the vacuum structure and dyon spectrum of N = 2 supersymmetric gauge theory in four dimensions, with gauge group SU (2). The theory turns out to have remarkably rich and physical properties which can nonetheless be described... more

This inequality confirms that for monopoles Z = nap amine the bosonic terms in the Hamiltonian of a magnetic monopole for real 6°: We would like to make a few comments:

Fig. 2: A non-trivial one-cycle on FE, comes from a contour in the x plane that loops around two of the branch points. The cuts in the x plane are indicated with dotted lines. and that is why P reverses the sign of a and ap as defined presently.

If a different choice is made for the 7;, the pair (ap, a) will be transformed by an element It remains to select f and verify the desired asymptotic behavior of ap and a near ‘irst of all, given (6.16), there is no problem in finding \. We can take

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Autonomic Healing of Polymer Composites

by Scott White

2001, Nature

Figure 1 The autonomic healing concept. A microencapsulated healing agent is embedded in a structural composite matrix containing a catalyst capable of polymerizing the healing agent. a, Cracks form in the matrix wherever damage occurs; b, the crack ruptures the microcapsules, releasing the healing agent into the crack plane through capillary action; ¢, the healing agent contacts the catalyst, triggering polymerization that bonds the crack faces closed. We began by analysing the effects of microcapsule geometry and properties on the mechanical triggering process. For example, capsule walls that are too thick will not rupture when the crack approaches, whereas capsules with very thin walls will break during processing. Other relevant design parameters are the toughness and the relative stiffness of the microcapsules, and the strength of the interface between the microcapsule and the matrix. Micro- mechanical modelling with the aid of the Eshelby—Mura equivalent inclusion method” has been used to study various aspects of the complex three-dimensional interaction between a crack and a microcapsule. An illustrative result from these studies is presented in Fig. 2a, which shows the effect of the relative stiffness of the microcapsule on the propagation path of an approaching crack. The crack, the sphere and the surrounding matrix are subjected to a far-field tensile loading, o... perpendicular to the crack plane.

(0.30). b, A time sequence of video images shows the rupture of a microcapsule and the release of the healing agent. A red dye was added for visualization. The elapsed time from the left to right image is 1/15. Scale bar, 0.25 mm. ec, A scanning electron microscope image shows the fracture plane of a self-healing material with a ruptured urea- formaldehyde microcapsule in a thermosetting matrix. Figure 2 Rupture and release of the microencapsulated healing agent. a, Stress state in the vicinity of a planar crack as it approaches a spherical inclusion embedded in a linearly elastic matrix and subjected to a remote tensile loading perpendicular to the fracture plane. The left and right figures correspond to an inclusion three times stiffer (E* = Esphere/E marx = 3) and three times more compliant (E* = 1/3) than the surrounding matrix, respectively. The Poisson’s ratios of the sphere and matrix are equa As apparent from the 02) stress distribution in the equatorial plane of the sphere in Fig. 2a, the stiffness of the sphere relative to the matrix strongly affects the stress state in the proximity of the crack tip and around the sphere itself. In the case ofa stiffer inclusion, the stress field in the immediate vicinity of the crack tip shows an asymmetry that indicates an undesirable tendency of the crack to be deflected away from the inclusion. The situation is reversed in the case of a more compliant spherical inclusion, and the crack is Observations by optical and scanning electron microscopy con- firmed the healing concept in Fig. 1 and substantiated the main findings from analytical studies in Fig. 2a. The time sequence of optical images in Fig. 2b shows the rupture of an embedded microcapsule filled with a red dye and the subsequent release of the healing agent into the crack plane. The scanning electron

monomer (middle), and poly(DCPD) film formed at the healed interface (bottom). The highlighted peak at 965 cm is characteristic of trans double bonds of ring-opened poly(DCPD). Figure 3 Chemistry of self-healing. a, Ruthenium-based Grubbs’ catalyst initiates ring-opening metathesis polymerization (ROMP) of dicyclopentadiene (DCPD). ring-opening metathesis polymerization (ROMP) of dicyclopentadiene (DCPD). b, Environmental ESEM micrograph and infrared analyses. IR spectra correspond to neat DCPD (top), an authentic sample of poly(DCPD) prepared with Grubbs’ catalyst and DCPD

In order to test the stability and activity of the catalyst in an epoxy matrix, solution-state 'H-NMR and solid-state *'P-NMR spectro- Figure 4 Self-healing efficiency in an epoxy polymer. a, Healing efficiency is obtained by fracture toughness testing of tapered double-cantilever beam (TDCB) specimens. The virgin fracture toughness is determined by propagating the starter crack along the mid- plane of the specimen. Subsequently, the load is removed and the crack allowed to heal at room temperature with no manual intervention. The healed fracture toughness is then measured by retesting the specimen. b, Post-fracture analysis of the specimens revealed that the healed crack failed in an interfacial manner from one side of the epoxy/poly(DCPD) interface to the other. The ESEM image in b shows one area of the fracture plane of a healed specimen in which the poly(DCPD) film is still attached to the interface on the right side of the image. The film that originally covered the interface on the left side of the image is found on the opposite mating surface of the specimen.

In this Letter, the middle infrared spectrum in Fig. 3b, correspond- ing to an authentic sample of poly(DCPD) prepared with Grubbs’ catalyst and DCPD monomer, was a duplicate of the top spectrum owing to a formatting error. The corrected spectra are shown below.

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OPGL is a key regulator of osteoclastogenesis, lymphocyte development and lymph-node organogenesis

by yun kong

1999, Nature

The tumour-necrosis-factor-family molecule osteoprotegerin ligand (OPGL; also known as TRANCE, RANKL and ODF) has been identi®ed as a potential osteoclast differentiation factor and regulator of interactions between T cells and dendritic... more

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Mycorrhizal fungal diversity determines plant biodiversity ecosystem variability and productivity

by andres wiemken and

1998, Nature

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Isolation of rare circulating tumour cells in cancer patients by microchip technology

by Daniel Irimia and

2007, Nature

Viable tumour-derived epithelial cells (circulating tumour cells or CTCs) have been identified in peripheral blood from cancer patients and are probably the origin of intractable metastatic disease 1-4 . Although extremely rare, CTCs... more

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Oxytocin increases trust in humans

by Paul Zak

2005, Nature

Trust pervades human societies 1,2 . Trust is indispensable in friendship, love, families and organizations, and plays a key role in economic exchange and politics 3 . In the absence of trust among trading partners, market transactions... more

Figure 1| The trust game. Both subjects receive an initial endowment of 12 monetary units (MU). The investor can send 0, 4, 8 or 12 MU to the trustee. The experimenter triples each MU the investor transfers. After the investor’s decision is made, the trustee is informed about the investor’s transfer. Then the trustee has the option of sending any amount between zero and his total amount available back to the investor. For example, if the investor has sent 12 MU, the trustee possesses 48 MU (12 MU own endowment + 36 MU tripled transfer) and can, therefore choose any back transfer from 0 to 48 MUs. The experimenter does not triple the back transfer. The investor’s final payoff corresponds to the initial endowment minus the transfer to the trustee, plus the back transfer from the trustee. The trustee’s final payoff is given by his initial endowment plus the tripled transfer of the investor, minus the back transfer to the investor. At the end of the experiment, the earned MU are exchanged into real money according to a publicly announced exchange rate (see Methods). Each subject made four decisions in the same player role while paired with four different, randomly selected interaction partners. Trust pervades human societies'”. Trust is indispensable in friend- ship, love, families and organizations, and plays a key role in economic exchange and politics’. In the absence of trust among trading partners, market transactions break down. In the absence of trust in a country’s institutions and leaders, political legitimacy breaks down. Much recent evidence indicates that trust contrib- utes to economic, political and social success*’. Little is known, however, about the biological basis of trust among humans. Here we show that intranasal administration of oxytocin, a neuro- peptide that plays a key role in social attachment and affiliation in non-human mammals**, causes a substantial increase in trust among humans, thereby greatly increasing the benefits from social interactions. We also show that the effect of oxytocin on trust is not due to a general increase in the readiness to bear risks. On the contrary, oxytocin specifically affects an individual’s willingness to accept social risks arising through interpersonal interactions. These results concur with animal research suggesting an essential role for oxytocin as a biological basis of prosocial approach behaviour.

Figure 2 | Transfers in the trust and the risk experiment. Each observation represents the average transfer amount (in MU) over four transfer decisions per investor. a, Relative frequency of investors’ average transfers in oxytocin (filled bars) and placebo (open bars) groups in the trust experiment (n = 58). Subjects given oxytocin show significantly higher transfer levels. b, Relative frequency of investors’ average transfers in oxytocin (filled bars) and placebo (open bars) groups in the risk experiment (n = 61). Subjects in the oxytocin and the placebo group show statistically identical transfer levels.

Figure 3 | Average back transfer of trustees to their investors. The graph shows the average back transfer by trustees for different levels of investor transfer in the oxytocin and placebo groups. The dotted line shows the level of the back transfer necessary to achieve payoff equality between the investor and the trustee. The dashed line shows a level of back transfer equal to the investor’s transfer to the trustee. The trustees’ back transfers are on average slightly higher than the amount sent by the investor. Trustees in both treatment groups make higher back transfers in response to higher original investor transfer levels. However, there is no statistically significant difference in back transfers between subjects in the oxytocin and the placebo groups.

Table 1 | Median and average transfer behaviour of investors

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